BS-virus-finder: virus integration calling using bisulfite sequencing data.

Background: DNA methylation plays a key role in the regulation of gene expression and carcinogenesis. Bisulfite sequencing studies mainly focus on calling single nucleotide polymorphism, different methylation region, and find allele-specific DNA methylation. Until now, only a few software tools have focused on virus integration using bisulfite sequencing data. Findings: We have developed a new and easy-to-use software tool, named BS-virus-finder (BSVF, RRID:SCR_015727), to detect viral integration breakpoints in whole human genomes. The tool is hosted at https://github.com/BGI-SZ/BSVF. Conclusions: BS-virus-finder demonstrates high sensitivity and specificity. It is useful in epigenetic studies and to reveal the relationship between viral integration and DNA methylation. BS-virus-finder is the first software tool to detect virus integration loci by using bisulfite sequencing data.

Crowdsourced direct-to-consumer genomic analysis of a family quartet.

BACKGROUND: We describe the pioneering experience of a Spanish family pursuing the goal of understanding their own personal genetic data to the fullest possible extent using Direct to Consumer (DTC) tests. With full informed consent from the Corpas family, all genotype, exome and metagenome data from members of this family, are publicly available under a public domain Creative Commons 0 (CC0) license waiver. All scientists or companies analysing these data ("the Corpasome") were invited to return results to the family. METHODS: We released 5 genotypes, 4 exomes, 1 metagenome from the Corpas family via a blog and figshare under a public domain license, inviting scientists to join the crowdsourcing efforts to analyse the genomes in return for coauthorship or acknowldgement in derived papers. Resulting analysis data were compiled via social media and direct email. RESULTS: Here we present the results of our investigations, combining the crowdsourced contributions and our own efforts. Four companies offering annotations for genomic variants were applied to four family exomes: BIOBASE, Ingenuity, Diploid, and GeneTalk. Starting from a common VCF file and after selecting for significant results from company reports, we find no overlap among described annotations. We additionally report on a gut microbiome analysis of a member of the Corpas family. CONCLUSIONS: This study presents an analysis of a diverse set of tools and methods offered by four DTC companies. The striking discordance of the results mirrors previous findings with respect to DTC analysis of SNP chip data, and highlights the difficulties of using DTC data for preventive medical care. To our knowledge, the data and analysis results from our crowdsourced study represent the most comprehensive exome and analysis for a family quartet using solely DTC data generation to date.

Omics-based interpretation of synergism in a soil-derived cellulose-degrading microbial community.

Reaching a comprehensive understanding of how nature solves the problem of degrading recalcitrant biomass may eventually allow development of more efficient biorefining processes. Here we interpret genomic and proteomic information generated from a cellulolytic microbial consortium (termed F1RT) enriched from soil. Analyses of reconstructed bacterial draft genomes from all seven uncultured phylotypes in F1RT indicate that its constituent microbes cooperate in both cellulose-degrading and other important metabolic processes. Support for cellulolytic inter-species cooperation came from the discovery of F1RT microbes that encode and express complimentary enzymatic inventories that include both extracellular cellulosomes and secreted free-enzyme systems. Metabolic reconstruction of the seven F1RT phylotypes predicted a wider genomic rationale as to how this particular community functions as well as possible reasons as to why biomass conversion in nature relies on a structured and cooperative microbial community.

Paired-end sequencing of long-range DNA fragments for de novo assembly of large, complex Mammalian genomes by direct intra-molecule ligation.

BACKGROUND: The relatively short read lengths from next generation sequencing (NGS) technologies still pose a challenge for de novo assembly of complex mammal genomes. One important solution is to use paired-end (PE) sequence information experimentally obtained from long-range DNA fragments (>1 kb). Here, we characterize and extend a long-range PE library construction method based on direct intra-molecule ligation (or molecular linker-free circularization) for NGS. RESULTS: We found that the method performs stably for PE sequencing of 2- to 5- kb DNA fragments, and can be extended to 10-20 kb (and even in extremes, up to ∼35 kb). We also characterized the impact of low quality input DNA on the method, and develop a whole-genome amplification (WGA) based protocol using limited input DNA (<1 µg). Using this PE dataset, we accurately assembled the YanHuang (YH) genome, the first sequenced Asian genome, into a scaffold N50 size of >2 Mb, which is over 100-times greater than the initial size produced with only small insert PE reads(17 kb). In addition, we mapped two 7- to 8- kb insertions in the YH genome using the larger insert sizes of the long-range PE data. CONCLUSIONS: In conclusion, we demonstrate here the effectiveness of this long-range PE sequencing method and its use for the de novo assembly of a large, complex genome using NGS short reads.

Comprehensive comparison of three commercial human whole-exome capture platforms.

BACKGROUND: Exome sequencing, which allows the global analysis of protein coding sequences in the human genome, has become an effective and affordable approach to detecting causative genetic mutations in diseases. Currently, there are several commercial human exome capture platforms; however, the relative performances of these have not been characterized sufficiently to know which is best for a particular study. RESULTS: We comprehensively compared three platforms: NimbleGen's Sequence Capture Array and SeqCap EZ, and Agilent's SureSelect. We assessed their performance in a variety of ways, including number of genes covered and capture efficacy. Differences that may impact on the choice of platform were that Agilent SureSelect covered approximately 1,100 more genes, while NimbleGen provided better flanking sequence capture. Although all three platforms achieved similar capture specificity of targeted regions, the NimbleGen platforms showed better uniformity of coverage and greater genotype sensitivity at 30- to 100-fold sequencing depth. All three platforms showed similar power in exome SNP calling, including medically relevant SNPs. Compared with genotyping and whole-genome sequencing data, the three platforms achieved a similar accuracy of genotype assignment and SNP detection. Importantly, all three platforms showed similar levels of reproducibility, GC bias and reference allele bias. CONCLUSIONS: We demonstrate key differences between the three platforms, particularly advantages of solutions over array capture and the importance of a large gene target set.