EP1006781A1 - Soybean having epistatic genes affecting yield - Google Patents

Soybean having epistatic genes affecting yield

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Publication number
EP1006781A1
EP1006781A1 EP98920117A EP98920117A EP1006781A1 EP 1006781 A1 EP1006781 A1 EP 1006781A1 EP 98920117 A EP98920117 A EP 98920117A EP 98920117 A EP98920117 A EP 98920117A EP 1006781 A1 EP1006781 A1 EP 1006781A1
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European Patent Office
Prior art keywords
locus
linked
modifying
quantitative trait
soybean plant
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EP98920117A
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German (de)
French (fr)
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EP1006781A4 (en
Inventor
Karl G. Lark
James Orf
Kevin Chase
Fred Adler
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University of Utah
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University of Utah
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    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6888Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/6895Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for plants, fungi or algae
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01HNEW PLANTS OR NON-TRANSGENIC PROCESSES FOR OBTAINING THEM; PLANT REPRODUCTION BY TISSUE CULTURE TECHNIQUES
    • A01H6/00Angiosperms, i.e. flowering plants, characterised by their botanic taxonomy
    • A01H6/54Leguminosae or Fabaceae, e.g. soybean, alfalfa or peanut
    • A01H6/542Glycine max [soybean]
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01HNEW PLANTS OR NON-TRANSGENIC PROCESSES FOR OBTAINING THEM; PLANT REPRODUCTION BY TISSUE CULTURE TECHNIQUES
    • A01H5/00Angiosperms, i.e. flowering plants, characterised by their plant parts; Angiosperms characterised otherwise than by their botanic taxonomy
    • A01H5/10Seeds
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/13Plant traits
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/156Polymorphic or mutational markers

Definitions

  • QTL quantitative trait locus
  • Molecular markers are a type of phenotype which can be detected by molecular techniques such as hybridization to a labeled DNA probe.
  • Types of molecular markers include RFLP (restriction fragment length polymorphism) , SSR (simple sequence repeat) markers , isozyme markers and the like.
  • markers provide two additional operational advantages. First, since they exist as features of the plant DNA itself, they can be detected soon after germination, for example by analysis of leaf DNA of seedlings. Selection for plants carrying the marker can be performed at the seedling stage, thereby saving the space and energy formerly needed to grow large numbers of plants to maturity. Second, molecular markers do not depend on gene expression for detection. Their use is unlikely to lead to misleading results, such as can occur when environmental or other variables modify expression of conventional marker genes.
  • Rl recombinant inbred
  • An Rl population is begun by a cross between two parent inbred (homozygous) cultivars.
  • the cultivars are preferably chosen so that a large amount of allelic variation exists between them. Only those molecular markers that are polymorphic between the two cultivars, i.e. , have a distinguishable difference between the two cultivars, can be used. Therefore, the greater the overall allelic variation between cultivars, the greater will be the number of usable molecular markers.
  • the individual progeny of the first cross are then selfed for several generations. The selfing process occurs naturally in soybean, which is a self -pollinator.
  • each segregant in the Rl population can be analyzed en masse in repeated experiments measuring various traits of agronomic interest. Simultaneously, allelic variation of individual molecular markers can be determined. It should be possible, in principle, to analyze such data for correlations between specific traits and specific marker alleles and thus identify QTLs linked to marker alleles.
  • Epistasis is the genetic term used to denote situations where non-allelic genes interact non-additively to affect the expression of a phenotype.
  • Classical epistatic effects are observed, for example, between pigment genes and genes affecting pigment distribution. Where a gene for pigment synthesis is altered or inactivated, expression of a pigment distribution gene may not be observable.
  • Quantitative traits in plants are the result of interactions between multiple QTLs and the environment [Tanksley, S.O. (1993) Ann. Rev. Genet. 27:205-233]. The existence of epistasis among QTLs extends the complexity and difficulty of identifying molecular markers linked to QTLs.
  • the present invention provides a method for plant breeding to improve a quantitative trait of agronomic value.
  • the method entails identifying a molecular marker linked to a first quantitative trait locus (QTL) at least one allele of which has an effect on a quantitative trait.
  • QTL quantitative trait locus
  • the method further entails identifying a second molecular marker linked to a second locus, at least one allele of which exerts a modifying effect on expression of the trait affected by the first locus.
  • QTL quantitative trait locus
  • second locus at least one allele of which exerts a modifying effect on expression of the trait affected by the first locus.
  • the breeding process therefore results in a novel and unique plant variety distinguished from a first parent variety by having a gene that has the potential to interact to provide improvement in a trait of agronomic value, at least one allele of such a gene being contributed by a second parent variety.
  • the invention is exemplified by a variety of QTLs in soybean affecting a variety of traits of agronomic significance, including yield.
  • Rl populations were obtained from initial crosses between cultivar- 'Archer' and cultivar 'Noir 1' or between 'Archer' and cultivar 'Minsoy' or between 'Minsoy' and 'Noir,' followed by 8-10 generations of selfmg individual offspring of the initial cross.
  • two loci affecting yield were identified in an Rl population obtained from an 'Archer 7 'Noir 1 ' cross, one linked to marker
  • the 'Noir 1 ' allele of the T153a-linked modifier gene exerted a positive effect only on the 'Noir 1' allele of the Satt277-linked yield gene.
  • the 'Archer' allele of the T153a-linked modifier had no differential effect on the 'Archer' or 'Noir 1' alleles of Satt277-linked yield gene.
  • the mean yields ranged from 34.2 Bu/ac to 40.1 Bu/ac, depending upon the combination of alleles.
  • Introgression of both 'Noir 1 ' alleles into commercial varieties can therefore increase yield dramatically. The effect could be even larger than that described herein if an endogenous yield locus of the variety is more responsive to the 'Noir 1' modifier allele.
  • modifier genes frequently modify more than one trait, additional agronomic benefits can be expected from other traits upregulated by the 'Noir 1 ' modifier, whether or not the Satt277-linked QTL was present.
  • the invention therefore provides improved plant varieties exemplified by soybean in which a varietal parent has its genotype altered to include at least a modifier gene linked to the molecular marker T153a.
  • the alteration can include introgression of one or more QTLs for traits of agronomic value, each identifiable by at least one linked molecular marker.
  • a QTL identified for soybean yield linked to the molecular marker Satt277 is a QTL identified for soybean yield linked to the molecular marker Satt277.
  • the magnitude of the modifying effect of the T153a-linked gene on a QTL varies depending on the specific allele of each gene or locus. The maximum effect on yield so far observed was obtained from the combination of the 'Noir 1 ' allele of T153a and the 'Noir 1 ' allele of Satt277. Therefore, a preferred embodiment of an improved plant variety is a commercial soybean cultivar modified to carry 'Noir 1 ' alleles of both T153a- and Satt277- linked loci
  • each point represents a single plant, with its rank with respect to the measured trait on the vertical axis and its trait data plotted on the horizontal axis.
  • Fig. 1 is based on soybean yield data for an 'Archer' X 'Noir 1 ' Rl population combined from both Minnesota and Chile test graphs.
  • Fig. IA is a standard distribution graph of yield (bu/ac) on the horizontal axis vs. number of plants (vertical axis).
  • Figs. IB-IE are cumulative distribution graphs of yield (horizontal axis) graphed against the rank of each plant with respect to yield.
  • the data are graphed separately for all plants having the 'Archer' allele of marker T153a, (labeled A, graphed as horizontal strokes) and for all plants having the 'Noir 1 ' allele of market T153a (labeled B, graphed as vertical strokes).
  • the data are graphed separately for all plants having both the 'Archer' allele of T153a(A) and the 'Archer' allele of marker Satt277 (graphed as solid circles) and for all plants having both the 'Archer' allele of T153a(A) and 'Noir 1 ' allele of Satt277 (graphed as open circles).
  • Fig. IC the data are graphed separately for all plants having both the 'Archer' allele of T153a(A) and the 'Archer' allele of marker Satt277 (graphed as solid circles) and for all plants having both the 'Archer' allele of T153a(A) and 'Noir 1
  • Fig. 2 is based on soybean yield data of the same Rl population from a Chile field test only.
  • Fig. 2 A is a conventional distribution curve of all plants.
  • Figs. 2B-E are cumulative distribution curves.
  • A designates plants having the 'Archer' T153a allele
  • B designates all plants having 'Noir 1' T153a allele
  • "a” designates plants having the 'Archer' Satt277 allele
  • "b” designates plants having the 'Noir 1 ' Satt277 alleles.
  • Plants having a particular combination of alleles are designated by a combination of upper case and lower case letters, Aa. Ab, Ba or Bb.
  • Fig. 3 is based on yield data from a 1996 Minnesota field test of the same Rl population.
  • Fig. 3 A is a conventional distribution graph for all plants.
  • Figs. 3B-E are cumulative distribution curves. All allelic designations are the same as for Figs. 1 and 2.
  • Fig. 4 is based on yield data from a 1997 Minnesota field test of the same Rl population.
  • Fig. 4 A is a conventional distribution graph for all plants.
  • Figs. 4B-E are cumulative distribution curves. All allelic designations are the same as for Figs. 1-3.
  • Fig. 5 is a graph showing the relationship between Additive Log likelihood ratio (LLR) and probability (p) values.
  • Fig. 6 is a bar graph of additive LLR values in interaction affecting yield of various marker loci in combination with marker Satt277.
  • Fig. 7 A-D shows cumulative distribution curves for seed protein content (percent by weight on a 13% water basis) in a 'Minsoy' X 'Archer' recombinant inbred population.
  • Upper case letters designate marker Sat-001, lower case designates marker SattOOl.
  • a (or a) designates an 'Archer' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 7A A is shown as horizontal strokes, B as vertical strokes.
  • Fig. 8 A-D shows cumulative distribution curves for yield (bushels/acre) in a 'Minsoy' X 'Noir 1' recombinant inbred population.
  • Upper case marker Satt365
  • Lower case marker Satt567
  • a (or a) 'Noir 1' allele
  • B (or b) 'Minsoy' allele.
  • Fig. 9 A-D shows cumulative distribution curves for seed weight (mg/seed) in a
  • Fig. 10 A-D shows cumulative distribution curves for oil content (g/kg seed on 13% water basis) in a 'Minsoy' X 'Archer' recombinant inbred population.
  • Upper case letters designate alleles of marker Sat_039
  • lower case letters designate alleles of marker Satt281.
  • a (or a) designates an 'Archer' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 11 A-D shows cumulative distribution curves for reproductive period (days) in a 'Minsoy' X 'Archer' recombinant inbred population.
  • Upper case letters designate alleles of marker Satt256
  • lower case letters designate alleles of marker Sat_112.
  • a (or a) designates a 'Noir 1' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. IID a - horizontal strokes, b - vertical strokes.
  • Fig. 12A-D shows cumulative distribution curves for oil content (g/Ug seed on a 13T water basis) in a 'Minsoy' X 'Archer' recombinant inbred population.
  • Upper case letters designate alleles of marker Satt346, lower case letters designate alleles of marker Satt372B.
  • a (or a) designates an 'Archer' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 12A, A horizontal strokes
  • B vertical strokes.
  • Fig. 12B, Aa filled circles
  • Ab open circles.
  • Fig. 13 A-D shows cumulative distribution curves for yield (bu/ac) in a 'Minsoy' X 'Archer' recombinant inbred population.
  • Upper case letters designate alleles of marker
  • Fig. 14A-D shows cumulative distribution curves for reproductive period (days), in a
  • Fig. 15 A-D shows cumulative distribution curves for leaf area (cm 2 ) in a 'Minsoy' X 'Noir 1' recombinant inbred population.
  • Upper case letters designate alleles of marker Satt066, lower case letters designate alleles of marker SattlOO.
  • a (or a) designates a 'Noir 1' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 15A, A horizontal strokes, B - vertical strokes.
  • Fig. 16 A-D shows cumulative distribution curves for flowering time (days) in an 'Archer' X 'Minsoy' recombinant inbred population.
  • Upper case letters designate alleles of marker Satt082, lower case letters designate alleles of marker R079.
  • a (or a) designates an 'Archer' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 17 A-D shows cumulative distribution curves for flowering time (days) in a 'Noir 1' X 'Minsoy' recombinant inbred population.
  • Upper case letters designate alleles of marker Satt079
  • lower case letters designate alleles of marker Sat_003.
  • a (or a) designates a 'Noir 1' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 17B, Aa filled circles, Ab- open circles.
  • Fig. 17C Ba - filled squares, Bb - open squares.
  • B vertical strokes.
  • Fig. 17B, Aa filled circles, Ab- open circles.
  • Fig. 17C Ba - filled squares, Bb - open squares.
  • FIG. 18A-D shows cumulative distribution curves for time to maturity divided by height (days/cm) in a 'Noir 1' X 'Minsoy' recombinant inbred population.
  • Upper case letters designate alleles of marker KOllc
  • lower case letters designate alleles of marker Satt307.
  • a (or a) designates a 'Noir 1' allele
  • B (or b) designates a 'Minsoy' allele.
  • Fig. 18B, Aa filled circles, Ab- open circles.
  • Fig. 18C Ba - filled squares, Bb - open squares.
  • Quantitative Trait - a trait which displays a continuous range of variation over a number of different plant varieties.
  • the variation is considered to be affected by a plurality of genes.
  • the genes controlling quantitative traits are considered to control incremental changes of the variation, and may interact with one another.
  • quantitative traits can have an effect that is only indirectly related to their primary function.
  • a gene controlling the length of maturation time can also be identified as affecting plant height, since the plant will continue to grow throughout the maturation period.
  • Environmental interactions also play an important part in measurement of a quantitative trait. For example, a trait such as yield will be affected by a trait of nematode resistance, in nematode-containing soils.
  • QTL Quantitative Trait Locus
  • Linkage is defmed by classical genetics to describe the relationship of traits which co- segregate through a number of generations of crosses. Genetic recombination occurs with an assumed random frequency over the entire genome. Genetic maps are constructed by measuring the frequency of recombination between pairs of traits or markers. The closer the traits or markers lie to each other on the chromosome, the lower the frequency of recombination, the greater the degree of linkage. Traits or markers are considered herein to be linked if there is less than 1/10 probability of recombination per generation. A 1/100 probability of recombination is defmed as a map distance of 1.0 centiMorgan (l.OcM).
  • Molecular marker is a term used to denote a DNA sequence feature which is sufficiently unique to characterize a specific locus on the genome. Examples include restriction fragment length polymorphisms (RFLP) and single sequence repeats (SSR). RFLP markers occur because any sequence change in DNA, including a single base change, insertion, deletion or inversion, can result in loss (or gain) of a restriction endonuclease recognition site. The size and number of fragments generated by one such enzyme is therefore altered. A probe which hybridizes specifically to DNA in the region of such an alteration can be used to rapidly and specifically identify a region of DNA which displays allelic variation between two plant varieties. SSR markers occur where a short sequence displays allelic variation in the number of repeats of that sequence.
  • RFLP restriction fragment length polymorphisms
  • SSR single sequence repeats
  • PCR polymerase chain reaction
  • PCR-generated fragment size can be detected by gel electrophoresis .
  • Other types of molecular markers are known. All are used to define a specific locus on the soybean genome. Large numbers of these have been mapped. Each marker is therefore an indicator of a specific segment of DNA, having a unique nucleotide sequence. The map positions provide a measure of the relative positions of particular markers with respect to one another.
  • Varietal parent is a term used herein to denote one of two parents of a crossing program intended to introduce a specific locus into a commercial variety.
  • Various commercial varieties have been developed for optimal performance under specific climate and soil conditions. Often it will be the case that new genes are to be introduced from an extraneous non-adapted or non-commercial line into an existing commercial variety. Through repeated backcrossing and selection the desired loci can be introgressed into the commercial variety while retaining most of the genetic background and performance characteristics of the commercial variety.
  • the variety into which the new genes or loci are to be introduced is termed the varietal parent herein.
  • the variety, line or strain from which the new genes or loci are derived is termed the donor variety. For example, a donor strain can be a non-commercial inbred such as Noir 1.
