scholarly journals GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2048
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Milk Fat ◽  
Association Studies ◽  
High Yield ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Breeding Values ◽  
Genome Wide

High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk-related traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production and quality traits in Holstein cattle population from China. These traits included milk yield, fat, and protein. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a linear mixed model. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten single-nucleotide polymorphisms (SNPs) were detected above the genome-wide significant threshold (p < 4.0 × 10−7), including six located in previously reported quantitative traits locus (QTL) regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The study not only identified the effect of DGAT1 gene on milk fat and protein, but also discovered novel genetic loci and candidate genes related to milk traits. These novel genetic loci would be an important basis for molecular breeding in dairy cattle.

scholarly journals Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle

2020 ◽  
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Milk Yield ◽  
Genetic Variants ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Genome Wide

AbstractHigh-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a mixed linear model for individuals with and without phenotypic data. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the Fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.

scholarly journals Genome-Wide Association Studies in Indian Buffalo Revealed Genomic Regions for Lactation and Fertility

2021 ◽  
Vol 12 ◽  
Author(s):  
Vikas Vohra ◽  
Supriya Chhotaray ◽  
Gopal Gowane ◽  
Rani Alex ◽  
Anupama Mukherjee ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Association Studies ◽  
Post Partum ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Improvement Programs ◽  
Genomic Regions ◽  
Fertility Traits

Murrah breed of buffalo is an excellent dairy germplasm known for its superior milk quality in terms of milk fat and solids-not-fat (SNF); however, it is often reported that Indian buffaloes had lower lactation and fertility potential compared to the non-native cattle of the country. Recent techniques, particularly the genome-wide association studies (GWAS), to identify genomic variations associated with lactation and fertility traits offer prospects for systematic improvement of buffalo. DNA samples were sequenced using the double-digestion restriction-associated DNA (RAD) tag genotyping-by-sequencing. The bioinformatics pipeline was standardized to call the variants, and single-nucleotide polymorphisms (SNPs) qualifying the stringent quality check measures were retained for GWAS. Over 38,000 SNPs were used to perform GWAS on the first two principal components of test-day records of milk yields, fat percentages, and SNF percentages, separately. GWAS was also performed on 305 days’ milk yield; lactation persistency was estimated through the rate of decline after attaining the peak yield method, along with three other standard methods; and breeding efficiency, post-partum breeding interval, and age at sexual maturity were considered fertility traits. Significant association of SNPs was observed for the first principal component, explaining the maximum proportion of variation in milk yield. Furthermore, some potential genomic regions were identified to have a potential role in regulating milk yield and fertility in Murrah. Identification of such genomic regions shall help in carrying out an early selection of high-yielding persistent Murrah buffaloes and, in the long run, would be helpful in shaping their future genetic improvement programs.

scholarly journals Single-step genome-wide association studies (GWAS) and post-GWAS analyses to identify genomic regions and candidate genes for milk yield in Brazilian Girolando cattle

2020 ◽  
Vol 103 (11) ◽  
pp. 10347-10360
Author(s):  
Pamela I. Otto ◽  
Simone E.F. Guimarães ◽  
Mario P.L. Calus ◽  
Jeremie Vandenplas ◽  
Marco A. Machado ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Association Studies ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genomic Regions

scholarly journals Genome-Wide Association Study Identifies Candidate Genes Associated with Feet and Leg Conformation Traits in Chinese Holstein Cattle

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2259
Author(s):  
Ismail Mohamed Abdalla ◽  
Xubin Lu ◽  
Mudasir Nazar ◽  
Abdelaziz Adam Idriss Arbab ◽  
Tianle Xu ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Candidate Genes ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Chinese Holstein ◽  
Genome Wide ◽  
Chinese Holstein Cattle

