scholarly journals Explorations in genome-wide association studies and network analyses with dairy cattle fertility traits

2016 ◽  
Vol 99 (8) ◽  
pp. 6420-6435 ◽  
Author(s):  
K.L. Parker Gaddis ◽  
D.J. Null ◽  
J.B. Cole
Keyword(s):  
Dairy Cattle ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Network Analyses ◽  
Genome Wide ◽  
Fertility Traits

scholarly journals Measles Contributes to Rheumatoid Arthritis: Evidence from Pathway and Network Analyses of Genome-Wide Association Studies

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e75951 ◽  
Author(s):  
Guiyou Liu ◽  
Yongshuai Jiang ◽  
Xiaoguang Chen ◽  
Ruijie Zhang ◽  
Guoda Ma ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Network Analyses ◽  
Genome Wide

scholarly journals 301 Methods of genome-wide association studies and their applications in dairy cattle

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 31-31
Author(s):  
Li Ma
Keyword(s):  
Dairy Cattle ◽  
Complex Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetics Research ◽  
Genome Wide ◽  
Dairy Cattle Breeding

Abstract Genome-wide association studies (GWAS) has been widely used to map quantitative trait loci (QTL) of complex traits and diseases since 2007. To date, the human GWAS catalog has accumulated 4,410 publications and 172,351 associations, and the animal QTLdb has curated 983 publications and 130,407 QTLs for cattle, largest in livestock species. During the past 13 years of development, GWAS methods has evolved from simple linear regression, using principal components to address sample relatedness, mixed models, to Bayesian full model approaches. These methods have their advantages and limitations, so it is important to choose an appropriate method, especially for studies in livestock where sample size is often limited. Note that the most popular GWAS approach, the mixed model method, originated from animal breeding and genetics research. Leveraging the national cattle genomic database at the Council on Dairy Cattle Breeding (CDCB), we have conducted GWAS analyses of various dairy traits to identify QTLs and SNP markers of importance. Combining with sequence and functional annotation data, we seek to understand the genetic basis of complex traits and to reveal useful knowledge that can be incorporated into more accurate genomic predictions in the future.

scholarly journals Fine Mapping of Intracranial Aneurysm Susceptibility Based on a Genome-wide Association Study

2021 ◽  
Author(s):  
Eun Pyo Hong ◽  
Dong Hyuk Youn ◽  
Bong Jun Kim ◽  
Jun Hyong Ahn ◽  
Jeong Jin Park ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Fine Mapping ◽  
Bayes Factor ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Network Analyses ◽  
Genome Wide ◽  
A Genome

Abstract In addition to conventional genome-wide association studies (GWAS), a fine-mapping is increasingly used to identify the genetic function of variants associated with disease susceptibilities. Here, we used a fine-mapping approach to evaluate the casual variants based on a previous GWAS involving patients with intracranial aneurysm (IA). Fine-mapping analysis was conducted based on the chromosomal data provided by GWAS consisting 250 patients diagnosed with IA and 296 controls using posterior inclusion probability (PIP) and log10 transformed Bayes factor (log10BF). The narrow sense of heritability (h2) explained by each casual variant was estimated. Subsequent gene expression and functional network analyses were used to calculate the transcripts per million (TPM) values. Twenty causal candidate single nucleotide polymorphisms (SNPs) surpassed a genome-wide significance threshold for creditable evidence (log10BF > 6.1). Four SNPs including rs75822236 (R535H, GBA; log10BF = 15.06), rs112859779 (G141S, TCF24; log10BF = 12.12), rs79134766 (A208T, OLFML2A; log10BF = 14.92), and rs371331393 (Q1932X, ARHGAP32; log10BF = 20.88) showed a completed PIP value in each chromosomal region, suggesting a high probability of variant causality associated with IA. Expression in GBA was highly enriched in the whole blood (TPM = 33.13), while TCF24 were rarely expressed in all tissues and cells. No direct interaction was observed between the four casual genes; however, PSAP appeared to be particularly important via indirect correlation between other genes. Our results suggested that four mutations of GBA, TCF24, OLFML2A, and ARHGAP32 were linked to IA susceptibility and pathogenesis. Our approach may promise more informative mutations in the following GWAS.

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 Investigating the Effect of Imputed Structural Variants from Whole-Genome Sequence on Genome-Wide Association and Genomic Prediction in Dairy Cattle

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 541
Author(s):  
Long Chen ◽  
Jennie E. Pryce ◽  
Ben J. Hayes ◽  
Hans D. Daetwyler
Keyword(s):  
Dairy Cattle ◽  
Genomic Prediction ◽  
Complex Traits ◽  
Prediction Accuracy ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome Sequence ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide

Structural variations (SVs) are large DNA segments of deletions, duplications, copy number variations, inversions and translocations in a re-sequenced genome compared to a reference genome. They have been found to be associated with several complex traits in dairy cattle and could potentially help to improve genomic prediction accuracy of dairy traits. Imputation of SVs was performed in individuals genotyped with single-nucleotide polymorphism (SNP) panels without the expense of sequencing them. In this study, we generated 24,908 high-quality SVs in a total of 478 whole-genome sequenced Holstein and Jersey cattle. We imputed 4489 SVs with R2 > 0.5 into 35,568 Holstein and Jersey dairy cattle with 578,999 SNPs with two pipelines, FImpute and Eagle2.3-Minimac3. Genome-wide association studies for production, fertility and overall type with these 4489 SVs revealed four significant SVs, of which two were highly linked to significant SNP. We also estimated the variance components for SNP and SV models for these traits using genomic best linear unbiased prediction (GBLUP). Furthermore, we assessed the effect on genomic prediction accuracy of adding SVs to GBLUP models. The estimated percentage of genetic variance captured by SVs for production traits was up to 4.57% for milk yield in bulls and 3.53% for protein yield in cows. Finally, no consistent increase in genomic prediction accuracy was observed when including SVs in GBLUP.

scholarly journals Genome-Wide Association Studies for Milk Somatic Cell Score in Romanian Dairy Cattle

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1495
Author(s):  
Daniela Elena Ilie ◽  
Alexandru Eugeniu Mizeranschi ◽  
Ciprian Valentin Mihali ◽  
Radu Ionel Neamț ◽  
George Vlad Goilean ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Association Studies ◽  
Somatic Cell Score ◽  
The Body ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Cattle Breeds ◽  
Multiple Loci ◽  
Genome Wide

Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with −log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.

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