CN110106273B - Major QTL influencing thousand-grain weight of wheat and application thereof - Google Patents
Major QTL influencing thousand-grain weight of wheat and application thereof Download PDFInfo
- Publication number
- CN110106273B CN110106273B CN201910365528.1A CN201910365528A CN110106273B CN 110106273 B CN110106273 B CN 110106273B CN 201910365528 A CN201910365528 A CN 201910365528A CN 110106273 B CN110106273 B CN 110106273B
- Authority
- CN
- China
- Prior art keywords
- qtl
- thousand
- wheat
- grain weight
- weight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 241000209140 Triticum Species 0.000 title claims abstract description 24
- 235000021307 Triticum Nutrition 0.000 title claims abstract description 24
- 239000003550 marker Substances 0.000 claims abstract description 16
- 108090000623 proteins and genes Proteins 0.000 claims abstract description 16
- 238000009395 breeding Methods 0.000 claims abstract description 12
- 230000001488 breeding effect Effects 0.000 claims abstract description 12
- 210000000349 chromosome Anatomy 0.000 claims abstract description 7
- 230000000694 effects Effects 0.000 claims abstract description 6
- 230000001737 promoting effect Effects 0.000 claims abstract description 4
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 claims abstract description 4
- 108700006291 Sucrose-phosphate synthases Proteins 0.000 claims description 3
- 238000012214 genetic breeding Methods 0.000 abstract description 2
- 238000004458 analytical method Methods 0.000 description 9
- 230000002068 genetic effect Effects 0.000 description 8
- 238000013507 mapping Methods 0.000 description 6
- 238000000034 method Methods 0.000 description 6
- 238000000540 analysis of variance Methods 0.000 description 4
- 235000013339 cereals Nutrition 0.000 description 4
- 240000007228 Mangifera indica Species 0.000 description 3
- 235000014826 Mangifera indica Nutrition 0.000 description 3
- 230000000996 additive effect Effects 0.000 description 3
- BHELIUBJHYAEDK-OAIUPTLZSA-N Aspoxicillin Chemical compound C1([C@H](C(=O)N[C@@H]2C(N3[C@H](C(C)(C)S[C@@H]32)C(O)=O)=O)NC(=O)[C@H](N)CC(=O)NC)=CC=C(O)C=C1 BHELIUBJHYAEDK-OAIUPTLZSA-N 0.000 description 2
- 235000004936 Bromus mango Nutrition 0.000 description 2
- 240000003433 Miscanthus floridulus Species 0.000 description 2
- 235000009184 Spondias indica Nutrition 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000003205 genotyping method Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000003147 molecular marker Substances 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 108700028369 Alleles Proteins 0.000 description 1
- LZZYPRNAOMGNLH-UHFFFAOYSA-M Cetrimonium bromide Chemical compound [Br-].CCCCCCCCCCCCCCCC[N+](C)(C)C LZZYPRNAOMGNLH-UHFFFAOYSA-M 0.000 description 1
- 108091026890 Coding region Proteins 0.000 description 1
- 108020004414 DNA Proteins 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 238000001276 Kolmogorov–Smirnov test Methods 0.000 description 1
- 102000003960 Ligases Human genes 0.000 description 1
- 108090000364 Ligases Proteins 0.000 description 1
- 240000002853 Nelumbo nucifera Species 0.000 description 1
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 1
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 1
- 241000212324 Oenanthe <angiosperm> Species 0.000 description 1
- 241000767840 Semiaquilegia Species 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000009394 selective breeding Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
- 210000001519 tissue Anatomy 0.000 description 1
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING 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
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
- C12Q1/6895—Nucleic 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
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING 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
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/13—Plant traits
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING 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
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/156—Polymorphic or mutational markers
Landscapes
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Organic Chemistry (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Health & Medical Sciences (AREA)
- Biotechnology (AREA)
- Zoology (AREA)
- Wood Science & Technology (AREA)
- Immunology (AREA)
- Mycology (AREA)
- Microbiology (AREA)
- Molecular Biology (AREA)
- Botany (AREA)
- Biophysics (AREA)
- Physics & Mathematics (AREA)
- Biochemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Genetics & Genomics (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
The invention belongs to the field of wheat genetic breeding, and provides a main effect QTL influencing the thousand-grain weight of wheat, wherein the main effect QTL is positioned on the short arm of a 6A chromosome and between an SNP marker AX-109959301 on the left side and an SNP marker AX-109405872 on the right side; a candidate gene for coding a flowering promoting factor exists in the QTL locus; the interpretation rate of the QTL locus on the phenotypic variation of thousand seed weight is 14.6-22.3 percent respectively; the positive allelic variation of the QTL site is from a parent variety of half-mango, the thousand kernel weight can be improved by 3.6-6.4 g, and the QTL site has great application value in wheat breeding.
