Patent Application
20240043912
This patent application claims the benefit and priority of Chinese Patent Application No. 2022108894331, filed with the China National Intellectual Property Administration on Jul. 27, 2022, the disclosure of which is incorporated by reference herein in its entirety as part of the present application.
The present disclosure belongs to the technical field of molecular breeding, and in particular relates to a genomic selection (GS) breeding chip of Huaxi cattle and use thereof.
Breed is a determinant of the quality and efficiency of livestock and poultry farming. Traditional breeding is mainly based on conventional breeding methods or processes such as appearance assessment, pedigree records, performance determination, and descendant determination. Compared with pigs, poultry and other high reproductive livestock and poultry, beef cattle have long generation interval and low reproductive rate. In beef cattle, most of the important economic traits are quantitative traits, and traits such as carcass and meat quality have low heritability, high cost of determination, and difficult in early determination. These factors make the conventional breeding to conduct breed improvement and new breed breeding of beef cattle relatively slowly. Genomic selection (GS), the main selection and breeding technology in current livestock and poultry breeding, can effectively shorten generation interval and accelerate genetic progress. This method estimates an individual's genomic breeding value with genetic markers covering the entire genome. Based on the marker information and phenotype information of known populations, the association between markers and phenotypes is established. In this way, the effects of all genotype markers can be estimated on a genome-wide scale, and then reasonable predictions can be made for populations with unknown phenotypes, thereby achieving more comprehensive and reliable selection of varieties. The GS has been applied to the breeding practice of dairy cattle, beef cattle, pigs, chickens and other livestock and poultry, improves the accuracy of animal breeding, and significantly reduces the cost of breeding.
Single nucleotide polymorphism (SNP) genotyping detection technology is mainly based on whole-genome resequencing and SNP genotyping beadchip. The whole-genome resequencing can obtain the most comprehensive genome variation information, but has cumbersome operation procedures and complex data analysis. If this technology is applied to large-scale analysis with a large number of individuals, there may be relatively high sequencing and computing costs. The gene beadchip technology used for SNP genotyping arranges millions of DNA marker sequences on glass slides, silicon wafers and other solid-phase media, and fixes them to form an SNP beadarray. The DNA probe sequences on the chip are complementary hybridized with a target genome, and the SNP is genotyped by fluorescence scanning. At present, there are many types of beadchips used for SNP genotyping in the field of beef cattle breeding. The two most commercialized SNP beadchip products used in Chinese beef cattle breeding are Illumina BovineHD (770K) and Neogen GGP Bovine 100K. However, the markers used in existing commercial chips are mainly derived from foreign beef cattle breeds, and the effective information only account for about 80%, while many SNPs fail to be detected. Moreover, these beadchips lack the genomic genetic variation markers of Chinese beef cattle breeds, and show a high cost. This limits the popularization and application of GS in beef cattle breeding in China.
Compared with foreign beef cattle breeds, the slaughter rate, meat production rate, and carcass weight of local cattle breeds in China are significantly different from those in foreign countries with developed beef cattle industries. Huaxi cattle, as a new breed of large-scale specialized beef cattle that has been independently bred in China for more than 40 years, passed the examination and approval of the National Animal Genetic Resources Committee in 2021. The Huaxi cattle has gone through three breeding stages: hybridization exploration stage (1978-1993), germplasm innovation stage (1994-2003), and breeding improvement (2004-present). This breed has fast growth, high slaughter rate and net meat rate, and wide adaptability and distribution. Currently, the total stock of Huaxi cattle exceeds heads, and the core herd contains more than 3,600 heads, mainly distributed in Inner Mongolia, Henan, Hubei, Jilin, Yunnan, and Xinjiang. In order to promote the continuous breeding and variety promotion of Huaxi cattle, as well as improve the production performance and self-supplying ability of Chinese beef cattle, it is of great significance to design a genome-wide genotyping chip for GS breeding of the Huaxi cattle. This chip is intended to improve an accuracy of a genomic estimated breeding value (GEBV) for important economic traits of the Huaxi cattle, accelerate genetic progress, shorten generation intervals, launch early selection, and reduce breeding costs.
In view of this, an objective of the present disclosure is to provide a GS breeding chip of Huaxi cattle and use thereof. The breeding chip is evenly distributed on chromosomes of a whole-genome, and has high coverage, moderate throughput of sites, high cost performance, and desirable compatibility with existing commercial beadchips.
