SNP molecular marker related to buffalo growth traits, application and method for screening SNP molecular marker

Abstract

The application discloses a SNP molecular marker related to a buffalo growth trait, application and a method for screening the SNP molecular marker, and relates to the technical field of biology. The growth trait is average weaning body height of the buffalo, the SNP molecular marker is located at a 85470124th nucleotide site on a 4th chromosome of a buffalo reference genome, a molecular marker nucleotide sequence is shown as SEQ ID NO:1, and an A>G base mutation exists at a 51st position of the sequence. Through the preferred SNP molecular marker, the application can improve weaning body height of a buffalo offspring, speeds up genetic improvement of the buffalo, and thus effectively improves economic benefits of buffalo breeding.

Description

Technical Field

[0001] This invention relates to the field of biotechnology, specifically to a method for identifying, applying, and screening SNP molecular markers related to buffalo growth traits. Background Technology

[0002] Water buffalo are an important part of my country's animal husbandry, providing people with high-quality meat, milk, and other livestock products. With the improvement of people's living standards, the consumption of water buffalo meat and milk has been increasing year by year. Water buffalo meat, in particular, is very popular in some southern provinces. The current number of water buffalo in my country is insufficient to meet production needs, making genetic improvement of water buffalo and enhancing water buffalo breeding technology an urgent and crucial task in current breeding work.

[0003] Growth traits, including body weight and body size, are among the most important economic traits in buffalo production. Therefore, researching how to improve buffalo growth traits through selective breeding is of great significance to the entire buffalo industry and breeding research. Single nucleotide polymorphism (SNP) refers to DNA sequence polymorphism caused by variations in a single nucleotide (A, T, C, or G) at the same location in the genome between individuals. It mainly includes four forms: base transitions, transversions, insertions, and deletions. SNPs are characterized by their large number, wide distribution, low heterozygosity, good genetic stability, and suitability for high-throughput automated detection. Therefore, SNPs can be used as the preferred tool for molecular breeding, gene mapping, and population evolution research. Thus, by incorporating molecular markers with significant effects into marker-associated selection (MAS) and genomic selection (GS) using modern selective breeding techniques, the genetic improvement of buffalo growth traits can be significantly improved, thereby enhancing the production performance of offspring buffalo and contributing to the efficient development of my country's buffalo industry.

[0004] Growth traits in buffalo are complex traits controlled by multiple genes, making it difficult to accurately identify major genes using conventional genetic methods. Genome-wide association studies (GWAS) based on SNP microarrays or sequencing provide an effective method for screening molecular markers significantly associated with target traits. In modern livestock breeding, given the generally large size of livestock populations, using high-depth sequencing for base information acquisition would incur high costs, reducing economic efficiency. Meanwhile, the data quality of low-depth sequencing remains to be evaluated.

[0005] Therefore, to meet the requirements of large-scale population sequencing, providing low-cost, high-quality SNP locus information for GWAS analysis is a crucial factor in improving SNP screening efficiency. Those skilled in the art are dedicated to screening for novel SNP loci associated with buffalo growth traits, providing new molecular marker resources for marker-assisted selection in buffalo and accelerating the process of breeding improvement. Summary of the Invention

[0006] This invention provides a method for identifying, applying, and screening SNP molecular markers related to buffalo growth traits, aiming to solve the problems existing in the background art.

[0007] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: In a first aspect, the present invention discloses a SNP molecular marker associated with a growth trait of buffalo, wherein the growth trait is the average weaning height of buffalo, and the SNP molecular marker is located at nucleotide position 85470124 on chromosome 4 of the buffalo reference genome (Genome assembly NDDB_SH_1). The nucleotide sequence of the molecular marker is shown in SEQ ID NO:1, and there is an A>G base mutation at position 51 of the sequence.

