scholarly journals Genome Analysis Identified Novel Candidate Genes for Ascochyta Blight Resistance in Chickpea Using Whole Genome Re-sequencing Data

2017 ◽  
Vol 8 ◽  
Author(s):  
Yongle Li ◽  
Pradeep Ruperao ◽  
Jacqueline Batley ◽  
David Edwards ◽  
Jenny Davidson ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genome Analysis ◽  
Ascochyta Blight ◽  
Blight Resistance ◽  
Whole Genome ◽  
Sequencing Data

scholarly journals Whole genome variants across 57 pig breeds enable comprehensive identification of genetic signatures that underlie breed features

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingya Xu ◽  
Yuhua Fu ◽  
Yan Hu ◽  
Lilin Yin ◽  
Zhenshuang Tang ◽  
...  
Keyword(s):  
Body Weight ◽  
Candidate Genes ◽  
Complex Traits ◽  
Coat Color ◽  
Body Height ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Pig Breeds ◽  
Genome Variants

Abstract Background A large number of pig breeds are distributed around the world, their features and characteristics vary among breeds, and they are valuable resources. Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved pig breeds. Results In this study, we performed GWAS using a standard mixed linear model with three types of genome variants (SNP, InDel, and CNV) that were identified from public, whole-genome, sequencing data sets. We used 469 pigs of 57 breeds, and we identified and analyzed approximately 19 million SNPs, 1.8 million InDels, and 18,016 CNVs. We defined six biological phenotypes by the characteristics of breed features to identify the associated genome variants and candidate genes, which included coat color, ear shape, gradient zone, body weight, body length, and body height. A total of 37 candidate genes was identified, which included 27 that were reported previously (e.g., PLAG1 for body weight), but the other 10 were newly detected candidate genes (e.g., ADAMTS9 for coat color). Conclusion Our study indicated that using GWAS across a modest number of breeds with high density genome variants provided efficient mapping of complex traits.

scholarly journals Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562

2017 ◽  
Author(s):  
Bo Zhou ◽  
Steve S. Ho ◽  
Stephanie U. Greer ◽  
Xiaowei Zhu ◽  
John M. Bell ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Genome Analysis ◽  
Large Scale ◽  
Wide Spectrum ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Analysis ◽  
Multiple Allele ◽  
Specific Expression ◽  
Allele Specific

ABSTRACTK562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and Indels (both corrected for CN in aneuploid regions), loss of heterozygosity, mega-base-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs) including small and large-scale complex SVs and non-reference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor geneFHIT. Taking aneuploidy into account, we re-analyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.

scholarly journals Detection of complex structural variation from paired-end sequencing data

2017 ◽  
Author(s):  
Joseph G. Arthur ◽  
Xi Chen ◽  
Bo Zhou ◽  
Alexander E. Urban ◽  
Wing Hung Wong
Keyword(s):  
Genome Sequencing ◽  
Genome Analysis ◽  
Structural Variation ◽  
State Of The Art ◽  
Whole Genome ◽  
Structural Variants ◽  
Sequencing Data ◽  
Complex Structural Variation ◽  
Complex Structural ◽  
Paired End Sequencing

AbstractDetecting structural variants (SVs) from sequencing data is key to genome analysis, but methods using standard whole-genome sequencing (WGS) data are typically incapable of resolving complex SVs with multiple co-located breakpoints. We introduce the ARC-SV method, which uses a probabilistic model to detect arbitrary local rearrangements from WGS data. Our method performs well on simple SVs while surpassing state-of-the-art methods in complex SV detection.

scholarly journals Role of SNPs in the Biogenesis of Mature miRNAs

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ying Wang ◽  
Jidong Ru ◽  
Xianglian Meng ◽  
Jianhua Song ◽  
Qingfeng Jiang ◽  
...  
Keyword(s):  
Genome Analysis ◽  
Mature Mirnas ◽  
Mirna Biogenesis ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Sequence Alignments ◽  
Whole Genome Analysis ◽  
Functional Snps ◽  
Mirna Sequencing

Single nucleotide polymorphisms (SNPs) play a significant role in microRNA (miRNA) generation, processing, and function and contribute to multiple phenotypes and diseases. Therefore, whole-genome analysis of how SNPs affect miRNA maturation mechanisms is important for precision medicine. The present study established an SNP-associated pre-miRNA (SNP-pre-miRNA) database, named miRSNPBase, and constructed SNP-pre-miRNA sequences. We also identified phenotypes and disease biomarker-associated isoform miRNA (isomiR) based on miRFind, which was developed in our previous study. We identified functional SNPs and isomiRs. We analyzed the biological characteristics of functional SNPs and isomiRs and studied their distribution in different ethnic groups using whole-genome analysis. Notably, we used individuals from Great Britain (GBR) as examples and identified isomiRs and isomiR-associated SNPs (iso-SNPs). We performed sequence alignments of isomiRs and miRNA sequencing data to verify the identified isomiRs and further revealed GBR ethnographic epigenetic dominant biomarkers. The SNP-pre-miRNA database consisted of 886 pre-miRNAs and 2640 SNPs. We analyzed the effects of SNP type, SNP location, and SNP-mediated free energy change during mature miRNA biogenesis and found that these factors were closely associated to mature miRNA biogenesis. Remarkably, 158 isomiRs were verified in the miRNA sequencing data for the 18 GBR samples. Our results indicated that SNPs affected the mature miRNA processing mechanism and contributed to the production of isomiRs. This mechanism may have important significance for epigenetic changes and diseases.

Sign in / Sign up

Export Citation Format

Share Document