  • Agronomic trait is used herein as generally understood in the art to refer to traits or trait combinations which have the effect of making a plant variety valuable as a crop .
  • agronomic traits include crop yield , pathogen resistance , insect resistance , drought tolerance, nematode resistance, resistance to lodging and various adaptations to different climate and soil environments such as early maturity for northern climates, heat tolerance for southern climates , and various market-driven qualities such as seed protein content, oil content, color, flavor and the like.
  • Desirable agronomic traits can be expressed as ratios of quantitative traits as for example maturity /height, yield/height, yield/maturity, height/maturity and the like.
  • the populations included more than 230 plants.
  • Molecular mapping included more than 400 markers, of which about 300 were SSR markers and the remainder were RFLP markers. Mapping covered at least 2200 cM, including 22 linkage groups. Maps of the 'Archer' X 'Noir,' 'Archer' X 'Minsoy' and 'Minsoy' X 'Noir 1 ' populations are shown in Table 1. The Rl populations were planted in fields in
  • the 'Archer' X 'Noir 1 ' Rl population was screened generally for QTLs and concurrently mapped using RFLP and SSR markers, essentially as described previously for a 'Minsoy' x 'Noir 1 ' Rl population [Lark, K.G. et al. (1993) Theor. Appl. Genet. . 86:901-906, incorporated herein by reference; Mansur et al. (1993); Mansur et al (1996)]. Markers were analyzed by standard methods, such as described, e.g., by Mansur et al. (1996). Map positions for markers were determined by internal mapping [Lander et al.
  • LLR log likelihood ratio
  • An additive LLR was calculated to evaluate the likelihood that the observed effects of two loci in a specific allelic combination deviated from an assumed additive effect of all combinations of the two loci. The calculations were also based on the assumption that the data are normally distributed, and that the variances are given by the uncorrected sample variances, for example:
  • A, B, refer to alleles of the first locus and a, b refer to alleles of the second locus; and T denotes the total population. Subscripts denote sub-populations corresponding to the genotypes in question.
  • n A number of plants in the A group
  • a and B were used to denote different alleles of a given locus. For example at the
  • T153a linked locus A represents the 'Archer' allele
  • B represents the 'Noir 1 ' allele.
  • An unlinked second locus allele was denoted by lower case letters, e.g. at Satt277, a denotes the 'Archer' allele and b denotes the 'Noir 1 ' allele (See Fig. 1).
  • Each designated subgroup includes all tested plants of the Rl population which carry the designated allele or combination of alleles.
  • LLR values are natural logarithms of d e likelihood ratios. Therefore a difference of 1 unit corresponds to a factor of about 2.718, the numerical value of e.
  • a small additive log likelihood ratio indicates that the data can be effectively explained by die additive model, while a large LLR indicates diat the data are not additive.
  • the null LLR was tested by creating random groups from the data set. The order of die total set of plants was randomized, placing the first plants arbitrarily into an A group and the remaining plants into the B group. The resulting null LLR was then calculated. After a number of trials, the p value is based on number of times LLR was exceeded total number of trials
  • the additive LLR was calculated from the randomized populations. For example, the order of the A group data was randomized and separated into two groups corresponding to the frequency of a and b genotypes. The first group was then treated as the Aa group. The remaining group became the Ab group. (Group size was allocated according to the actual group sizes of the original data). In similar fashion the order of the B-group was randomized, a first group was assigned to Ba and the remaining group to Bb.
  • Additive LLR values and p-values are related as graphically shown in Fig. 5 , assuming normal distribution of data. For example, an LLR of 9 indicates a probability of slightly greater than 10 "5 (1 in 100,000) that a random assortment of the data could yield the observed differences in trait distribution. For higher LLR values, an accurate evaluation of p requires large numbers of simulations, (as many as 100 million). The greater the LLR, or the smaller the p-value, the more significant the data. Data showing lower LLR values are less significant, so that additional tests or larger trials might fail to support conclusions drawn from me original trial. Factors which affect the LLR, and titierefore the significance of data include the following:
  • the amount of variation controlled by the locus being tested me contribution of a QTL which has only a small effect on the measured trait can be difficult to measure significantly if the effects of other QTLs predominate;
  • the reproducibility of the test genetics and environment are the two factors affecting reproducibility.
  • the genetic variation within a given Rl population is set.
  • the degree of linkage between the marker and the locus the closer me marker physically lies to the locus, the greater me likelihood of observing an effect controlled by the locus.
  • an LLR value is a physical attribute of plant DNA, representing the length of DNA that includes the marker and e QTL controlling the trait.
  • FIG. 6 where the additive LLR values are shown for a modifier locus linked to T153a whose interaction with a QTL linked to marker Satt277 is to be described below as well as in Figs. 1-4.
  • a series of markers on group U3 map at varying distance from T153a. Marker Alll maps about 15.5 cM from T153a.
  • the additive LLR for interaction with Satt277 is less than 9.
  • the marker gmenod maps 5.7 cM from T153a, with an additive LLR greater than 16.
  • the marker T153a shows a slightly greater LLR than B172, suggesting even closer linkage to the modifier locus, almough the two markers appear very close to each other by conventional mapping.
  • the seed color locus I (a conventional trait) also lies close to me modifier locus although at present not as precisely mapped as molecular markers such as B 172.
  • I and R are actual genetic loci for the trait, not marker loci.
  • the phenotypic value is higher for black seeds than for yellow or brown seeds.
  • the additive LLR measured for the interaction between I and R is 32 and represents a case where the trait was measured directly, i.e. , the marker is the trait.
  • Trait associations having high LLR values, greater than about 9 measured as described, are useful as providing identification of epistatic interactions between traits closely linked to markers.
  • the high LLR interactions are also useful for identifying cloning markers, as well as marker pairs that "bracket" the locus, i.e. , lie on either side of the locus, such that the locus can be followed, without loss during crosses.
  • Preferred marker-linked interactions are those that display an LLR greater than about 12. Even more preferred interactions are those displaying an LLR greater than about 15 The most preferred interactions display an LLR greater than about 18. To date, it is believed ti at no epistatic interactions between a modifier locus and a QTL affecting yield have been reported with an LLR greater than 9.
  • loci that modify the expression of other loci is commonplace. However, modifying loci are typically closely linked to the gene or genes they modify. If mis were not the case, trait segregation after crossing would continually separate modifier and gene so that no evolutionary change could flow from the ability to modify the gene. However, in self-pollinating plants, no such selection pressure exists to maintain linkage between interacting loci. Unlinked interacting loci are expected to be found most frequently in self-pollinating plants. The methods of the invention are therefore applicable to all self-pollinating plant species including self-pollinating crop species including, without limitation, soybean, wheat, rice, oats and barley.
  • Marker-linked QTLs and modifiers thereof can be found in any of the foregoing crops and have interactive effects with an LLR greater than about 9, preferably greater than about 12, more preferably greater than about 15 , and most preferably greater than about 18. As demonstrated herein, such interactive effects can dramatically affect yield. Similarly, effects on QTLs controlling other traits of agronomic value have been found.
  • the dark seed color of me 'Noir 1 ' cultivar has been considered an undesirable trait for commercial soybeans.
  • the I locus which controls seed coat color has been noted as lying close to the T153a-linked modifier QTL.
  • Prior breeding efforts which used 'Noir 1,' but selected to avoid black seed color would have failed to exploit the modifier locus linked to T153a. It is unlikely that the locus in its 'Noir 1 ' allelic form currently exists in most commercial, white- seeded cultivars.
  • Seedlings from the initial cross are heterozygous at the loci of interest and must be selfed in order to provide a second generation (F2 plants) in which segregation occurs and in which a portion of the plants will be homozygous at the desired locus, in accord with well- known principles of genetics.
  • F2 plants second generation
  • both alleles of the desired loci are from the same donor plant source, e.g. 'Noir,' that cultivar can be used as one parent in the cross.
  • any parent having the desired alleles can be used (for example any of the described Rl lines).
  • Progeny segregant seedlings of the cross e.g.
  • F2 plants can be analyzed as seedlings for the presence of markers linked to the desired allele, for example, an allele of the T153a-linked modifying locus, or for the presence of an allele of the Satt277-linked QTL or the simultaneous presence of particular alleles of both loci.
  • markers linked to the desired allele for example, an allele of the T153a-linked modifying locus, or for the presence of an allele of the Satt277-linked QTL or the simultaneous presence of particular alleles of both loci.
  • Those plants possessing the desired loci are selected and grown to maturity for further evaluation. Further stages of crossing, back- crossing and selfing can be carried out as will be understood in the art, with selection for the presence of each desired locus, as described.
  • desired agronomic traits including mose of the varietal parent and those contributed by the QTL and die modifying locus can be carried out at d e breeder's discretion, to obtain true-breeding progeny having me desired traits. Because most of the desired agronomic traits are already present in the varietal parent, the result of the foregoing breeding process should derive most of its genetic background from the varietal parent, with the significant addition of die desired interacting pair of loci such as a T153a-linked modifier locus and a Satt227-linked QTL affecting yield. From cumulative distribution curves such as those of Figs.
  • the 'Noir 1' alleles, the modifier locus and the QTL are the preferred alleles of these loci. Improved lines also can be developed using other alleles of these loci.
  • the foregoing breeding process combines a varietal parent (first parent) and a donor parent (second parent) and results in a novel variety having genes of the varietal parent and at least one specific locus of die donor parent. It will be understood diat the existence of otiier modifiers in the varietal parent may effect the quantity of the desired trait observed after crossing. Other effects, including "linkage drag" are well known in the art of plant breeding to result in the introduction of genes located near the desired QTL, such that trait values in the crosses may be affected. Such phenomena are recognized and well understood characteristics of plant breeding which accompany the introgression process.
  • Fig. 2 the data of Fig. 1 were subdivided to display only the yield data from the Chile field test and in Fig. 3 are shown the data for the 1996 Minnesota field test.
  • die data of Fig. 1 were subdivided to display data of die 1997 Minnesota field test.
  • the similarity of the data of Figs. 2, 3 and 4 indicate mat the environmental differences between these three tests did not contribute to die epistatic effect.
  • the additive LLR for combined Chile and Minnesota tests is much greater than eid er test alone. Therefore, despite environmental differences, the cumulative effect of the data increases the significance of the epistatic effect and underscores the magnitude of die interaction in increasing yield and me closeness of the linkage. Yield can be affected indirectly by other quantitative traits.
  • loci diat do not significantly alter other traits of agronomic importance. For example, increasing yield while also increasing plant height can be counter-productive if me taller plants are more susceptible to lodging.
  • the preferred trait is one which can be introduced into an existing commercial variety without degrading o ier aspects of agronomic performance for which the variety has been developed. The QTL linked to Satt277 does not have a significant effect on odier traits that might indirectly affect yield.
  • Table 2 summarizes field data from field tests grown in Minnesota (MN96) and in Chile (CH95) standardized to averages of all plants in the Minnesota test (std MN96).
  • LLR and p-values were calculated for die interaction of the Satt277-linked QTL and its modifier, linked to T153a.
  • the traits measured were height (HT), lodging (LD), days to maturity (R8), seed weight (SW) and yield (YD).
  • HT height
  • LD lodging
  • R8 days to maturity
  • SW seed weight
  • YiD yield
  • the modifying locus linked to T153a is also closely linked to anotiier molecular marker, B172. Both map to linkage group U3 (Table 1). A gene which modifies or regulates another gene can regulate several odier genes as well.
  • the B172- or T153a-linked regulator function can be used to effect interactions with o ier QTLs. Therefore, the modifying locus linked to B172 and/or T153a can be useful by itself in a breeding program to enhance die activity of otiier endogenous QTLs in a varietal parent.
  • Markers B172 and T153a are RFLP probes. B172 and KOllc are available from Biogenetic Services, Inc. , 2308 - 6th Street East, Brookings, SD 57006. T153a was developed in the inventors' laboratory as described by Lark et al. (1993). The sequence of the T153a RFLP probe is given in SEQ ID NO: 1 (See Table 3).
  • markers designated by a number preceded by “Satt” or “Sat” are microsattelite DNA markers isolated at die United States Department of
  • Fig. 18D shows me distributions of plants having me 'Noir 1' allele of Satt307(a) and of plants having the 'Minsoy' allele of Satt307(b). Satt307 maps to linkage group U9.
  • FIGs. 18B and 18C An interaction of die two loci is readily seen from Figs. 18B and 18C.
  • Fig. 18B plants carrying the combination of 'Noir 1' allele of KOllc and 'Minsoy' allele of Satt307 (Ab) display higher maturity /height ratios than diose having me combination of 'Noir 1 ' K01 lc and 'Noir T Satt307.
  • FIG. 18C the effect of the 'Minsoy' allele of KOllc in combination with each of ie Satt307 alleles is shown (Ba and Bb).
  • the K01 lc marker is linked to a locus which exerts a modifying effect on die QTL linked to Satt307.
  • a very large LLR of 17.5 characterizes the magnitude of die interaction.
  • FIG. 8 A-D Further examples of interactions affecting yield are shown in Fig. 8 A-D and Fig. 13A- D.
  • Fig. 8 interacting loci linked to markers Satt365 and Satt567 were identified in a 'Minsoy' X 'Noir 1 ' Rl population. Field data were obtained in a 1993 Minnesota field Test. The interaction was characterized by an LLR of 9.82.
  • a pair of loci displaying an interaction between a modifying locus and a QTL affecting seed weight was found in me 'Archer' X 'Noir 1' Rl population.
  • the marker linked to die QTL was Satt315, and die modifying locus was linked to Satt080. Cumulative distributions are shown in Fig. 9A-D.
  • the interaction is characterized by an LLR of 10.58. The data were combined from all field trials.
  • the second interaction affecting oil content was observed from field data from a 1997 Minnesota test.
  • the interacting loci were linked to markers Sat_039 and to Satt281, respectively. Cumulative distributions are shown in Fig. 10 A-D.
  • the interaction was characterized by an LLR of 10.50.
  • the reproductive period (days from flowering to maturity) was affected by interacting loci in the 'Archer' X 'Minsoy' Rl population.
  • the loci were linked to marker Satt256 and to Satt_112, respectively.
  • Data were obtained in a 1995 Minnesota field test. Cumulative distribution curves are shown in Fig. 11 A-D.
  • the interaction was characterized by an LLR of 11.44.
  • Example 11 Leaf area (cm 2 ) was affected by an interaction identified in the 'Noir 1 ' X 'Minsoy' Rl population based on data obtained in a 1992 field test in Chile. The loci were linked to marker Satt066 and to marker SattlOO, respectively. Cumulative distributions are shown in Fig. 15A- D. The interaction was characterized by an LLR of 10.10.
  • interacting loci that significantly affect a variety of agronomic traits exist in plants, particularly self-pollinating plants such as soybean. Markers linked to such loci can be used in conventional plant breeding to improve or modify agronomic traits, by selecting for the combined presence of me desired alleles of the desired interacting pairs in the progeny of crosses. While the interactions have been observed in specific Rl populations, it will be understood that interacting loci are not limited to crosses with a specific line or to a specific Rl population or to a specific cross. The methods described herein can be reproducibly applied to identify interacting pairs of QTLs in any Rl line.
  • MOLECULE TYPE DNA (genomic)
  • ACCCCATCAT CCAGTACTCC ACGCTGTGCT GCTTCTTCAG 480
  • CCCCCAGTTC ACCGGCCACG CCGGCCAGTC CTCAACGGTG ACGGGCGTCT CCGACGCGCT 540

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Abstract

A method of plant breeding applicable to self-pollinating plants, and plants produced by use of the method, includes the use of molecular markers linked to interacting loci that affect traits of agronomic value. The method allows one to identify a first molecular marker linked to a quantitative trait locus (QTL) and a second molecular marker linked to a modifying locus having an epistatic effect in combination with the QTL. Conventional breeding steps can then be used to introgress the interacting loci into other plant varieties.