[0008] SEQ ID NO:1: CCTTACATTCCACAGCTTTCATAAAAATTCATGTTACAGAGGAAATTCTCN(A / G)AGCATTCGCTACAGCTGGCAAGCCCTGCTGGGGGCCCACAGAGTGTTAAC.

[0009] In a preferred embodiment of the present invention, the A or G base polymorphism site at the 51st bp of the sequence SEQ ID NO:1 is expressed as one of three genotypes: AA, AG, or GG, wherein the A allele is the dominant allele.

[0010] Secondly, this invention discloses the application of SNP molecular markers as described in the first aspect in the breeding of high-yield buffalo average weaning bodies.

[0011] In a preferred embodiment of the present invention, the following steps are included: (1) Detect the molecular markers as described in the first aspect in the selection of buffalo; (2) Screen individuals whose genotype of the molecular marker mentioned in step (1) is AA or AG; (3) The individuals selected in step (2) are the buffaloes with high average weaning body dominance traits. These buffaloes are bred to improve the high weaning body performance of offspring buffaloes.

[0012] Thirdly, the present invention discloses a method for screening for dominant traits in the average weaned body of buffalo using molecular markers as described in the first aspect, comprising the following steps: (1) Detect the molecular markers as described in the first aspect in the selection of buffalo; (2) Screen individuals whose genotype of the molecular marker mentioned in step (1) is AA or AG; (3) The individuals selected in step (2) are buffaloes with high dominance of average weaning body traits.

[0013] Fourthly, the present invention discloses the application of a molecular marker as described in the first aspect in improving buffalo growth traits, wherein the buffalo growth trait is the average weaning height of the buffalo.

[0014] In a preferred embodiment of the present invention, the following steps are included: (1) Detection of molecular markers as described in the first aspect in the reserve breeding buffalo; (2) Select individuals whose genotype of the molecular marker mentioned in step (1) is AA or AG; (3) Mating the individuals selected in step (2).

[0015] (4) Detect the molecular markers as described in the first aspect on the buffalo individuals born after mating in step (3), select individuals of type AA or AG according to the selection criteria in step (2), and propagate the selected buffalo individuals to increase the frequency of gene A at this locus generation by generation, thereby improving the high performance of the weaned buffalo offspring.

[0016] Fifthly, the present invention discloses a method for detecting and judging the productive traits of buffalo using molecular markers as described in the first aspect, which detects whether the base at the 51st bp of the sequence shown in SEQ ID NO:1 is A or G, and among the three genotypes of AA, AG or GG, the weaning height of buffalo of type AA or AG is superior to that of buffalo of type GG.

[0017] In a sixth aspect, the present invention discloses a method for screening SNP molecular markers as described in the first aspect, comprising the following steps: (1) Extract buffalo genomic DNA and perform whole-genome low-depth and high-depth resequencing to obtain raw sequencing data; (2) Quality control of the raw sequencing data, alignment to the buffalo reference genome, and use the Sentieon+Beagle strategy to detect genetic variations and fill genotypes on all autosomes of the sample to obtain SNP locus data; (3) Using the FarmCPU model with rMVP software, SNP sites and buffalo weaning height were analyzed by GWAS to obtain the SNP molecular markers related to the growth traits of the buffalo.

[0018] In a preferred embodiment of the present invention, the low depth is 1×-2×, the high depth is 15×-20×, and the number of low depths is higher than that of high depths. By using fewer high-depth sequencing results to fill the genotypes of more low-depth sequencing results, the sequencing cost is reduced.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention combines low-depth resequencing with genotype filling and uses GWAS analysis to screen for significant SNP molecular markers that affect buffalo growth traits. These markers are then used in marker-assisted selection and genomic selection to select genotypes that are beneficial to improving buffalo growth traits for breeding. This gradually increases the gene frequency of dominant alleles, thus accelerating the process of breeding cattle improvement and bringing huge economic benefits to buffalo farming.