To achieve the above objective, the present disclosure provides the following technical solutions:
The present disclosure provides a molecular marker combination for whole-genome genotyping of Huaxi cattle, including seven marker panels; where a first marker panel includes 7,221 SNPs; a second marker panel includes 22,937 SNPs and 1 Indel; a third marker panel includes 249 SNPs; a fourth marker panel includes 3,907 SNPs and 2 Indels; a fifth marker panel includes 6,190 SNPs; a sixth marker panel includes a total of 74,098 markers verified in a Huaxi cattle population from Illumina BovineHD chip and Neogen GGP Bovine 100K chip; and a seventh marker panel includes 2,617 SNPs.
The present disclosure further provides a whole-genome breeding chip of Huaxi cattle, including the molecular marker combination.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in detection for genotyping of the Huaxi cattle.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in genome-wide association study (GWAS) of the Huaxi cattle.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in parentage testing of the Huaxi cattle.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in GS breeding of the Huaxi cattle.
the present disclosure provides a molecular marker combination for whole-genome genotyping of Huaxi cattle, where genotyping objects involve 112,177 SNPs and 3 Indel sites, including seven marker panels. A first marker panel has a total of 7,221 SNPs associated with important economic traits of Huaxi cattle, including 3,065 SNPs obtained from GWAS analysis of important economic traits such as growth and development traits, fattening traits, carcass traits, meat quality traits, and reproductive traits, as well as 4,158 SNPs obtained by BayesB analysis on 11 important economic traits. A second marker panel has a set of functional region SNPs and Indels that integrate genome resequencing, transcriptome, exome, epigenome and other omics data, with a total of 22,938 markers including 3,800 SNPs related to three tissue-specific gene expressions of longissimus dorsi muscle, liver, and subcutaneous fat, 9,242 SNPs in the exon region related to the difference between high and low phenotypes screened by exon capture sequencing, 1 Indel, and 9,985 SNPs involved in epigenetic and gene regulation screened by ATAC-seq (assay for transposase accessible chromatin with high-throughput sequencing). A third marker panel has 249 SNPs for identification of genetic relationship. A fourth marker panel has 3,907 functional SNPs and 2 Indels related to important economic traits and diseases of beef cattle, with a total of 3,909 markers. A fifth marker panel has a total of 6,190 SNPs related to important economic traits of beef cattle reported in the QTL database. A sixth marker panel has a total of 74,098 effective SNPs verified in the Huaxi cattle population by Illumina BovineHD beadchip and Neogen GGP Bovine 100K beadchip. A seventh marker panel has a total of 2,617 SNPs filling a gap region larger than 100 kb. The mentioned-above seven marker panels have a total of 112,177 SNPs and 3 Indels for the synthesis of probes and the customization of liquid-phase chips for genotyping by target sequencing.
In the present disclosure, the whole-genome breeding chip also has the following five features. A first is functional correlation: the trait-associated markers of Huaxi cattle selected involve seven categories of growth, fattening, carcass, meat quality, reproduction, disease, and health, with a total of 129 traits, including 13,581 important functional SNPs. Applying these SNPs to GS breeding can ensure the accuracy of GEBV estimation so as to accelerate the GS breeding process of Huaxi cattle. A second is pertinence and effectiveness: the selected markers come from the research results and data accumulation of population genetic evaluation and trait mining/utilization of Huaxi cattle. The functional markers have been verified by high-density beadchips and re-sequencing, and a polymorphism of the SNPs is excellent in the population, showing desirable validity. A third is innovation: through the optimal design of multi-level omics such as re-sequencing, transcriptome, exome, and epigenome, the newly discovered trait-specific functional SNPs and Indels of Huaxi cattle are selected. These markers are not recorded in the existing Ensemble database. A fourth is comprehensiveness: GEBV comprehensive evaluation is conducted on slaughter traits, meat quality traits, body size traits, and five traits used by genomic China beef index (GCBI) with high accuracy. A fifth is practicality and cost performance the breeding chip shows uniform distribution of chromosomes in the whole-genome, high coverage, and moderate throughput of markers. This breeding chip has desirable compatibility with existing commercial beadchips and high cost performance.
