scholarly journals BitMapperBS: a fast and accurate read aligner for whole-genome bisulfite sequencing

2018 ◽  
Author(s):  
Haoyu Cheng ◽  
Yun Xu
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Standard Technique ◽  
Whole Genome ◽  
Sequencing Data ◽  
Methylation Analysis ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Computational Bottleneck ◽  
Dna Methylation Analysis

AbstractAs a gold-standard technique for DNA methylation analysis, whole-genome bisulfite sequencing (WGBS) helps researchers to study the genome-wide DNA methylation at single-base resolution. However, aligning WGBS reads to the large reference genome is a major computational bottleneck in DNA methylation analysis projects. Although several WGBS aligners have been developed in recent years, it is difficult for them to efficiently process the ever-increasing bisulfite sequencing data. Here we propose BitMapperBS, an ultrafast and memory-efficient aligner that is designed for WGBS reads. To improve the performance of BitMapperBS, we propose various strategies specifically for the challenges that are unique to the WGBS aligners, which are ignored in most existing methods. Our experiments on real and simulated datasets show that BitMapperBS is one order of magnitude faster than the state-of-the-art WGBS aligners, while achieves similar or better sensitivity and precision. BitMapperBS is freely available at https://github.com/chhylp123/BitMapperBS.

scholarly journals Analyzing whole genome bisulfite sequencing data from highly divergent genotypes

2019 ◽  
Vol 47 (19) ◽  
pp. e117-e117 ◽  
Author(s):  
Phillip Wulfridge ◽  
Ben Langmead ◽  
Andrew P Feinberg ◽  
Kasper D Hansen
Keyword(s):  
Dna Methylation ◽  
Genetic Variation ◽  
Bisulfite Sequencing ◽  
Joint Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Personal Genomes

Abstract In the study of DNA methylation, genetic variation between species, strains or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here, we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that this increases power. We apply our method to a human normal-cancer dataset, and show this improves accuracy and power, illustrating the broad applicability of our approach. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, while accounting for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question.

scholarly journals Analyzing whole genome bisulfite sequencing data from highly divergent genotypes

2016 ◽  
Author(s):  
Phillip Wulfridge ◽  
Ben Langmead ◽  
Andrew P. Feinberg ◽  
Kasper D. Hansen
Keyword(s):  
Dna Methylation ◽  
Genetic Variation ◽  
Bisulfite Sequencing ◽  
Inbred Mouse ◽  
Mouse Strains ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

AbstractIn the study of DNA methylation, genetic variation between species, strains, or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here we use whole-genome bisulfite sequencing data on two highly divergent inbred mouse strains to study this problem. We find that while the large number of strain-specific CpGs necessitates considerations regarding the reference genomes used during alignment, properties such as CpG density are surprisingly conserved across the genome. We introduce a method for including strain-specific CpGs in differential analysis, and show that accounting for strain-specific CpGs increases the power to find differentially methylated regions between the strains. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, and also allowing us to account for differences in the spatial occurrences of CpGs. Our results have implications for analysis of genetic variation and DNA methylation using bisulfite-converted DNA.

scholarly journals GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data

2012 ◽  
Vol 41 (4) ◽  
pp. e55-e55 ◽  
Author(s):  
Touati Benoukraf ◽  
Sarawut Wongphayak ◽  
Luqman Hakim Abdul Hadi ◽  
Mengchu Wu ◽  
Richie Soong
Keyword(s):  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

scholarly journals MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data

BMC Genomics ◽  
2015 ◽  
Vol 16 (Suppl 12) ◽  
pp. S11 ◽  
Author(s):  
Wen-Wei Liao ◽  
Ming-Ren Yen ◽  
Evaline Ju ◽  
Fei-Man Hsu ◽  
Larry Lam ◽  
...  
Keyword(s):  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

164 Genome-wide DNA Methylation Profiling in in Utero Heat-stressed Pigs as Measured by Whole-genome Bisulfite Sequencing

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 87-88
Author(s):  
Luiz F Brito ◽  
Jacob M Maskal ◽  
Shi-Yi Chen ◽  
Hinayah R Oliveira ◽  
Jason R Graham ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Heat Stress ◽  
Cellular Response ◽  
Bisulfite Sequencing ◽  
Cholesterol Biosynthesis ◽  
In Utero ◽  
Whole Genome ◽  
Whole Genome Bisulfite Sequencing ◽  
Differentially Methylated Genes ◽  
Genome Bisulfite Sequencing

Abstract In utero heat stress (IUHS) has several postnatal consequences in pigs that compromise health, increase stress response, and reduce performance. These phenotypes may be caused by epigenetic modifications such as DNA methylation, which are heritable molecular modifications that impact gene expression and phenotypic outcomes without changing the DNA sequence. Therefore, we aimed to compare the DNA methylation profiles between in-utero thermoneutral (IUTN) and IUHS pigs to identify differentially methylated regions. Twenty-four pregnant gilts were evenly assigned to either a thermoneutral (17.5 ± 2.1°C) or heat stress (cycling 26 to 36°C) chamber from d 0 to 59 of gestation, followed by thermoneutral conditions (20.9 ± 2.3°C) for the rest of gestation and until the piglets were weaned. At 105 d of age, 10 IUTN and 10 IUHS piglets were euthanized and Longissimus dorsi muscle samples were collected and used to perform whole-genome bisulfite sequencing (WGBS). Purified genomic DNA was fragmented and bisulfite conversion was performed. Illumina platforms were used to sequence WGBS libraries. All pigs had similar proportions of methylation at CpG sites. Two-hundred-sixty-eight genomic regions were differentially methylated between IUTN and IUHS pigs. These identified regions are located across all pig chromosomes and ranged from 2 (SSC18) to 40 (SSC10). Eighty-five unique differentially-methylated genes were identified. These genes have been reported to be involved in key biological processes such as transcriptional repressor activity and tRNA processing (e.g., SKOR2,TRMT6, TSEN2), cellular response to heat stress (e.g.,CCAR2), placental vascularization (e.g.,FZD5), central nervous system (e.g.,VEPH1), cholesterol biosynthesis (e.g., CYB5R1), insulin receptor substrate (e.g.,IRS2), synaptic transmission (e.g.,RIMBP2), neurotrophic factor receptor activity (e.g.,LIFR), immune response (e.g., CD84), DNA repair (e.g., CHD1L), and cell proliferation and endocrine signaling (e.g., SSTR1, CYB5R1). These findings contribute to a better understanding of the epigenomic mechanisms underlying postnatal consequences of IUHS in pigs.

Sign in / Sign up

Export Citation Format

Share Document