CN109385481B - Application of serpinA3 and vitronectin genes in Sujiang boar breeding and breeding method thereof - Google Patents
Application of serpinA3 and vitronectin genes in Sujiang boar breeding and breeding method thereof Download PDFInfo
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Abstract
The invention relates to the technical field of genetic engineering, in particular to a method for breeding Sujiang male pigs, application of a serpinA3 gene and/or a vitronectin gene in breeding Sujiang male pigs and a kit for breeding Sujiang male pigs. The invention discovers the functional relationship between the serpin A3 and the vitronectin gene and the feed efficiency of Sujiang pigs for the first time, and by applying the serpin A3 and the vitronectin gene to the breeding of the Sujiang pigs, the breeding pigs with high feed efficiency can be bred, and the economic benefit of the Sujiang pig farm is improved.
Description
Technical Field
The invention relates to the technical field of genetic engineering, in particular to application of serpinA3 and vitronectin genes in Sujiang boar breeding and a breeding method thereof.
Background
The Sujiang pigs are bred to new-variety pigs with high litter size, good meat quality and high lean meat percentage, and the pigs have good body shape, appearance, reproduction and production performance after being bred for multiple generations[1]. At present, the feed cost accounts for more than 50 percent of the total cost of modern intensive livestock and poultry breeding production, and the feed efficiency has great influence on the economic benefit of large-scale livestock and poultry breeding. Feed efficiency is generally evaluated at home and abroad by a Feed-to-Feed ratio (Feed/Gain, F/G) or a heavy-to-Feed ratio (Gain/Feed, G/F), i.e., a Feed Conversion Rate (FCR). However, the evaluation of the feed efficiency by F/G or G/F index has the following disadvantages: firstly, the feed consumption should be the actual feed intake of pigs, not the general feed consumption, and how to accurately measure the feed intake is a difficult problem, and even different trough designs can cause feed intake fluctuation[2](ii) a Second, body weight has an effect on feed efficiency because individuals of different body weights have differences in energy requirements for maintenance, and individuals with low maintenance requirementsHas higher feed efficiency[3](ii) a Third, the daily energy level has an impact on feed efficiency due to uncertainty in feed quality (stable energy intake) and daily energy measurements[4-5]. Therefore, the feed efficiency cannot be accurately reflected by adopting the material-to-weight ratio or the heavy material ratio. Generally, in order to improve the feed efficiency, the feed intake of animals can be improved by regulating and controlling the nutrition of the external environment[6-7]For example, focusing on digestibility of pig feed material[8]Concentration of the compound[9]And energy[10]. However, with the coming of the world resource crisis, the improvement of the production performance of pigs by breeding grain-saving pigs or applying molecular genetic means is a necessary trend for future development by improving the feed efficiency from the interior of the pigs.
In the past decades, the selection of lean meat percentage, daily gain, backfat thickness and other properties by pig breeding enterprises nearly reaches the selection limit, and the bottleneck of indirectly improving the feed efficiency by improving the growth properties is present. However, the physiological phenomenon that the energy needed by the individual pigs to maintain the basal metabolism is different provides a new idea for breeders, namely, the feed efficiency can be further improved by reducing the energy needed by the individual pigs to maintain. Maintenance requirements reflect feed efficiency by Residual Feed Intake (RFI) index. The residual feed intake is an index for estimating the feed efficiency of the livestock and poultry, which is proposed by Koch et al in 1963, and is the difference between the actual feed intake of the livestock and the expected feed intake according to the body size and the growth speed of the livestock and poultry. In other words, RFI is the difference between the actual feed intake of the livestock and the predicted feed intake required for maintenance and weight gain.
In actual breeding, individuals with low RFI level are selected, and on the premise that the total feed intake is the same, the less feed intake an individual needs to maintain, the more feed intake is used for growth, and the higher the feed efficiency is[11-12]. Therefore, on the premise of not influencing the initial growth, reproduction and meat quality breeding targets of the Sujiang pigs, the feed efficiency can be improved, the feeding cost can be reduced, excrement and carbon emission can be reduced by continuously selecting individuals with low RFI levels, the production benefit of a breeding enterprise can be improved, the environmental pollution can be reduced, and the economic benefit and the environmental quality can be cooperatively developed.
However, there are limitations to selecting individuals with low levels of RFI, or simply by selecting them for phenotype selection. For example, the values of feed efficiency between individuals with high RFI levels and individuals with low RFI levels screened by phenotypic selection differed but were not significant. This may be because the number of individuals used for selection is small, the phenotypic selection error is large, multiple generations may be required for significant differences, or there may be no significant change over multiple generations.
Complex metabolic pathways are known to affect feed efficiency, involving energy metabolism[13]Lipid metabolism[14]Against oxidative stress[15]Immune defense[16]And insulin formation[17]And the like. Research shows that serine protease inhibitor A3 protein (serine protease inhibitor A3 or serina 3) participating in the processes of actin filament assembly and immune response and vitronectin (vitronectin) participating in blood homeostasis and regulating subcutaneous fat deposition directly play an important role in influencing the metabolic pathway of porcine RFI, and finally influence the feed efficiency by regulating energy utilization and establishing energy balance in vivo. Therefore, the relation between the serpinA3 and vitronectin genes and the feed efficiency of Sujiang pigs is explored, the two genes with obvious alleles are excavated and applied, and the Sujiang pigs with low RIF level are bred, so that an effective method is provided for the breeding of the grain-saving Sujiang pig new strain with high feed efficiency.