Description
Technical Field
The invention belongs to the field of wheat genetic breeding, and particularly relates to a major QTL influencing the thousand-grain weight of wheat and application thereof.
Background
Wheat is one of the most important food crops in the world, and the yield of the wheat is an important factor influencing the development and stability of national economy. Therefore, increasing yield has always been one of the most important breeding goals for breeders. The thousand kernel weight is one of three factors of the wheat yield, and the improvement of the thousand kernel weight is an important way for improving the wheat yield. Therefore, breeders have studied thousand kernel weight as an important index in breeding.
Among the three yield factors, the heritability of grain weight is the largest and the yield trait is the least affected by the environment. Thousand kernel weight is a quantitative trait, controlled by multiple genes. With the gradual maturity of QTL mapping technology and the extensive development of new markers, there will be more gene mapping related to thousand kernel weight. Many scholars at home and abroad position the QTL of the thousand-grain weight and find that the QTL for controlling the thousand-grain weight of wheat is distributed on a plurality of chromosomes of the wheat.
However, so far, the QTL and molecular marker about the thousand-grain weight of wheat are rarely applied to breeding. Because most of the previous wheat QTL are linkage maps constructed by utilizing SSR markers, the marker density is low, and most of the SSR markers are designed according to non-coding regions. And the SNP marker is designed according to a transcriptome or a gene sequence, thereby providing a better method for mining candidate genes. The density of the genetic map constructed by using SNP is increased, and the located QTL linkage markers are more easily applied to breeding. Therefore, the SNP chip has a large positioning genetic effect, is easy to apply to spike length QTL in molecular assisted breeding, and has great significance for improving wheat yield and breeding.
Disclosure of Invention
The purpose of the patent is to provide a major QTL influencing the thousand-grain weight of wheat, and the marker is an SNP marker and is convenient to apply in breeding.
The invention realizes the purpose through the following technical scheme:
the patent provides a major QTL influencing the thousand kernel weight of wheat, and the major QTL locus is positioned on the short arm of a 6A chromosome and is between a SNP marker AX-109959301 and a right marker AX-109405872.
Candidate genes respectively encoding flowering promoting factors and sucrose phosphate synthase exist in the QTL provided by the patent.
The interpretation rate of phenotypic variation of thousand kernel weight by the QTL locus provided by the patent is 14.6%, 16.3% and 22.3% in three environments respectively.
The mapping population of the patent is a recombinant inbred line population consisting of 186F 6 generation lines, and the parents are local variety semimango and promoted variety Jimai 22.
The positive allelic variation of the QTL locus of the patent is used for the half mango of a parent variety, and the thousand seed weight can be improved by 3.6-6.4 g.
The main effect QTL locus provided by the patent has huge application in wheat breeding.
