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Title: Advances and Challenges in Metatranscriptomic Analysis

Abstract

Sequencing-based analyses of microbiomes have traditionally focused on addressing the question of community membership and profiling taxonomic abundance through amplicon sequencing of 16 rRNA genes. More recently, shotgun metagenomics, which involves the random sequencing of all genomic content of a microbiome, has dominated this arena due to advancements in sequencing technology throughput and capability to profile genes as well as microbiome membership. While these methods have revealed a great number of insights into a wide variety of microbiomes, both of these approaches only describe the presence of organisms or genes, and not whether they are active members of the microbiome. To obtain deeper insights into how a microbial community responds over time to their changing environmental conditions, microbiome scientists are beginning to employ large-scale metatranscriptomics approaches. Here, we present a comprehensive review on computational metatranscriptomics approaches to study microbial community transcriptomes. We review the major advancements in this burgeoning field, compare strengths and weaknesses to other microbiome analysis methods, list available tools and workflows, and describe use cases and limitations of this method. We envision that this field will continue to grow exponentially, as will the scope of projects (e.g. longitudinal studies of community transcriptional responses to perturbations over time)more » and the resulting data. This review will provide a list of options for computational analysis of these data and will highlight areas in need of development.« less

Authors:
; ;
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); Defense Threat Reduction Agency (DTRA); USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1566265
Alternate Identifier(s):
OSTI ID: 1597345
Report Number(s):
LA-UR-19-24619
Journal ID: ISSN 1664-8021; 904
Grant/Contract Number:  
KP1601010, 4000150817; 89233218CNA000001; CB10152; R-00480-16-0; CB10623; LANLF59T; LANLF59C; KP1601010; 4000150817-877
Resource Type:
Published Article
Journal Name:
Frontiers in Genetics
Additional Journal Information:
Journal Name: Frontiers in Genetics Journal Volume: 10; Journal ID: ISSN 1664-8021
Publisher:
Frontiers
Country of Publication:
Switzerland
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; RNASeq; microbiome; workflows; gene expression; omics

Citation Formats

Shakya, Migun, Lo, Chien-Chi, and Chain, Patrick S. G. Advances and Challenges in Metatranscriptomic Analysis. Switzerland: N. p., 2019. Web. doi:10.3389/fgene.2019.00904.
Shakya, Migun, Lo, Chien-Chi, & Chain, Patrick S. G. Advances and Challenges in Metatranscriptomic Analysis. Switzerland. doi:10.3389/fgene.2019.00904.
Shakya, Migun, Lo, Chien-Chi, and Chain, Patrick S. G. Wed . "Advances and Challenges in Metatranscriptomic Analysis". Switzerland. doi:10.3389/fgene.2019.00904.
@article{osti_1566265,
title = {Advances and Challenges in Metatranscriptomic Analysis},
author = {Shakya, Migun and Lo, Chien-Chi and Chain, Patrick S. G.},
abstractNote = {Sequencing-based analyses of microbiomes have traditionally focused on addressing the question of community membership and profiling taxonomic abundance through amplicon sequencing of 16 rRNA genes. More recently, shotgun metagenomics, which involves the random sequencing of all genomic content of a microbiome, has dominated this arena due to advancements in sequencing technology throughput and capability to profile genes as well as microbiome membership. While these methods have revealed a great number of insights into a wide variety of microbiomes, both of these approaches only describe the presence of organisms or genes, and not whether they are active members of the microbiome. To obtain deeper insights into how a microbial community responds over time to their changing environmental conditions, microbiome scientists are beginning to employ large-scale metatranscriptomics approaches. Here, we present a comprehensive review on computational metatranscriptomics approaches to study microbial community transcriptomes. We review the major advancements in this burgeoning field, compare strengths and weaknesses to other microbiome analysis methods, list available tools and workflows, and describe use cases and limitations of this method. We envision that this field will continue to grow exponentially, as will the scope of projects (e.g. longitudinal studies of community transcriptional responses to perturbations over time) and the resulting data. This review will provide a list of options for computational analysis of these data and will highlight areas in need of development.},
doi = {10.3389/fgene.2019.00904},
journal = {Frontiers in Genetics},
number = ,
volume = 10,
place = {Switzerland},
year = {2019},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.3389/fgene.2019.00904

Citation Metrics:
Cited by: 7 works
Citation information provided by
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