[0020] This invention verifies the effect of the SNP molecular marker on weaning height in buffalo, and it can be applied to the genetic improvement of breeding cattle to increase weaning height, thereby improving the weaning height of offspring and increasing the market competitiveness of breeding enterprises. Attached Figure Description

[0021] Figure 1 Manhattan plot of buffalo growth traits. The black circles and arrows point to the molecular markers screened in this invention, which are located on buffalo chromosome 4. Detailed Implementation

[0022] The preferred embodiments of the present invention will be described in detail below with reference to examples. It should be understood that the following examples are given for illustrative purposes only and are not intended to limit the scope of the invention. Those skilled in the art can make various modifications and substitutions to the present invention without departing from its spirit and essence. The following examples are used to illustrate the present invention but are not intended to limit its scope. Unless otherwise specified, the equipment and reagents used in the examples are all commercially available.

[0023] In this embodiment of the invention, whole-genome resequencing was performed on 209 river buffalo (54 Mediterranean buffalo, 102 Mora buffalo, and 53 Nere-Raffi buffalo). Low-depth whole-genome resequencing (average sequencing depth approximately 1.65×) was performed on all buffalo, while high-depth whole-genome resequencing (average sequencing depth approximately 18.67×) was performed on 15 of them. The resequencing data were then aligned to the buffalo reference genome (Genome assembly NDDB_SH_1). The Sentieon+Beagle strategy was used to detect genetic variations and fill genotypes on all autosomes of the 209 samples, obtaining SNP locus data for GWAS studies related to buffalo body weight and body size traits. Finally, an SNP (g.85470124AG) associated with weaning body height was identified. Referring to Ensembl, the nucleotide sequences of the 50 bp upstream and downstream of this SNP site were obtained. The nucleotide sequence of this fragment is shown in SEQ ID NO:1, where there is an A>G base mutation at position 51, where G is the nucleotide of the allele mutation. The specific nucleotide sequence of SEQ ID NO:1 is as follows: CCTTACATTCCACAGCTTTCATAAAAATTCATGTTACAGAGGAAATTCTCN(A / G)AGCATTCGCTACAGCTGGCAAGCCCTGCTGGGGGCCCACAGAGTGTTAAC.

[0024] The N at position 51 of the above sequence represents an A51-G51 allele mutation, resulting in nucleotide polymorphism in the SEQ ID NO:1 sequence. GWAS analysis showed that g.85470124AG was significantly associated with the growth trait (weaning height) in buffalo. Individuals with genotypes AA or AG had significantly higher average weaning height than those with genotype GG, indicating that A is an allele that favors improved growth. This molecular marker can be used to detect the growth trait associated with average weaning height in buffalo. Furthermore, when the nucleotide at position 51 of the sequence shown in SEQ ID NO:1 is A, it is beneficial for buffalo to have a higher average weaning height, which is of great significance for buffalo breeding.

[0025] The molecular markers screened in this invention can be applied to genotypic analysis of genes related to buffalo growth traits or association analysis of buffalo growth traits, providing new molecular marker resources for marker-assisted selection of buffalo growth traits.

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the embodiments, but these should not be construed as limiting the scope of protection of this invention.

[0027] Example 1: Whole Genome Resequencing 1. Blood sample collection A veterinary lancet was used to collect 5 mL of blood from the buffalo jugular vein into an EDTA anticoagulant tube. The anticoagulant tube was placed in an ice box with plenty of ice packs and brought back to the laboratory. The sample was stored in a refrigerator at 4°C.

[0028] Genomic DNA extraction and whole-genome resequencing Blood DNA was extracted using the Genomic DNA Mini-Extraction Kit (catalog number: d3024) from Tianmo Biotechnology, following the instructions. The qualified genomic DNA was sent to Beijing Berry Genomics Co., Ltd. for secondary quality control and library construction. Whole-genome resequencing was then performed using BGI Genomics' MGISEQ-200 platform. All samples underwent low-depth whole-genome resequencing; the average sequencing depth of the 209 samples was approximately 1.65×, with a total data volume of 592 Gb. High-depth sequencing was performed on 15 samples, with an average depth of approximately 18.67×, resulting in a total data volume of 861 Gb.