Description

SOYBEAN HAVING EPISTATIC GENES AFFECTING YIELD
CROSS REFERENCE TO RELATED APPLICATIONS
This application claims priority from United States Provisional Application No. 60/045,421 filed May 2, 1997, and from United States Patent Application Serial No. , filed April 30, 1998.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT
The research leading to the invention was supported in part by National Institute of
Health grant GM 42337. The U.S. government has certain rights in the invention.
BACKGROUND OF THE INVENTION
Plant breeders of field crops are primarily concerned with agronomic traits such as plant height, germination time, time to maturity, crop yield, resistance to disease, resistance to environmental stress and the like. Such traits are seldom controlled by a single gene with an all or nothing effect. Instead, the traits are typically controlled by genes whose effects are marginally quantitative, i.e. their effects are observable primarily by comparing quantitative measurements of specific traits and observing an increment or decrement of the trait. The locus of such a trait on a genetic map is therefore termed a quantitative trait locus (QTL). The term QTL is sometimes used synonymously to mean the gene affecting the trait. Identifying specific QTLs, mapping them and understanding the genetic and molecular basis for their action was largely impossible prior to the development of molecular markers. Molecular markers are a type of phenotype which can be detected by molecular techniques such as hybridization to a labeled DNA probe. Types of molecular markers include RFLP (restriction fragment length polymorphism) , SSR (simple sequence repeat) markers , isozyme markers and the like. For a review, see Dudley, J.W. (1989) Crop. Sci. .33:660-668.
The power of molecular markers lies in the large number that can be generated and in the ease and rapidity with which they can be measured. Prior to the advent of RFLP markers, only 17 linkage groups covering approximately 420 centimorgans had been identified in soybean using 57 classical markers such as flower color, seed coat color, seed coat peroxidase, root fluorescence, specific pest resistances and the like [Palmer, R.G. et al. (1987) Qualitative Genetics and Cy to genetics, In Wilcox, J.R. (ed) Soybean Improvement, Production and Uses 2nd Ed. Agronomy 16:145-199]. In contrast, Keim et al. (1990) Genetics 126:735-742. constructed a genetic map that included 130 RFLP markers in 26 linkage groups, covering approximately 1200 cM. Later, Diers et al. (1992) Theor. Appl. Genet..83:608-612 expanded die map to 252 markers in 31 linkage groups, covering 2147 cM. Libraries of molecular marker probes and PCR primers have been made for most agronomically important species in addition to soybean including tomato, maize, wheat and barley. The genetic maps of all such species have been significantly improved by the use of molecular markers.
Molecular markers have proven to be of great value for increasing the speed and efficiency of plant breeding. Most traits of agronomic value, e.g. pest resistance, yield and the like, are difficult to measure, often requiring a full growth season and statistical analysis of field trial results. Interpretation of the data can be obscured or confused by environmental variables. Occasionally it has been possible for breeders to make use of conventional markers such as flower color which could be readily followed through the breeding process. If the desired QTL is linked closely enough to a conventional marker, the likelihood of recombination occurring between them is sufficiently low that the QTL and the marker co- segregate throughout a series of crosses. The marker becomes, in effect, a surrogate for the
QTL itself. Prior to the advent of molecular markers, the opportunities for carrying out marker-linked breeding were severely limited by the lack of suitable markers mapping sufficiently close to the desired trait. Map distance is simply a function of recombination frequency between two markers, QTLs or markers and QTLs. Consequently, if a marker and a QTL map too far apart, too much recombination will occur during a series of crosses or self- pollinations such that the marker becomes no longer associated with the QTL. Having a wide selection of molecular markers available throughout the genetic map provides breeders the means to follow almost any desired trait through a series of crosses, by measuring the presence or absence of a marker linked to the QTL which affects that trait. The primary obstacle is the initial step of identifying a linkage between a marker and a QTL affecting the desired trait.
Molecular markers provide two additional operational advantages. First, since they exist as features of the plant DNA itself, they can be detected soon after germination, for example by analysis of leaf DNA of seedlings. Selection for plants carrying the marker can be performed at the seedling stage, thereby saving the space and energy formerly needed to grow large numbers of plants to maturity. Second, molecular markers do not depend on gene expression for detection. Their use is unlikely to lead to misleading results, such as can occur when environmental or other variables modify expression of conventional marker genes.
Identifying specific markers with specific traits of agronomic value remains a significant problem. In particular, identifying QTLs with linked markers has only become possible with the availability of a large number of molecular markers to which QTLs can be linked [Dudley
(1993)] . An important tool for evaluating quantitative traits and linkage to molecular markers is the recombinant inbred (Rl) population. Rl populations include individual lines representing stable inbred (therefore homozygous) segregant progeny from a single genetic cross [Burr, B. et al. (1988) Genetics 188:519-526; Carillo, J.M. et al. (1990) Theor. Appl. Genet. .79:321-
330]. An Rl population is begun by a cross between two parent inbred (homozygous) cultivars. The cultivars are preferably chosen so that a large amount of allelic variation exists between them. Only those molecular markers that are polymorphic between the two cultivars, i.e. , have a distinguishable difference between the two cultivars, can be used. Therefore, the greater the overall allelic variation between cultivars, the greater will be the number of usable molecular markers. The individual progeny of the first cross are then selfed for several generations. The selfing process occurs naturally in soybean, which is a self -pollinator. In order to ensure equal representation from all individuals of the cross, segregants are maintained separately during subsequent generations, a process known as single seed descent. During several generations of selfing, the progeny tend toward homozygosity at each locus, although each locus could have originated from either one of the original parent cultivars. As a result, the population eventually contains genes that are mostly homozygous at each locus, but which are randomly mixed as to parental source in a multiplicity of combinations depending on recombination events. After eight generations of selfmg, the theoretical frequency of heterozygosity is 1 in28. Therefore, the Rl population is essentially homozygous. As a result, each segregant in the Rl population can be analyzed en masse in repeated experiments measuring various traits of agronomic interest. Simultaneously, allelic variation of individual molecular markers can be determined. It should be possible, in principle, to analyze such data for correlations between specific traits and specific marker alleles and thus identify QTLs linked to marker alleles.
"Epistasis " is the genetic term used to denote situations where non-allelic genes interact non-additively to affect the expression of a phenotype. Classical epistatic effects are observed, for example, between pigment genes and genes affecting pigment distribution. Where a gene for pigment synthesis is altered or inactivated, expression of a pigment distribution gene may not be observable. Quantitative traits in plants are the result of interactions between multiple QTLs and the environment [Tanksley, S.O. (1993) Ann. Rev. Genet. 27:205-233]. The existence of epistasis among QTLs extends the complexity and difficulty of identifying molecular markers linked to QTLs.
Lark, K.G. et al. (Proc. Nat. Acad. Sci. USA 92:4656-4660) reported the identification of certain epistatic QTLs in soybean where trait variation at one locus was conditional upon a specific allele at another, in an Rl population obtained from a cross between cultivar 'Minsoy' and cultivar 'Noir 1. ' To identify such pairs of loci, the authors chose as the first locus a QTL that had been found to be associated with a measured trait, such as plant height. They then scanned through height data relating to unlinked loci, dividing the population of Rl lines into pairwise combinations of the first locus and a second locus. Since, at each locus, there were two identifiable alleles, each pairwise combination actually resulted in four possible combinations:
1) Locus 1 from 'Minsoy' and Locus 2 from 'Minsoy' 2) Locus 1 from 'Minsoy' and Locus 2 from 'Noir 1'
3) Locus 1 from 'Noir 1 ' and Locus 2 from 'Minsoy'
4) Locus 1 from 'Noir 1' and Locus 2 from ' Noir'
Since the molecular markers used were known to be polymorphic between 'Minsoy' and 'Noir, ' each of the four possible combinations could be identified and scored for distribution of plant heights. Instead of graphing the data as conventional distribution curves (number of plants with a given height on the ordinate vs height on the abscissa), the data were graphed as cumulative distributions. Height was graphed on the abscissa against the rank of each plant from shortest to tallest on the ordinate. Both the positions of the resulting distribution curves and their shape were indicators of interaction. In this way, several loci were identified which, alone, had no apparent effect on plant height but one allele of which did affect the height controlled by another locus. The maximum plant height controlled by a given first gene was therefore conditional upon the simultaneous presence in the plant of the proper allele of a second gene. An interaction of the same type was reported for yield, which was distinguishable from effects on plant height and on maturity . The analytical methods described by Lark et al (1995) and Chase, K. et al. (1997), Theor. Appl. Genet. .94:724-730, incorporated herein by reference, were employed in the present invention. A detailed description appears infra in the Examples.
SUMMARY OF THE INVENTION
The present invention provides a method for plant breeding to improve a quantitative trait of agronomic value. The method entails identifying a molecular marker linked to a first quantitative trait locus (QTL) at least one allele of which has an effect on a quantitative trait. The method further entails identifying a second molecular marker linked to a second locus, at least one allele of which exerts a modifying effect on expression of the trait affected by the first locus. Once markers for the desired alleles of the first and second loci are identified, conventional breeding methods can be employed to introduce both loci into other plant varieties and to select for their simultaneous presence through successive rounds of crossing and selection. It may be that only one of the loci need be introduced if the other is already present in the variety to be improved. The breeding process therefore results in a novel and unique plant variety distinguished from a first parent variety by having a gene that has the potential to interact to provide improvement in a trait of agronomic value, at least one allele of such a gene being contributed by a second parent variety.
The invention is exemplified by a variety of QTLs in soybean affecting a variety of traits of agronomic significance, including yield. Rl populations were obtained from initial crosses between cultivar- 'Archer' and cultivar 'Noir 1' or between 'Archer' and cultivar 'Minsoy' or between 'Minsoy' and 'Noir,' followed by 8-10 generations of selfmg individual offspring of the initial cross. As an example of the invention two loci affecting yield were identified in an Rl population obtained from an 'Archer 7 'Noir 1 ' cross, one linked to marker
T153a and the other to marker Satt277. Analysis of the effects of these genes, singly and in combination with one another revealed a locus affecting yield linked to Satt277 and a second locus acting as a modifier of the yield effect of Satt277, linked to T153a. These markers mapped to separate linkage groups.
The 'Noir 1 ' allele of the T153a-linked modifier gene exerted a positive effect only on the 'Noir 1' allele of the Satt277-linked yield gene. The 'Archer' allele of the T153a-linked modifier had no differential effect on the 'Archer' or 'Noir 1' alleles of Satt277-linked yield gene.
The mean yields ranged from 34.2 Bu/ac to 40.1 Bu/ac, depending upon the combination of alleles. The yield increment was 17.3 % . Introgression of both 'Noir 1 ' alleles into commercial varieties can therefore increase yield dramatically. The effect could be even larger than that described herein if an endogenous yield locus of the variety is more responsive to the 'Noir 1' modifier allele. Furthermore, since modifier genes frequently modify more than one trait, additional agronomic benefits can be expected from other traits upregulated by the 'Noir 1 ' modifier, whether or not the Satt277-linked QTL was present.
Analogous results were observed with respect to markers linked to other loci affecting traits of agronomic significance, including seed weight, flowering date, maturity/height (low values for tall, early maturing plants; high values for short, late maturing plants), average leaf area, protein content, oil content, and reproductive period and can, in principle, be obtained for any desired trait.
The invention therefore provides improved plant varieties exemplified by soybean in which a varietal parent has its genotype altered to include at least a modifier gene linked to the molecular marker T153a. In addition the alteration can include introgression of one or more QTLs for traits of agronomic value, each identifiable by at least one linked molecular marker. Of special interest is a QTL identified for soybean yield linked to the molecular marker Satt277. The magnitude of the modifying effect of the T153a-linked gene on a QTL varies depending on the specific allele of each gene or locus. The maximum effect on yield so far observed was obtained from the combination of the 'Noir 1 ' allele of T153a and the 'Noir 1 ' allele of Satt277. Therefore, a preferred embodiment of an improved plant variety is a commercial soybean cultivar modified to carry 'Noir 1 ' alleles of both T153a- and Satt277- linked loci.
BRIEF DESCRIPTION OF THE DRAWINGS
In Figs. 1-4, 7-18 and throughout this text, the letters a, A, b, and B are used to designate the parental alleles of specific markers in the three Rl lines. In 'Archer' X 'Minsoy' and 'Archer' X 'Noir 1' lines, a and A designate 'Archer' alleles. In 'Minsoy' X 'Noir 1' lines, a and A designate 'Noir 1' alleles. Thus, in 'Archer' X 'Minsoy' : A, a = 'Archer' alleles
B, b = 'Minsoy' alleles in 'Archer' X 'Noir 1 ' : A, a = 'Archer' alleles
B, b = 'Noir 1' alleles in 'Noir 1' X 'Minsoy* : A, a = 'Noir 1' alleles
B, b = 'Minsoy' alleles Capital letters designate the marker shown in the left-hand panel of each figure. Lower case letters designate the markers shown in the right hand panel of each figure. In each cumulative distribution graph, each point represents a single plant, with its rank with respect to the measured trait on the vertical axis and its trait data plotted on the horizontal axis.
Fig. 1 is based on soybean yield data for an 'Archer' X 'Noir 1 ' Rl population combined from both Minnesota and Chile test graphs. Fig. IA is a standard distribution graph of yield (bu/ac) on the horizontal axis vs. number of plants (vertical axis). Figs. IB-IE are cumulative distribution graphs of yield (horizontal axis) graphed against the rank of each plant with respect to yield. In Fig. IB, the data are graphed separately for all plants having the 'Archer' allele of marker T153a, (labeled A, graphed as horizontal strokes) and for all plants having the 'Noir 1 ' allele of market T153a (labeled B, graphed as vertical strokes). In Fig. IC, the data are graphed separately for all plants having both the 'Archer' allele of T153a(A) and the 'Archer' allele of marker Satt277 (graphed as solid circles) and for all plants having both the 'Archer' allele of T153a(A) and 'Noir 1 ' allele of Satt277 (graphed as open circles). In Fig. ID, all plants having 'Noir 1' T153a plus 'Archer' Satt277 (Ba) are graphed as solid squares, and all plants having 'Noir 1 ' T153a and 'Noir 1' Satt277 (Bb) are graphed as open squares. In Fig. IE, all plants having 'Archer' alleles of Satt277 (horizontal strokes) and 'Noir
1' alleles of Satt277 (vertical strokes) are graphed.
Fig. 2 is based on soybean yield data of the same Rl population from a Chile field test only. Fig. 2 A is a conventional distribution curve of all plants. Figs. 2B-E are cumulative distribution curves. As described for Fig. 1, A designates plants having the 'Archer' T153a allele, B designates all plants having 'Noir 1' T153a allele, "a" designates plants having the 'Archer' Satt277 allele, "b" designates plants having the 'Noir 1 ' Satt277 alleles. Plants having a particular combination of alleles are designated by a combination of upper case and lower case letters, Aa. Ab, Ba or Bb. Fig. 3 is based on yield data from a 1996 Minnesota field test of the same Rl population. Fig. 3 A is a conventional distribution graph for all plants. Figs. 3B-E are cumulative distribution curves. All allelic designations are the same as for Figs. 1 and 2.
Fig. 4 is based on yield data from a 1997 Minnesota field test of the same Rl population. Fig. 4 A is a conventional distribution graph for all plants. Figs. 4B-E are cumulative distribution curves. All allelic designations are the same as for Figs. 1-3.
Fig. 5 is a graph showing the relationship between Additive Log likelihood ratio (LLR) and probability (p) values.
Fig. 6 is a bar graph of additive LLR values in interaction affecting yield of various marker loci in combination with marker Satt277.
Fig. 7 A-D shows cumulative distribution curves for seed protein content (percent by weight on a 13% water basis) in a 'Minsoy' X 'Archer' recombinant inbred population. Upper case letters designate marker Sat-001, lower case designates marker SattOOl. A (or a) designates an 'Archer' allele, B (or b) designates a 'Minsoy' allele. Fig. 7A, A is shown as horizontal strokes, B as vertical strokes. Fig. 7B, Aa = filled circles, Ab = open circles. Fig. 7C, Ba = filled squares, Bb = open squares. Fig. 7D, a = horizontal strokes, b = vertical strokes.
