High speed BLASTN: an accelerated MegaBLAST search
                    tool

Chen, Ying; Ye, Weicai; Zhang, Yongdong; Xu, Yuesheng

doi:10.1093/nar/gkv784

Cited by 426 publications

(342 citation statements)

References 31 publications

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“…We next manually examined each matching entry from the missing gene list and confirmed its orthology with the correct human (GRCh37) or lizard (anoCar2) ortholog by searching for evidence of complete or partial synteny. However, in cases where synteny analysis was not possible, we used a criterion of reciprocal best BLAT alignments of nucleotide and/or protein sequences against the human and lizard genome assemblies, or best BLASTn (Chen et al 2015) alignment to identify nucleotide sequences in NCBI’s database for future correction.…”

Section: Methodsmentioning

confidence: 99%

A New Chicken Genome Assembly Provides Insight into Avian Genome Structure

Warren

Hillier

Tomlinson

et al. 2017

G3 Genes|Genomes|Genetics

250

267

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The importance of the Gallus gallus (chicken) as a model organism and agricultural animal merits a continuation of sequence assembly improvement efforts. We present a new version of the chicken genome assembly (Gallus_gallus-5.0; GCA_000002315.3), built from combined long single molecule sequencing technology, finished BACs, and improved physical maps. In overall assembled bases, we see a gain of 183 Mb, including 16.4 Mb in placed chromosomes with a corresponding gain in the percentage of intact repeat elements characterized. Of the 1.21 Gb genome, we include three previously missing autosomes, GGA30, 31, and 33, and improve sequence contig length 10-fold over the previous Gallus_gallus-4.0. Despite the significant base representation improvements made, 138 Mb of sequence is not yet located to chromosomes. When annotated for gene content, Gallus_gallus-5.0 shows an increase of 4679 annotated genes (2768 noncoding and 1911 protein-coding) over those in Gallus_gallus-4.0. We also revisited the question of what genes are missing in the avian lineage, as assessed by the highest quality avian genome assembly to date, and found that a large fraction of the original set of missing genes are still absent in sequenced bird species. Finally, our new data support a detailed map of MHC-B, encompassing two segments: one with a highly stable gene copy number and another in which the gene copy number is highly variable. The chicken model has been a critical resource for many other fields of study, and this new reference assembly will substantially further these efforts.

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Section: Methodsmentioning

confidence: 99%

A New Chicken Genome Assembly Provides Insight into Avian Genome Structure

Warren

Hillier

Tomlinson

et al. 2017

G3 Genes|Genomes|Genetics

250

267

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“…Mitochondrial barcode COI sequences were downloaded for each species from GenBank (KU568756.1 and KU568963.1) and were subsequently queried against the assembled transcriptomes using BLASTN (Chen et al. ).…”

Section: Methodsmentioning

confidence: 99%

Phylogenomic incongruence, hypothesis testing, and taxonomic sampling: The monophyly of characiform fishes*

et al. 2018

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Phylogenomic studies using genome‐wide datasets are quickly becoming the state of the art for systematics and comparative studies, but in many cases, they result in strongly supported incongruent results. The extent to which this conflict is real depends on different sources of error potentially affecting big datasets (assembly, stochastic, and systematic error). Here, we apply a recently developed methodology (GGI or gene genealogy interrogation) and data curation to new and published datasets with more than 1000 exons, 500 ultraconserved element (UCE) loci, and transcriptomic sequences that support incongruent hypotheses. The contentious non‐monophyly of the order Characiformes proposed by two studies is shown to be a spurious outcome induced by sample contamination in the transcriptomic dataset and an ambiguous result due to poor taxonomic sampling in the UCE dataset. By exploring the effects of number of taxa and loci used for analysis, we show that the power of GGI to discriminate among competing hypotheses is diminished by limited taxonomic sampling, but not equally sensitive to gene sampling. Taken together, our results reinforce the notion that merely increasing the number of genetic loci for a few representative taxa is not a robust strategy to advance phylogenetic knowledge of recalcitrant groups. We leverage the expanded exon capture dataset generated here for Characiformes (206 species in 23 out of 24 families) to produce a comprehensive phylogeny and a revised classification of the order.

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“…These 15 gene families were selected from a set of 112 phylogenetically informative bacterial gene families (Wu et al 2013) for their ability to accurately recruit metagenomic reads to the correct species. To evaluate how informative different gene families are for estimation of abundance, we simulated 100 100-bp reads from each of the 112 gene families in each of the 5952 species and used HS-BLASTN (Chen et al 2015) to map these reads back to a database that contained the full-length gene sequences. To simulate the presence of novel species and strains, we discarded alignments between reads and reference sequences from the same genome.…”

Section: Species Abundance Estimationmentioning

confidence: 99%

An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography

et al. 2016

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We present the Metagenomic Intra-species Diversity Analysis System (MIDAS), which is an integrated computational pipeline for quantifying bacterial species abundance and strain-level genomic variation, including gene content and single-nucleotide polymorphisms (SNPs), from shotgun metagenomes. Our method leverages a database of more than 30,000 bacterial reference genomes that we clustered into species groups. These cover the majority of abundant species in the human microbiome but only a small proportion of microbes in other environments, including soil and seawater. We applied MIDAS to stool metagenomes from 98 Swedish mothers and their infants over one year and used rare SNPs to track strains between hosts. Using this approach, we found that although species compositions of mothers and infants converged over time, strain-level similarity diverged. Specifically, early colonizing bacteria were often transmitted from an infant's mother, while late colonizing bacteria were often transmitted from other sources in the environment and were enriched for sporeformation genes. We also applied MIDAS to 198 globally distributed marine metagenomes and used gene content to show that many prevalent bacterial species have population structure that correlates with geographic location. Strain-level genetic variants present in metagenomes clearly reveal extensive structure and dynamics that are obscured when data are analyzed at a coarser taxonomic resolution.[Supplemental material is available for this article.]Microbial species play important roles in the different environments that they inhabit. However, different strains of the same species can differ significantly in their gene content (Greenblum et al. 2015;Zhu et al. 2015) and single-nucleotide polymorphisms (SNPs) (Schloissnig et al. 2013;Kashtan et al. 2014;Lieberman et al. 2014). These strain-level differences are important for understanding microbial evolution, adaptation, pathogenicity, and transmission. For example, strain-level differences have shed light on ecological differentiation of closely related bacteria (Shapiro et al. 2012), uncovered the presence of ancient subpopulations of marine bacteria (Kashtan et al. 2014), and highlighted extensive intra-species recombination (Snitkin et al. 2011;Rosen et al. 2015). Strain-level variation is also important for understanding microbial pathogenicity. Differences at the nucleotide level can lead to within-host adaptation of pathogens (Lieberman et al. 2014), and differences in gene content can confer drug resistance, convert a commensal bacterium into a pathogen (Snitkin et al. 2011), or lead to outbreaks of highly virulent strains (Rasko et al. 2011).Metagenomic shotgun sequencing has the potential to shed light onto strain-level heterogeneity among bacterial genomes within and between microbial communities, yielding a genomic resolution not achievable by sequencing the 16S ribosomal RNA gene alone ) and circumventing the need for culture-based approaches. However, limitations of existing computational methods and ...

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High speed BLASTN: an accelerated MegaBLAST search tool

Cited by 426 publications

References 31 publications

A New Chicken Genome Assembly Provides Insight into Avian Genome Structure

A New Chicken Genome Assembly Provides Insight into Avian Genome Structure

Phylogenomic incongruence, hypothesis testing, and taxonomic sampling: The monophyly of characiform fishes*

An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography

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