[0029] Example 2: Genome alignment, genetic variation detection, and genotype filling 1. Analysis of raw sequencing data and genome alignment High-depth sequencing data and low-depth sequencing data were subjected to the same quality control process, and the Sentieon+Beagle strategy was used to perform genetic variation detection and genotyping on all samples.

[0030] (1) The raw data was filtered using Fastp software. The filtering criteria were as follows: reads with a base quality value below 20 exceeding 30% were removed; reads with n bases greater than 5% were removed. Clean reads were obtained after the above quality control steps.

[0031] (2) Use BWA software to align cleanreads to the buffalo reference genome (Genome assembly NDDB_SH_1).

[0032] (3) Use Samtools software to sort the compared BAM files.

[0033] (4) Use Picard to mark repeated reads.

[0034] (5) Use Samtools software to build indexes.

[0035] Detection of variant sites and genotyping (1) GATKHaploytypeCaller generates gvcf files for each sample according to the autosomal number.

[0036] (2) GATKCombineGVCFs merges the gvcf files of each sample of a single chromosome.

[0037] (3) GATKGenotypeGVCFs were used for population SNP calling based on chromosomes.

[0038] (4) GATKMergeVcfs merges the vcf files of autosomal populations.

[0039] (5) GATKSelectVariants filters the SNPs in the vcf files of the population.

[0040] (6) GATK Variant Filtration to mark false positive SNP sites.

[0041] (7) The grep command filters labeled SNP sites (8) Plink software filters SNP sites (geno0.1--maf0.05--hwe1e-06).

[0042] (9) Construct a reference panel using sequencing data from high-depth samples and fill in the missing sites using Beagle software.

[0043] (10) Use Sentieon Haplotyper and GVCFtyper modules to detect and genotype population genome genetic variations.

[0044] (11) Using Beagle to fill in the genotypes, we finally obtained 26,131,221 high-quality SNPs.

[0045] Example 3: Application of g.85470124AG molecular marker genotyping method in association analysis of growth traits in buffalo. Association analysis between the g.85470124AG molecular marker and buffalo growth traits (weaning height): (1) The phenotypes used for the association analysis between genotype and growth traits were measured by professional technicians in strict accordance with the measurement specifications. The data of body weight, body height and body length were collected, totaling 161 samples.

[0046] (2) GWAS analysis of SNP loci and weaning body height was performed using the FarmCPU model with rMVP software. The FarmCPU model used both fixed-effects and random-effects models for iteration. The fixed-effects analysis model is as follows: y = Xb + Z t u t+ S i d i + e In the formula, y It is the observer vector of the property; b It is an individual fixed effects vector, including the first three principal components of the SNP, birth season, birth parity, and birth weight; u t The t pseudo-quantitative trait nucleotide genotype matrix is ​​used as a fixed effect; X and Z t They are b and u t The correlation matrix; S i It is the i-th SNP tag. d i This is the corresponding effect value; e It is a random residual effect vector that conforms to a normal distribution. e ~ N ( 0, Iσ e 2 ).

[0047] Example 4: Investigating the effects of different genotypes of g.85470124AG on growth traits in buffalo. The results are shown in Table 1. GWAS analysis showed that g.85470124AG was significantly associated with buffalo growth traits (weaning height).

[0048] AA 54 92.37±2.68 2.85e-07 AG 74 90.50±3.35 GG 33 88.03±4.35 Note: P The values ​​are from genome-wide association analysis of the GCTA mixed linear model.

[0049] Table 2 shows the differences in weaning height among individuals with the three genotypes within the population.