Fig. 8 A-D shows cumulative distribution curves for yield (bushels/acre) in a 'Minsoy' X 'Noir 1' recombinant inbred population. Upper case = marker Satt365, Lower case = marker Satt567, A (or a) = 'Noir 1' allele, B (or b) = 'Minsoy' allele. Fig. 8 A, A= horizontal strokes, B = vertical strokes; Fig. 8B, Aa = filled circles, Ab = open circles; Fig. 8C, Ba = filled squares, Bb = open squares; Fig. 8D, a = horizontal strokes, b = vertical strokes.
Fig. 9 A-D shows cumulative distribution curves for seed weight (mg/seed) in a
'Minsoy' X 'Noir 1' recombinant inbred population. Upper case letters designate alleles of marker Satt080; lower case letters designate alleles of marker Satt315; A (or a) designates a 'Noir 1 ' allele; B (or b) designates a 'Minsoy' allele. Fig. 9 A, A = horizontal strokes, B = vertical strokes. Fig. 9B, Aa = filled circles, Ab = open circles. Fig. 9C, Ba - filled squares, Bb = open squares. Fig. 9D, a = horizontal strokes, b = vertical strokes.
Fig. 10 A-D shows cumulative distribution curves for oil content (g/kg seed on 13% water basis) in a 'Minsoy' X 'Archer' recombinant inbred population. Upper case letters designate alleles of marker Sat_039, lower case letters designate alleles of marker Satt281. A (or a) designates an 'Archer' allele, B (or b) designates a 'Minsoy' allele. Fig. IOA, A = horizontal strokes, B = vertical strokes. Fig. 10B, Aa = filled circles, Ab = open circles. Fig. IOC, Ba = filled squares, Bb = open squares. Fig. 10D, a = horizontal strokes, b = vertical strokes.
Fig. 11 A-D shows cumulative distribution curves for reproductive period (days) in a 'Minsoy' X 'Archer' recombinant inbred population. Upper case letters designate alleles of marker Satt256, lower case letters designate alleles of marker Sat_112. A (or a) designates a 'Noir 1' allele, B (or b) designates a 'Minsoy' allele. Fig. 11 A, A = horizontal strokes, B = vertical strokes. Fig. 11B, Aa = filled circles, Ab = open circles. Fig. 11C, Ba = filled squares, Bb = open squares. Fig. IID, a - horizontal strokes, b - vertical strokes.
Fig. 12A-D shows cumulative distribution curves for oil content (g/Ug seed on a 13T water basis) in a 'Minsoy' X 'Archer' recombinant inbred population. Upper case letters designate alleles of marker Satt346, lower case letters designate alleles of marker Satt372B. A (or a) designates an 'Archer' allele, B (or b) designates a 'Minsoy' allele. Fig. 12A, A = horizontal strokes, B = vertical strokes. Fig. 12B, Aa = filled circles, Ab = open circles.
Fig. 12C, Ba = filled squares, Bb = open squares. Fig. 12 D, a = horizontal strokes, b - vertical strokes.
Fig. 13 A-D shows cumulative distribution curves for yield (bu/ac) in a 'Minsoy' X 'Archer' recombinant inbred population. Upper case letters designate alleles of marker
Satt507, lower case letters designate alleles of marker Satt561. A (or a) designates an 'Archer' allele, B (or b) designates a 'Minsoy' allele. Fig. 13A, A = horizontal strokes B - vertical strokes, Fig, 13B, Aa = filled circles, Ab = open circles. Fig. 13C, Ba = filled squares, Bb = open squares. Fig. 13D, a = horizontal strokes, b = vertical strokes.
Fig. 14A-D shows cumulative distribution curves for reproductive period (days), in a
'Minsoy' X 'Noir 1' recombinant inbred population. Upper case letters designate alleles of marker Satt032, lower case letters designate alleles of marker HSP176. A (or a) designates a 'Noir 1' allele, B (or b) designates a 'Minsoy' allele. Fig. 14A, A = horizontal strokes, B = vertical strokes. Fig. 14B, Aa = filled circles, Ab = open circles. Fig. 14C, Ba = filled squares, Bb = open squares. Fig. 14D, a = horizontal strokes, b = vertical strokes.
Fig. 15 A-D shows cumulative distribution curves for leaf area (cm2) in a 'Minsoy' X 'Noir 1' recombinant inbred population. Upper case letters designate alleles of marker Satt066, lower case letters designate alleles of marker SattlOO. A (or a) designates a 'Noir 1' allele, B (or b) designates a 'Minsoy' allele. Fig. 15A, A = horizontal strokes, B - vertical strokes. Fig. 15B, Aa = filled circles, Ab = open circles. Fig. 15C, Ba = filled squares, Bb = open squares. Fig. 15D, a = horizontal strokes, b = vertical strokes.
Fig. 16 A-D shows cumulative distribution curves for flowering time (days) in an 'Archer' X 'Minsoy' recombinant inbred population. Upper case letters designate alleles of marker Satt082, lower case letters designate alleles of marker R079. A (or a) designates an 'Archer' allele, B (or b) designates a 'Minsoy' allele. Fig. 16A, A = horizontal strokes, B = vertical strokes. Fig. 156, Aa = filled circles, Ab = open circles. Fig. 16C, Ba = filled squares, Bb = open squares. Fig. 16D, a = horizontal strokes, b = vertical strokes.
Fig. 17 A-D shows cumulative distribution curves for flowering time (days) in a 'Noir 1' X 'Minsoy' recombinant inbred population. Upper case letters designate alleles of marker Satt079, lower case letters designate alleles of marker Sat_003. A (or a) designates a 'Noir 1' allele, B (or b) designates a 'Minsoy' allele. Fig. 17A, A= horizontal strokes, B = vertical strokes. Fig. 17B, Aa = filled circles, Ab- open circles. Fig. 17C, Ba - filled squares, Bb - open squares. Fig. 17D, a - horizontal strokes, b = vertical strokes. Fig. 18 A-D shows cumulative distribution curves for time to maturity divided by height (days/cm) in a 'Noir 1' X 'Minsoy' recombinant inbred population. Upper case letters designate alleles of marker KOllc, lower case letters designate alleles of marker Satt307. A (or a) designates a 'Noir 1' allele, B (or b) designates a 'Minsoy' allele. Fig. 18A, A= horizontal strokes, B = vertical strokes. Fig. 18B, Aa = filled circles, Ab- open circles. Fig. 18C, Ba - filled squares, Bb - open squares. Fig. 18D, a - horizontal strokes, b = vertical strokes.
DETAILED DESCRIPTION OF THE INVENTION
The following terms are used as defined herein:
Quantitative Trait - a trait which displays a continuous range of variation over a number of different plant varieties. The variation is considered to be affected by a plurality of genes. The genes controlling quantitative traits are considered to control incremental changes of the variation, and may interact with one another. By their nature, quantitative traits can have an effect that is only indirectly related to their primary function. For example, a gene controlling the length of maturation time can also be identified as affecting plant height, since the plant will continue to grow throughout the maturation period. Environmental interactions also play an important part in measurement of a quantitative trait. For example, a trait such as yield will be affected by a trait of nematode resistance, in nematode-containing soils.
Quantitative Trait Locus (QTL) is an operational term used to denote a region of the plant genome that can be associated with a quantitative trait. The term QTL is sometimes used synonymously with the gene affecting the trait. However, since QTLs are identified by linkage to molecular markers, the "locus" is more accurately described as the segment of genome remaining linked to the marker through a series of generations while continuing to affect the trait (under appropriate conditions). Physically that segment will include the gene but can also include flanking DNA.
Linkage is defmed by classical genetics to describe the relationship of traits which co- segregate through a number of generations of crosses. Genetic recombination occurs with an assumed random frequency over the entire genome. Genetic maps are constructed by measuring the frequency of recombination between pairs of traits or markers. The closer the traits or markers lie to each other on the chromosome, the lower the frequency of recombination, the greater the degree of linkage. Traits or markers are considered herein to be linked if there is less than 1/10 probability of recombination per generation. A 1/100 probability of recombination is defmed as a map distance of 1.0 centiMorgan (l.OcM).
Molecular marker is a term used to denote a DNA sequence feature which is sufficiently unique to characterize a specific locus on the genome. Examples include restriction fragment length polymorphisms (RFLP) and single sequence repeats (SSR). RFLP markers occur because any sequence change in DNA, including a single base change, insertion, deletion or inversion, can result in loss (or gain) of a restriction endonuclease recognition site. The size and number of fragments generated by one such enzyme is therefore altered. A probe which hybridizes specifically to DNA in the region of such an alteration can be used to rapidly and specifically identify a region of DNA which displays allelic variation between two plant varieties. SSR markers occur where a short sequence displays allelic variation in the number of repeats of that sequence. Sequences flanking the repeated sequence can serve as polymerase chain reaction (PCR) primers. Depending on the number of repeats at a given allele of the locus, the length of d e DNA segment generated by PCR will be different in different alleles. The differences in PCR-generated fragment size can be detected by gel electrophoresis . Other types of molecular markers are known. All are used to define a specific locus on the soybean genome. Large numbers of these have been mapped. Each marker is therefore an indicator of a specific segment of DNA, having a unique nucleotide sequence. The map positions provide a measure of the relative positions of particular markers with respect to one another. When a trait is stated to be linked to a given marker it will be understood that the actual DNA segment whose sequence affects the trait lies within about 10 cM of the marker. More precise and definite localization can be obtained if markers are identified on both sides of the QTL. By measuring the appearance of the marker(s) in progeny of crosses, the existence of the QTL can be detected by relatively simple molecular tests, without actually evaluating the appearance of the trait itself, which can be difficult and time consuming. Epistasis is a well-known term of genetics, referring to an interaction of two genes where the result is other than the sum of the effects attributable to each gene acting in the absence of the other. An additive effect is not epistatic. In epistasis, the mechanism of the interaction is not taken into account. Consequently, even if no effect can be observed for one or both genes alone, an effect dependant on the presence of both is termed epistatic.
Varietal parent is a term used herein to denote one of two parents of a crossing program intended to introduce a specific locus into a commercial variety. Various commercial varieties have been developed for optimal performance under specific climate and soil conditions. Often it will be the case that new genes are to be introduced from an extraneous non-adapted or non-commercial line into an existing commercial variety. Through repeated backcrossing and selection the desired loci can be introgressed into the commercial variety while retaining most of the genetic background and performance characteristics of the commercial variety. The variety into which the new genes or loci are to be introduced is termed the varietal parent herein. The variety, line or strain from which the new genes or loci are derived is termed the donor variety. For example, a donor strain can be a non-commercial inbred such as Noir 1.
Agronomic trait is used herein as generally understood in the art to refer to traits or trait combinations which have the effect of making a plant variety valuable as a crop . Common examples of agronomic traits include crop yield , pathogen resistance , insect resistance , drought tolerance, nematode resistance, resistance to lodging and various adaptations to different climate and soil environments such as early maturity for northern climates, heat tolerance for southern climates , and various market-driven qualities such as seed protein content, oil content, color, flavor and the like. The foregoing list is exemplary and not exhaustive, as will be understood in the art. Desirable agronomic traits can be expressed as ratios of quantitative traits as for example maturity /height, yield/height, yield/maturity, height/maturity and the like.
Recombinant inbred (Rl) populations were developed between soybean cultivars 'Noir
1' (PI290136) and 'Archer' (PI546487), between 'Archer' and 'Minsoy' (PI27890), and between 'Minsoy' and 'Noir 1. ' [Each plant variety or strain introduced into me U.S. through the U.S. Dept. of Agriculture system is assigned an identifying number by the Plant Introduction Office, Germplasm Services Lab. USDA-ARS, BARC-West, Belts ville, MD, 20705, see publication INTSOY Series 31, see also Cianzio, S.R. et al. (1991) Crop Sci. 31:1707 for further description of 'Archer'] essentially as described previously [Lark, K.G. et al. (1995) incorporated herein by reference; Mansur, L.M. et al. (1996) Crop Sci..36: 1327- 1336 incorporated hereby by reference; Mansur, L.M. et al. (1993) Theor. Appl. Genet.
86:907-913, incorporated herein by reference.] The populations included more than 230 plants. Molecular mapping included more than 400 markers, of which about 300 were SSR markers and the remainder were RFLP markers. Mapping covered at least 2200 cM, including 22 linkage groups. Maps of the 'Archer' X 'Noir,' 'Archer' X 'Minsoy' and 'Minsoy' X 'Noir 1 ' populations are shown in Table 1. The Rl populations were planted in fields in
Minnesota (45 °N 93 °W) and in Chile (34°S 70°W) as a test of environmental effects. Field tests and measurements of quantitative traits were performed essentially as described [Mansur et al. (1993)]. Yield was measured as kg soybeans/ha on a 13 % moisture basis. Height was measured in cm, flowering and maturity dates were expressed as days from planting, seed weight as mg/seed and leaf area as cm2. Protein and oil content were each expressed as grams
(protein or oil) per kg seed on the basis of 13% (w/w) water content.
The 'Archer' X 'Noir 1 ' Rl population was screened generally for QTLs and concurrently mapped using RFLP and SSR markers, essentially as described previously for a 'Minsoy' x 'Noir 1 ' Rl population [Lark, K.G. et al. (1993) Theor. Appl. Genet..86:901-906, incorporated herein by reference; Mansur et al. (1993); Mansur et al (1996)]. Markers were analyzed by standard methods, such as described, e.g., by Mansur et al. (1996). Map positions for markers were determined by internal mapping [Lander et al. (1987) Genomics 1: 174-181] using "Mapmaker" and Mapmaker QTL [Lincoln, S.E. et al. (1993) Whitehead Inst. of Med. Res. Tech. Report, Cambridge, MA]. Genetic maps obtained from the three populations are given in Table 1. Analysis of marker-QTL associations was investigated by standard one-way analysis of variance in which marker-genotype groups were used as class variables [Osborn, T.C. et al. (1987) Theor. Appl. Genet. 74:350-356] or using Mapmaker/QTL [Lincoln et al. (1993)]. The means for each marker allelic group were compared. In order to identify epistatic interactions between pairwise combinations of markers, deviations from the additive effects of the means for each marker were analyzed for significance essentially as described by Lark et al. (1995) and by Chase et al. (1997). The statistical likelihood of a given deviation from a simple additive effect was calculated as a probability that the observed difference could occur by random variation. Those with lower probability for chance deviation from additive were then analyzed in greater detail as potential epistatic interactions.
The significance of differences observed between trait values assorted by marker allele was evaluated by calculating a log likelihood ratio (LLR), a natural logarithm of the ratio of likelihoods of me observed result compared to an average of all results [Bickel et al. (1997), Mathematical Statistics, Holden Day, Oakland, CA] . In comparing the effect of a single allele, a null LLR was calculated for me difference between the observed data and the average of all plants tested. An additive LLR was calculated to evaluate the likelihood that the observed effects of two loci in a specific allelic combination deviated from an assumed additive effect of all combinations of the two loci. The calculations were also based on the assumption that the data are normally distributed, and that the variances are given by the uncorrected sample variances, for example:
is the sample variable for the Ab population where A, B, refer to alleles of the first locus and a, b refer to alleles of the second locus; and T denotes the total population. Subscripts denote sub-populations corresponding to the genotypes in question.
Null LLR values were calculated as
where nA = number of plants in the A group
∑PAi where μ . = mean trait value of the A sub group =
A n A _ where P^ = the phenotypic value for the t'th plant in the A subgroup (i.e., the trait value), and
Σ(P -μ f where σ = variance of the A subgroup = ' nΛ ~ l
The letters A and B were used to denote different alleles of a given locus. For example at the
T153a linked locus, A represents the 'Archer' allele, B represents the 'Noir 1 ' allele. An unlinked second locus allele was denoted by lower case letters, e.g. at Satt277, a denotes the 'Archer' allele and b denotes the 'Noir 1 ' allele (See Fig. 1). Each designated subgroup includes all tested plants of the Rl population which carry the designated allele or combination of alleles.
