Jingfa Xiao

PGAP: Pan-genomes analysis pipeline

Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAPs performance has been evaluated on 11 Streptococcus pyogenes strains. Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net. Contact: junyu@big.ac.cn; xiaojingfa@big.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Genome sequence and genetic diversity of the common carp, Cyprinus carpio

The common carp, Cyprinus carpio, is one of the most important cyprinid species and globally accounts for 10% of freshwater aquaculture production. Here we present a draft genome of domesticated C. carpio (strain Songpu), whose current assembly contains 52,610 protein-coding genes and approximately 92.3% coverage of its paleotetraploidized genome (2n = 100). The latest round of whole-genome duplication has been estimated to have occurred approximately 8.2 million years ago. Genome resequencing of 33 representative individuals from worldwide populations demonstrates a single origin for C. carpio in 2 subspecies (C. carpio Haematopterus and C. carpio carpio). Integrative genomic and transcriptomic analyses were used to identify loci potentially associated with traits including scaling patterns and skin color. In combination with the high-resolution genetic map, the draft genome paves the way for better molecular studies and improved genome-assisted breeding of C. carpio and other closely related species.

Bioinformatics clouds for big data manipulation

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.ReviewersThis article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

Cassava genome from a wild ancestor to cultivated varieties

Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology.

ParaAT: a parallel tool for constructing multiple protein-coding DNA alignments.

Constructing multiple homologous alignments for protein-coding DNA sequences is crucial for a variety of bioinformatic analyses but remains computationally challenging. With the growing amount of sequence data available and the ongoing efforts largely dependent on protein-coding DNA alignments, there is an increasing demand for a tool that can process a large number of homologous groups and generate multiple protein-coding DNA alignments. Here we present a parallel tool - ParaAT that is capable of parallelly constructing multiple protein-coding DNA alignments for a large number of homologs. As testified on empirical datasets, ParaAT is well suited for large-scale data analysis in the high-throughput era, providing good scalability and exhibiting high parallel efficiency for computationally demanding tasks. ParaAT is freely available for academic use only at http://cbb.big.ac.cn/software.

Comparative genomic analysis of Streptococcus suis reveals significant genomic diversity among different serotypes

BackgroundStreptococcus suis (S. suis) is a major swine pathogen and an emerging zoonotic agent. Serotypes 1, 2, 3, 7, 9, 14 and 1/2 are the most prevalent serotypes of this pathogen. However, almost all studies were carried out on serotype 2 strains. Therefore, characterization of genomic features of other serotypes will be required to better understand their virulence potential and phylogenetic relationships among different serotypes.ResultsFour Chinese S. suis strains belonging to serotypes 1, 7, 9 and 1/2 were sequenced using a rapid, high-throughput approach. Based on the 13 corresponding serotype strains, including 9 previously completed genomes of this bacterium, a full comparative genomic analysis was performed. The results provide evidence that (i) the pan-genome of this species is open and the size increases with addition of new sequenced genomes, (ii) strains of serotypes 1, 3, 7 and 9 are phylogenetically distinct from serotype 2 strains, but all serotype 2 strains, plus the serotype 1/2 and 14 strains, are very closely related. (iii) all these strains, except for the serotype 1 strain, could harbor a recombinant site for a pathogenic island (89 K) mediated by conjugal transfer, and may have the ability to gain the 89 K sequence.ConclusionsThere is significant genomic diversity among different strains in S. suis, and the gain and loss of large amount of genes are involved in shaping their genomes. This is indicated by (i) pairwise gene content comparisons between every pair of these strains, (ii) the open pan-genome of this species, (iii) the observed indels, invertions and rearrangements in the collinearity analysis. Phylogenetic relationships may be associated with serotype, as serotype 2 strains are closely related and distinct from other serotypes like 1, 3, 7 and 9, but more strains need to be sequenced to confirm this.

PanGP: A tool for quickly analyzing bacterial pan-genome profile

Summary: Pan-genome analyses have shed light on the dynamics and evolution of bacterial genome from the point of population. The explosive growth of bacterial genome sequence also brought an extremely big challenge to pan-genome profile analysis. We developed a tool, named PanGP, to complete pan-genome profile analysis for large-scale strains efficiently. PanGP has integrated two sampling algorithms, totally random (TR) and distance guide (DG). The DG algorithm drew sample strain combinations on the basis of genome diversity of bacterial population. The performance of these two algorithms have been evaluated on four bacteria populations with strain numbers varying from 30 to 200, and the DG algorithm exhibited overwhelming advantage on accuracy and stability than the TR algorithm. Availability: PanGP was developed with a user-friendly graphic interface and it was available at http://PanGP.big.ac.cn. Contact: xiaojingfa@big.ac.cn or wujy@big.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Gene expression analysis of induced pluripotent stem cells from aneuploid chromosomal syndromes

BackgroundHuman aneuploidy is the leading cause of early pregnancy loss, mental retardation, and multiple congenital anomalies. Due to the high mortality associated with aneuploidy, the pathophysiological mechanisms of aneuploidy syndrome remain largely unknown. Previous studies focused mostly on whether dosage compensation occurs, and the next generation transcriptomics sequencing technology RNA-seq is expected to eventually uncover the mechanisms of gene expression regulation and the related pathological phenotypes in human aneuploidy.ResultsUsing next generation transcriptomics sequencing technology RNA-seq, we profiled the transcriptomes of four human aneuploid induced pluripotent stem cell (iPSC) lines generated from monosomy × (Turner syndrome), trisomy 8 (Warkany syndrome 2), trisomy 13 (Patau syndrome), and partial trisomy 11:22 (Emanuel syndrome) as well as two umbilical cord matrix iPSC lines as euploid controls to examine how phenotypic abnormalities develop with aberrant karyotype. A total of 466 M (50-bp) reads were obtained from the six iPSC lines, and over 13,000 mRNAs were identified by gene annotation. Global analysis of gene expression profiles and functional analysis of differentially expressed (DE) genes were implemented. Over 5000 DE genes are determined between aneuploidy and euploid iPSCs respectively while 9 KEGG pathways are overlapped enriched in four aneuploidy samples.ConclusionsOur results demonstrate that the extra or missing chromosome has extensive effects on the whole transcriptome. Functional analysis of differentially expressed genes reveals that the genes most affected in aneuploid individuals are related to central nervous system development and tumorigenesis.

GSA: Genome Sequence Archive*

With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.

Complete Genome Sequence of Streptococcus suis Serotype 14 Strain JS14

Streptococcus suis is an important zoonotic agent leading to a variety of diseases in swine and can be transmitted to human beings upon close contact. Here, we report the complete genome sequence of S. suis serotype 14 strain JS14 which was isolated from a diseased pig in Jiangsu Province, China.