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. 2021 Jan;30(1):193-206.
doi: 10.1111/mec.15583. Epub 2020 Aug 29.

Rapid evolutionary changes in gene expression in response to climate fluctuations

Affiliations

Rapid evolutionary changes in gene expression in response to climate fluctuations

Elena Hamann et al. Mol Ecol. 2021 Jan.

Abstract

There is now abundant evidence of rapid evolution in natural populations, but the genetic mechanisms of these changes remain unclear. One possible route to rapid evolution is through changes in the expression of genes that influence traits under selection. We examined contemporary evolutionary gene expression changes in plant populations responding to environmental fluctuations. We compared genome-wide gene expression, using RNA-seq, in two populations of Brassica rapa collected over four time points between 1997 and 2014, during which precipitation in southern California fluctuated dramatically and phenotypic and genotypic changes occurred. By combining transcriptome profiling with the resurrection approach, we directly examined evolutionary changes in gene expression over time. For both populations, we found a substantial number of differentially expressed genes between generations, indicating rapid evolution in the expression of many genes. Using existing gene annotations, we found that many changes occurred in genes involved in regulating stress responses and flowering time. These appeared related to the fluctuations in precipitation and were potentially adaptive. However, the evolutionary changes in gene expression differed across generations within and between populations, indicating largely independent evolutionary trajectories across populations and over time. Our study provides strong evidence for rapid evolution in gene expression, and indicates that changes in gene expression can be one mechanism of rapid evolutionary responses to selection episodes. This study also illustrates that combining resurrection studies with transcriptomics is a powerful approach for investigating evolutionary changes at the gene regulatory level, and will provide new insights into the genetic basis of contemporary evolution.

Keywords: Brassica rapa; RNA-seq; drought stress; flowering time; resurrection study.

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Conflict of interest statement

The authors have no conflict of interest to declare.

Figures

FIGURE 1
FIGURE 1
Number of DEGs identified between generations (at 1% FDR) in (a) ARB and (b) BB for 2004 vs. 1997 ('04 vs. '97), 2011 vs. 2004 ('11 vs. '04), 2014 vs. 2011 ('14 vs. '11), and the long‐term comparison 2014 vs. 1997 ('14 vs. '97). Upregulated genes are shown in orange (above the zero line) and downregulated genes in blue (below the zero‐line), with the hatched portion of the bars representing the percentage of annotated genes. The total number of up‐ and downregulated genes are detailed at the top of the bars and the percentage of annotated genes is indicated in parenthesis. On the x‐axis, the years in red (2004, 2014) represent drought periods, while the years in blue (1997, 2011) represent wet periods. The total number of genes analysed for each comparison differed depending on filtering for lowly expressed genes. Specifically, our analyses included 41,577 genes for ARB ’04 vs. ’97, 43,562 genes for ARB ’11 vs. ’04, 43,384 for ARB ’14 vs. ’11, 41,674 for ARB ’14 vs. ’97, 42,578 for BB ’04 vs. ’97, 43,388 for BB ’11 vs. ’04, 43,290 for BB ’14 vs. ’11, and 42,744 for BB ’14 vs. ’97
FIGURE 2
FIGURE 2
Functional classification of annotated DEGs identified for the long‐term generation comparison (2014 vs. 1997) in (a) ARB and (b) BB into enriched GO terms for biological processes associated with stress responses (in dark red), regulation of flowering time (in yellow), and other functions (in blue). Asterisks indicate the five GO categories found in both populations (all others are unique to one population). For ARB, out of the 865 DEGs that were identified between 2014 and 1997, 514 were annotated, and 305 were grouped under GO terms. For BB, out of the 84 DEGs that were identified between 2014 and 1997, 29 were annotated, and 22 were grouped under GO terms
FIGURE 3
FIGURE 3
Comparison of common and unique evolutionary changes across time within each population. Number of DEGs at 1% FDR, and percentages in parentheses, between pairwise generation comparisons (i.e., ’04 vs. ’97, ’11 vs. ’04, ’14 vs. ’11, and ’14 vs. ’97) within populations for (a) ARB and (b) BB
FIGURE 4
FIGURE 4
Expression patterns of one representative gene cluster across generations in (a) ARB and (b) BB. The gene cluster represented for ARB includes 12 genes, and 8 for BB. The expression of single genes within each cluster are plotted in grey, in addition to their mean expression profile in blue. Gene expression is shown as log2‐transformed, median‐centred reads per kilobase of target transcript length per million reads (RPKM). Biological samples on the x‐axis are clustered based on expression similarities of all highly significant DEGs (0.1% FDR cutoff and 4‐fold expression change) identified across generations within population (see full heatmaps for both generation in S9–10). Predrought generations are shown in blue (1997 and 2011), and post‐drought generations are shown in red (2004 and 2014)
FIGURE 5
FIGURE 5
Common and unique evolutionary changes between the ARB and BB populations across generations (DEGs at 1% FDR) for (a–d) all generation comparisons; (e) functional classification of the 15 annotated (out of the 24 total) common DEGs between ARB'14 vs. ’97 and BB'14 vs. ’97 into GO terms for biological processes associated with stress response (in red), regulation growth and flowering time (in yellow) and other processes (in blue); and (f) common evolutionary changes in expression profiles of transcription factors found in the ARB and BB populations across predrought (1997) and post‐drought generations (2014)

Comment in

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