Additive LLR values were calculated as
n aBi aB - (fia + ( B - τ))f
nAbAb - {βA + μb - μτ))f +
2σ Ab
where the subscripts Aa, Ab, aB and bB represent the four possible allelic combinations of two unlinked loci and T represents the total population. LLR values are natural logarithms of d e likelihood ratios. Therefore a difference of 1 unit corresponds to a factor of about 2.718, the numerical value of e. A small additive log likelihood ratio indicates that the data can be effectively explained by die additive model, while a large LLR indicates diat the data are not additive.
The probability, p, that the LLR value could be exceeded by a random assortment of the data was calculated by a Monte Carlo simulation [Manly (1991) Randomization and Monte
Carlo Methods in Biology. Chapman and Hall, New York] specific to the data obtained for a given trait and locus or pair of loci. The null LLR was tested by creating random groups from the data set. The order of die total set of plants was randomized, placing the first plants arbitrarily into an A group and the remaining plants into the B group. The resulting null LLR was then calculated. After a number of trials, the p value is based on number of times LLR was exceeded total number of trials
For the additive LLR, one trial consisted of randomizing the second locus while keeping the first locus fixed. The additive LLR was calculated from the randomized populations. For example, the order of the A group data was randomized and separated into two groups corresponding to the frequency of a and b genotypes. The first group was then treated as the Aa group. The remaining group became the Ab group. (Group size was allocated according to the actual group sizes of the original data). In similar fashion the order of the B-group was randomized, a first group was assigned to Ba and the remaining group to Bb.
Additive LLR values and p-values are related as graphically shown in Fig. 5 , assuming normal distribution of data. For example, an LLR of 9 indicates a probability of slightly greater than 10"5 (1 in 100,000) that a random assortment of the data could yield the observed differences in trait distribution. For higher LLR values, an accurate evaluation of p requires large numbers of simulations, (as many as 100 million). The greater the LLR, or the smaller the p-value, the more significant the data. Data showing lower LLR values are less significant, so that additional tests or larger trials might fail to support conclusions drawn from me original trial. Factors which affect the LLR, and titierefore the significance of data include the following:
1. The amount of variation controlled by the locus being tested: me contribution of a QTL which has only a small effect on the measured trait can be difficult to measure significantly if the effects of other QTLs predominate;
2. The number of plants in the test: it is well understood that small sample size can lead to erroneous conclusions, and that variance can be calculated more accurately as sample size is increased;
3. The reproducibility of the test: genetics and environment are the two factors affecting reproducibility. The genetic variation within a given Rl population is set.
Environmental variation in growing conditions can differ widely in tests done at different times, or in different locations. The tests described herein were conducted in Minnesota and in Chile. For example, certain loci having an otherwise reproducible effect in Chile did not display the same effect in Minnesota trials, and vice- versa;
4. The degree of linkage between the marker and the locus: the closer me marker physically lies to the locus, the greater me likelihood of observing an effect controlled by the locus. The greater the distance between marker and locus, me greater the likelihood of a recombination event occurring to separate the linkage, and therefore the greater the possibility for the effect to be influenced by some genetic element other than the locus tested.
When data are compared for the same Rl population, same QTL, same number of tested plants, and same environment, the LLR value becomes a measure of the physical distance on the chromosome, between the marker and the QTL. Under these circumstances, an LLR value is a physical attribute of plant DNA, representing the length of DNA that includes the marker and e QTL controlling the trait. The foregoing is illustrated by data shown in Fig. 6, where the additive LLR values are shown for a modifier locus linked to T153a whose interaction with a QTL linked to marker Satt277 is to be described below as well as in Figs. 1-4. A series of markers on group U3 (See Table 1) map at varying distance from T153a. Marker Alll maps about 15.5 cM from T153a. The additive LLR for interaction with Satt277 is less than 9. The marker gmenod maps 5.7 cM from T153a, with an additive LLR greater than 16. The marker T153a shows a slightly greater LLR than B172, suggesting even closer linkage to the modifier locus, almough the two markers appear very close to each other by conventional mapping. The seed color locus I (a conventional trait) also lies close to me modifier locus although at present not as precisely mapped as molecular markers such as B 172.
Data have also been obtained for the additive LLR of I and R for the phenotype of NIT (near infrared transmittance) [Chase et al. (1997)] . I and R are actual genetic loci for the trait, not marker loci. The phenotypic value is higher for black seeds than for yellow or brown seeds. The additive LLR measured for the interaction between I and R is 32 and represents a case where the trait was measured directly, i.e. , the marker is the trait. Although this LLR value is very high it is not necessarily a theoretical maximum, since other locus interactions could result in higher or lower LLR values even if these associated markers were part of the locus itself, because, as noted, the LLR calculation can be affected by environmental effects, assay conditions, data distribution and sample size
Trait associations having high LLR values, greater than about 9 measured as described, are useful as providing identification of epistatic interactions between traits closely linked to markers. The high LLR interactions are also useful for identifying cloning markers, as well as marker pairs that "bracket" the locus, i.e. , lie on either side of the locus, such that the locus can be followed, without loss during crosses. Preferred marker-linked interactions are those that display an LLR greater than about 12. Even more preferred interactions are those displaying an LLR greater than about 15 The most preferred interactions display an LLR greater than about 18. To date, it is believed ti at no epistatic interactions between a modifier locus and a QTL affecting yield have been reported with an LLR greater than 9. The fact, now described herein, that interactions between a modifier locus and a QTL affecting yield do exist provides markers that can be used for crop breeding to increase crop yield and also provide cloning tools for isolating the DNA that includes me locus, whether the sequence be coding or non-coding.
Identification of interacting loci has been considered to be difficult heretofore (Tanksley, 1993). In addition, die identification of interactions between a QTL and a modifier locus poses greater difficulty since the modifier may, by itself, have no appreciable effect on the trait. In that case, the modifier can only be revealed by pairwise screenings accompanied by an analytical memod capable of detecting an interaction. Lark (1995) described a method which could, in principle, detect such interactions. An interaction between BLT53C of 'Minsoy' and BLT29 of 'Noir 1 ' affecting yield displayed a modest epistatic effect. However, the LLR (termed "lod" therein) was only 7.2.
The existence of loci that modify the expression of other loci is commonplace. However, modifying loci are typically closely linked to the gene or genes they modify. If mis were not the case, trait segregation after crossing would continually separate modifier and gene so that no evolutionary change could flow from the ability to modify the gene. However, in self-pollinating plants, no such selection pressure exists to maintain linkage between interacting loci. Unlinked interacting loci are expected to be found most frequently in self-pollinating plants. The methods of the invention are therefore applicable to all self-pollinating plant species including self-pollinating crop species including, without limitation, soybean, wheat, rice, oats and barley. Marker-linked QTLs and modifiers thereof can be found in any of the foregoing crops and have interactive effects with an LLR greater than about 9, preferably greater than about 12, more preferably greater than about 15 , and most preferably greater than about 18. As demonstrated herein, such interactive effects can dramatically affect yield. Similarly, effects on QTLs controlling other traits of agronomic value have been found.
Once useful loci are identified, conventional breeding can be undertaken to introduce the loci together into a commercial cultivar by selecting for the markers in progeny plants.
The higher the LLR, the closer the marker to the locus, as described above, and the lower the likelihood of d e marker separating from the locus as a result of recombination. Selection can be made even more reliable by employing two markers, bracketing the locus, i.e. , positioned with respect to the locus such tiiat the locus physically lies between the markers.
The dark seed color of me 'Noir 1 ' cultivar has been considered an undesirable trait for commercial soybeans. The I locus which controls seed coat color has been noted as lying close to the T153a-linked modifier QTL. Prior breeding efforts which used 'Noir 1,' but selected to avoid black seed color would have failed to exploit the modifier locus linked to T153a. It is unlikely that the locus in its 'Noir 1 ' allelic form currently exists in most commercial, white- seeded cultivars.
Conventional crossing methods applicable to soybean are used to introduce a modifier locus such as the T153a-linked modifier locus, and/or a second marker-linked QTL such as the Satt277-linked QTL from a donor parent into a commercial soybean variety (varietal parent).
Seedlings from the initial cross (FI plants) are heterozygous at the loci of interest and must be selfed in order to provide a second generation (F2 plants) in which segregation occurs and in which a portion of the plants will be homozygous at the desired locus, in accord with well- known principles of genetics. Where both alleles of the desired loci are from the same donor plant source, e.g. 'Noir,' that cultivar can be used as one parent in the cross. However, any parent having the desired alleles can be used (for example any of the described Rl lines). Progeny segregant seedlings of the cross (e.g. F2 plants) can be analyzed as seedlings for the presence of markers linked to the desired allele, for example, an allele of the T153a-linked modifying locus, or for the presence of an allele of the Satt277-linked QTL or the simultaneous presence of particular alleles of both loci. Those plants possessing the desired loci are selected and grown to maturity for further evaluation. Further stages of crossing, back- crossing and selfing can be carried out as will be understood in the art, with selection for the presence of each desired locus, as described. Selection for desired agronomic traits including mose of the varietal parent and those contributed by the QTL and die modifying locus can be carried out at d e breeder's discretion, to obtain true-breeding progeny having me desired traits. Because most of the desired agronomic traits are already present in the varietal parent, the result of the foregoing breeding process should derive most of its genetic background from the varietal parent, with the significant addition of die desired interacting pair of loci such as a T153a-linked modifier locus and a Satt227-linked QTL affecting yield. From cumulative distribution curves such as those of Figs. 1-4 it will be possible to determine the preferred alleles for each interacting pair of loci, for example, in breeding for improved yield, the 'Noir 1' alleles, the modifier locus and the QTL are the preferred alleles of these loci. Improved lines also can be developed using other alleles of these loci. The foregoing breeding process combines a varietal parent (first parent) and a donor parent (second parent) and results in a novel variety having genes of the varietal parent and at least one specific locus of die donor parent. It will be understood diat the existence of otiier modifiers in the varietal parent may effect the quantity of the desired trait observed after crossing. Other effects, including "linkage drag" are well known in the art of plant breeding to result in the introduction of genes located near the desired QTL, such that trait values in the crosses may be affected. Such phenomena are recognized and well understood characteristics of plant breeding which accompany the introgression process.
Example 1:
During the course of screening the soybean 'Archer' x 'Noir 1' Rl population for epistatic effects on yield, a surprisingly strong interaction was found between a first locus linked to T153a and to B172 and a second locus linked to Satt277. The data were graphed as a series of cumulative distributions, as shown in Fig. 1. The data are the combined yield results from all field tests including bom Minnesota and Chile test graphs. Panel B is a standard distribution curve of yield (bu/ac) on die horizontal axis as a function of the number of plants. Panels B-E are cumulative distribution graphs in which yield, (horizontal axis) is graphed against me rank of each plant with respect to yield. In panel A, all plants having either the 'Archer' allele of T153a (A) or the 'Noir 1 ' allele of T153a (B) were graphed as separate curves. Essentially normal distributions were observed in the yield tests.
The mean yields (bu/ac) of these two subpopulations are set forth just above the panel.
In reviewing these data it is important to emphasize that individual plants are homozygous with respect to individual loci, although each locus could be derived from either 'Archer' or 'Noir
1. ' In panel E, the data are graphed for subpopulations that display eidier the 'Archer' allele of Satt277 (a) or the 'Noir 1 ' allele of Satt277 (b). Qualitatively, it can be seen that, whatever else was present in the genes of these two subpopulations, diose bearing the 'Noir 1' allele of Satt277 tended to be higher yielding. Satt277 was therefore considered to be linked to a QTL affecting yield. By comparison, in panel B, little difference in the distributions could be seen. In fact the curves cross one another. However, when subpopulations bearing a different assortment of both markers were compared, a striking difference emerged. In panel C, the subpopulation bearing bom the 'Archer' T153a and 'Archer' Satt277 alleles (Aa) was compared with diat bearing d e 'Archer' T153a and 'Noir 1' Satt277 alleles (Ab). In these combinations, little difference between me groups was observed; however, both subpopulations displayed higher yields than diose of panel B, as shown by slightly greater mean yields and slight right-ward shift of the entire distribution. However, in panel D, subpopulations having the 'Noir 1' T153a allele (B) displayed distinctively different yields depending on whether the Satt277 was from 'Archer' (a) or from 'Noir 1' (b). The combination of 'Noir 1' alleles of both the T153a locus and the Satt277 locus (Bb) displayed a greater yield than any other combination of the alleles at the two loci. The additive LLR was 27.67, indicating mat a strong modifier of the Satt277 QTL of 'Noir 1' is closely linked to T153a in 'Noir 1. '
Since T153a had no measurable effect on yield by itself, its effect was to modify die expression of the QTL linked to Satt277.
In Fig. 2, the data of Fig. 1 were subdivided to display only the yield data from the Chile field test and in Fig. 3 are shown the data for the 1996 Minnesota field test. In Fig. 4, die data of Fig. 1 were subdivided to display data of die 1997 Minnesota field test. The similarity of the data of Figs. 2, 3 and 4 indicate mat the environmental differences between these three tests did not contribute to die epistatic effect. In fact, the additive LLR for combined Chile and Minnesota tests is much greater than eid er test alone. Therefore, despite environmental differences, the cumulative effect of the data increases the significance of the epistatic effect and underscores the magnitude of die interaction in increasing yield and me closeness of the linkage. Yield can be affected indirectly by other quantitative traits. Increased length of time to maturity can increase yield by allowing soybeans to grow larger (given a long enough growing season). Similarly, increased plant height can allow more branches to bear more seed pods per plant. For practical plant-breeding purposes, it is preferred to use loci diat do not significantly alter other traits of agronomic importance. For example, increasing yield while also increasing plant height can be counter-productive if me taller plants are more susceptible to lodging. The preferred trait is one which can be introduced into an existing commercial variety without degrading o ier aspects of agronomic performance for which the variety has been developed. The QTL linked to Satt277 does not have a significant effect on odier traits that might indirectly affect yield.
Table 2 summarizes field data from field tests grown in Minnesota (MN96) and in Chile (CH95) standardized to averages of all plants in the Minnesota test (std MN96). In this test LLR and p-values were calculated for die interaction of the Satt277-linked QTL and its modifier, linked to T153a. The traits measured were height (HT), lodging (LD), days to maturity (R8), seed weight (SW) and yield (YD). By comparing the additive LLR values it can be seen that no significant effect existed regarding the traits height, lodging or days to maturity. A modest effect was noted for seed weight (LLR=7.81). By far the strongest effect was on yield itself (LLR =27.67). The yield effect controlled by me interaction of the two loci tested therefore had occurred without concomitant increases in height, lodging or days to maturity. These results stand in contrast to certain QTLs previously identified as affecting yield [Mansur et al. (1996)] . For example, in that study, a R79-linked QTL had a pronounced effect on maturity, while a Satt79-linked QTL had effects on botii height and maturity.
The modifying locus linked to T153a is also closely linked to anotiier molecular marker, B172. Both map to linkage group U3 (Table 1). A gene which modifies or regulates another gene can regulate several odier genes as well. The B172- or T153a-linked regulator function can be used to effect interactions with o ier QTLs. Therefore, the modifying locus linked to B172 and/or T153a can be useful by itself in a breeding program to enhance die activity of otiier endogenous QTLs in a varietal parent. Markers B172 and T153a are RFLP probes. B172 and KOllc are available from Biogenetic Services, Inc. , 2308 - 6th Street East, Brookings, SD 57006. T153a was developed in the inventors' laboratory as described by Lark et al. (1993). The sequence of the T153a RFLP probe is given in SEQ ID NO: 1 (See Table 3).
Example 2:
In this and die following examples, markers designated by a number preceded by "Satt" or "Sat" are microsattelite DNA markers isolated at die United States Department of
Agriculture, Agriculture Research Service, and are available upon request to Dr. Perry Cregan, USDA-ARS, Beltsville, MD [Cregan, P. et al. (1998) Genomics]. The markers A
397, A 489, and KOllc are available from Biogenetic Services, Inc. (address, supra).
