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Ten years of transcriptomics in wild populations: what have we learned about their ecology and evolution?
Author(s) -
Alvarez Mariano,
Schrey Aaron W.,
Richards Christina L.
Publication year - 2015
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.13055
Subject(s) - biology , transcriptome , dna microarray , molecular ecology , ecology , evolutionary biology , genome , gene , computational biology , gene expression , functional ecology , genetics , ecosystem , population , demography , sociology
Molecular ecology has moved beyond the use of a relatively small number of markers, often noncoding, and it is now possible to use whole‐genome measures of gene expression with microarrays and RNA seq (i.e. transcriptomics) to capture molecular response to environmental challenges. While transcriptome studies are shedding light on the mechanistic basis of traits as complex as personality or physiological response to catastrophic events, these approaches are still challenging because of the required technical expertise, difficulties with analysis and cost. Still, we found that in the last 10 years, 575 studies used microarrays or RNA seq in ecology. These studies broadly address three questions that reflect the progression of the field: (i) How much variation in gene expression is there and how is it structured? (ii) How do environmental stimuli affect gene expression? (iii) How does gene expression affect phenotype? We discuss technical aspects of RNAseq and microarray technology, and a framework that leverages the advantages of both. Further, we highlight future directions of research, particularly related to moving beyond correlation and the development of additional annotation resources. Measuring gene expression across an array of taxa in ecological settings promises to enrich our understanding of ecology and genome function.