The present disclosure provides a molecular marker combination for whole-genome genotyping of Huaxi cattle, including 112,177 SNPs and 3 Indels, where genome position information of the marker loci is shown in SEQ ID NO: 1 to SEQ ID NO: 112180.
In the present disclosure, the whole-genome breeding chip is preferably a liquid-phase chip, and detection of the molecular markers can be genotyping based on targeted capture sequencing technology. The ARS-UCD 1.2/bosTau9 version is preferably used as a reference genome of cattle. In the examples, the genome-wide breeding chip of Huaxi cattle is named “Cattle110K” chip. The working principle is: based on a DNA extracted from the tested blood sample, targeted capture and sequencing are conducted through base pairing, so as to realize the gene detection and genotyping of a target region. With the “Cattle110K” chip, the DNA samples of Huaxi cattle can be detected, such that this chip is applied to the whole-genome of Huaxi cattle for SNP genotyping, genomic selection, GWAS, population genetics analysis, gene fine mapping, genome-wide linkage study, parentage testing, and germplasm evaluation.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in genome-wide association study (GWAS) of the Huaxi cattle. In the present disclosure, the use is preferably the same as the above content, and is not repeated here.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in parentage testing of the Huaxi cattle. In the present disclosure, the use is preferably the same as the above content, and is not repeated here.
The present disclosure further provides use of the molecular marker combination or the genome-wide breeding chip in GS breeding of the Huaxi cattle. In the present disclosure, the use is preferably the same as the above content, and is not repeated here.
The GS breeding chip of Huaxi cattle and the use thereof provided by the present disclosure are described in detail below with reference to the examples, but these examples should not be understood as limiting the claimed scope of the present disclosure.
Acquisition of Seven Marker Panels for Cattle110K Huaxi Cattle Genome-Wide SNP Chip
In the present disclosure, the molecular marker combination involved 7 panels in total.
In the present disclosure, a method for obtaining a first panel of markers preferably included: 1,233 individuals with the most complete phenotype data records were selected among 4,694 individuals genotyped with the Illumina BovineHD (770K) beadchip. Taking the whole-genome resequencing data of 44 Huaxi cattle individuals as a reference group, the BovineHD results of 1,233 individuals were imputed into the level of resequencing genotype data. SNPs with MAF less than 0.05, individual deletion rate greater than 10%, and without HWE (hardy-weinberg equilibrium) P value of 1×10−6 were eliminated, and finally a total of 6,776,719 SNPs were remained for screening SNPs closely related to important economic traits of Huaxi cattle. Preferably, there were two parts: a first part was to conduct GWAS on important economic traits such as growth and development traits, fattening traits, carcass traits, meat quality traits, and reproductive traits. Specifically, the traits included growth and development traits (birth weight, weaning weight, yearling weight), fattening traits (daily gain during fattening period), carcass weight traits (carcass weight, lean meat weight, bone weight), carcass meat production traits (dressing percentage, lean meat percentage, carcass meat percentage), carcass morphological traits (carcass length, carcass depth, hind leg depth of carcass), meat quality traits (marbling, tenderness, pH value), and reproductive traits (calving ease). A total of 3,065 SNPs (P<5×10−8) significantly associated with traits were obtained after deduplication. A second part was to conduct BayesB analysis on a total of 11 important economic traits, including weaning weight, daily gain during fattening period, slaughter weight, carcass weight, chuck roll weight, ribeye weight, retail meat weight, dressing percentage, lean meat percentage, marbling score, and shear force. Sorting was done according to SNP effect value, and the top 0.01% of loci were selected. After deduplication, a total of 4,158 large-effect SNPs were obtained. Based on the combination of the above trait-associated analysis results, a total of 7,221 functional SNPs of important economic traits of Huaxi cattle were obtained through biostatistical analysis and deduplication. The information of first marker panel was shown in Table 1:
