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Author

Min Tang

Other affiliations: Nanjing Agricultural University
Bio: Min Tang is an academic researcher from China Agricultural University. The author has contributed to research in topics: Metagenomics & Shotgun sequencing. The author has an hindex of 11, co-authored 19 publications receiving 2568 citations. Previous affiliations of Min Tang include Nanjing Agricultural 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 Aspöck6, Daniela Bartel6, Alexander Blanke8, Simon Berger3, Alexander Böhm6, 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 Letsch6, 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 Pass6, 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. Szucsich6, Meihua Tan, Xuemei Tan, Min Tang, Jingbo Tang, Gerald Timelthaler6, Shigekazu Tomizuka8, Michelle D. Trautwein24, Xiaoli Tong25, Toshiki Uchifune8, Manfred Walzl6, 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 ability of the new Illumina PCR-free pipeline for DNA metabarcoding to detect small arthropod specimens and its tendency to avoid most, if not all, false positives suggests its great potential in biodiversity-related surveillance, such as in biomonitoring programs.
Abstract: Next-generation-sequencing (NGS) technologies combined with a classic DNA barcoding approach have enabled fast and credible measurement for biodiversity of mixed environmental samples. However, the PCR amplification involved in nearly all existing NGS protocols inevitably introduces taxonomic biases. In the present study, we developed new Illumina pipelines without PCR amplifications to analyze terrestrial arthropod communities. Mitochondrial enrichment directly followed by Illumina shotgun sequencing, at an ultra-high sequence volume, enabled the recovery of Cytochrome c Oxidase subunit 1 (COI) barcode sequences, which allowed for the estimation of species composition at high fidelity for a terrestrial insect community. With 15.5 Gbp Illumina data, approximately 97% and 92% were detected out of the 37 input Operational Taxonomic Units (OTUs), whether the reference barcode library was used or not, respectively, while only 1 novel OTU was found for the latter. Additionally, relatively strong correlation between the sequencing volume and the total biomass was observed for species from the bulk sample, suggesting a potential solution to reveal relative abundance. The ability of the new Illumina PCR-free pipeline for DNA metabarcoding to detect small arthropod specimens and its tendency to avoid most, if not all, false positives suggests its great potential in biodiversity-related surveillance, such as in biomonitoring programs. However, further improvement for mitochondrial enrichment is likely needed for the application of the new pipeline in analyzing arthropod communities at higher diversity.

247 citations

Journal ArticleDOI
TL;DR: A novel multiplex sequencing and assembly pipeline allowing for simultaneous acquisition of full mitogenomes from pooled animals without DNA enrichment or amplification is developed and demonstrates the plausibility of a multi-locus mito-metagenomics approach as the next phase of the current single- locus metabarcoding method.
Abstract: The advent in high-throughput-sequencing (HTS) technologies has revolutionized conventional biodiversity research by enabling parallel capture of DNA sequences possessing species-level diagnosis. However, polymerase chain reaction (PCR)-based implementation is biased by the efficiency of primer binding across lineages of organisms. A PCR-free HTS approach will alleviate this artefact and significantly improve upon the multi-locus method utilizing full mitogenomes. Here we developed a novel multiplex sequencing and assembly pipeline allowing for simultaneous acquisition of full mitogenomes from pooled animals without DNA enrichment or amplification. By concatenating assemblies from three de novo assemblers, we obtained high-quality mitogenomes for all 49 pooled taxa, with 36 species >15 kb and the remaining >10 kb, including 20 complete mitogenomes and nearly all protein coding genes (99.6%). The assembly quality was carefully validated with Sanger sequences, reference genomes and conservativeness of protein coding genes across taxa. The new method was effective even for closely related taxa, e.g. three Drosophila spp., demonstrating its broad utility for biodiversity research and mito-phylogenomics. Finally, the in silico simulation showed that by recruiting multiple mito-loci, taxon detection was improved at a fixed sequencing depth. Combined, these results demonstrate the plausibility of a multi-locus mito-metagenomics approach as the next phase of the current single-locus metabarcoding method.

240 citations

Journal ArticleDOI
TL;DR: It is shown that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees, and species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline.
Abstract: 1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline. 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes. 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93·7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R2 = 24·9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline. 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and distributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

126 citations

Journal ArticleDOI
TL;DR: Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding, but for large‐scale ecological studies, metabarcode currently remains the most commonly used approach for diversity assessment.
Abstract: New applications of DNA and RNA sequencing are expanding the field of biodiversity discovery and ecological monitoring, yet questions remain regarding precision and efficiency. Due to primer bias, the ability of metabarcoding to accurately depict biomass of different taxa from bulk communities remains unclear, while PCR-free whole mitochondrial genome (mitogenome) sequencing may provide a more reliable alternative. Here, we used a set of documented mock communities comprising 13 species of freshwater macroinvertebrates of estimated individual biomass, to compare the detection efficiency of COI metabarcoding (three different amplicons) and shotgun mitogenome sequencing. Additionally, we used individual COI barcoding and de novo mitochondrial genome sequencing, to provide reference sequences for OTU assignment and metagenome mapping (mitogenome skimming), respectively. We found that, even though both methods occasionally failed to recover very low abundance species, metabarcoding was less consistent, by failing to recover some species with higher abundances, probably due to primer bias. Shotgun sequencing results provided highly significant correlations between read number and biomass in all but one species. Conversely, the read-biomass relationships obtained from metabarcoding varied across amplicons. Specifically, we found significant relationships for eight of 13 (amplicons B1FR-450 bp, FF130R-130 bp) or four of 13 (amplicon FFFR, 658 bp) species. Combining the results of all three COI amplicons (multiamplicon approach) improved the read-biomass correlations for some of the species. Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding. However, for large-scale ecological studies, metabarcoding currently remains the most commonly used approach for diversity assessment.

101 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

Journal ArticleDOI
TL;DR: PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses that includes the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, and new output formats to facilitate interoperability with downstream software.
Abstract: PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses. PartitionFinder 2 is substantially faster and more efficient than version 1, and incorporates many new methods and features. These include the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, new output formats to facilitate interoperability with downstream software, and many new models of molecular evolution. PartitionFinder 2 is freely available under an open source license and works on Windows, OSX, and Linux operating systems. It can be downloaded from www.robertlanfear.com/partitionfinder. The source code is available at https://github.com/brettc/partitionfinder.

3,445 citations

Journal Article
TL;DR: FastTree as mentioned in this paper uses sequence profiles of internal nodes in the tree to implement neighbor-joining and uses heuristics to quickly identify candidate joins, then uses nearest-neighbor interchanges to reduce the length of the tree.
Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

2,436 citations

Journal ArticleDOI
TL;DR: RAxML-NG is presented, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML, which offers improved accuracy, flexibility, speed, scalability, and usability compared with RAx ML/ exaML.
Abstract: MOTIVATION Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets. RESULTS We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric. AVAILABILITY AND IMPLEMENTATION The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng. RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

1,765 citations

Journal ArticleDOI
TL;DR: This work presents BUSCO v3 with example analyses that highlight the wide‐ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.
Abstract: Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.

1,575 citations