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ABSTRACT: Using whole-genome sequencing to determine the population structure of Candida haemulonii species complex

PROVIDER: PRJNA606185 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11092000_1.fastq.gz	Fastqsanger.gz
	SRR11092000_2.fastq.gz	Fastqsanger.gz
	SRR11092001_1.fastq.gz	Fastqsanger.gz
	SRR11092001_2.fastq.gz	Fastqsanger.gz
	SRR11092002_1.fastq.gz	Fastqsanger.gz

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Project description:We used custom Nimblegen microarrays representing whole-larval transcriptomes for two species (Papilio zelicaon [this submission] and Erynnis propertius [submitted seperately]) to assess gene expression differences affecting tolerance to climatic regimes. Many individuals were sourced from populations from the northern periphery and center of the species' (shared) range; these were each divided into groups treated under peripheral and central climate regimes, resulting in 4 experimental groups for each species (Peripheral Source, Peripheral treatment; Peripheral Source, Central Treatment; Central Source, Peripheral Treatment; Central Source, Central Treatment). Using technical microarray replicates allowed us to use ANOVA to identify genes whose expression may underlie local adaptation to climate (i.e., those showing an interaction term between source and population). Abstract: Population differences may determine geographic range shifts and adaptive evolution under climate change. Local adaptation in peripheral populations could preclude or slow range expansions, and populations with different genetic make-up could have distinct trajectories that produce complex spatial patterns of population change. To investigate the genetic extent of local responses to climate change, we exposed poleward-periphery and central populations of two Lepidoptera to reciprocal, common-garden climatic conditions and compared whole-transcriptome expression. We found significant expression differences between populations in both species. In addition, several hundred genes including genes involved in energy metabolism and oxidative stress responded in a localized fashion in the species that exhibits greater population structure and local adaptation. Expression levels of these genes are most divergent in the same environment in which we previously detected phenotypic divergence in metabolism. By contrast, we found no localized genes in the species with higher gene flow, reflecting the lack of previously observed local adaptation. These results suggest that population differences do not generalize easily, even for related species living in the same climate, but some taxa deserve population-level consideration when predicting the effects of climate change.

Project description:We used custom Nimblegen microarrays representing whole-larval transcriptomes for two species (Erynnis propertius [this submission] and Papilio zelicaon [submitted seperately]) to assess gene expression differences affecting tolerance to climatic regimes. Many individuals were sourced from populations from the northern periphery and center of the species' (shared) range; these were each divided into groups treated under peripheral and central climate regimes, resulting in 4 experimental groups for each species (Peripheral Source, Peripheral treatment; Peripheral Source, Central Treatment; Central Source, Peripheral Treatment; Central Source, Central Treatment). Using technical microarray replicates allowed us to use ANOVA to identify genes whose expression may underlie local adaptation to climate (i.e., those showing an interaction term between source and population). Abstract: Population differences may determine geographic range shifts and adaptive evolution under climate change. Local adaptation in peripheral populations could preclude or slow range expansions, and populations with different genetic make-up could have distinct trajectories that produce complex spatial patterns of population change. To investigate the genetic extent of local responses to climate change, we exposed poleward-periphery and central populations of two Lepidoptera to reciprocal, common-garden climatic conditions and compared whole-transcriptome expression. We found significant expression differences between populations in both species. In addition, several hundred genes including genes involved in energy metabolism and oxidative stress responded in a localized fashion in the species that exhibits greater population structure and local adaptation. Expression levels of these genes are most divergent in the same environment in which we previously detected phenotypic divergence in metabolism. By contrast, we found no localized genes in the species with higher gene flow, reflecting the lack of previously observed local adaptation. These results suggest that population differences do not generalize easily, even for related species living in the same climate, but some taxa deserve population-level consideration when predicting the effects of climate change.

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