In the present disclosure, a second marker panel was a set of functional region markers integrating omics data from three sources. The three sources were: (1) transcriptome data of the longissimus dorsi muscle, liver, and subcutaneous fat of 120 adult cattle. Association analysis was conducted between the genotype of Illumina BovineHD beadchip and the gene expression level as a phenotype. By mapping and locating cis-eQTL and trans-eQTL, a total of 3,800 markers related to the expression of tissue-specific genes were selected. (2) Targeted sequence capture was conducted on all known exons and gene regulatory regions in the bovine genome, and individuals with phenotypic differences in body length and heart girth were selected. After high-throughput sequencing, the capture sequencing data of the high- and low-phenotype groups were obtained separately. A total of 9,243 markers were selected, including 9,242 SNPs in the exon region and 1 Indel that were related to differences between phenotype groups. (3) For the open chromatin region of the genome, ATAC-seq data involved in epigenetics and gene regulation were obtained: at the cellular level, the different stages of myoblast proliferation and differentiation were analyzed, and the difference peak regions in different stages were mapped to the SNP loci of Illumina BovineHD beadchip, such that 5,437 SNPs were obtained; at the individual level, the ATAC-seq data of the longissimus dorsi muscle of adult Huaxi cattle were analyzed, and the differential peak regions were mapped to the resequencing data of 44 Huaxi cattle individuals. A SNP with the highest MAF was selected in each interval, and 4,561 SNPs were obtained. By combining the two parts of ATAC-seq results, 9,985 SNPs involved in epigenetic and gene regulation were selected. Based on the sets of functional regions identified above, a total of 22,938 functional markers from different sources of omics data were obtained through biostatistical analysis and deduplication. The information of second marker panel was shown in Table 2:
In the present disclosure, a third marker panel was preferably a total of 249 SNPs for identifying genetic relationship, and the SNPs information was shown in Table 3:
In the present disclosure, a fourth marker panel was preferably integrated with the relevant research results of the inventor's team in the previous period and published literature in PUBMED. The specific traits included 73 traits in five categories including growth, fattening, carcass, meat quality, and genetic diseases of beef cattle. Applied methods included single-trait GWAS, multi-trait GWAS, wssGWAS, Bayesian analysis, selection signal detection, haplotype, CNV and ROH analysis. A total of 3,909 markers were obtained, including 3,907 functional SNPs and 2 Indels. The information of fourth marker panel was shown in Table 4:
In the present disclosure, a fifth marker panel was preferably a total of 6,190 functional SNPs related to beef cattle traits obtained from public databases. The acquisition of the fifth marker panel preferably included: currently known quantitative trait loci (QTL) and SNPs data of bovine species were downloaded from the online animal QTL database (https://www.animalgenome.org/cgi-bin/QTLdb/BT/index). A total of 7,763 QTLs related to five major traits of beef cattle, including exterior, health, meat and carcass, production, reproduction, and the included SNPs information were obtained. According to the rs number of each marker, their corresponding physical positions in the “ARS-UCD 1.2/bosTau9” genome version were found, and a total of 6,190 SNPs with MAF>0.05 in Huaxi cattle population were selected. The information of fifth marker panel was shown in Table 5:
In the present disclosure, a sixth marker panel was preferably obtained from two current mainstream commercial beadchips to obtain effective information SNPs of Huaxi cattle, and an obtaining method preferably included: genotyping results of Illumina BovineHD beadchip and Neogen GGP Bovine 100K beadchip in Huaxi cattle population were allowed to have quality control at a MAF of greater than 0.1, a genotype deletion rate of less than 10%, and a P value with HWE testing of 1×10−6, while a total of 74,098 effective information markers were retained in Huaxi cattle population.
In the present disclosure, a method for obtaining a seventh marker panel preferably included: the markers derived from the above six marker panels were summarized, and a total of 109,563 variations of the ARS-UCD 1.2/bosTau9 genome version were obtained by deduplication of biostatistical methods. In order to ensure that the markers were evenly distributed on the chromosome, the gap regions of the genome larger than 100 kb were filled. The sources of filling SNPs were preferably prioritized as follows: Illumina BovineHD beadchip, whole-genome resequencing data, and Neogen GGP Bovine 100K beadchip. Considering the MAF value and a distance from the SNP locus in each gap to both ends, a total of 2,617 SNPs for gap filling with uniform distribution of chromosomes were finally obtained and added to the chip. The information of seventh marker panel was shown in Table 6:
The present disclosure provided a molecular marker combination for whole-genome breeding of Huaxi cattle, where 112,180 genetic variations were evenly covered on the whole-genome (
Statistics and Use of Heritability of Various Traits of Huaxi Cattle Based on Cattle110K Chip
The Cattle110K chip provided by the present disclosure was used to detect the genotypes of 1,233 individuals in the Huaxi cattle resource population. For the important economic traits of Huaxi cattle, a REML method of Asreml software was used to estimate the heritability of each trait based on two different SNP numbers of Cattle110K chip and Illumina BovineHD (770K) beadchip. Through the heritability estimation of traits such as slaughter, meat quality, growth, and GCBI (Table 7), 110K and 770K showed stable heritability at two different SNP numbers, proving the reliability of the Cattle110K chip for GS.
