Zhiqiang Hu

NeSSM: A Next-Generation Sequencing Simulator for Metagenomics

Background Metagenomics can reveal the vast majority of microbes that have been missed by traditional cultivation-based methods. Due to its extremely wide range of application areas, fast metagenome sequencing simulation systems with high fidelity are in great demand to facilitate the development and comparison of metagenomics analysis tools. Results We present here a customizable metagenome simulation system: NeSSM (Next-generation Sequencing Simulator for Metagenomics). Combining complete genomes currently available, a community composition table, and sequencing parameters, it can simulate metagenome sequencing better than existing systems. Sequencing error models based on the explicit distribution of errors at each base and sequencing coverage bias are incorporated in the simulation. In order to improve the fidelity of simulation, tools are provided by NeSSM to estimate the sequencing error models, sequencing coverage bias and the community composition directly from existing metagenome sequencing data. Currently, NeSSM supports single-end and pair-end sequencing for both 454 and Illumina platforms. In addition, a GPU (graphics processing units) version of NeSSM is also developed to accelerate the simulation. By comparing the simulated sequencing data from NeSSM with experimental metagenome sequencing data, we have demonstrated that NeSSM performs better in many aspects than existing popular metagenome simulators, such as MetaSim, GemSIM and Grinder. The GPU version of NeSSM is more than one-order of magnitude faster than MetaSim. Conclusions NeSSM is a fast simulation system for high-throughput metagenome sequencing. It can be helpful to develop tools and evaluate strategies for metagenomics analysis and it’s freely available for academic users at http://cbb.sjtu.edu.cn/~ccwei/pub/software/NeSSM.php.

Genomic variation in 3,010 diverse accessions of Asian cultivated rice

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence–absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.Analyses of genetic variation and population structure based on over 3,000 cultivated rice (Oryza sativa) genomes reveal subpopulations that correlate with geographic location and patterns of introgression consistent with multiple rice domestication events.

RPAN: rice pan-genome browser for ∼3000 rice genomes

A pan-genome is the union of the gene sets of all the individuals of a clade or a species and it provides a new dimension of genome complexity with the presence/absence variations (PAVs) of genes among these genomes. With the progress of sequencing technologies, pan-genome study is becoming affordable for eukaryotes with large-sized genomes. The Asian cultivated rice, Oryza sativa L., is one of the major food sources for the world and a model organism in plant biology. Recently, the 3000 Rice Genome Project (3K RGP) sequenced more than 3000 rice genomes with a mean sequencing depth of 14.3×, which provided a tremendous resource for rice research. In this paper, we present a genome browser, Rice Pan-genome Browser (RPAN), as a tool to search and visualize the rice pan-genome derived from 3K RGP. RPAN contains a database of the basic information of 3010 rice accessions, including genomic sequences, gene annotations, PAV information and gene expression data of the rice pan-genome. At least 12 000 novel genes absent in the reference genome were included. RPAN also provides multiple search and visualization functions. RPAN can be a rich resource for rice biology and rice breeding. It is available at http://cgm.sjtu.edu.cn/3kricedb/ or http://www.rmbreeding.cn/pan3k.

Revealing Missing Human Protein Isoforms Based on Ab Initio Prediction, RNA-seq and Proteomics

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.

RNA virus receptor Rig-I monitors gut microbiota and inhibits colitis-associated colorectal cancer

BackgroundRetinoic acid-inducible gene-I (Rig-I) is an intracellular viral RNA receptor, which specifically recognizes double-stranded viral RNA initiating antiviral innate immunity. Increasing evidences showed that Rig-I had broader roles in antibacterial immunity and cancer protection. However, the potential roles and mechanisms of Rig-I in gut flora regulation and colorectal cancer (CRC) progression remain unclear.MethodsImmunohistochemistry was performed to detect Rig-I protein in 38 pairs of CRC tissue and matched adjacent mucosa, and immunofluorescence and western blot were also used to detect Rig-I protein expression in AOM/DSS-induced mice CRC samples. High-throughput sequencing was conducted to evaluate gut microbiota changes in Rig-I-deficient mice. Immunofluorescence and flow cytometry were used to detect IgA expression. Additionally, real-time quantitative PCR was performed to detect RNA expression in mouse intestines and cultured cells, and western blot was used to detect phosphorylation of STAT3 in IL-6-stimulated B cell line.ResultsRig-I was downregulated in human and mouse CRC samples and Rig-I-deficient mice were more susceptible to AOM/DSS-induced colitis-associated colorectal cancer (CAC). Furthermore, Rig-I-deficient mice displayed gut microbiota disturbance compared to wild type mice. IgA, Reg3γ and Pdcd1 levels were decreased in intestines of Rig-I-deficient mice. Phosphorylation of STAT3 in IL-6-stimulated 1B4B6 was decreased.ConclusionRig-I could regulate gut microbiota through regulating IgA and IL6-STAT3-dependent Reg3γ expression. Besides, Rig-I could inhibit CRC progression.

24-hour-restraint stress induces long-term depressive-like phenotypes in mice

There is an increasing risk of mental disorders, such as acute stress disorder (ASD), post-traumatic stress disorder (PTSD) and depression among survivors who were trapped in rubble during earthquake. Such long-term impaction of a single acute restraint stress has not been extensively explored. In this study, we subjected mice to 24-hour-restraint to simulate the trapping episode, and investigated the acute (2 days after the restraint) and long-term (35 days after the restraint) impacts. Surprisingly, we found that the mice displayed depression-like behaviors, decreased glucose uptake in brain and reduced adult hippocampal neurogenesis 35 days after the restraint. Differential expression profiling based on microarrays suggested that genes and pathways related to depression and other mental disorders were differentially expressed in both PFC and hippocampus. Furthermore, the depression-like phenotypes induced by 24-hour-restraint could be reversed by fluoxetine, a type of antidepressant drug. These findings demonstrated that a single severe stressful event could produce long-term depressive-like phenotypes. Moreover, the 24-hour-restraint stress mice could also be used for further studies on mood disorders.