Measurements of maturity (number of days from planting to maturity) divided by plant height (cm) in the 'Minsoy' X 'Noir 1' Rl population revealed a pair of interacting QTLs, one linked to marker Satt307, the other linked to marker KOllc. A high value for the maturity/height ratio is obtained for short plants which mature late. A low value for maturity /height is obtained for tall plants which mature early. Figure 18 A-D shows the cumulative distribution curves showing the interaction of the two QTLs, Fig. 18A shows the distributions of plants carrying the 'Noir 1' allele of KOllc(A) and of plants carrying the 'Minsoy' allele of K011c(B). KOllc maps to linkage group U12. Fig. 18D shows me distributions of plants having me 'Noir 1' allele of Satt307(a) and of plants having the 'Minsoy' allele of Satt307(b). Satt307 maps to linkage group U9. These data demonstrate that a 'Minsoy' QTL allele linked to Satt307 has an effect of increasing maturity /height, while little or no single-locus effect is observed linked to KOllc.
An interaction of die two loci is readily seen from Figs. 18B and 18C. In Fig. 18B, plants carrying the combination of 'Noir 1' allele of KOllc and 'Minsoy' allele of Satt307 (Ab) display higher maturity /height ratios than diose having me combination of 'Noir 1 ' K01 lc and 'Noir T Satt307. In Fig. 18C, the effect of the 'Minsoy' allele of KOllc in combination with each of ie Satt307 alleles is shown (Ba and Bb). The K01 lc marker is linked to a locus which exerts a modifying effect on die QTL linked to Satt307. A very large LLR of 17.5 characterizes the magnitude of die interaction.
Example 3:
A pair of interacting loci affecting seed protein content was identified in me 'Archer' X 'Minsoy' Rl population. These were linked, respectively, to the markers Sat__001 (modifying locus) and SattOOl. Field data were obtained in a 1997 Minnesota field test. The interaction was characterized by an LLR of 11.20. Cumulative distributions are shown in Fig. 7.
Example 4:
Further examples of interactions affecting yield are shown in Fig. 8 A-D and Fig. 13A- D. In Fig. 8, interacting loci linked to markers Satt365 and Satt567 were identified in a 'Minsoy' X 'Noir 1 ' Rl population. Field data were obtained in a 1993 Minnesota field Test. The interaction was characterized by an LLR of 9.82.
In Fig. 13 an even more striking interaction was identified in an 'Archer' X 'Minsoy' Rl population. The QTL was linked to marker Satt561, the modifying locus was linked to marker Satt507. Field data were obtained in a 1997 Minnesota field trial. The interaction was characterized by an LLR or 12.67.
Example 5:
Two pairs of loci displaying an interaction between a modifying locus and a QTL affecting flowering date were found in die 'Minsoy' X 'Noir 1' Rl population. A marker linked to die QTL was Sat_003, mapped to linkage group U 11, and die modifying locus was linked to Satt079, mapped to linkage group U9. Cumulative distributions are shown in Fig. 17A-D. Data were combined from field trials in Chile (1993) and Minnesota (1992). The interaction is characterized by an LLR of 10.36.
Another pair of interacting loci affecting flowering time were identified in me ' Archer '
X 'Minsoy' Rl population. The markers were Satt082 and R079. Data were obtained in a 1995 Minnesota field test. Cumulative distributions are shown in Fig. 16A-D. The interaction was characterized by an LLR of 10.06.
Example 6:
A pair of loci displaying an interaction between a modifying locus and a QTL affecting seed weight was found in me 'Archer' X 'Noir 1' Rl population. The marker linked to die QTL was Satt315, and die modifying locus was linked to Satt080. Cumulative distributions are shown in Fig. 9A-D. The interaction is characterized by an LLR of 10.58. The data were combined from all field trials.
Example 7:
Two interactions affecting oil content (g oil per lOOg seed normalized to 13 % moisture) were identified in the 'Archer' X 'Minsoy' Rl population. The first, based on data from a
1996 Minnesota field test, was identified between a QTL linked to marker Satt372B and a modifier linked to marker Satt346. Cumulative distribution curves are shown in Fig. 12 A-D.
The interaction was characterized by an LLR of 10.57.
The second interaction affecting oil content was observed from field data from a 1997 Minnesota test. The interacting loci were linked to markers Sat_039 and to Satt281, respectively. Cumulative distributions are shown in Fig. 10 A-D. The interaction was characterized by an LLR of 10.50.
Example 8:
The reproductive period (days from flowering to maturity) was affected by interacting loci in the 'Archer' X 'Minsoy' Rl population. The loci were linked to marker Satt256 and to Satt_112, respectively. Data were obtained in a 1995 Minnesota field test. Cumulative distribution curves are shown in Fig. 11 A-D. The interaction was characterized by an LLR of 11.44.
A second interaction affecting reproductive period was observed in die 'Noir 1' X
'Minsoy' Rl population. The loci were linked to marker Satt032 and to marker HSP176, respectively. Data were pooled from all field tests. The interaction was characterized by an LLR of 9.72. Cumulative distributions are presented in Fig. 14 A-D.
Example 11: Leaf area (cm2) was affected by an interaction identified in the 'Noir 1 ' X 'Minsoy' Rl population based on data obtained in a 1992 field test in Chile. The loci were linked to marker Satt066 and to marker SattlOO, respectively. Cumulative distributions are shown in Fig. 15A- D. The interaction was characterized by an LLR of 10.10.
The foregoing examples illustrate that interacting loci that significantly affect a variety of agronomic traits exist in plants, particularly self-pollinating plants such as soybean. Markers linked to such loci can be used in conventional plant breeding to improve or modify agronomic traits, by selecting for the combined presence of me desired alleles of the desired interacting pairs in the progeny of crosses. While the interactions have been observed in specific Rl populations, it will be understood that interacting loci are not limited to crosses with a specific line or to a specific Rl population or to a specific cross. The methods described herein can be reproducibly applied to identify interacting pairs of QTLs in any Rl line.
ul U4a u6 U8
Satt287 6.8 T028 25.4 Sattl52 9.1 Sattl84 23.3
Satt285 0.3 Satt509 050k 1.0 R013 9.2
Sct_046 42.8 25.4 BL004 9.1 R249b 1.9
KOllf 5.8 u4b Sattl59 13.9 K227 1.4
BL049b 0.0 Satt298 8.1 Sat_084 1.9 Satt032 1.6
Satt280 0.6 Satt597 3.6 Satt485 1.3 Sattl69 2.4
Sattl83 1.3 Set 026 0.2 Sattl25 5.3 A109g 1.5
A109h 1.7 G214e 2.9 Satt080 2.9 A235b 0.0
Sct_001 34.4 Sat 095 18.2 L,103a 0.0 Satt295 0.0
ScttOll 6.8 Satt359 0.2 B162 33.8 A109d 2.7
K375 1.8 Sat_123 16.1 Satt237 3.5 NP008 0.7
R189 2.5 Satt484 2.8 Sat 091 5.8 Satt203 4.0 050i Satt453 G214g 0.0 Sat 110 7.0
105.1 52.1 Satt234 7.8 Satt436 17.9
U2 u5 Satt257 6.3 A295 12.3
Satt573 8.3 Satt275 0.0 Sat 125 14.4 Satt071 5.5
K274 1.9 Sattl63 0.7 A363a 1.1 Sattl47 0.4
G214C 0.8 Satt038 12.3 A455 L058 0.5
G214z 0.2 Satt570 14.2 117.3 Sattl29
A510b 0.6 Sattl30 8.1 u7 92.4
Satt263 0.0 Sat_131 0.9 Satt276 10.1 u9
Satt045 0.3 Satt324 11.1 Satt449 0.0 A121 24.6
BL049a 0.4 L156 3.4 Satt042 3.7 L199a 11.3
R028 37.2 R017 2.4 Satt591 1.9 Sat 062 7.5
Satt553 2.7 L050b 5.8 Sattl55 2.4 Satt432 1.3
Satt231 Satt303 1.7 G214h 7.6 Satt281 4.0
52.5 Sattl38 5.9 R183 4.3 A109f 10.8 u3 Sattl99 0.2 Satt050 9.5 Satt291 34.2
Satt390 8.7 G214f 7.1 T153b 5.2 Satt305 19.5
Set 067 21.4 Satt012 6.7 NOD26 0.5 L059 14.2
Satt207 30.0 Satt288 25.6 Satt385 0.6 Sat_076 1.0
Satt315 3.6 Satt472 0.8 BL053b 3.7 Satt363 2.6
T153a 0.0 L002a 0.1 Satt545 3.5 Satt286 0.8
B172 2.4 A235a 1.8 A975a 10.8 B 032a 3.8
Sattl87 3.1 Sat 117 1.7 Satt599 2.4 Satt277 5.6
GMENOD2B 2.4 Sat_043 2.9 Sattl74 8.8 Satt489 21.4
Satt424 7.6 Sct_187 0.5 Satt211 14.4 Sct_028 3.5
Allla 10.6 A378 0.2 Satt200 Satt433 0.9
Sat 115 5.5 Sat 064 5.6 89.8 Satt316 7.3
Satt089 41.9 050J Satt372B 10.8
Satt329 24.4 119.7 Satt37l 3.5
Sattl58 0.0 Satt357
Sattl02B 2.2 188.4
Sat 131b 1.4 ulO
Satt333 30.3 L185 2.0
Satt409 7.9 A1 1b 2.0
Satt228 0.5 Satt353 2.0 144 10.8 A381 29.4
Satt378 Sattl92 12.2
214.7 Sctt009 8.1 BL046 58.4 Sattlδl 0.0
Noir X Archer Satt317 4.9
Sattl42 7.6
Satt302
TABLE 1 126 . 7 (first page) ull U13 U17 u22
Satt404 2. 1 Sattl76 0.2 B 053d 13.6 Sct_186 0. .1
GMSC514 1. 7 Satt040 15.0 Satt571 2.9 SOYGPATR 22. ,6
Satt590 8. 9 Satt252 4.2 Satt419 9.0 K001
Satt201 27. 1 Satt423 4.8 Satt367 7.1 22. .7
Satt540 2. 4 l 4.3 A352b 0.4 U24
R079 12. 9 Sattl60 4.2 L204b 0.3 Satt242 12. .3
Satt463 1. 7 Sat_039 48.9 BL002 5.1 Sattl02 0. ,5
Satt245 11. 9 Sat 133 23.2 A109e 23.1 A315 19. ,6
Sat_003 13. ,1 L063 1.5 Sat_105 21.9 Satt046 0. .4
Sattl75 6. 3 BL053h 1.0 Sat_104 10.9 Satt337 1. ,2
Sct_147 6. 8 HSP176 2.5 Satt292 14.4 G214v 1. ,5
Satt306 19. .8 R045 0.6 GMGLPSI2 2.7 Satt326 3. .5
M121 7. ,6 L050n 3.1 Sattl48 16.3 Satt240 2. .4
Sat 121 1. .7 Sat_120 0.4 Satt440 2.4 Satt559 1. .2
Satt571b 3. .0 Sct_033 1.7 L050f 3.9 Satt273 23. .3
Satt346 1. .9 Satt335 9.2 KOlld Satt260 5. .3
Satt2l0 16. .7 Sct_188 0.0 133.9 BL053i 9. .0
Satt308 3. .0 Satt072 12.1 ul8 A661 1. .8
Satt336 Satt490 3.3 Sat 112 3.5 Sattl96
148. .5 Sattl44 36.6 Satt411 7.8 81. .8 ul2 Sat_090 22.2 A053a 0.0 U26
A124 4. .3 Satt395 L194a G214 0. .0
Sattl35 14, .4 199.0 11.4 A352a 24. .4
Satt372 6. .7 ul4 ul9 Set 034 3, .2
Satt002 4. .2 Satt495 24.6 Sat 096 38.0 Sattl68 2. .2
Satt582 7. .2 Sat_071 16.0 Satt095 6.3 Satt416 8. .6
Sat_092 35. .8 Satt523 0.9 Sattl57 5.4 Satt304 5. .2
Fr2 1 .5 B124a 0.0 Satt558 9.5 Satt070 0. .4
Satt543 0 .2 A459 4.2 Satt296 22.3 BL057 4. .9
Satt226 0 .0 A204 1.5 Satt005 2.2 Satt066 10. .1
Satt082 4 .3 G2141 3.5 Satti4i 0.0 Satt534 6, .2
Sat_001 0 .7 Satt462 20.5 KOllb 7.6 Satt063 3 .4
Satt301 6 .6 Satt481 0.4 Satt041 2.8 Satt560
GMHSP179 1 .9 Sattl56 3.6 Satt546 7.4 68 .5 204C 3 .0 Sct_010 0.8 L0501 10.6 U28
Sattl86 11 .6 Satt076 5.6 Sat_069 11.5 G214y 0 .0
Satt031 0 .1 Sat_113 7.0 Satt274 Sat 085 0 .0
Sat_022 0 .0 Sattl66 24.4 123.7 Sat_077 1 .1
A141a 6 .5 Satt006 2.4 U21 Sattl36 50 .4
Satt386 A489 5.4 Sat 132 5.9 Satt338 1 .5
109 .1 K385 8.2 SattSOO 25.9 Sattl80 8.7
G214U 7.9 G214θ 2.8 175 --
Satt373 Satt259 16.6 61 .9
137.1 KOlle 2.8
Sattl88 0.4
Satt550 0.3
Satt094 0.3
Sattl73 0.0
Sat_110B 10.2
Satt563 2.1
Satt478 7.8
Satt477 4.4
Sattl23 14.8
Satt592 4.5
Satt581 13.4
Noir X Archer Sattl53 6.5
Sat 108
TABLE 1 118.8
(second page) ul U4 u7 U9 Satt287 7. Satt509 12.0 Satt276 16.2 Sat_130 31.2 Sct_046 39. Sattl97 9.5 Satt382 2.9 Sat_062 6.7 Scaa003 0. A262a 9.7 Satt449 0.0 Satt281 3.6 L050a 1. B 043 6.7 Satt454 0.8 Satt422 0.0 Satt406 23. Satt597 0.6 Satt364 2.5 Satt291 18.8 ScttOll 4. BL019b 2 K258 2 Satt305 0.0 Satt244 0. Sct_026 3 Satt073 0 Sattl70 5. K375 1. Sat_095 25 A053b 0 GMAC7L 28. Satt548 3. Sat_123 27 L194b 0 R092 0. Satt431 6 Satt484 11 AllOa 38 148 2. L050i Satt453 Satt385 6 Sat_076 3.
88.0 109.0 NOD26A 4 Satt286 4. u2 u5 Satt545 12 Satt277 3, Satt045 0.6 Sattl63 0.4 Satt599 2 Satt205 2. Satt204 0.0 Satt038 1.5 Sattl74 4 Sattl34 0. Satt268 2.7 Satt309 8.8 Satt211 1 SattlOO 5.0 G214b 1.4 Satt570 26.4 T155 A397 2.1 L163 1.0 Satt324 1 3 94.9 Satt079 2. Satt369 10.3 Sat_131 26 6 u8 K365 0. Alllb 5.7 Satt564 10 5 Satt605 4.5 Sct_028 3. C009C Satt012 10 3 Sattl69 0.0 Satt433 3.