Genetic Background Analysis of Huaxi Cattle Based on Cattle110K Genotyping Results
In order to verify use of the GS breeding chip of Huaxi cattle in the genotype identification of Huaxi cattle population, the Cattle110K chip of the present disclosure was used to evaluate the genetic diversity of a total of 9 cattle breeds (populations). The breeds (populations) included Huaxi cattle, Mongolian cattle, Sanhe cattle, Charolais cattle, Australian Simmental cattle, Canadian Simmental cattle, American Simmental cattle, German Simmental cattle, and French Simmental cattle. The source and number of samples of each breed were shown in Table 8.
Cluster analysis was conducted by Neighbor-joining method, and an individual-based phylogenetic tree was constructed. As shown in
By calculating the Nei's genetic distance and F-statistic (Fst) value or fixation index between each population, the degree of genetic difference between Huaxi cattle and other cattle breeds at the population level was analyzed. The results were shown in Table 9. The Nei distance between the 9 populations ranged from 0.0734 to 0.2252, where Huaxi cattle had the closest genetic distance (0.0734) to Australian Simmental cattle, and had a farther genetic distance (0.1801) to Mongolian cattle. The Fst values of the 9 populations ranged from 0.0251 to 0.1231, where Huaxi cattle had the least degree of differentiation (0.0323) from Australian Simmental cattle, and had a greater degree of differentiation from Mongolian cattle and Sanhe cattle.
Evaluation of Imputation Accuracy of Cattle110K
In the Huaxi cattle resource population, 414 individuals with Cattle110K chip genotyping data were selected as a verification group, and 4,203 individuals with Illumina BovineHD beadchip genotyping data were selected as a reference group. Through the Beagle v5.0 software, SNP genotypes of Cattle110K chip was imputed to marker density of Illumina BovineHD beadchip. The genotype concordance and genotype correlation coefficient were used as evaluation criteria for the accuracy of genotype imputation. On one hand, the percentage of correctly imputed genotypes was calculated for each individual, resulting in the average genotype concordance of 0.986 for the 414 individuals. Among them, 408 individuals had a percentage greater than 0.950, accounting for 98.55% of the total individuals. On the other hand, the correlation coefficient between the imputed and true genotype was calculated for each individual. The average genotype correlation coefficient of 414 individuals was Among them, 396 individuals had a coefficient greater than 0.950, accounting for 95.65% of the total individuals.
GWAS of the Important Economic Traits of Huaxi Cattle Based on Cattle110K Chip
The Cattle110K chip provided by the present disclosure was used to detect the genotypes of 1,233 individuals in the Huaxi cattle resource population. The quality control standards of the genotype data were as follows: a SNP call rate was greater than 90%, a MAF was greater than 0.05, and a P value of the HWE testing was less than 1×10−6. After quality control, a total of 104,575 SNPs were remaining for GWAS on the important economic traits of Huaxi cattle, including hip height (weaning), abdominal circumference (6 months old), slaughter weight, dressing percentage, carcass length, and marbling score.
A general linear model was applied for the GWAS analysis. P value of independent test was 4.78×10−7 (0.05/104575) as a significance threshold of the whole-genome (
Use of GS Breeding Based on Cattle110K Chip
The Cattle110K chip provided by the present disclosure was used to conduct genome-wide genetic evaluation on Huaxi cattle population. A specific method included: (1) genotyping was conducted on 1,233 individuals in the Huaxi cattle resource group established in a pasture of the Wulagai management area of Xilin-Gol League in Inner Mongolia. (2) Genotype quality control was conducted at a SNP call rate of greater than 90%, a MAF of greater than 0.05, and a P value of HWE testing of less than 1×10−6. (3) GEBV prediction of 7 important economic traits including slaughter, meat quality, and body size, and 5 GCBI traits (calving ease, weaning weight, average daily gain during fattening period, carcass weight, and dressing percentage) was estimated using GBLUP and BayesB methods, separately. (4) An accuracy of GEBV was calculated by 5-fold cross-validation, and the results of the Cattle110K chip and Illumina BovineHD beadchip were compared. The calculation results were shown in Table 10.