Feet and leg conformation traits are considered one of the most important economical traits in dairy cattle and have a great impact on the profitability of milk production. Therefore, identifying the single nucleotide polymorphisms (SNPs), genes and pathways analysis associated with these traits might contribute to the genomic selection and long-term plan selection for dairy cattle. We conducted genome-wide association studies (GWASs) using the fixed and random model circulating probability unification (FarmCPU) method to identify SNPs associated with bone quality, heel depth, rear leg side view and rear leg rear view of Chinese Holstein cows. Phenotypic measurements were collected from 1000 individuals of Chinese Holstein cattle and the GeneSeek Genomic Profiler Bovine 100 K SNP chip was utilized for individual genotyping. After quality control, 984 individual cows and 84,906 SNPs remained for GWAS work; as a result, we identified 20 significant SNPs after Bonferroni correction. Several candidate genes were identified within distances of 200 kb upstream or downstream to the significant SNPs, including ADIPOR2, INPP4A, DNMT3A, ALDH1A2, PCDH7, XKR4 and CADPS. Further bioinformatics analyses showed 34 gene ontology terms and two signaling pathways were significantly enriched (p ≤ 0.05). Many terms and pathways are related to biological quality, metabolism and development processes; these identified SNPs and genes could provide useful information about the genetic architecture of feet and leg traits, thus improving the longevity and productivity of Chinese Holstein dairy cattle.

scholarly journals Genome wide association study in 3,173 outbred rats identifies multiple loci for body weight, adiposity, and fasting glucose

2018 ◽  
Author(s):  
Apurva S. Chitre ◽  
Oksana Polesskaya ◽  
Katie Holl ◽  
Jianjun Gao ◽  
Riyan Cheng ◽  
...  
Keyword(s):  
Body Weight ◽  
Candidate Genes ◽  
Family Relationships ◽  
Fasting Glucose ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Genome Wide

AbstractObjectiveObesity is influenced by genetic and environmental factors. Despite success of human genome wide association studies (GWAS), the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify genetic loci underlying obesity and related morphometric and metabolic traits.MethodsWe measured obesity-relevant traits including body weight, body length, body mass index, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat GWAS to date. Genetic loci were identified using a linear mixed model that accounted for the complex family relationships of the HS and covariate to account for differences among the three phenotyping centers.ResultsWe identified 32 independent loci, several of which contained only a single gene (e.g. Epha5, Nrg1 and Klhl14) or obvious candidate genes (Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and extensive pleiotropy at individual loci.ConclusionsThese studies demonstrate utility of HS rats for investigating the genetics of obesity related traits across institutions and identify several candidate genes for future functional testing.

scholarly journals Genome-wide Association Study-based Identification Genes Influencing Agronomic Traits in Rice (Oryza Sativa L.)

2020 ◽  
Author(s):  
aijun wang ◽  
Xinyue Shu ◽  
yuqi Jiang ◽  
Li Ma ◽  
xiaomei jia ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Candidate Genes ◽  
Human Population ◽  
Agronomic Traits ◽  
Association Studies ◽  
Rice Genome ◽  
Genome Wide Association ◽  
High Yield ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract BackgroundRice (Oryza sativa L.) is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. To needs of the rapidly increasing human population worldwide, cultivation of rice varieties with high yield and quality, more genes or QTLs association with yield traits are required.ResultsCurrently, correlations among different traits and gene interactions both affect the rice breeding. Here, we re-sequenced 259 rice accessions, generating 1, 371.65 Gb of raw data. Furthermore, we performed genome-wide association studies (GWAS) on 13 agronomic traits using 2.8 million single nucleotide polymorphisms (SNPs) characterized in 259 rice accessions. Phenotypic data and best linear unbiased prediction (BLUP) values of each of the 13 traits over two years of each trait were used for GWAS. The result showed that 816 SNP signals were significantly associated (−log10P≥5) with the 13 agronomic traits. We detected candidate genes related to target traits within 200 kb upstream and downstream of the associated SNP loci, based on linkage disequilibrium (LD) blocks in the whole rice genome. These candidate genes were further identified though haplotype block construction. ConclusionsThis study provides an important genomic resource and valuable new information for breeding high yielding breeding rice cultivars through genomic selection.

scholarly journals Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Biological Aging ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Biomarkers Of Aging ◽  
Genome Wide ◽  
Shared Genetic

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

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