Construction of Metatranscriptomic Libraries for 5′ End Sequencing of rRNAs for Microbiome Research

Tiirola, Marja; Mäki, Anita

doi:10.1007/978-1-0716-1585-0_7

Cited by 1 publication

(1 citation statement)

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“…The metatranscriptomics approach explores the metabolically active fraction of a sample via sequencing RNA transcripts. Here, total RNA or messenger RNA (mRNA) in a sample is converted to complementary DNA (cDNA), allowing it to be further pre-processed as needed in a stable form [ 86 , 87 ]. The cDNA strands are then sequenced, creating a map of active gene expression and regulation [ 88 , 89 ].…”

Section: Meta-omics Tools To Unravel Microbial Community Diversity An...mentioning

confidence: 99%

Ecosystem-specific microbiota and microbiome databases in the era of big data

Lobanov

Gobet

Joyce

2022

Environmental Microbiome

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The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB’s), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB’s, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB’s.

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