21.7 Satt288 27 7 Satt321 4.0 Satt202 4. u3 Satt472 4 4 Satt254 0. Satt372B 10. Satt390 31.6 154 0.0 Sattl79 5. A676 0.0 Satt493 0.8 Sat_117 5.2 Satt203 0. Satt371 All Ob 0.0 A690b 1.1 Satt580 8. 142.9 Sattl77 6.6 Sct_187 2.1 Satt507 0. ulO Satt315 12.0 Sat_064 3.3 Sat_106 7 A262e 10. Sattl87 2.3 A586 Satt436 6 A089 8. GMENOD2B 2.8 129.6 Sat_036 43 Sattl92 1. A975b 23.6 U6 Sattl29 0.8 Satt442 4. Sat_115 1.8 Sattl52 11.6 Sattl47 Sctt009 17, Satt089 3.9 Satt009 9.4 80.5 Satt052 2. Sattll9 5 4 A280 1.7 Satt253 6.1 Satt233 2 9 Satt485 2.1 BL019a 8.4 G214d 4 6 Sattl25 19.6 Satt302 4.9 Satt437 5 2 Satt387 12.8 Satt317 2.6 Satt329 3 0 Satt521 4.0 Sattl42 0.2 Sat_040 0 5 Satt549 2.9 Sattlδl 16.8 Sattl02b 0.0 BL015 4.9 Satt434 5.3 Sattl58 0.6 Satt312 9.4 K007a Satt421 14.2 Satt257 9.3 89.2 B 053a 1.3 Satt022 A065 11.7 87.9 BL036a 1.9 Satt409 0.8 K644c 5.5 Satt228 8.0 Minsoy X Archer Satt429
150.8 TABLE 1 (third page) Ull ul3 Ul7 U21
GMSC514 2.3 Satt040 0.0 T098 20.6 Satt358 4. 4
Satt590 6.2 ' Sattl76 0.0 Satt562 0.7 Satt487 3. 5
Satt201 6.6 Satt586 1.8 Satt419 2.5 SattSOO 5. 4
SattlΞO 12.8 G214k 3.3 Satt367 4.4 Satt445 15. 5
Satt567 0.7 BL030 2.0 Satt587 5.2 Satt259 3. 2
Satt540 2.9 Sattl45 5.1 Sattl27 13.3 Satt347 14. 7
R079 10.5 Satt348 0.6 Sat_105 10.2 L050O 0. 9
Satt463 6.4 Satt252 10.8 Satt049 8.3 Satt576 0. 0
Satt220 2.9 Sat_039 10.0 K644b 0.9 Satt345 0. 5
A584 3.7 SattlδO 26.9 TOlOb 9.6 Satt094 0. 6
Sat_003 5.3 A401b 13.6 Satt330 5.7 Sattl88 0. 0
Sattl75 6.2 K265 8.0 Satt292 2.8 Sattl28 0. 2
Satt494 0.8 Sat_103 13.0 Sattl62 15.2 G214p 8. .4
Sct_147 4.4 BL0531 4.3 Sattl48 17.2 L050m 16. 5
Satt306 15.8 A186 0.4 Sct_189 1.7 Satt563 2. 2
Satt551 6.5 K644a 6.1 Satt478b Satt478 28. .0
Sat_121 9.9 K007b 2.0 118.3 Satt592 5. ,6
Satt346 15.4 Sct_033 3.4 Ul8 Satt581 9. 8
Satt308 2.6 Satt335 10.9 T183 2.6 Sattl53 1. ,3
Satt336 Satt072 9.2 Satt575 6.2 Satt243 5. .5
122.0 Satt490 5.8 Sat_112 3.9 TOlOa 0. .0 ul2 Sattl44 1.8 Satt411 6.6 B 027 15. .8
BL053k 12.1 L195 4.7 G214n 1.6 ScaaOOl ScttOOδ 5.0 K014 10.0 Satt384 142. .3
L072 8.0 Satt554 7.5 21.0 U24
A401a 0.5 Satt522 12.4 ul9 Satt539 3. .0
G214i 26.6 Sat_090 18.4 Sattl57 16.0 Sat_087 9. .8
Satt372 13.6 Sat_074 Satt542 21.8 Satt242 2. .5
Satt582 0.3 192.3 Satt290 2.8 Sat_119 12. .1
Sat_092 16.1 ul4 Satt005 1.2 R051 4. .2
Satt397 9.8 Satt495 8.7 Sat_089 6.7 Sattl37 2 .4
Satt389 5.3 BL007 2.2 Satt041 14.5 Sattl78 2 .6
Satt514 0.0 Sattl82 3.2 Sattl72 0.0 G214q 0 .0
Satt528 0.0 Satt238 14.5 Sat_069 15.9 Satt046 0 .0
Satt311 1.3 Sattl43 15.6 Satt459 1.6 Satt544 0 .3
Satt464 0.1 Satt462 3.1 Satt274 20.4 C009B 3 .4
Satt488 0.1 L050d 27.4 Satt271 Satt326 0 .0
Satt574 0.1 Sattl56 2.1 100.9 SattOOl 1 .1
Satt543 0.6 Satt481 2.7 Frl 1 .0
Satt082 2.2 Sct_010 1.0 Satt273 1 .4
Sat_001 0.0 Satt076 5.1 Satt240 30 .7
Satt305B 1.9 Sat_113 3.1 Satt260 27 .3
G214J 6.3 Satt527 0.5 Sattl96 1 .3
GMHSP179 8.2 Satt535 3.9 Sat_020 9 .3 Satt310 0.0 050e 18.7 Satt588
Sattl86 9.6 Sattl66 48.0 112 .5
Satt031 0.0 Satt513 0.0 Minsoy X Archer Satt413 7.2 Satt373 2.3
Satt256 6.9 G214U 2.3 Sct_137 A802 TABLE 1 142.1 164.3 (fourth page) U26
LI91 13. ,5
Sattl26 0. .0
G214w 16. .1
T270 54. .3
Satt416 15. .5
Satt304 7. .0
Satt020 0. .2
G214r 3. .4
G214S 3. .0
L201 3. .3
Satt066 6. .6
Satt534 5, .0
Satt063 13. .5
A234 23. .0
G214t
164, .4
U28
L192 2 .9
Sattl36 1. .4
Sat_077 0 .2
Satt399 0 .2
Sat_085 0 .7
G214X 13 .0
A063 6 .1
Satt369B 26 .0
Satt338 3 .3
SattlδO 7 .2
L175
60 . 8
Minsoy X Archer
TABLE 1 (fifth page) ul u3 u4 U5
Satt405 11.6 A170 1.3 T028 17. .5 Sattl63 3. 3
Satt285 0.0 Satt390 4.6 KOlla 21. ,0 Satt038 1. 9
A060a 3.1 Sct_067 12.9 A109C 3. .9 Satt309 16. 7
Set 046 25.3 Satt207 7.0 Satt509 13. .9 Sattl30 0. 9
Satt456 0.0 Satt493 0.6 Sattl97 8. .1 Satt235 8. 3
Satt529 0.0 Satt589 1.0 A262a 3. .2 Sat_131 1. 3
L216a 0.2 Sattl77 1.1 T092 13. .5 Satt324 5. 2
L050a 0.0 AllOb 8.1 Kl 0. .9 BL036b 2. 0
Sattl83 0.6 Satt315 4.5 BL043 0, .0 Satt394 0. 0
Satt596 0.0 L199b 0.0 Satt298 9, .2 L156 0. 1
Scaa003 0.3 T153a 0.0 Ξct_026 0 .2 Sattllδ 3. .1
Satt414 0.0 A262b 1.3 G214e 1 .8 A510C 1. ,1
Sattl32 0.4 I 0.3 L204e 0, .8 ScttOlO 0. ,0 gl73a 0.8 B172 0.4 Satt430 0 .0 R017 1. ,9
Satt380 0.5 BL024 1.9 Satt583 0 .0 L002b 0. ,6
Sct_001 0.0 Sattl87 1.3 Satt415 0 .1 L050b 5. .3
Satt215 22.8 A510a 3.5 Sat_095 19 .1 Satt566 0. .0
Satt244 4.9 GMEN0D2B 2.2 Sat 123 22 .7 Satt303 0. .0
K375 1.8 A975b 0.2 L050q 8 .1 Sat_088 2. .2
R189 0.4 Satt424 5.0 Satt453 Satt564 0. .0
Satt548 4.9 Allla 16.8 145 .9 Sattl38 3, .3
G815 6.0 Sat_115 4.9 Sattl99 0 .0
Satt431 9.5 Satt089 5.0 Satt505 0 .7
A132 Sattll9 0.0 G214f 3 .1
93.3 Satt377 9.4 Satt012 0 .0 u2 Satt233 3.2 Satt517 10 .2
Satt598 0.0 G214d 3.8 Satt288 0 .0
Satt573 1.9 Satt437 1.4 Satt588b 5 .7
Sat 136 4.8 Satt327 1.2 T005 16 .2
A510b 0.0 Satt329 1.7 Satt472 1 .8
G214C 0.1 Satt508 0.0 A235a 0 .3
Sat 107 0.1 A690a 1.7 Sattl91 0 .3
K274 0.0 Sattl58 1.3 L002a 2 .9
Satt491 0.3 Satt470 0.0 L154 12 .7
Satt602 0.1 Satt421 1.9 A690b 2 .0
Satt300B 1.3 Sat 131b 0.1 Set 187 2 .4
R028 0.0 Satt555b 0.4 A378 1 .6
Satt045 0.0 Sat 040 0.1 A586
Sattl85 0.0 Sat 097 0.4 117 . 6
Satt355 0.0 K443 1.0
Satt483 0.0 Satt333 11.6
Satt452 0.0 A505 0.4
Sattll7 0.0 Satt455 0.0
BL049a 0.6 BL053a 0.7
B124b 1.2 A065 12.4
A427 0.4 BL036a 1.1
S123 126 0.0 Satt409 9.7
G214b 2.0 Satt228 0.2
L163 4.3 L144 6.1
Satt369 9.4 Satt538 0.0
Satt553 0.0 Satt429 3.3
C009C 0.0 Satt378
Satt231 3.3 157.1 Minsoy X Noir
A711
30 . 4
TABLE 1 (sixth page) u6 u7 U8 U9
L2 23. 2 Satt276 9. 7 Sattl84 1.9 A121 12.8
BL004 1. 5 Sattl65 4. 9 M373 17.2 Sat 130 10.3
Sattl59 0. 5 Satt364 0. 8 Satt531 0.0 A059 1.6
Sattl52 1. 0 Satt382 0. 0 R013 16.0 L199a 0.6
Satt009 2. 2 Satt248 0. 0 K227 4.2 A262d 9.3
Satt530 0. 0 Satt042 0. 5 Satt368 0.0 Sat_062 5.9
Sat_084 0. 9 Satt471 1. 9 Satt482 0.0 Satt432 2.7
A280 0. 7 A329 1. 4 Satt032 0.4 Satt281 3.1
Satt393 0. 0 SattS91 0. 0 Satt605 0.4 Satt520 0.0
Satt584 8. 4 K258 0. 9 Satt532 0.0 Satt422 0.1
Satt080 4. 8 Satt300 0. 0 Satt502 0.8 Satt291 31.8
Satt387 0. 0 Sattl55 1. .0 Satt547 0.2 Sattl70 3.4
L103a 0. ,0 Satt073 0. .3 Satt603 0.0 A426 1.2
B162 7. ,5 AllOa 0. .2 Satt342 0.2 GMAC7 9.5
Rpg4 14. ,8 L194b 0. .2 Satt421b 2.5 L059 8.5
Satt521 4. .8 G214h 0. .2 A235b 0.0 Satt363 0.0
Satt549 2. .2 A053b 6. .5 Satt383 0.0 Satt376 0.0
Sll 0, .1 A064b 0. .0 Sattl79 2.2 L148 0.8
GMABAB 1, .0 R183 2, .1 NP008 0.1 R092 0.4
Satt339 0. .4 Satt050 9, .2 Satt402 0.1 Sat_076 1.2
Satt237 0, .0 T153b 1, .6 Satt203 1.7 Satt286 2.2
BL015 1. .2 A262c 11 .3 Satt370 2.8 BL032a 3.2
Satt255 0 .0 Satt385 3 .8 Satt507 1.7 Satt277 4.5
Sat_091 3 .4 BL053b 1 .6 Sat 110 0.0 Satt557 0.0
Satt312 1 .7 Satt545 3 .3 Sat_106 1.2 Satt365 0.6
G214g 0 .0 A975a 5 .4 Sattl98 0.6 Satt489 0.0
Satt234 19 .5 K636 9 .4 Satt439 0.0 Satt319 0.0
Ξatt022 0 .8 Sattl74 3 .5 Satt436 1.0 Sattl34 0.0
Sat 125 10 .1 Satt200 0 .5 Satt468 2.6 Satt289 0.0
A455 4 .8 T155 0 .0 Sat 036 14.2 A109a 0.2
A363a Satt236 0 .5 A295 9.9 L050c 0.0
115 .7 Satt511 0.8 Satt071 9.1 SattlOO 1.5
Satt258 0 .0 Satt408 1.9 Satt460 0.0
B170 0 .0 Sattl47 4.0 A397 0.4
Satt225 L058 3.7 Satt079 0.9
82 .1 C063 BL029 0.4
101.1 K365 0.6
Satt307 0.0
Sct_028 3.3
Satt316 1.2
Satt202 3.6
C056 20.5
Satt371 4.3
A676 2.9
Satt357
154 . 4
Minsoy X Noir
TABLE 1 (sevendi page) ulO ul2 ul3
L185 9.0 BL032b 2. 1 Satt569 0. ,0 BL007 0. ,7
Pv7 1.1 A064a 7. 4 G214k 0. ,0 BL010 1. ,2
Satt353 2.5 L072 2. 2 Sattl93 0. ,0 Satt446 0. ,2
A381 3.2 Sctt008 9. ,2 Satt030 0. .2 Satt232 2. ,3
R249a 23.0 Satt328 0. ,0 Satt343 0. .0 Sattl82 6. .8
A089 10.5 A401a 1. ,3 Satt325 2. .2 Satt238 0. ,7
Sattl92 1.2 G214i 3. .4 GMRUBP 2. .8 Sat_071 0. ,0
Satt442 1.3 A124 1. .9 BL030 0. ,7 BL039 6. .8
BL053C 1.3 Satt458 0. .8 Sattl45 0. .0 Satt523 3. .1
BL046 10.0 Sattl35 17. .2 Satt269 8. .4 B124a 0. .0
Satt296B 0.0 Satt002 9. .0 Satt423 3. .5 A459 0. .0
A131 0.0 Sat 092 0, .4 Wl 5. .3 Sattl43 0. .0
A404 1.6 Sattl54 9, .8 Sat_039 37, .2 Sat_134 0. .6
Sat_122 0.9 Satt397 11, .4 Sat 133 0. .0 Satt398 0. .0
Satt052 1.4 Satt389 4. .9 K265 13. .6 Satt418 0. .8
Satt279 0.7 Satt311 0, .0 L063 0. .4 A204 0. ,9
Satt253 0.0 Fr2 3. .2 A186 2. .4 Satt313 0. .8
Satt314 5.5 Satt543 2, .9 HSP176 0. .4 Satt284 0. .2
BL019a 7.4 Sat 001 0, .4 Satt334 0. .0 G2141 0. .7
Ps 3.8 G214J 0, .0 K644a 1, .0 G214m 5. .2
Satt302 5.0 Satt301 0 .6 R045 0, .0 Satt462 3. .9
Satt293 0.0 L026b 1 .2 Rpgl 3 .3 L050d 18, .0
Sattl42 4.1 KOllc 5 .8 Satt510 0 .0 Satt481 1, .4
A748 0.1 L204C 14 .7 Set 033 1 .8 Sattl56 15 .3
Satt317 17.8 A141a 0 .9 Sat_120 8 .2 Sat_113 2 .1
Satt434 9.5 Sat 086 6 .8 A708 0 .7 Satt527 0 .4
K007a Satt256 0 .5 Ξct_188 9 .1 L050e 0 .2
121.0 Satt386 2 .9 Satt490 5 .9 Satt561 5 .4 ull Sct_137 L195 2 .6 Sat 099 9 .9 Satt404 9.1 K014 7 .2 G173b 2 .6
Satt590 7.4 121 .1 Satt554 7 .4 Dtl 2 .6
Sattl50 17.5 Satt522 48 .9 Satt006 3 .1
Satt567 1.9 Sat_074 1 .3 A489 6 .3
Satt435 0.0 Satt395 L103b 0 .2
R079 0.0 175 . 0 K385 5 .6
A060b 6.9 Satt513 0 .4
Satt463 2.8 Satt373 3 .8
Satt245 4.1 A363b 0 .0
A584 0.4 A802 0 .0
Satt220 2.1 B174a
Satt323 0.3 112 . 4
L204d 0.0
Satt536 0.6
Sat_003 7.1
Satt494 8.4
Satt306 14.3
M121 1.1
Satt551 0.5
BL025 7.8
Sat_121 1.3
Satt250 6.3
Satt210 13.5
Satt336 2.4 P M. fainsoy X Noir
Satt308
116 . 0 TABLE 1 (eighth page) tr1 > Ω n cn ι-3 p n ω ω ?. _.' p cn cn cn cn ω ?. cn
H O to pi i H tr o o o o i j pi pj pi cn pj vo in H rt rt 00 ) μ- rr rt H in to rt Ω rt rt rt rt it* rr rr it* ui ιf*| rt ui in I rt o cn rt tr" rt rr rt| it* rt ui pj pi H Ul tr H if* (X. f-ti p> t-> TJ H M Ul I-4 tr o
CO H -J CD if* ii* cn cn vo ui o it* it* to ui VD O co to H H I-1
H o o to VD cn t o VO to o Ul H O H Ul H Ul Ul l o if* o it* H cn t -j o O to o o -J O l o -J M σi H o to O m m n Ω cn cn CO i π cn cn cn
H pi Ul to pi pi pi o pi Pi Pi O rt o Ul rt ιf- H rt rt rt H rt rt rt rr H Ul rt UJ •M rt rt H rt rr O to Ul i if* pi o ui o tr o H Ul
O cr H M pi -J to J t- lt* it* to I-1 if*
O O o if* t ^1 -j ^1 -j to i- VO co UJ Ul ^j oo to UJ o ra
I-1 ^1 t- Ul H H
O H o o o o cn o 00 00 it* H H H H to il* ^J O VO f* -o en Ul o o -0 H l in
F cn CO -
H O i pi
-0 -J rt rt
Ul t* rt rt i c n 03 if* o it* H H ■f*
M in ui to
u24 u26
K401 23.9 Satt577 9. ,4
Satt539 2.3 L191 2. .1
Sat 087 5.6 T270 9. .2
Ep 3.0 Sattl26 27. .7
Satt242 2.6 Sct_034 4. .7
Sat_119 18.4 Sattl68 1. .5
R051 0.9 Satt416 7. .7
A315 0.0 Sat 083 3. .0
Sattl02 6.4 Satt556 0. .0
Sattl37 3.4 Satt474 0. .0
Sattl78 4.1 Satt070 0, .1
Satt555 0.0 Set 094 0, .1
Satt349 1.0 Satt272 0. .1
Satt247 0.0 Sattl22 0. .1
Satt375 0.0 Satt020 0, .1
Satt381 0.0 G214r 0 .2
Satt552 0.0 BL057 0 .9
Satt553b 0.0 L201 0, .2
Satt441 0.0 G214S 3 .6
Satt417 0.2 Satt066 8 .9
Sattl67 0.2 Satt534 12 .6
Satt046 0.1 A516 3 .5
Sattl24 0.1 A234 0 .0
SOYPRP1 0.0 Satt560 10 .3
G214q 0.1 G214t
Satt264 0.1 106 .1
C009b 0.2
Satt518 0.4
Satt337 1.9
Sat_116 0.0
Satt326 0.2
SattOOl 0.7
Satt559 0.0
Frl 0.1
Sat_lll 0.6
Sat_043 28.5
Satt475 0.0
Satt260 22.4
R 5.1
Sat 020 1.0
A661 12.5
Satt588
146 . 4
Minsoy X Noir
TABLE 1 (tenth page) TABLE 2
Table 3 SEQ ID NO:
CTJC-^ -K-^ACATAACCAGAGT CAACTC^
GAGGAC-TCC--ΑCCCCATCλT-X-^^
COVGTCCTC-A-A-CC-WTCΛ^
- -X-ΛCKK-y v--AAATAAaATCGAA Tσ^
CX3-ftAG-ATGAAa--A£^QAAC-^C T^
T TTσ<-OClAATAC-K-ΛaTGAGAGCT G^ SEQUENCE LISTING
(1) GENERAL INFORMATION:
(i) APPLICANT: THE UNIVERSITY OF UTAH
(ii) TITLE OF INVENTION: Soybean Having Epistatic Genes Affecting Yield
(iii) NUMBER OF SEQUENCES: 1
(iv) CORRESPONDENCE ADDRESS:
(A) ADDRESSEE: Greenlee, Winner and Sullivan, P.C.