Disclosure of Invention
As described above, the current breeding method for the sujiang pigs with high feed efficiency is performed by screening individuals with low RFI level. However, the breeding method has many defects, such as large error, insufficient accuracy, long breeding time, and may need to go through multiple generations to complete. Therefore, the invention expects to breed the Sujiang pigs by adopting molecular genetic analysis, thereby providing an effective method for breeding the grain-saving Sujiang pig new strain with high feed efficiency.
The inventor unexpectedly discovers for the first time that serpinA3 and vitronectin genes have a significant correlation with the feed efficiency of Sujiang pigs. More specifically, the inventors found that B, a significant allele of serpinA3 gene, was present1And/or vitronectinSignificant allele of n gene B2The individual Sujiang pigs of (a) have low RFI levels and their feed efficiency can be improved by at least about 5% or more. Based on this finding, the present inventors have completed the present invention.
Accordingly, in a first aspect, the present invention provides a method of breeding a Sujiang boar, the method comprising the steps of: i. carrying out genotyping detection on the serpinA3 gene and/or the vitronectin gene of the Sujiang boar; selecting the significant allele B carrying serpinA3 gene1And/or dominant allele B of the vitronectin gene2The Sujiang boars are reserved for breeding.
In a second aspect, the invention provides an application of the serpinA3 gene and/or the vitronectin gene in breeding Sujiang boars.
In a third aspect, the present invention provides a kit for breeding Sujiang boars, comprising: a) primer pair 1 for amplifying serpinA3 gene, and/or primer pair 2 for amplifying vitronectin gene; and b) a use instruction for breeding Sujiang boars by utilizing the kit.
By the method, the Sujiang pigs can be bred more directly, accurately and quickly, so that an effective method is provided for the breeding of the grain-saving Sujiang pig new strain with high feed efficiency. The breeding method of the invention can breed the Sujiang breeding boar with higher feed efficiency, save the pig raising period and improve the economic benefit of the Sujiang pig farm.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a technical roadmap for the present invention;
FIG. 2 is a diagram of the amplified allele SSCP of primer set 1;
FIG. 3 is a diagram of primer pair 2 amplified allele SSCP.
Detailed Description
The present invention is described in more detail below. It should be noted that the summary above and the detailed description below are merely intended to specifically illustrate the present invention and are not intended to limit the invention in any way. The scope of the invention is to be determined by the appended claims without departing from the spirit and scope of the invention.
As described above, the current breeding method for the sujiang pigs with high feed efficiency is performed by screening individuals with low RFI level. However, the breeding method has many defects, such as large error, insufficient accuracy, long breeding time, and may need to go through multiple generations to complete. Therefore, the invention expects to breed the Sujiang pigs by adopting molecular genetic analysis, thereby providing an effective method for breeding the grain-saving Sujiang pig new strain with high feed efficiency.
Molecular Marker Assisted Selection (MAS) is a universal method for identifying and utilizing Quantitative Trait Loci (QTL) linked favorable alleles of chromosome regions to promote livestock breeding, and is an important auxiliary method for global genome-wide association analysis (GWAS) at present. There is a recombination event between a significant allele and a QTL and the effect of the allele may be different, so the MAS implementation must first determine the positive or negative effect of the dominant allele. At present, a more efficient method for implementing MAS is to find and identify a functional gene or a new allele of a known functional gene, evaluate the positive and negative effects of the functional gene on different phenotypic traits, and have better accuracy, and MAS is an effective method widely accepted by researchers at present for researching single traits.
The inventor unexpectedly discovers for the first time that serpinA3 and vitronectin genes have a significant correlation with the feed efficiency of Sujiang pigs at the gene level by utilizing MAS technology. More specifically, the inventors found that B, a significant allele of serpinA3 gene, was present1And/or dominant allele B of the vitronectin gene2The individual Sujiang pigs of (a) have low RFI levels and their feed efficiency can be improved by at least about 5% or more. Based on this finding, the present inventors have completed the present invention.
Accordingly, in a first aspect, the present invention provides a method of breeding a Sujiang boar, the method comprising the steps of: i Pair Su ginger boarCarrying out genotyping detection on the serpinA3 gene and/or the vitronectin gene; ii selection of the significant allele B carrying the serpinA3 Gene1And/or dominant allele B of the vitronectin gene2The Sujiang boars are reserved for breeding.
Reference herein to a "significant allele" is to an allele associated with lower feed consumption or to an allele associated with low RFI levels. In other words, the Sujiang boar bred by the method carries serpinA3 gene significant allele B1And/or dominant allele B of the vitronectin gene2Will have a low RFI level and thus a desirably high feed efficiency.
