Short read sequence typing (SRST): multi-locus sequence types from short reads.
Short read sequence typing (SRST): multi-locus sequence types from short reads.
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DOI：
10.1186/1471-2164-13-338
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发表时间：
2012-07-24
期刊：
影响因子：
4.4
通讯作者：
Holt KE
中科院分区：
文献类型：
--
作者：
Inouye M;Conway TC;Zobel J;Holt KE
多位点序列分型（MLST）已成为细菌病原体群体分析的金标准。该方法侧重于少数基因座（通常为7个）的序列，以划分群体，并且简单，稳健，便于在实验室之间和随着时间的推移比较结果。在过去的十年中，研究人员和人口健康专家投入了大量的精力建立了近100种不同细菌的公共MLST数据库，这些数据库包含了大量与MLST序列类型相关的重要信息，如分离的时间和地点，宿主或小生境，血清型甚至临床或耐药性谱。测序技术的最新进展意味着在全基因组水平上进行细菌种群分析越来越可行。与MLST相比，这在分辨率和遗传特征分析方面提供了巨大的收益，并最终将取代MLST用于细菌分型和种群分析。然而，鉴于MLST数据库中目前可用的数据丰富，保持与MLST方案的向后兼容性至关重要，以便可以在其适当的历史背景下理解新的基因组分析。我们提出了一个软件工具，SRST，从短读集的序列类型的快速和准确的检索，使用输入很容易从公共数据库下载。SRST使用读数作图和等位基因分配评分，结合序列覆盖度和变异性，以确定每个MLST基因座处最可能的等位基因。对500多个可公开访问的Illumina读段集中超过3,500个基因座的分析表明，SRST在等位基因分配方面高度准确。SRST输出与常见的分析工具兼容，如eBURST，克隆框架或PhyloViz，允许新基因组数据和MLST数据之间的轻松比较。还可以为新等位基因生成比对、fastq和堆积文件。SRST是一种新的软件工具，用于使用短读段数据准确分配序列类型。该工具的几种用途，包括高通量测序项目的质量控制，质粒MLST和分析爆发调查期间的基因组数据。SRST是开源的，需要Python、BWA和SamTools，可从http://srst.sourceforge.net获得。
Multi-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context. We present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles. SRST is a novel software tool for accurate assignment of sequence types using short read data. Several uses for the tool are demonstrated, including quality control for high-throughput sequencing projects, plasmid MLST and analysis of genomic data during outbreak investigation. SRST is open-source, requires Python, BWA and SamTools, and is available from http://srst.sourceforge.net.
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DOI：
10.1056/nejmoa1106920
发表时间：
2011-08-25
期刊：
The New England journal of medicine
影响因子：
--
作者：
Rasko DA;Webster DR;Sahl JW;Bashir A;Boisen N;Scheutz F;Paxinos EE;Sebra R;Chin CS;Iliopoulos D;Klammer A;Peluso P;Lee L;Kislyuk AO;Bullard J;Kasarskis A;Wang S;Eid J;Rank D;Redman JC;Steyert SR;Frimodt-Møller J;Struve C;Petersen AM;Krogfelt KA;Nataro JP;Schadt EE;Waldor MK
通讯作者：
Waldor MK
影响因子：
3.3
作者：
Didelot, Xavier;Falush, Daniel
通讯作者：
Falush, Daniel
影响因子：
5.2
作者：
Garcia-Fernandez, Aurora;Chiaretto, Giuseppina;Carattoli, Alessandra
通讯作者：
Carattoli, Alessandra
影响因子：
3.2
作者：
Feil, EJ;Li, BC;Spratt, BG
通讯作者：
Spratt, BG
DOI：
10.1126/science.1182395
发表时间：
2010-01-22
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Harris SR;Feil EJ;Holden MT;Quail MA;Nickerson EK;Chantratita N;Gardete S;Tavares A;Day N;Lindsay JA;Edgeworth JD;de Lencastre H;Parkhill J;Peacock SJ;Bentley SD
通讯作者：
Bentley SD