scholarly journals Genome-wide association study of endo-parasite phenotypes using imputed whole-genome sequence data in dairy and beef cattle

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Alan J. Twomey ◽  
Donagh P. Berry ◽  
Ross D. Evans ◽  
Michael L. Doherty ◽  
David A. Graham ◽  
...  
Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1163
Author(s):  
Manuel J. Wolf ◽  
Tong Yin ◽  
Guilherme B. Neumann ◽  
Paula Korkuć ◽  
Gudrun A. Brockmann ◽  
...  

This genome-wide association study (GWAS) aimed to identify sequence variants (SVs) and candidate genes associated with fertility and health in endangered German Black Pied cattle (DSN) based on whole-genome sequence (WGS) data. We used 304 sequenced DSN cattle for the imputation of 1797 genotyped DSN to WGS. The final dataset included 11,413,456 SVs of 1886 cows. Cow traits were calving-to-first service interval (CTFS), non-return after 56 days (NR56), somatic cell score (SCS), fat-to-protein ratio (FPR), and three pre-corrected endoparasite infection traits. We identified 40 SVs above the genome-wide significance and suggestive threshold associated with CTFS and NR56, and three important potential candidate genes (ARHGAP21, MARCH11, and ZNF462). For SCS, most associations were observed on BTA 25. The GWAS revealed 61 SVs, a cluster of 10 candidate genes on BTA 13, and 7 pathways for FPR, including key mediators involved in milk fat synthesis. The strongest associations for gastrointestinal nematode and Dictyocaulus viviparus infections were detected on BTA 8 and 24, respectively. For Fasciola hepatica infections, the strongest associated SVs were located on BTA 4 and 7. We detected 200 genes for endoparasite infection traits, related to 16 pathways involved in host immune response during infection.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 25-25
Author(s):  
Muhammad Yasir Nawaz ◽  
Rodrigo Pelicioni Savegnago ◽  
Cedric Gondro

Abstract In this study, we detected genome wide footprints of selection in Hanwoo and Angus beef cattle using different allele frequency and haplotype-based methods based on imputed whole genome sequence data. Our dataset included 13,202 Angus and 10,437 Hanwoo animals with 10,057,633 and 13,241,550 imputed SNPs, respectively. A subset of data with 6,873,624 common SNPs between the two populations was used to estimate signatures of selection parameters, both within (runs of homozygosity and extended haplotype homozygosity) and between (allele fixation index, extended haplotype homozygosity) the breeds in order to infer evidence of selection. We observed that correlations between various measures of selection ranged between 0.01 to 0.42. Assuming these parameters were complementary to each other, we combined them into a composite selection signal to identify regions under selection in both beef breeds. The composite signal was based on the average of fractional ranks of individual selection measures for every SNP. We identified some selection signatures that were common between the breeds while others were independent. We also observed that more genomic regions were selected in Angus as compared to Hanwoo. Candidate genes within significant genomic regions may help explain mechanisms of adaptation, domestication history and loci for important traits in Angus and Hanwoo cattle. In the future, we will use the top SNPs under selection for genomic prediction of carcass traits in both breeds.


2017 ◽  
Author(s):  
◽  
Wouter Van Rheenen ◽  
Sara L. Pulit ◽  
Annelot M. Dekker ◽  
Ahmad Al Khleifat ◽  
...  

AbstractThe most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1 %), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.


Sign in / Sign up

Export Citation Format

Share Document