In this context, by "low RFI level" is meant a level of RFI of-0.214 Kg/d to-0.106 Kg/d. Sujiang boars with low RFI levels had the expected growth traits: including feed efficiency, average daily gain and/or backfat thickness over a predetermined weight period. More specifically, when the expected growth trait refers to feed efficiency within a predetermined weight period, it refers to feed efficiency of 2.93:1-3.02:1 at a predetermined weight period of 30-90 KG; when the expected growth traits refer to average daily gain in a predetermined weight stage, the average daily gain is above 650g/d when the predetermined weight stage is 30-90 KG; when the expected growth trait is backfat thickness within a predetermined weight period, the expected growth trait is backfat thickness of 1.8-3.28cm when the predetermined weight period is 30-90 KG. If the RFI level of the Sujiang boars is not in the range, the RFI level is not beneficial to saving the pig raising period, and the RFI level is not beneficial to improving the economic benefit of the Sujiang pig raising farm.
In one embodiment, the serpinA3 gene significant allele B1Has a sequence shown as SEQ ID NO 6, a significant allele B of a vitronectin gene2Having the sequence shown.
The allele A of serpinA3 gene can be known by sequence alignment1And B1Alleles A of the vitronectin and vitronectin genes2Respectively with its allele B2And C2There is only one base difference between them. More specifically, allele A1At base 123AAllele B thereof1The corresponding position of (A) is C; allele A2Base T at position 306 in its allele B2Is C, at position 137, at its allele C2Is a.
It will be appreciated by those skilled in the art that, in the present invention, in addition to the sequence represented herein exclusively by SEQ ID NO 6 and itself, sequences each comprising the base differences described above, having a certain sequence homology, for example 80% to 100% homology thereto (e.g.81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100%) respectively and still retaining their functionality may be utilised. The phrase "still retaining its functionality" as used herein means: the presence of the homologous sequence in Sujiang boars, without having SEQ ID NO 6 and/or the sequence itself, is still indicative of the low RFI levels described above in Sujiang boars.
In one embodiment, the genotyping in step i employs PCR-SSCP typing.
The PCR-SSCP typing method is also called Polymerase Chain Reaction-Single Strand Conformation Polymorphism (Polymerase Chain Reaction-Single Strand Conformation Polymorphism) typing method, and is a simple, rapid and economic method for displaying Single base mutation (point mutation) in PCR Reaction products on the basis of PCR technology. The method has been used in the fields of screening and detecting oncogene and cancer suppressor gene mutation, analysis of pathogenic gene of genetic disease, gene diagnosis, gene mapping, etc.
In SSCP assays, double-stranded DNA (dsDNA) is denatured into single-stranded DNA (ssDNA), each of which assumes a unique folded conformation based on their internal sequence, even though single strands of DNA of the same length form different conformations due to different base sequences, even single bases. Under non-denaturing conditions, these single-stranded DNAs are separated by electrophoresis on a non-denaturing polyacrylamide gel, and the mobility and band pattern of the single-stranded DNA depend on their folded conformation and the temperature at which they are electrophoresed. The single-stranded DNA with the same length has different base sequences, and even the difference of single base can form different conformations, thereby causing different migration speeds during electrophoresis. When a change such as a base substitution occurs in the target DNA, a electrophoretic shift occurs, and the presence or absence of a gene mutation is discriminated.
In one embodiment, the serpinA3 gene is PCR amplified with primer pair 1, SEQ ID NO 1 and SEQ ID NO 2, and the vitronectin gene is PCR amplified with primer pair 2, SEQ ID NO 3 and SEQ ID NO 4.
However, it will be understood by those skilled in the art that the serpinA3 gene and the vitronectin gene may be amplified using other primer pairs not described herein, in addition to the primer pairs listed above, as long as the primers are capable of amplifying significant alleles of both genes.
In one embodiment, the following steps are performed before performing step i:
a1) measuring phenotype data of the Sujiang boar to be bred, wherein the phenotype data comprises: initial measurement of body weight, final measurement of body weight, average daily feed intake, intermediate metabolic body weight, backfat thickness, and average daily gain;
a2) calculating the residual feed intake and breeding value EBVRFIAnd a composite selection index I;
a3) selecting individuals having a combined selection index I of 0.24-1.62 for further use in steps I) to ii).
In step a2), calculating the residual feed intake and breeding value EBVRFIAnd the overall selection index I may be performed by:
first, the remaining feed intake RFI is calculated using equation (1):
RFI＝ADFI-(b1×OnBW+b2×OffBW+b3×metaMidBW+b4×ADG+b5×BFA) (1)
for Sujiang boars, the remaining feed intake RFI is calculated by specifically adopting the formula (2):
RFI＝ADFI+0.11323×OnBW+0.11673×OffBW-0.96405×metaMidBW-0.30524×ADG-0.02367×BFA) (2)
where ADFI denotes average daily food intake, OnBW denotes initial body weight, OffBW denotes final body weight, metaMidBW denotes intermediate metabolic body weight, ADG denotes average daily gain, and BF denotes backfat thickness, where metaMidBW ═ [ (OnBW + OffBW)/2] × 0.75.
Subsequently, with the remaining feed intake RFI as a target trait and the average daily gain ADG and backfat thickness BF as constraint traits, RFI breeding values EBV were calculated according to the following modelsRFIADG value of EBVADGAnd BF Breeding value EBVBF：
EBVRFI＝ADFI-group-year-onage-OffBW-ADG-BF-e (3)
EBVADG＝ADG-group-year-onage-e (4)
EBVBF＝BF-group-year-offwt-e (5)
Wherein ADFI, OffBW, ADG and BF are as defined above, onage represents the initial measurement age, group is the measurement population, year is the measurement year, and e is the random residual.
