微生物群
基因组
生物
计算生物学
数据科学
工作流程
背景(考古学)
仿形(计算机编程)
微生物种群生物学
人体微生物群
生物信息学
计算机科学
遗传学
基因
细菌
古生物学
数据库
操作系统
作者
Yancong Zhang,Kelsey N. Thompson,Tobyn Branck,Yan Yan,Long H. Nguyen,Eric A. Franzosa,Curtis Huttenhower
出处
期刊:Annual review of biomedical data science
[Annual Reviews]
日期:2021-07-20
卷期号:4 (1): 279-311
被引量:28
标识
DOI:10.1146/annurev-biodatasci-031121-103035
摘要
Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.
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