Has the advantages that: in the patent, a new major QTL is positioned on the short arm of the 6A chromosome, and the thousand kernel weight is obviously influenced. The site positive allelic variation comes from local variety Miscanthus semiaquilegia. This provides a new, available allele for wheat yield breeding. The SNP marker closely linked with the QTL is AX-109959301, and the SNP marker can be converted into a KASP marker for molecular assisted selective breeding. Candidate genes, namely flowering promoting factors and sucrose phosphate synthetase, provide available genes for wheat yield breeding.
Detailed Description
Example 1
NO.1 experimental materials and methods
No.1.1 Experimental materials and field management
The mapping population is a recombinant inbred line population (RIL) consisting of 186F 6 generation lines, and the parents are the local variety Miscanthus semiperma and the dominant variety Jimai 22.
RIL populations and parents were planted in Jinan in 2015-2016 and in 2016, and in the lotus in 2015-2016. The field test adopts a completely random block design and three repetitions. Each cell has 3 rows, 4 meters long, 25 cm distance, 100 plants planted in each row. The field management adopts local conventional management.
Measurement of 1.2 thousand Kernel weight
After harvesting, 1000 seeds were taken from each line and their weights were measured, and the average value was taken for statistical analysis of the data.
Statistical analysis of No.1.3
The analysis of the trait data was performed using SPSS 15.0 software. The distribution test was performed by the Kolmogorov-Smirnov (K-S) test method. When P >0.05, the trait is shown to fit a normal distribution.
Genotype Variance (VG), environmental Variance (VE), genotype and environmental interaction Variance (VGE), and error Variance (VE) were calculated using the R software package Sommer (Covarrubias-Pazaran, 2016). The generalized heritability (h2) is calculated from the equation h2= VG/[ VG + VGE/N + Ve/(N × R) ], where N and R are the number of environments and the number of repetitions, respectively.
Genotyping and molecular marker analysis of NO.1.4SNP
Total genomic DNA was extracted from young leaf tissues of the parents and RIL using the CTAB method (Doyle and Doyle, 1987). The wheat 55K SNP chip developed by China academy of agricultural sciences Jia progressive research is used for genotyping parents and RIL groups, and the chip contains 53063 SNP markers.
1.4 linkage analysis
A genetic map constructed using Carthagene. The specific construction process of the map is as follows: after SNPs with parent polymorphism are selected, filtering SNPs with genotype deletion rate more than 10%, and grouping the markers by using group commands based on the filtered high-quality SNPs by adopting different LOD thresholds (genetic distance threshold is 80 cM); and then constructing a frame map for each linkage group by using a buildfw command (parameter: buildfw 33 { } 0), optimizing the marking sequence on the map by using three algorithms of greedy (parameter: greedy 105250), flips (parameter: flips 511) and poll to obtain the frame map with stable marking sequence and position, finally adding the rest marks in the linkage group into the frame map (parameter: buildfw 00 { frame map } 0), and optimizing the marking sequence by using the greedy, the flips and the poll again to obtain the final genetic map. The recombination exchange rate was converted to genetic map-distance units (cM) by the Haldane function.
Positioning No.1.5QTL
QTL analysis is carried out on each character under each environment by using a complete interval mapping method (ICIM-ADD) of QTL IciMapping v 4. The LOD value of 2.5 was used as a threshold for significance. The confidence interval is the two LOD descent support intervals for the 95% confidence interval (van oijen, 1992). In the additive QTL effect, positive and negative for the additive effect indicates that the positive allelic variation is from sempervirens or jimai 22. Phenotypic variation interpretations (PVEs) were calculated by stepwise regression (Li et al, 2007). The semiono genotype is 0, i.e. the wheat 22 genotype is 2. Thus, when the additive effect is positive, the positive allelic variation is from hemimangoes.
Screening of candidate Gene No.1.5
The annotation files of the 55K SNP chips provide genetic information between adjacent SNPs. We analyzed all genes between two SNPs located by QTL and identified candidate genes that might be associated with the trait of interest.
No.2 results and analysis
2.1 phenotypic variation and related assays
Phenotypic performance and quality trait variance analysis was first performed on the parental and RIL populations.