Then, a comprehensive selection index (I) is calculated according to formula (6) using the respective breeding values obtained by the calculation:
I＝-aEBVRFI+bEBVADG-cEBVBF (6)
herein, EBV is set for the weights of target traits (RFI) and constraint traits (ADG and BF)RFI75% of EBVADG15% of EBVBFAccounting for 10 percent. Thus, equation (6) above for calculating the integrated selection index I may be further defined as equation (7) below:
I＝-0.75EBVRFI+0.15EBVADG-0.1EBVBF (7)
if the I of a selected individual Sujiang boar is 0.24-1.62, it indicates that the selected individual Sujiang boar has the required RFI level, and therefore the individual is selected to continue to be used in steps I-ii.
The above steps a1) to a3) essentially constitute a phenotypic selection method. By additionally introducing these several steps, traditional phenotypic selection methods can be organically combined with the molecular genetic selection methods of the present invention, whereby Sujiang boars with the desired growth traits can be selectively bred by first selecting individuals with low RFI levels and then selecting individuals carrying the significant alleles described herein.
The traditional Sujiang boar breeding method is to initially develop the Sujiang boar breeding by taking the feed efficiency character as a secondary breeding target and combining phenotype determination. The method has larger error and low accuracy. In addition, the method requires a long breeding time, and has obvious differences after multiple generations, and sometimes even after multiple generations. However, compared with the traditional Sujiang pig breeding method, the Sujiang boar breeding method is implemented by judging whether the individuals carry the significant alleles of the serpinA3 and/or the vitronectin genes, and the method can realize accurate Sujiang boar breeding by detecting the significant alleles even in the zero generation of low RFI individuals. On the basis of the molecular genetic analysis method, a more perfect breeding method for the Sujiang boars is provided by further assisting the traditional breeding method.
In a second aspect, the invention relates to the use of a serpinA3 gene and/or a vitronectin gene in the breeding of Sujiang boars.
In one embodiment, the B gene carrying the significant allele of serpinA3 is selected1And/or dominant allele B of the vitronectin gene2The Sujiang boars are reserved for breeding.
In a specific embodiment, significant allele B of serpinA3 gene1Significant allele B with sequence SEQ ID NO 6, a vitronectin gene2Has a sequence.
The allele A of serpinA3 gene can be known by sequence alignment1And B1Alleles A of the vitronectin and vitronectin genes2Respectively with its allele B2And C2There is only one base difference between them. More specifically, allele A1The 123 th base A is in its allele B1The corresponding position of (A) is C; allele A2Base T at position 306 in its allele B2Is C, at position 137, at its allele C2Is a.
As described herein in the first aspect, it will be appreciated by those skilled in the art that in the present invention, in addition to the sequence represented herein exclusively by SEQ ID NO 6 and itself, sequences each comprising a base difference as described above, having a certain sequence homology thereto, for example 80% to 100% homology (e.g. 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100%, respectively) and still retaining their functionality may be utilised. The phrase "still retaining its functionality" as used herein means: the presence of the homologous sequence in Sujiang boars, without having SEQ ID NO 6 and/or the sequence itself, is still indicative of the low RFI levels described above in Sujiang boars.
As described above, in Sujiang boars bred by Sujiang boar breeding using serpinA3 and/or vitronectin gene, significant allele B of serpinA3 gene is carried1And/or dominant allele B of the vitronectin gene2Will have a low RFI level and thus a desirably high feed efficiency.
Furthermore, the use may be combined with a phenotypic selection method, as described in the first aspect of the invention. More specifically, the phenotypic selection method described in the first aspect of the present invention, comprising the steps a1) -a3), may be performed in advance before the application of serpinA3 and/or a vitronectin gene.
In a third aspect, the present invention relates to a kit for breeding Sujiang boars, comprising: a) primer pair 1 for amplifying serpinA3 gene, and/or primer pair 2 for amplifying vitronectin gene; and b) a use instruction for breeding Sujiang boars by utilizing the kit.
In one embodiment, the upstream primer sequence of primer pair 1 comprises SEQ ID NO 1 and the downstream primer sequence comprises SEQ ID NO 2.
In another embodiment, the upstream primer sequence of primer pair 2 comprises SEQ ID NO 3 and the downstream primer sequence comprises SEQ ID NO 4.
When the Sujiang pig individual is bred by the method of the first aspect of the invention, the kit of the invention can be adopted, thereby realizing the rapid and accurate breeding of the Sujiang pig with low RFI level.
By the method, the Sujiang pigs can be bred more directly, accurately and quickly, so that an effective method is provided for the breeding of the grain-saving Sujiang pig new strain with high feed efficiency. The breeding method of the invention can breed the Sujiang breeding boar with higher feed efficiency, save the pig raising period and improve the economic benefit of the Sujiang pig farm.
The present invention will be described in more detail and with reference to the following examples and drawings.
Examples
Example 1 evaluation of Sujiang boars with Low RFI levels
Measurement of phenotypic data
Sujiang backup boars with the initial measurement weight of 30KG are selected, 56 replacement boars are fed with daily ration according to the standard given in lean type pig feeding technology (Zhou Guang hong. lean type pig feeding technology. Beijing: Jindun Press, 2008), and the final measurement weight is 90 KG. In the process of phenotype data collection, a boar performance measuring system or manual feeding is utilized to measure and record the initial measurement day age, the average daily gain, the average daily feed intake and the feed consumption, and the back fat thickness is measured by utilizing a living body back fat instrument. The results are shown in Table 1.