Regarding the slaughter traits such as lean meat weight, dressing percentage, and carcass length, the accuracy of GEBV calculated by GBLUP and BayesB methods was relatively consistent in Cattle110K chip provided by the present disclosure and Illumina BovineHD beadchip. Specifically, in the lean meat weight and dressing percentage traits, the accuracy of Cattle110K calculated by the GBLUP and BayesB was higher than that of Illumina BovineHD. The accuracy of lean meat weight increased by 5.81% and 7.11%, respectively, and the accuracy of dressing percentage increased by 6.86% and 3.11%, respectively. In terms of carcass length trait, the accuracy of Cattle110K calculated by the GBLUP and BayesB was slightly lower than that of Illumina BovineHD, with a decrease of 1.58% and 7.73%, respectively.
For the two meat traits of shear force and ribeye area, the GEBV results of Cattle110K chip and Illumina BovineHD beadchip with the two analysis methods were slightly different. Specifically, in the shear force trait, the accuracy of Cattle110K calculated by the GBLUP and BayesB was higher than that of Illumina BovineHD, which increased by 2.71% and 9.60%, respectively. In the ribeye area trait, the GBLUP result of Cattle110K was 2.12% higher than that of Illumina BovineHD, while the BayesB result showed a decrease of 0.21%.
For the two body size traits of body length and heart girth at 12 months of age, the GEBV results of Cattle110K chip and Illumina BovineHD beadchip with the two analysis methods were slightly different. Specifically, in the body length trait, the GBLUP result of Cattle110K was 0.18% higher than that of Illumina BovineHD, while the BayesB result showed a decrease of 8.87%. In the terms of heart girth trait, the accuracy results of GEBV calculated by GBLUP and BayesB methods using Cattle110K chip were lower than those of Illumina BovineHD beadchip, with a decrease of 0.80% and 5.55%, respectively.
For the five GCBI traits, including weaning weight, average daily gain during fattening period, carcass weight, dressing percentage, and calving ease, the GEBV results of Cattle110K chip and Illumina BovineHD beadchip with the two analysis methods were slightly different. Specifically, in the weaning weight trait, the GBLUP result of Cattle110K was 0.20% lower than that of Illumina BovineHD, while the BayesB result showed an increase of 3.22%. In the average daily gain trait during fattening period, the GBLUP result of Cattle110K was 0.31% higher than that of Illumina BovineHD, while the BayesB result showed a decrease of 1.65%. In the carcass weight trait, the GBLUP result of Cattle110K was 3.97% higher than that of Illumina BovineHD, while the BayesB result showed a decrease of 2.84%. In the dressing percentage trait, the accuracy results of Cattle110K were improved in both methods by 2.91% and 1.94%, respectively. In the calving ease, the GBLUP result of Cattle110K was 1.31% lower than that of Illumina BovineHD, while the BayesB results showed an increase of 1.71%.
From the above results, although the number of markers used by the Cattle110K chip provided by the present disclosure was lower than that of the Illumina BovineHD chip (770K), the results of genetic evaluation of traits such as slaughter, meat quality, growth and development, and GCBI traits showed that the accuracy of GEBV prediction of the Cattle110K chip was highly consistent with that of Illumina BovineHD beadchip. Compared with the accuracy results estimated by Illumina BovineHD, the accuracy of Cattle110K calculated by GBLUP and BayesB was improved or decreased by not more than 10%. This indicated that the SNPs selected in the Cattle110K chip of Huaxi cattle could provide informative and accurate data for GS, and the evaluation results of many traits were better, thereby contributing the genetic improvement in GS breeding of Huaxi cattle.
The above are merely preferred implementations of the present disclosure. It should be noted that several improvements and modifications may further be made by a person of ordinary skill in the art without departing from the principle of the present disclosure, and such improvements and modifications should also be deemed as falling within the protection scope of the present disclosure.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022108894331 | Jul 2022 | CN | national |