TABLE 1 phenotypic Performance and quality trait ANOVA of the Oenanthe Mangifera indica/Jimai 22 RIL population
Note: i represents 2016 of planting in Jinan; II represents 2016 Netzian planting; and III represents the planting of 2017 Jinan.
Table 1 shows the mean, standard deviation and coefficient of variation for thousand kernel weight for the RIL population. The parents and the parents have obvious difference in thousand grain weight, and the local variety Jimai 22 is higher than half mango (Table 1). The phenotypic variation of the RIL population is obvious, and in different environments, the phenotypic variation of some strains has a super-parent phenomenon, and reaches a significant level, which indicates that thousand seed weight is a quantitative genetic trait controlled by a plurality of genes. According to the Kolmogorov-Smirnov test, both ear length and spikelet number fit a normal distribution (P > 0.05) (Table 1).
Thousand kernel weight analysis of variance was performed on the parental and RIL populations.
Table 2: analysis of variance of thousand seed weights of half-mango/Jimai 22 RIL population
Note: p <0.05, P <0.01, P < 0.001.
Analysis of variance showed that genotype, environment and genotype x environment interaction had a very significant impact on all traits (table 2). The generalized heritability of thousand grains is 0.9 respectively.
QTL analysis of 2.2 thousand Kernel weight
QTL analysis was performed for thousand seed weight using the complete interval mapping method (ICIM-ADD), and the results are shown in Table 3.
Table 3: QTL positioning of thousand grain weight of half-mango/Jimai 22 RIL population
Note: i represents 2016 of planting in Jinan; II represents 2016 Netzian planting; III represents 2017 planting in Jinan; PVE phenotypic variation interpretation rate.
A new major QTL is positioned between AX-109959301 and AX-109405872 on the short arm of a 2D chromosome and can be detected in three environments, the closely linked marker is AX-109959301, the interpretation rates of the phenotypic variation are 14.6%, 22.3% and 16.3%, the allelic variation with the positive effect on the phenotypic variation is from a local variety of hemimangoes, and the thousand kernel weight can be increased by 3.6-6.4 g.
Screening of candidate Gene No.2.3
Annotation analysis of the genes between AX-109959301 and AX-109405872 on the short arm of chromosome 6A revealed 2 candidate genes that are likely to be involved in thousand kernel weight, encoding flowering-promoting factors and sucrose phosphate synthase, respectively.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (1)
1. The application of the major QTL influencing the thousand-grain weight of the wheat in the thousand-grain weight breeding is characterized in that: the main effect QTL locus is positioned on the short arm of the 6A chromosome and is positioned between an SNP marker AX-109959301 and an SNP marker AX-109405872; the main effect QTL locus is closely linked with an SNP marker left marker AX-109959301; a candidate gene encoding a flowering promoting factor and sucrose phosphate synthase exists in the QTL locus.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910365528.1A CN110106273B (en) | 2019-05-01 | 2019-05-01 | Major QTL influencing thousand-grain weight of wheat and application thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910365528.1A CN110106273B (en) | 2019-05-01 | 2019-05-01 | Major QTL influencing thousand-grain weight of wheat and application thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110106273A CN110106273A (en) | 2019-08-09 |
| CN110106273B true CN110106273B (en) | 2022-07-19 |
Family
ID=67488041
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910365528.1A Expired - Fee Related CN110106273B (en) | 2019-05-01 | 2019-05-01 | Major QTL influencing thousand-grain weight of wheat and application thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110106273B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112582023B (en) * | 2020-12-17 | 2021-08-17 | 河南省农业科学院粮食作物研究所 | Corn molecule breeding method based on whole genome association analysis and multi-environment prediction model |