TABLE 1 measurement results of the respective properties
Second, RFI data model fitting and calculation
Based on the phenotypic data measurements (see table 1), the optimal RFI model of the fitted pigs was analyzed using a multiple linear regression method to finally estimate the Remaining Feed Intake (RFI) of the individual, the data model being represented by equation (1):
RFI＝ADFI-(b1×OnBW+b2×OffBW+b3×metaMidBW+b4×ADG+b5×BF) (1)
wherein ADFI is average daily feed intake, OnBW is initial body weight, OffBW is final body weight, metaMidBW is intermediate metabolic body weight, ADG is average daily gain, BF is backfat thickness, and metaMidBW ═ [ (OnBW + OffBW)/2] × 0.75.
For the Sujiang pigs, the RFI data model is specifically shown by equation (2):
RFI＝ADFI+0.11323×OnBW+0.11673×OffBW-0.96405×metaMidBW-0.30524×ADG-0.02367×BF) (2)
the results are shown in Table 2.
TABLE 2 RFI measurement results
Low RFI level selection of Sujiang pigs
In the present invention, the selection of Sujiang pigs with low RFI levels takes into account not only the RFI level itself, but also the average daily gain and backfat thickness. Therefore, the present inventors calculated RFI breeding values (EBV) based on the following model using RFI as a target trait and Average Daily Gain (ADG) and backfat thickness (BF) as constraint traitsRFI) ADG value (EBV)ADG) And backfat thickness (EBV) valueBF)：
EBVRFI＝ADFI-group-year-onage-OffBW-ADG-BF-e (3)
EBVADG＝ADG-group-year-onage-e (4)
EBVBF＝BF-group-year-OffBW-e (5)
Wherein ADFI is average daily feed intake, OffBW is final body weight, once age, ADG is average daily gain, BF is backfat thickness, group is determined population, year is determined year, and e is random residual.
EBVRFI、EBVADGAnd EBVBFThe calculations of (a) were performed by the GPS software, and the results are shown in table 3.
TABLE 3 results of breeding values
Subsequently, the overall selection index (I) is calculated using equation (6):
I＝-aEBVRFI+bEBVADG-cEBVBF (6)
in the present invention, 75% of RFI breeding value, 15% of average daily gain breeding value, and 10% of average back fat thickness are set for the target trait (remaining feed intake (RFI)) and the constraint trait (average daily gain (ADG) and back fat thickness (BF)). Thus, equation (6) above for calculating the integrated selection index (I) may be further defined as equation (7) below:
I＝-0.75EBVRFI+0.15EBVADG-0.1EBVBF (7)
selecting individuals with I values of 0.24-1.62, low RFI levels, and RFI levels of-0.214Kg/d to-0.106 Kg/d. The results of the overall selection index (I) are shown in Table 4.
TABLE 4 selection results for Integrated selection index (I)
The production trait results for individuals selected using different composite selection indices (I) are shown below, where the feed consumption of individuals with low RFI levels is lower than the feed consumption of individuals with high RFI levels.
TABLE 5 high and Low RFI Individual Productivity traits
| Low RFI (n ═ 9) | High RFI (n ═ 10) | |
| Feed consumption (Kg) | 179.6±2.64 | 185.2±3.27 |
| Average daily gain (g/d) | 655.3±4.32 | 671.2±2.83 |
| Average backfat thickness (cm) | 2.92±2.1 | 2.85±3.3 |
Example 2 screening of alleles having a significant impact on feed efficiency
Firstly, 220 parts of blood are collected from Sujiang boars used in example 1, and DNA is extracted by using a Na-OH two-step method, which comprises the following steps: punching a hole (diameter is 1.2mm) on the FTA card for sampling, soaking a small blood sample point for 30 minutes by 200 microliters of 20mM NaOH, adding 200 microliters of 1-time TE into the aspirated color-changing liquid, standing for 5 minutes at room temperature, and completely aspirating residual liquid until the small blood sample point is dried.
II, allelic typing analysis
The primers used for PCR amplification were as follows:
the amplification primer pair (primer pair 1) of serpinA3 gene is:
upstream primer (SEQ ID NO 1): AGCCTCTTCACCCTTCTAGGCCG
Downstream primer (SEQ ID NO 2): GTAGAGGCTGAAGGCGAAGTCA
The amplification primer pair (primer pair 2) of the vitro gene is as follows:
upstream primer (SEQ ID NO 3): AGGCAACTCCTCTTCTCTG
Downstream primer (SEQ ID NO 4): GCTTGCACTCGGCCACGTAGT
The PCR reaction system of the two pairs of primers is as follows:
the two pairs of primers have the following PCR reaction conditions: pre-denaturation at 95 ℃ for 5 minutes, denaturation at 94 ℃ for 30 seconds, annealing at 30 seconds (annealing temperature: 58 ℃ for primer set 1 and 60 ℃ for primer set 2), extension at 72 ℃ for 45 seconds, and finally extension at 72 ℃ for 10 minutes.
