scholarly journals Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Yang Wu ◽  
Zhili Zheng ◽  
Peter M. Visscher ◽  
Jian Yang
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Wide

scholarly journals Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Gabriel Costa Monteiro Moreira ◽  
Clarissa Boschiero ◽  
Aline Silva Mello Cesar ◽  
James M. Reecy ◽  
Thaís Fernanda Godoy ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Fat Deposition ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide

scholarly journals Genome-Wide Association Study Using Whole-Genome Sequencing Identifies a Genomic Region on Chromosome 6 Associated With Comb Traits in Nandan-Yao Chicken

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuliang Yang ◽  
Leqin Zou ◽  
Tiantian Sun ◽  
Wenwen Xu ◽  
Linghu Zeng ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Improvement ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Chromosome 6 ◽  
Whole Genome ◽  
Genome Wide

Comb traits have potential economic value in the breeding of indigenous chickens in China. Identifying and understanding relevant molecular markers for comb traits can be beneficial for genetic improvement. The purpose of this study was to utilize genome-wide association studies (GWAS) to detect promising loci and candidate genes related to comb traits, namely, comb thickness (CT), comb weight (CW), comb height, comb length (CL), and comb area. Genome-wide single-nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs) in 300 Nandan-Yao chickens were detected using whole-genome sequencing. In total, we identified 134 SNPs and 25 INDELs that were strongly associated with the five comb traits. A remarkable region spanning from 29.6 to 31.4 Mb on chromosome 6 was found to be significantly associated with comb traits in both SNP- and INDEL-based GWAS. In this region, two lead SNPs (6:30,354,876 for CW and CT and 6:30,264,318 for CL) and one lead INDEL (a deletion from 30,376,404 to 30,376,405 bp for CL and CT) were identified. Additionally, two genes were identified as potential candidates for comb development. The nearby gene fibroblast growth factor receptor 2 (FGFR2)—associated with epithelial cell migration and proliferation—and the gene cytochrome b5 reductase 2 (CYB5R2)—identified on chromosome 5 from INDEL-based GWAS—are significantly correlated with collagen maturation. The findings of this study could provide promising genes and biomarkers to accelerate genetic improvement of comb development based on molecular marker-assisted breeding in Nandan-Yao chickens.

scholarly journals Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Julia Höglund ◽  
Nima Rafati ◽  
Mathias Rask-Andersen ◽  
Stefan Enroth ◽  
Torgny Karlsson ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Accurate Determination ◽  
Genome Wide Association ◽  
Inflammatory Biomarkers ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide ◽  
Common Genetic Variants

AbstractGenome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.

scholarly journals Whole genome sequencing identifies common and rare structural variants contributing to hematologic traits in the NHLBI TOPMed program

2021 ◽  
Author(s):  
Marsha M. Wheeler ◽  
Adrienne M Stilp ◽  
Shuquan Rao ◽  
Bjarni V Halldorsson ◽  
Doruk V Beyter ◽  
...  
Keyword(s):  
Blood Cell ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Regulatory Elements ◽  
Chromatin Domain ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Structural Variants ◽  
Genome Wide

Genome-wide association studies (GWAS) have identified thousands of single nucleotide variants and small indels that contribute to the genetic architecture of hematologic traits. While structural variants (SVs) are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of SVs to quantitative blood cell trait variation is unknown. Here we utilized SVs detected from whole genome sequencing (WGS) in ancestrally diverse participants of the NHLBI TOPMed program (N=50,675). Using single variant tests, we assessed the association of common and rare SVs with red cell-, white cell-, and platelet-related quantitative traits. The results show 33 independent SVs (23 common and 10 rare) reaching genome-wide significance. The majority of significant association signals (N=27) replicated in independent datasets from deCODE genetics and the UK BioBank. Moreover, most trait-associated SVs (N=24) are within 1Mb of previously-reported GWAS loci. SV analyses additionally discovered an association between a complex structural variant on 17p11.2 and white blood cell-related phenotypes. Based on functional annotation, the majority of significant SVs are located in non-coding regions (N=26) and predicted to impact regulatory elements and/or local chromatin domain boundaries in blood cells. We predict that several trait-associated SVs represent the causal variant. This is supported by genome-editing experiments which provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

scholarly journals Genome-wide discovery of epistatic loci affecting antibiotic resistance using evolutionary couplings

2018 ◽  
Author(s):  
Benjamin Schubert ◽  
Rohan Maddamsetti ◽  
Jackson Nyman ◽  
Maha R. Farhat ◽  
Debora S. Marks
Keyword(s):  
Antibiotic Resistance ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Vast Number ◽  
Genome Wide

ABSTRACTThe analysis of whole genome sequencing data should, in theory, allow the discovery of interdependent loci that cause antibiotic resistance. In practice, however, identifying this epistasis remains a challenge as the vast number of possible interactions erodes statistical power. To solve this problem, we extend a method that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled and associated with antibiotic resistance. Our method reduces the number of tests required for an epistatic genome-wide association study and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 250 epistatic pairs that influence the dose needed to inhibit growth for five different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in an independent dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of loci occurred in unreported genes, including murE which was associated with cefixime. About half of the novel epistasis we report involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC associated with ciprofloxacin. Still, many combinations involved unreported loci and genes. Our work provides a systematic identification of epistasis pairs affecting antibiotic resistance in N. gonorrhoeae and a generalizable method for epistatic genome-wide association studies.

scholarly journals Genome-Wide Identification and Analysis of Variants in Domestic and Wild Bactrian Camels Using Whole-Genome Sequencing Data

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Nemat Hedayat-Evrigh ◽  
Reza Khalkhali-Evrigh ◽  
Mohammad Reza Bakhtiarizadeh
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Mountain Regions ◽  
Genome Wide ◽  
Risk Of Extinction ◽  
Bactrian Camels ◽  
First Time

The population size of Bactrian camels is smaller than dromedary, and they are distributed in cold and mountain regions and are also at the risk of extinction in some countries such as Iran. To identify and investigate the genome-wide variations, whole-genome sequencing of two Iranian Bactrian camels were performed with 37.4- and 42.6-fold coverage for the first time. Along with Iranian Bactrian camels, sequencing data from two Mongolian domestic and two wild Bactrian camels deposited in the NCBI were reanalyzed. The analysis eventuated to the identification of 4,908,998, 4,485,725, and 4,706,654 SNPs for Iranian, Mongolian domestic, and wild Bactrian camels, respectively. Also, INDEL variations ranged from 358,311 to 533,188 in all six camels. Results of variants annotation in all samples revealed that more than 88 percent of SNPs and INDELs were located in the intergenic and intronic regions. We found that 800,530 SNPs were common among all studied camels, containing 4,046 missense variants that affected 2,428 genes. Investigation of common genes among all camels containing the missense SNPs showed that there are 98 zinc finger and 4 fertility-related genes (ZP1, ZP2, ZP4, and ZPBP) in this set.

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