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Xin Zhou

Bio: Xin Zhou is an academic researcher from China Agricultural University. The author has contributed to research in topics: DNA barcoding & Phylogenetic tree. The author has an hindex of 44, co-authored 140 publications receiving 9603 citations. Previous affiliations of Xin Zhou include Beijing Genomics Institute & Rutgers University.


Papers
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Journal ArticleDOI
Bernhard Misof, Shanlin Liu, Karen Meusemann1, Ralph S. Peters, Alexander Donath, Christoph Mayer, Paul B. Frandsen2, Jessica L. Ware2, Tomas Flouri3, Rolf G. Beutel4, Oliver Niehuis, Malte Petersen, Fernando Izquierdo-Carrasco3, Torsten Wappler5, Jes Rust5, Andre J. Aberer3, Ulrike Aspöck6, Ulrike Aspöck7, Horst Aspöck7, Daniela Bartel7, Alexander Blanke8, Simon Berger3, Alexander Böhm7, Thomas R. Buckley9, Brett Calcott10, Junqing Chen, Frank Friedrich11, Makiko Fukui12, Mari Fujita8, Carola Greve, Peter Grobe, Shengchang Gu, Ying Huang, Lars S. Jermiin1, Akito Y. Kawahara13, Lars Krogmann14, Martin Kubiak11, Robert Lanfear15, Robert Lanfear16, Robert Lanfear17, Harald Letsch7, Yiyuan Li, Zhenyu Li, Jiguang Li, Haorong Lu, Ryuichiro Machida8, Yuta Mashimo8, Pashalia Kapli3, Pashalia Kapli18, Duane D. McKenna19, Guanliang Meng, Yasutaka Nakagaki8, José Luis Navarrete-Heredia20, Michael Ott21, Yanxiang Ou, Günther Pass7, Lars Podsiadlowski5, Hans Pohl4, Björn M. von Reumont22, Kai Schütte11, Kaoru Sekiya8, Shota Shimizu8, Adam Slipinski1, Alexandros Stamatakis3, Alexandros Stamatakis23, Wenhui Song, Xu Su, Nikolaus U. Szucsich7, Meihua Tan, Xuemei Tan, Min Tang, Jingbo Tang, Gerald Timelthaler7, Shigekazu Tomizuka8, Michelle D. Trautwein24, Xiaoli Tong25, Toshiki Uchifune8, Manfred Walzl7, Brian M. Wiegmann26, Jeanne Wilbrandt, Benjamin Wipfler4, Thomas K. F. Wong1, Qiong Wu, Gengxiong Wu, Yinlong Xie, Shenzhou Yang, Qing Yang, David K. Yeates1, Kazunori Yoshizawa27, Qing Zhang, Rui Zhang, Wenwei Zhang, Yunhui Zhang, Jing Zhao, Chengran Zhou, Lili Zhou, Tanja Ziesmann, Shijie Zou, Yingrui Li, Xun Xu, Yong Zhang, Huanming Yang, Jian Wang, Jun Wang, Karl M. Kjer2, Xin Zhou 
07 Nov 2014-Science
TL;DR: The phylogeny of all major insect lineages reveals how and when insects diversified and provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.
Abstract: Insects are the most speciose group of animals, but the phylogenetic relationships of many major lineages remain unresolved. We inferred the phylogeny of insects from 1478 protein-coding genes. Phylogenomic analyses of nucleotide and amino acid sequences, with site-specific nucleotide or domain-specific amino acid substitution models, produced statistically robust and congruent results resolving previously controversial phylogenetic relations hips. We dated the origin of insects to the Early Ordovician [~479 million years ago (Ma)], of insect flight to the Early Devonian (~406 Ma), of major extant lineages to the Mississippian (~345 Ma), and the major diversification of holometabolous insects to the Early Cretaceous. Our phylogenomic study provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.

1,998 citations

Journal ArticleDOI
TL;DR: The conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution, compared with two other popular transcriptome assemblers.
Abstract: Motivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 � 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge. Results: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these wellannotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. Availability and implementation: Source code and user manual are available at http://sourceforge.net/projects/soapdenovotrans/. Contact: xieyl@genomics.cn or bgi-soap@googlegroups.com Supplementary information: Supplementary data are available at Bioinformatics online.

730 citations

Posted Content
TL;DR: SOAPdenovo-Trans as mentioned in this paper is a de novo transcriptome assembler designed specifically for RNA-Seq that provides higher contiguity, lower redundancy, and faster execution.
Abstract: Motivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining the sequences for a large number of genes from an organism with no reference genome. With the rapidly increasing throughputs and decreasing costs of next generation sequencing, RNA-Seq has gained in popularity; but given the typically short reads (e.g. 2 x 90 bp paired ends) of this technol- ogy, de novo assembly to recover complete or full-length transcript sequences remains an algorithmic challenge. Results: We present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. Its performance was evaluated on transcriptome datasets from rice and mouse. Using the known transcripts from these well-annotated genomes (sequenced a decade ago) as our benchmark, we assessed how SOAPdenovo- Trans and two other popular software handle the practical issues of alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy, and faster execution. Availability and Implementation: Source code and user manual are at this http URL Contact: xieyl@genomics.cn or bgi-soap@googlegroups.com

615 citations


Cited by
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Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
TL;DR: Efforts have been put to improve efficiency, flexibility, support for 'big data' (R's long vectors), ease of use and quality check before a new release of ape.
Abstract: Summary After more than fifteen years of existence, the R package ape has continuously grown its contents, and has been used by a growing community of users The release of version 50 has marked a leap towards a modern software for evolutionary analyses Efforts have been put to improve efficiency, flexibility, support for 'big data' (R's long vectors), ease of use and quality check before a new release These changes will hopefully make ape a useful software for the study of biodiversity and evolution in a context of increasing data quantity Availability and implementation ape is distributed through the Comprehensive R Archive Network: http://cranr-projectorg/package=ape Further information may be found at http://ape-packageirdfr/

4,303 citations

Journal ArticleDOI
TL;DR: The approach to utilizing available RNA-Seq and other data types in the authors' manual curation process for vertebrate, plant, and other species is summarized, and a new direction for prokaryotic genomes and protein name management is described.
Abstract: The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.

4,104 citations

Journal ArticleDOI
TL;DR: This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts.
Abstract: High-throughput sequencing of mRNA (RNA-seq) has become the standard method for measuring and comparing the levels of gene expression in a wide variety of species and conditions. RNA-seq experiments generate very large, complex data sets that demand fast, accurate and flexible software to reduce the raw read data to comprehensible results. HISAT (hierarchical indexing for spliced alignment of transcripts), StringTie and Ballgown are free, open-source software tools for comprehensive analysis of RNA-seq experiments. Together, they allow scientists to align reads to a genome, assemble transcripts including novel splice variants, compute the abundance of these transcripts in each sample and compare experiments to identify differentially expressed genes and transcripts. This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts. The protocol's execution time depends on the computing resources, but it typically takes under 45 min of computer time. HISAT, StringTie and Ballgown are available from http://ccb.jhu.edu/software.shtml.

3,755 citations