After PCR amplification, SSCP typing is carried out on the PCR product obtained by the amplification of the two pairs of primers, and the specific method is as follows:
mu.l of the PCR product was mixed with 60. mu.l of denaturing loading buffer (98% deionized formamide, 10mM EDTA, 0.025% bromophenol blue, 0.025% xylene blue FF), denatured at 105 ℃ for 5 minutes, immediately cooled in an ice bath for 10 minutes, 10% (primer pair 1) and 14% (primer pair 2) of non-denatured polyacrylamide gel were electrophoresed at 10.5 ℃ at room temperature under a cooling cycle of 4.2 ℃ and 390V for 19 hours, and photographed by color development after silver staining. Respectively sequencing the band type samples which are homozygote and heterozygote and detected by the SSCP to obtain the allele obtained by the amplification of the two pairs of primers, wherein:
the first allele of the serpinA3 gene (denoted A herein1Alleles) were as follows, wherein: the bold underlined section indicates exons:
the second allele of the serpinA3 gene (denoted herein as B)1Alleles) were as follows, wherein: the bold underlined part indicates the exon, and it is relative to A1The allele only differs at position 123, changing from a to C, the boxed base in the sequence below:
first allele sequence of the vitronectin gene (denoted as A herein)2Alleles) were as follows, wherein: the bold underlined section indicates exons:
second allele sequence of the vitronectin Gene (denoted herein as B)2Alleles) were as follows, wherein: the bold underlined part indicates the exon, and it differs from the a2 gene only at position 306, changing from T to C, the boxed base in the sequence below:
third allele sequence of the vitronectin gene (denoted herein as C)2Alleles) were as follows, wherein: the bold underlined part indicates the exon, and it differs from the a2 gene only at position 137, changing from G to a, the boxed base in the sequence below:
three, significant allele determination
The specific method for judging the significant allele comprises the following steps:
the effect of allele presence/absence on feed consumption was assessed using the general linear mixed effects model (GLMM). The presence and absence of alleles were defined as 1 and 0, respectively, for the feed consumption of the target trait. Considering allele effect, sex effect and age effect as fixed factors and family effect as random factors, the least square variance analysis is carried out by matching the following models,
Yijkng＝μ+Mi+Gj+Wg+Ck+Xn+eijkng
wherein: y isijkngTarget characters are obtained; μ is the population mean; miIs genotype, allelic effect; gjIs an age effect; wgIs a sex effect; ckIs the family effect; xnTwo or more than two interaction effects; e.g. of the typeijkngIs a random residual effect.
The analysis results were taken as "mean + standard error", where P <0.05 is significant, P <0.1 indicates an influential trend, and P >0.15 indicates no influential.
The analytical results are shown in Table 6. As can be seen from the table, carry B1Alleles (178 + -2.48 Kg, P < 0.05) and B2The feed consumption of individuals with alleles (176.1 + -5.38 Kg, P < 0.05) is significantly lower.
TABLE 6 Effect of alleles on pig feed consumption (weight phase 30Kg-90Kg)
As can be seen from the above, the SSCP detection of the sample to be detected can be used to determine the individual allele B1And B2SSCP banding pattern, optionally carrying allele B1And/or B2Individuals with SSCP banding patterns for breeding.
The invention has been described in detail by way of general illustration and specific embodiments, but it will be apparent to those skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Reference to the literature
[1] Banks, Jiwenlin, Zhaxuting, et al, culture and prospect of new varieties of Sujiang pigs [ J ], pig industry science, 2016, 33 (8): 129-132.
[2]Baxter MR.The Design of the Feeding Environment for the Pig[D].PhD Thesis:University of Aberdeen,1986.
[3]Saintilan R,Merour I,Brossard L,et al.Genetics of residual feed intake in growing pigs:relationships with production traits,and nitrogen and phosphorus excretion traits[J].Journal of Animal Science,2013,91(6):2542-2554.
[4]Patience JF,Rossoni-serao MC,Gutierrez NA.A review of feed efficiency in swine:biology and application[J],Jouranl of Animal Science Biotechnology,2015,6(1):33.
[5]Koch RM,Gregory KE,Chambers D,et al.Efficiency of feed use in beef cattle[J],Journal of Animal Science,1963,22:486-94.
[6]Dehaer,LCM and Devries AG.Feed-intake patterns of and feed digestibility in growing pigs housed individually or in groups[J],Proceeding Science,1993,33:277-292.
[7]Vallimont JE,Dechow CD,Daubert JM.Heritability of gross feed efficiency and associations with yield,intake,residual intake,body weight,and body condition score in 11 commercial Pennsylvania tie stalls[J],Journal of Dairy Science,2011,94(4):2108-2113.
[8]Liermann W,Berk A,Boschen V,et al.Effects of diets differing in protein source and technical treatment on digestibility,performance and visceral and biochemical parameters of fattening pigs[J],Archives of Animal Nutrition,2016,70(3):190-208.
[9]Camara L,Berrocoso JD,Coma J,et al.Growth performance and carcass quality of crossbreds pigs from two Pietrain sire fines fed isoproteic diets varying in energy concentration[J],Meat Science,2016,114:69-74.
[10]Addah W,Dzewu RR,Alenyorege B.Effects of dietary restriction followed by high dietary energy or protein on compensatory growth of Ashanti Black x Large White crossbred weaner pigs[J],Tropical Animal Health and Production,2015,1-6.