(B) STREET: 5370 Manhattan Circle, #201
(C) CITY: Boulder
(D) STATE: Colorado (Ξ) COUNTRY: US
(F) ZIP: 80303
(v) COMPUTER READABLE FORM:
(A) MEDIUM TYPE: Floppy disk
(B) COMPUTER: IBM PC compatible
(C) OPERATING SYSTEM: PC-DOS/MS-DOS
(D) SOFTWARE: Patentin Release #1.0, Version #1.30
(vi) CURRENT APPLICATION DATA:
(A) APPLICATION NUMBER: WO
(B) FILING DATE: 01-MAY-1998
(C) CLASSIFICATION:
(vii) PRIOR APPLICATION DATA:
(A) APPLICATION NUMBER: US 60/045,021
(B) FILING DATE: 02-MAY-1997
(vii) PRIOR APPLICATION DATA;
(A) APPLICATION NUMBER: Unassigned
(B) FILING DATE: 30-APR-1998
(viii) ATTORNEY/AGENT INFORMATION:
(A) NAME: Greenlee, Lorance L
(B) REGISTRATION NUMBER: 27,894
(C) REFERENCE/DOCKET NUMBER: 24-96WO
(ix) TELECOMMUNICATION INFORMATION:
(A) TELEPHONE: 303-499-8080
(B) TELEFAX: 303-499-8089
(2) INFORMATION FOR SEQ ID NO : 1 :
(i) SEQUENCE CHARACTERISTICS:
(A) LENGTH: 884 base pairs
(B) TYPE: nucleic acid (C) STRANDEDNESS: single
(D) TOPOLOGY: linear
[ii) MOLECULE TYPE: DNA (genomic)
(xi) SEQUENCE DESCRIPTION: SEQ ID NO : 1 :
CTGCAGGTAC ATAAGCAGAG TTCAACTCGT GCGATCCTGA GAAAACTCCA TTAGGATATT 60
CCTACCTTCT AGACTGGTGT GAACATTAGC ATTCATCAAA TTTCTTATGA TTTTCAGCAT 120
CTAATGTCGT TCAACAAGCA TCCTGTATCG TAAATCTTCA AGTGATCATA CTAATCGCGT 180
TCTAAGGCTA AACATGCAAA ACCTAGCTGT GAAAATAACT CTCATAGCAT AGCATTTGAA 240
TGATTCACCA ATCAATTCGG AACAATCGAG AAACCTAGCG ACGCACCTGC AATTGGCGAT 300
CAATCTGCGT GGCGGGATCC TTCATGGTGT GGCCGTGCGT GTTGAAGCTG AGCGACGAGA 360
AGAACGGCAC GAAGAACGTT GGGCGAGTTC CGGATCCGAA ACCCTGACCG CTTCTCTGCC 420
CTCGCCGGCG TTGAGGAGCG ACCCCATCAT CCAGTACTCC ACGCTGTGCT GCTTCTTCAG 480
CCCCCAGTTC ACCGGCCACG CCGGCCAGTC CTCAACGGTG ACGGGCGTCT CCGACGCGCT 540
CCGGCGGTCA ATCATGCCGA CGTTGAATCG GCGAGGGAGA TCGTACATGA AAACCCGAAG 600
AGGAGGCTCG GGTGCACAGG GAGCAGGTGC AGCCGCGGGT AACTTTAGGC GAGGGAAGAA 660
ATAAGATCGA ATTGTCGAGG GTGCCAATGA AAATTGAGTA AGAGAAGACG AGCAAGAGCA 720
CGAAGATGAA CGAGAGAACC ACTTTTCCAT ACATTGCAGT TTTTTCTTCT TCTTGTTTTG 780
TTTTTTGAAA TATTTTGGGG AATAGCAGTG AGAGCTTGAT TGATGCTTGT ACGTTATCTT 840
CTTCTTCTGC AGTATATATT ATATAATTAT AAATTGTGGA TTGT 884

Claims

WE CLAIM:
1. A soybean plant having genes of a first parent and comprising a specific molecular marker-linked locus of a second parent, said marker-linked locus being selected from the group consisting of a modifying locus and a quantitative trait locus affecting an agronomic trait.
2. The soybean plant of claim 1 wherein the modifying locus is linked to molecular marker T153a.
3. The soybean plant of claim 1 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a.
4. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting yield.
5. The soybean plant of claim 4 wherein the modifying locus is linked to T153a.
6. The soybean plant of claim 4 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a.
7. The soybean plant of claim 4 wherein the quantitative trait locus is linked to Satt277.
8. The soybean plant of claim 4 wherein the quantitative trait locus is linked to the 'Noir 1 ' allele of Satt277.
9. The soybean plant of claim 4 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a and the quantitative trait locus is linked to the 'Noir 1 ' allele of Satt277.
10. The soybean plant of claim 4 wherein the quantitative trait locus is linked to Satt567 and the modifying locus is linked to Satt365.
11. The soybean plant of claim 4 wherein the quantitative trait locus is linked to Satt561 and the modifying locus is linked to Satt507.
12. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting maturity /height.
13. The soybean plant of claim 12 wherein the quantitative trait locus is linked to Sat307.
14. The soybean plant of claim 12 wherein the modifying locus is linked to KOI lc.
15. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting seed protein content.
16. The soybean plant of claim 15 wherein the quantitative trait locus is linked to SatOOl .
17. The soybean plant of claim 15 wherein the modifying locus is linked to Sat_001.
18. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting flowering date.
19. The soybean plant of claim 18 wherein the quantitative trait locus is linked to R079.
20. The soybean plant of claim 18 wherein the modifying locus is linked to Satt082.
21. The soybean plant of claim 18 wherein the quantitative trait locus is linked to Sat_003.
22. The soybean plant of claim 18 wherein the modifying locus is linked to Satt079.
23. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting seed oil content.
24. The soybean plant of claim 23 wherein the quantitative trait locus is linked to Satt281.
25. The soybean plant of claim 23 wherein the modifying locus is linked to Sat_039.
26. The soybean plant of claim 23 wherein the quantitative trait locus is linked to Satt372B .
27. The soybean plant of claim 23 wherein the modifying locus is linked to Satt346.
28. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting seed weight.
29. The soybean plant of claim 28 wherein the quantitative trait locus is linked to Satt315.
30. The soybean plant of claim 28 wherein the modifying locus is linked to Satt080.
31. The soybean plant of claim 1 wherein the plant comprises both a modifying locus and a quantitative trait locus affecting reproductive period.
32. The soybean plant of claim 31 wherein the quantitative trait locus is linked to Satt_l 12.
33. The soybean plant of claim 31 wherein the modifying locus is linked to Satt256.
34. The soybean plant of claim 31 wherein the quantitative locus is linked to HSP176.
35. The soybean plant of claim 31 wherein the modifying locus is linked to Satt032.
36. A method of soybean breeding comprising crossing a first, varietal parent with a second, donor parent, said donor parent bearing a molecular marker linked locus selected from the group consisting of a modifying locus and a quantitative trait locus affecting yield, thereby producing a population of FI progeny plants, selfing the FI progeny plants, thereby producing a population of F2 plants, at least a portion of which are homozygous for the molecular marker-linked locus, identifying the F2 plants that are homozygous for a molecular marker-linked locus.
37. The method of claim 36 wherein the modifying locus is linked to molecular marker T153a.
38. The method of claim 36 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a.
39. The method of claim 36 wherein the step of identifying F2 plants comprises testing for the presence of both the modifying locus and the quantitative trait locus.
40. The method of claim 39 wherein the modifying locus is linked to T153a.
41. The method of claim 39 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a.
42. The method of claim 39 wherein the quantitative trait locus is linked to Satt277.
43. The method of claim 39 wherein the quantitative trait locus is linked to the 'Noir 1 ' allele of Satt277.
44. The method of claim 39 wherein the modifying locus is linked to the 'Noir 1 ' allele of T153a and the quantitative trait locus is linked to the 'Noir 1' allele of Satt277.
45. The method of claim 36 wherein the modifying locus is linked to a marker selected from the group Satt365, KOllc, Satt507, Sat_001, Satt082, Satt079, Sat_039, Satt346, Satt080 or Satt256 or Satt032.
46. The method of claim 36 wherein the quantitative trait locus is linked to a marker selected from the group Satt307, SattOOl, Satt567, Satt561, Sat_003, R079, Satt281, Satt372B, Satt315, Sat_112 or HSP176.
47. The method of claim 36 wherein the modifying locus and the quantitative trait locus are linked to pairs of markers selected from the group of pairs Satt567 and Satt365, Satt561 and Satt501, KOllc and Satt307, SattOOl and Sat_001, Satt281 and Sat_039, Satt372B and Satt346, Satt079 and Sat_003, Satt082 and R079, Satt315 and Satt080, Sat_l 12 and Satt256, and HSP176 and Satt032.
48. A self-pollinating plant having genes of a first parent and genes of a second parent, said genes of the second parent comprising a modifying locus and a quantitative trait locus affecting yields, the modifying locus interacting with the quantitative trait locus with an LLR at least about 9.
49. The plant of claim 48 comprising a soybean variety wherein the modifying locus and the quantitative trait locus are linked to pairs of markers selected from the group of pairs
Satt Xπ and SattOOl, Satt365 and Satt567, Satt080 and Satt315, Sat_039 and Satt281, Satt256 and Sat_112, Satdt346 and Satt372B, Satt032 and HSP176, Satt066 and SattlOO, and Satt082 and R079.
50. The plant of claim 48 wherein the modifying locus interacts with the quantitative trait locus with an LLR of at least about 12.
51. The plant of claim 50 comprising a soybean variety wherein the modifying locus is linked to marker Satt507 and the quantitative trait locus is linked to marker Satt561.
52. The plant of claim 48 wherein the modifying locus interacts with the quantitative trait locus with an LLR of at least about 15.
53. The plant of claim 52 comprising a soybean variety wherein the modifying locus is linked to marker KOl lc and the quantitative trait locus is linked to marker Satt307.
54. The plant of claim 48 wherein the modifying locus interacts with the quantitative trait locus with an LLR of at least about 18.
55. The plant of claim 54 wherein the modifying locus is linked to T153a and the quantitative trait locus is linked to marker Satt277.
EP98920117A 1997-05-02 1998-05-01 Soybean having epistatic genes affecting yield Withdrawn EP1006781A4 (en)

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US70281 1987-07-06
US4542197P 1997-05-02 1997-05-02
US45421P 1997-05-02
US7028198A 1998-04-30 1998-04-30
PCT/US1998/008866 WO1998049887A1 (en) 1997-05-02 1998-05-01 Soybean having epistatic genes affecting yield

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CA2572761C (en) * 2004-07-09 2015-02-24 Monsanto Technology Llc Soy compositions having improved organoleptic properties and methods of generation
EP1781821A2 (en) 2004-08-06 2007-05-09 Pioneer Hi-Bred International, Inc. Genetic loci associated with phytophthora tolerance in soybean
WO2006039449A1 (en) * 2004-09-29 2006-04-13 Monsanto Technology Llc High yielding soybean plants with low linolenic acid
CN101475939B (en) * 2007-12-31 2012-01-18 东北农业大学 Quantitative inheritance loci related to soybean 100-seed weight and soybean yield and use thereof
CN101613753B (en) * 2009-08-07 2012-06-06 中国科学院遗传与发育生物学研究所 A pair of special primers for assisted evaluation of relevant locus of soybean seed weight and method thereof
WO2012158897A1 (en) 2011-05-17 2012-11-22 National Ict Australia Limited Computer-implemented method and system for detecting interacting dna loci
CN103320427B (en) * 2012-03-20 2014-12-10 东北农业大学 Method for assisting in identifying resistance of soybeans to soybean mosaic viruses
CN103045588B (en) * 2012-12-11 2014-08-20 南京农业大学 Molecular marker of major QTL (Quantitative Trait Locus) of soybean seed protein content and application thereof
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BR9809203A (en) 2000-06-27

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