| CN115976263B (en) * | 2022-12-19 | 2024-01-12 | 中国农业大学 | KASP molecular marker of wheat thousand grain weight major QTL and application thereof |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107916299A (en) * | 2017-12-27 | 2018-04-17 | 山西省农业科学院小麦研究所 | Common wheat SNP site marks and its application in the detection of wheat correlated traits |
| CN108796117A (en) * | 2018-06-20 | 2018-11-13 | 山东省农业科学院作物研究所 | One main effect QTL and its application for influencing wheat quality and yield traits |
| CN109402284A (en) * | 2018-10-26 | 2019-03-01 | 山东省农业科学院作物研究所 | One main effect QTL for influencing wheat spike length and its application |
-
2019
- 2019-05-01 CN CN201910365528.1A patent/CN110106273B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107916299A (en) * | 2017-12-27 | 2018-04-17 | 山西省农业科学院小麦研究所 | Common wheat SNP site marks and its application in the detection of wheat correlated traits |
| CN108796117A (en) * | 2018-06-20 | 2018-11-13 | 山东省农业科学院作物研究所 | One main effect QTL and its application for influencing wheat quality and yield traits |
| CN109402284A (en) * | 2018-10-26 | 2019-03-01 | 山东省农业科学院作物研究所 | One main effect QTL for influencing wheat spike length and its application |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110106273A (en) | 2019-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109402284B (en) | Major QTL influencing wheat head length and application thereof | |
| CN110106273B (en) | Major QTL influencing thousand-grain weight of wheat and application thereof | |
| Liu et al. | Genetic diversity of wheat gene pool of recurrent selection assessed by microsatellite markers and morphological traits | |
| CN108371105A (en) | A kind of High Density Molecular label supplemental polymeric breeding method based on core pedigree kind | |
| CN111508560A (en) | Method for constructing high-density genotype map of outcrossing species | |
| CN114107550B (en) | QTL (quantitative trait locus), molecular marker, amplification primer and application related to soybean hundred-grain weight | |
| CN115058534A (en) | Molecular marker closely linked with corn northern leaf blight disease-resistant locus and application thereof | |
| CN110692512A (en) | Method for rapidly predicting heterosis based on crop genome size | |
| Ding et al. | Identification of stable quantitative trait loci underlying waterlogging tolerance post-anthesis in common wheat (Triticum aestivum) | |
| CN107201403B (en) | Cotton fiber length related QTL and application thereof | |
| Njuguna et al. | Genetic diversity of diploid Japanese strawberry species based on microsatellite markers | |
| Vaquero et al. | Mating system in rye: variability in relation to the population and plant density | |
| CN103834647B (en) | Wheat Dwarfing gene Rht dC20closely linked SSR marker Xgwm537 and uses thereof | |
| Gardenhire et al. | Trisomic Analysis of Greenbug Resistance in Barley, Hordeum vulgare L. 1 | |
| CN113951134B (en) | Efficient corn breeding method based on single plant evaluation and whole genome selection technology | |
| CN107447022B (en) | SNP molecular marker for predicting corn heterosis and application thereof | |
| CN107299130B (en) | Molecular marker linked with rice stigma exposure rate QTL and application thereof | |
| Zou et al. | Screening of salinity tolerance and genome-wide association study in 249 peanut accessions (Arachis hypogaea L.). | |
| CN115725771A (en) | Molecular marker related to soybean aging resistance, amplification primer and application thereof | |
| Zhao et al. | Identification of the candidate gene controlling tiller angle in common wheat through genome-wide association study and linkage analysis | |
| CN114196685A (en) | Corn stalk puncture strength gene ZmFLS2 and application of molecular marker thereof | |
| CN111118192B (en) | KASP molecular marker of wheat ear base small ear fruition main effect QTL and application thereof | |
| CN110106272B (en) | Tetraploid elytrigia elongata 3E chromosome molecular marker and application thereof | |
| CN112481407A (en) | Longan SNP molecular marker and application thereof in genetic map construction and single fruit weight character positioning | |
| CN115443907B (en) | High-yield large-fruit peanut hybrid combination selection method based on whole genome selection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20220719 |