[0050] AA vs AG 1.86e-03 ** AA vs GG 6.15e-08 *** AG vs GG 2.13×10−3 ** Note:* P <0.05, *** P <0.001.

[0051] As shown in Tables 1 and 2, for the weaning height trait in buffalo, individuals with genotypes AA or AG had significantly higher weaning height than individuals with genotype GG, indicating that A is an allele that is beneficial to the improvement of growth traits.

[0052] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A SNP molecular marker associated with buffalo growth traits, characterized in that, The growth trait is the average weaning height of buffalo. The SNP molecular marker is located at nucleotide position 85470124 on chromosome 4 of the buffalo reference genome. The molecular marker nucleotide sequence is shown in SEQ ID NO:

1. There is an A>G base mutation at position 51 of this sequence.

2. The SNP molecular marker related to buffalo growth traits according to claim 1, characterized in that, The A or G base polymorphism site at position 51 bp in sequence SEQ ID NO:1 is expressed as one of three genotypes: AA, AG, or GG, with the A allele being the dominant allele.

3. The application of the SNP molecular marker as described in claim 1 or 2 in the breeding of high-yield buffalo average weaning bodies.

4. The application according to claim 3, characterized in that, The steps include the following:

1. To detect the molecular markers as described in claim 1 in the selected buffalo; 2. Screen individuals whose molecular marker genotype is AA or AG in step (1); 3. The individuals selected in step (2) are the buffaloes with high average weaning body dominance traits. These buffaloes are then bred to improve the high weaning body performance of offspring buffaloes.

5. A method for screening for dominant traits in buffalo average weaning bodies using molecular markers as described in claim 1 or 2, characterized in that, The steps include the following: (1) Detect the molecular markers as described in claim 1 in the selected buffalo; (2) Screen individuals whose genotype of the molecular marker mentioned in step (1) is AA or AG; (3) The individuals selected in step (2) are buffaloes with high dominance of average weaning body traits.

6. The application of the molecular marker as described in claim 1 or 2 in improving buffalo growth traits, wherein the buffalo growth trait is the average weaning height of the buffalo.

7. The application according to claim 6, characterized in that, The steps include the following: (1) Detection of the molecular markers as described in claim 1 on reserve buffalo; (2) Select individuals whose genotype of the molecular marker mentioned in step (1) is AA or AG; (3) The individuals selected in step (2) are bred. (4) The buffalo individuals born after mating in step (3) are tested for the molecular markers as described in claim 1. According to the selection criteria in step (2), individuals of type AA or AG are selected, and the selected buffalo individuals are propagated to increase the frequency of gene A at this locus generation by generation, thereby improving the weaning performance of the offspring buffalo.

8. A method for detecting and determining the productive traits of buffalo using the molecular markers as described in claim 1 or 2, characterized in that, The base at position 51 bp in the sequence shown in SEQ ID NO:1 was determined to be either A or G. Among the three genotypes of AA, AG, or GG, the AA or AG genotypes of buffalo showed a higher weaning height than the GG genotype.

9. A method for screening SNP molecular markers as described in claim 1 or 2, characterized in that, The steps include the following: (1) Extract buffalo genomic DNA and perform whole-genome low-depth and high-depth resequencing to obtain raw sequencing data; (2) Quality control of the raw sequencing data, alignment to the buffalo reference genome, and use the Sentieon+Beagle strategy to detect genetic variations and fill genotypes on all autosomes of the sample to obtain SNP locus data; (3) Using the FarmCPU model with rMVP software, SNP sites and buffalo weaning height were analyzed by GWAS to obtain the SNP molecular markers related to the growth traits of the buffalo.

10. The method according to claim 9, characterized in that, The low-depth sequencing depth is 1×-2×, and the high-depth sequencing depth is 15×-20×. The number of low-depth sequencing results is higher than that of high-depth sequencing results. The genotype is filled by a large number of low-depth sequencing results with fewer high-depth sequencing results, thereby reducing sequencing costs.

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