[11]Kennedy BW,Vanderwerf JHJ,Meuwissen THE.Genetic and statistical properties of residual feed-intake[J],Journal of Animal Science,1993,71:3239-3250.
[12]Cai W,Casey DS,Dekkers JCM.Selection response and genetic parameters for residual feed intake in Yorkshire swine[J],Journal of Animal Science,2008,86:287-298.
[13]Jegou M,Gondret F,Vincent A,et al.Whole blood transcriptomics is relevant to identify molecular changes in response to genetic selection for feed efficiency and nutritional status in the pig[J],Plos One,2016,11(1):e0146550.
[14]Jing L,Hou Y,Wu H,et al.Transcriptome analysis of mRNA and miRNA in skeletal muscle indicates an important network for differential residual feed intake in Pigs[J],Scientific Reports,2014(5):11953.
[15]Vincent A,Louveau I,Gondret F,et al.Divergent selection for residual feed intake affects the transcriptomic and proteomic profiles of pig muscle[J],Journal of Animal Science,2015,93(6):2745-2758.
[16]Do DN,Starthe AB,Ostersen T,et al.Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake[J],Front Genetics,2014,(5):307.
[17]Vigors S,Sweeney T,Oshea CJ,et al.Pigs that are divergent in feed efficiency,differ in intestinal enzyme and nutrient transporter gene expression,nutrient digestibility and microbial activity[J],Animal,2016,10(11):1848-1855.
Sequence listing
<110> Jiangsu agriculture and animal husbandry science and technology occupational academy
Application of <120> serpinA3 and vitronectin gene in Sujiang boar breeding and breeding method thereof
<130> CF180506S
<160> 9
<170> SIPOSequenceListing 1.0
<210> 1
<211> 23
<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 1
agcctcttca cccttctagg ccg 23
<210> 2
<211> 22
<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 2
gtagaggctg aaggcgaagt ca 22
<210> 3
<211> 19
<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 3
aggcaactcc tcttctctg 19
<210> 4
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<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 4
gcttgcactc ggccacgtag t 21
<210> 5
<211> 408
<212> DNA
<213> Sujiang pig (Sujiang Sus scrofa)
<400> 5
agcctcttca cccttctagg ccgtttccca ctgggaaaag cagcagctgt tacagtgctt 60
gctggcaagg ctgaagggaa gctccgggta taacaatgca cacaggctcc ccaggagggc 120
gcatacccat acccatcgga ggtcacagag ccagctagtg gcacagagga ggcagcggga 180
ggctctcggg gcttggtctg gccctgcctg ctcagatgat ctttgctttt cagagtggag 240
acgatgtcac ccctcctggc tctggggctc ttgttggccg ggttctgtcc tgctgtcttc 300
tgccaccctg gtggcccaac aaaggccgct gaggacggag acaatgggat gcacgtggac 360
agcctcagcc tggcttccag aaacactgac ttcgccttca gcctctac 408
<210> 6
<211> 408
<212> DNA
<213> Sujiang pig (Sujiang Sus scrofa)
<400> 6
agcctcttca cccttctagg ccgtttccca ctgggaaaag cagcagctgt tacagtgctt 60
gctggcaagg ctgaagggaa gctccgggta taacaatgca cacaggctcc ccaggagggc 120
gcctacccat acccatcgga ggtcacagag ccagctagtg gcacagagga ggcagcggga 180
ggctctcggg gcttggtctg gccctgcctg ctcagatgat ctttgctttt cagagtggag 240
acgatgtcac ccctcctggc tctggggctc ttgttggccg ggttctgtcc tgctgtcttc 300
tgccaccctg gtggcccaac aaaggccgct gaggacggag acaatgggat gcacgtggac 360
agcctcagcc tggcttccag aaacactgac ttcgccttca gcctctac 408
<210> 7
<211> 385
<212> DNA
<213> Sujiang pig (Sujiang Sus scrofa)
<400> 7
aggcaactcc tcttctctgg ttccctcatc catgacctct catctctctg tcccttcctc 60
aggcatcaga acctagttta ccagacgtga ggccggaggt gctgccatgg cacccctgag 120
gccccttctg atgctggccc tgctggcatg ggttgctctg gctgaccaag gtgcgggagg 180
atatggatat tggtgaccat ttgggtcaat gtagggtggg taagtgtggc ctggcctggg 240
cggtgccagc tgtcatactc cctctccaca gagtcgtgca agggccgctg cacagacggc 300
ttcattgccg aaaggaagtg tcagtgtgac gagctgtgct cttactacca gagctgctgc 360
gctgactacg tggccgagtg caagc 385
<210> 8
<211> 385
<212> DNA
<213> Sujiang pig (Sujiang Sus scrofa)
<400> 8
aggcaactcc tcttctctgg ttccctcatc catgacctct catctctctg tcccttcctc 60
aggcatcaga acctagttta ccagacgtga ggccggaggt gctgccatgg cacccctgag 120
gccccttctg atgctggccc tgctggcatg ggttgctctg gctgaccaag gtgcgggagg 180
atatggatat tggtgaccat ttgggtcaat gtagggtggg taagtgtggc ctggcctggg 240
cggtgccagc tgtcatactc cctctccaca gagtcgtgca agggccgctg cacagacggc 300
ttcatcgccg aaaggaagtg tcagtgtgac gagctgtgct cttactacca gagctgctgc 360
gctgactacg tggccgagtg caagc 385
<210> 9
<211> 385
<212> DNA
<213> Sujiang pig (Sujiang Sus scrofa)
<400> 9
aggcaactcc tcttctctgg ttccctcatc catgacctct catctctctg tcccttcctc 60
aggcatcaga acctagttta ccagacgtga ggccggaggt gctgccatgg cacccctgag 120
gccccttctg atgctgaccc tgctggcatg ggttgctctg gctgaccaag gtgcgggagg 180
