Integrated genome sizing (IGS) approach for the parallelization of whole genome analysis.

BACKGROUND: The use of whole genome sequence has increased recently with rapid progression of next-generation sequencing (NGS) technologies. However, storing raw sequence reads to perform large-scale genome analysis pose hardware challenges. Despite advancement in genome analytic platforms, efficient approaches remain relevant especially as applied to the human genome. In this study, an Integrated Genome Sizing (IGS) approach is adopted to speed up multiple whole genome analysis in high-performance computing (HPC) environment. The approach splits a genome (GRCh37) into 630 chunks (fragments) wherein multiple chunks can simultaneously be parallelized for sequence analyses across cohorts. RESULTS: IGS was integrated on Maha-Fs (HPC) system, to provide the parallelization required to analyze 2504 whole genomes. Using a single reference pilot genome, NA12878, we compared the NGS process time between Maha-Fs (NFS SATA hard disk drive) and SGI-UV300 (solid state drive memory). It was observed that SGI-UV300 was faster, having 32.5 mins of process time, while that of the Maha-Fs was 55.2 mins. CONCLUSIONS: The implementation of IGS can leverage the ability of HPC systems to analyze multiple genomes simultaneously. We believe this approach will accelerate research advancement in personalized genomic medicine. Our method is comparable to the fastest methods for sequence alignment.

Development of the variant calling algorithm, ADIScan, and its use to estimate discordant sequences between monozygotic twins.

Calling variants from next-generation sequencing (NGS) data or discovering discordant sequences between two NGS data sets is challenging. We developed a computer algorithm, ADIScan1, to call variants by comparing the fractions of allelic reads in a tester to the universal reference genome. We then created ADIScan2 by modifying the algorithm to directly compare two sets of NGS data and predict discordant sequences between two testers. ADIScan1 detected >99.7% of variants called by GATK with an additional 724 393 SNVs. ADIScan2 identified ∼500 candidates of discordant sequences in each of two pairs of the monozygotic twins. About 200 of these candidates were included in the ∼2800 predicted by VarScan2. We verified 66 true discordant sequences among the candidates that ADIScan2 and VarScan2 exclusively predicted. ADIScan2 detected many discordant sequences overlooked by VarScan2 and Mutect, which specialize in detecting low frequency mutations in genetically heterogeneous cancerous tissues. Numbers of verified sequences alone were >5 times more than expected based on recently estimated mutation rates from whole genome sequences. Estimated post-zygotic mutation rates were 1.68 × 10-7 in this study. ADIScan1 and 2 would complement existing tools in screening causative mutations of diverse genetic diseases and comparing two sets of genome sequences, respectively.

Evolutionary Analyses of Hanwoo (Korean Cattle)-Specific Single-Nucleotide Polymorphisms and Genes Using Whole-Genome Resequencing Data of a Hanwoo Population.

Advances in next generation sequencing (NGS) technologies have enabled population-level studies for many animals to unravel the relationships between genotypic differences and traits of specific populations. The objective of this study was to perform evolutionary analysis of single nucleotide polymorphisms (SNP) in genes of Korean native cattle Hanwoo in comparison to SNP data from four other cattle breeds (Jersey, Simmental, Angus, and Holstein) and four related species (pig, horse, human, and mouse) obtained from public databases through NGS-based resequencing. We analyzed population structures and differentiation levels for the five cattle breeds and estimated species-specific SNPs with their origins and phylogenetic relationships among species. In addition, we identified Hanwoo-specific genes and proteins, and determined distinct changes in protein-protein interactions among five species (cattle, pig, horse, human, mouse) in the STRING network database by additionally considering indirect protein interactions. We found that the Hanwoo population was clearly different from the other four cattle populations. There were Hanwoo-specific genes related to its meat trait. Protein interaction rewiring analysis also confirmed that there were Hanwoo-specific protein-protein interactions that might have contributed to its unique meat quality.

Synteny Portal: a web-based application portal for synteny block analysis.

Recent advances in next-generation sequencing technologies and genome assembly algorithms have enabled the accumulation of a huge volume of genome sequences from various species. This has provided new opportunities for large-scale comparative genomics studies. Identifying and utilizing synteny blocks, which are genomic regions conserved among multiple species, is key to understanding genomic architecture and the evolutionary history of genomes. However, the construction and visualization of such synteny blocks from multiple species are very challenging, especially for biologists with a lack of computational skills. Here, we present Synteny Portal, a versatile web-based application portal for constructing, visualizing and browsing synteny blocks. With Synteny Portal, users can easily (i) construct synteny blocks among multiple species by using prebuilt alignments in the UCSC genome browser database, (ii) visualize and download syntenic relationships as high-quality images, (iii) browse synteny blocks with genetic information and (iv) download the details of synteny blocks to be used as input for downstream synteny-based analyses, all in an intuitive and easy-to-use web-based interface. We believe that Synteny Portal will serve as a highly valuable tool that will enable biologists to easily perform comparative genomics studies by compensating limitations of existing tools. Synteny Portal is freely available at http://bioinfo.konkuk.ac.kr/synteny_portal.

FCMM: A comparative metagenomic approach for functional characterization of multiple metagenome samples.

Next-generation sequencing (NGS) technologies make it possible to obtain the entire genomic content of microorganisms in metagenome samples. Thus, many studies have developed methods for the processing and analysis of metagenomic NGS reads, including analyses for predicting functions and their enrichments in environmental metagenome samples. Especially, comparative functional studies by using multi-metagenome samples are essential for identifying and comparing different characteristics of multiple environmental samples. In this paper, we introduce a pipeline for functional characterization of multiple metagenome samples to infer major functions as well as their quantitative scores in a comparative metagenomics manner. The pipeline performs the annotation of functions related to expected proteins in the metagenome samples, calculates their enrichment scores based on the reads per kilobase per million reads (RPKM) measure, and predicts the relative abundance of associated functions by a statistical test. The results from single sample analysis are then used to find common and sample-specific major functions. By applying the pipeline to six different environmental metagenome samples, including two ocean (Antarctica aquatic and Baltic Sea) and four terrestrial (Acid mine drainage, human gut microbiome, Amazon River, and Wasca soil) samples, we were able to predict common functions as well as environment-specific functions. Our pipeline is available at http://bioinfo.konkuk.ac.kr/FCMM/.