EUPAN enables pan-genome studies of a large number of eukaryotic genomes

Summary: Pan‐genome analyses are routinely carried out for bacteria to interpret the within‐species gene presence/absence variations (PAVs). However, pan‐genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan‐genome analysis toolkit, enabling automatic large‐scale eukaryotic pan‐genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan‐genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re‐sequencing projects primarily focusing on single nucleotide polymorphisms. Availability and Implementation: EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non‐commercial use (CC BY‐NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html. Contact: ccwei@sjtu.edu.cn or jianxin.shi@sjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Loci and natural alleles underlying robust roots and adaptive domestication of upland ecotype rice in aerobic conditions

A robust (long and thick) root system is characteristic of upland japonica rice adapted to drought conditions. Using deep sequencing and large scale phenotyping data of 795 rice accessions and an integrated strategy combining results from high resolution mapping by GWAS and linkage mapping, comprehensive analyses of genomic, transcriptomic and haplotype data, we identified large numbers of QTLs affecting rice root length and thickness (RL and RT) and shortlisted relatively few candidate genes for many of the identified small-effect QTLs. Forty four and 97 QTL candidate genes for RL and RT were identified, and five of the RL QTL candidates were validated by T-DNA insertional mutation; all have diverse functions and are involved in root development. This work demonstrated a powerful strategy for highly efficient cloning of moderate- and small-effect QTLs that is difficult using the classical map-based cloning approach. Population analyses of the 795 accessions, 202 additional upland landraces, and 446 wild rice accessions based on random SNPs and SNPs within robust loci suggested that there could be much less diversity in robust-root candidate genes among upland japonica accessions than in other ecotypes. Further analysis of nucleotide diversity and allele frequency in the robust loci among different ecotypes and wild rice accessions showed that almost all alleles could be detected in wild rice, and pyramiding of robust-root alleles could be an important genetic characteristic of upland japonica. Given that geographical distribution of upland landraces, we suggest that during domestication of upland japonica, the strongest pyramiding of robust-root alleles makes it a unique ecotype adapted to aerobic conditions.

MetaBinG2: a fast and accurate metagenomic sequence classification system for samples with many unknown organisms

BackgroundMany methods have been developed for metagenomic sequence classification, and most of them depend heavily on genome sequences of the known organisms. A large portion of sequencing sequences may be classified as unknown, which greatly impairs our understanding of the whole sample.ResultHere we present MetaBinG2, a fast method for metagenomic sequence classification, especially for samples with a large number of unknown organisms. MetaBinG2 is based on sequence composition, and uses GPUs to accelerate its speed. A million 100xa0bp Illumina sequences can be classified in about 1xa0min on a computer with one GPU card. We evaluated MetaBinG2 by comparing it to multiple popular existing methods. We then applied MetaBinG2 to the dataset of MetaSUB Inter-City Challenge provided by CAMDA data analysis contest and compared community composition structures for environmental samples from different public places across cities.ConclusionCompared to existing methods, MetaBinG2 is fast and accurate, especially for those samples with significant proportions of unknown organisms.ReviewersThis article was reviewed by Drs. Eran Elhaik, Nicolas Rascovan, and Serghei Mangul.

Genome-Wide Analysis Of Repetitive Elements Associated With Gene Regulation

Nearly half of the human genome is made up of transposable elements (TEs) and evidence supports a possible role for TEs in gene regulation. Here, we have integrated publicly available genomic, epigenetic and transcriptomic data to investigate this potential function in a genome-wide manner. Results show that although most TE classes are primarily involved in reduced gene expression, Alu elements are associated with up regulated gene expression. This is consistent with our previously published work which showed that intronic Alu elements are capable of generating alternative splice variants in protein-coding genes, and further illustrates how Alu elements can alter protein function or gene expression level. Furthermore, non-coding regions were found to have a great density of TEs within regulatory sequences, most notably in repressors. Our exhaustive analysis of recent datasets has extended and updated our understanding of TEs in terms of their global impact on gene regulation, and indicates a significant association between repetitive elements and gene regulation.ABSTRACT Nearly half of the human genome is made up of transposable elements (TEs) and there is evidence that TEs are involved in gene regulation. Here, we have integrated publicly available genomic, epigenetic and transcriptomic data to investigate this in a genome-wide manner. A bootstrapping statistical method was applied to minimize the confounder effects from different repeat types. Our results show that although most TE classes are primarily associated with reduced gene expression, Alu elements are associated with up regulated gene expression. Furthermore, Alu elements had the highest probability of any TE class of contributing to regulatory regions of any type defined by chromatin state. This suggests a general model where clade specific SINEs may contribute more to gene regulation than ancient/ancestral TEs. Finally, non-coding regions were found to have a high probability of TE content within regulatory sequences, most notably in repressors. Our exhaustive analysis has extended and updated our understanding of TEs in terms of their global impact on gene regulation, and suggests that the most recently derived types of TEs, i.e. clade or species specific SINES, have the greatest overall impact on gene regulation.