4.7 Article

Expression profiling and local adaptation of Boechera holboellii populations for water use efficiency across a naturally occurring water stress gradient

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MOLECULAR ECOLOGY
卷 15, 期 5, 页码 1229-1237

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WILEY
DOI: 10.1111/j.1365-294X.2006.02818.x

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Arabidopsis; Boechera; drought tolerance; local adaptation; transcription profiling

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We studied the physiological basis of local adaptation to drought in Boechera holboellii, a perennial relative of Arabidopsis thaliana, and used cDNA-AFLPs to identify candidate genes showing differential expression in these populations. We compared two populations of B. holboellii from contrasting water environments in a reciprocal transplant experiment, as well as in a laboratory dry-down experiment. We continuously measured the water content of soils using time domain reflectometery (TDR). We compared populations for their water use efficiency (WUE), root/shoot ratios (R:S) and leaf mass per unit area (LMA) in the field and in the laboratory, and identified candidate genes that (i) responded plastically to water stress and (ii) were differentially expressed between the two populations. Genotypes from the drier site had higher WUE, which was attributable to a large reduction in transpirational water loss. The xeric-adapted population also had increased investment in root biomass and greater leaf mass per unit area. Reciprocal transplants in the field had significantly greater survival in their native habitat. In total, 450 cDNA-AFLP fragments showed significant changes between drought and control treatments. Furthermore, some genes showed genotype (population)-specific patterns of up- or down-regulation in response to drought. Three hundred cDNA-AFLP bands were sequenced leading to the identification of cDNAs coding for proteins involved in signal transduction, transcriptional regulation, redox regulation, oxidative stress and pathways involved in stress adaptation. Some of these proteins could contribute a physiological advantage under drought, making them potential targets for natural selection.

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