atatggatat tggtgaccat ttgggtcaat gtagggtggg taagtgtggc ctggcctggg 240
cggtgccagc tgtcatactc cctctccaca gagtcgtgca agggccgctg cacagacggc 300
ttcatcgccg aaaggaagtg tcagtgtgac gagctgtgct cttactacca gagctgctgc 360
gctgactacg tggccgagtg caagc 385
Claims (6)
1. A method for breeding Sujiang boars, comprising the following steps:
i. carrying out genotyping detection on the serpinA3 gene and/or the vitronectin gene of the Sujiang boar;
selecting the significant allele B carrying serpinA3 gene1And/or dominant allele B of the vitronectin gene2The Sujiang boars are reserved for breeding;
wherein serpinA3 gene significant allele B1Has a sequence shown as SEQ ID NO 6, a significant allele B of a vitronectin gene2Has a sequence shown as SEQ ID NO 8.
2. The method for breeding Sujiang boars according to claim 1, wherein the genotyping in step i is performed by PCR-SSCP typing.
3. The method for breeding Sujiang boars according to claim 2, wherein the serpinA3 gene is PCR amplified with primers of 1 (SEQ ID NO 1 and SEQ ID NO 2), and the vitronectin gene is PCR amplified with primers of 2 (SEQ ID NO 3 and SEQ ID NO 4).
4. The method for breeding Sujiang boars according to any one of claims 1 to 3, wherein the following steps are performed before performing step i:
a1) measuring phenotype data of the Sujiang boar to be bred, wherein the phenotype data comprises: initial measurement of body weight, final measurement of body weight, average daily feed intake, intermediate metabolic body weight, backfat thickness, and average daily gain;
a2) calculating the residual feed intake and breeding value EBVRFIAnd a composite selection index I;
a3) selecting individuals with the comprehensive selection index I of 0.24-1.62 to continue to step I-step ii;
wherein the residual feed intake breeding value EBVRFIAnd the calculation formula of the comprehensive selection index I is as follows:
EBVRFI=ADFI-group-year-onage-OffBW-ADG-BF-e （3）
EBVADG=ADG-group-year-onage-e （4）
EBVBF=BF-group-year-OffBW-e （5）
I=-0.75EBVRFI+0.15EBVADG-0.1EBVBF （7）
ADFI represents average daily food intake, OffBW represents final body weight, ADG represents average daily gain, BF represents backfat thickness, onage represents initial measurement age, group represents measurement population, year represents measurement year, and e represents random residual.
5. Application of primer pair for amplifying serpinA3 gene and/or vitronectin gene in breeding Sujiang boar, wherein significant allele B carrying serpinA3 gene is selected1And/or dominant allele B of the vitronectin gene2The Sujiang boars are reserved for breeding; significant allele B of serpinA3 gene1Having the sequence SEQ ID NO 6, a significant allele B of the vitronectin gene2Has the sequence SEQ ID NO 8.
6. A kit for breeding Sujiang boars, the kit comprising:
a) for amplification of significant allele B of serpinA3 Gene1And/or for amplifying dominant allele B of the vitronectin gene2The primer pair 2 of (1); and
b) the use instruction of the Sujiang boar breeding by using the kit;
among them, serpinA3 gene significant allele B1Has a sequence shown as SEQ ID NO 6, a significant allele B of a vitronectin gene2Has a sequence shown as SEQ ID NO 8;
the sequence of an upstream primer of the primer pair 1 is SEQ ID NO 1, and the sequence of a downstream primer is SEQ ID NO 2; the upstream primer sequence of the primer pair 2 is SEQ ID NO 3, and the downstream primer sequence is SEQ ID NO 4.
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| CN108300789A (en) * | 2017-11-14 | 2018-07-20 | 中国农业大学 | With the relevant SNP marker of the multiple important economical traits of pig and its application |
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| CN108300789A (en) * | 2017-11-14 | 2018-07-20 | 中国农业大学 | With the relevant SNP marker of the multiple important economical traits of pig and its application |
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| Genome-wide association analysis reveals genetic loci and candidate genes for feeding behavior and eating efficiency in Duroc boars;Rongrong Ding;《PLOS ONE》;20170816;第1-15页 * |
| Identification of potential serum biomarkers to predict feed efficiency in young pigs;J. K. Grubbs;《J Anim Sci》;20160430;第94卷(第4期);第1482-1492页 * |
| Serpina3 and Vitronectin as Biomarkers for Feed Efficiency in Swine;B. M. Patterson;《Meat and Muscle Biology》;20170131;第1卷(第2期);第166页 * |
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