| Abstract Detail
Population Genetics/Genomics Liao, Irene [1], Cao, Gongyuan [1], Rifkin, Joanna [2], Rausher, Mark [1]. Identifying candidate genes contributing to nectar trait divergence in the selfing syndrome. Identifying candidate genes has been an important endeavor for understanding trait evolution, but this endeavor is often more complicated for polygenic traits. Here, we present a multi-step approach that combines quantitative genetics, transcriptome profiling, and population genomics to identify candidate genes that may be responsible for nectar trait divergence in the selfing syndrome. We focus on two nectar traits, nectar volume and nectar sugar concentration, between two sister morning glories, Ipomoea cordatotriloba and I. lacunosa, in which Ipomoea lacunosa produces less abundant and less concentrated nectar compared to I. cordatotriloba. We first use bulk-segregant RNA sequencing to describe the differentially expressed genes between recombinant inbred individuals that differ in nectar volume or nectar sugar concentration. We then use population genomics to identify possible genes and alleles that could contribute to nectar trait divergence. More specifically, we focus only on genes and alleles 1) that are found within QTL regions from a previous study, 2) that are expressed in the nectary, and 3) that meet population genomics expectations based on expectations from the history of divergence and introgression between I. lacunosa and I. cordatotriloba. From this approach, we identified approximately 120 candidate genes that may contribute to nectar trait divergence. This study also reveals that many nearly fixed differences contributed to polygenic trait divergence and that a handful of genes and alleles remain diverged between the two species even in the face of gene flow.
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1 - Duke University, Department Of Biology, 137 BioSciences, Durham, NC, 27708, USA
2 - 25 Willlcocks St, Toronto, ON, M5S3B2, Canada
Keywords:
nectar
trait divergence
quantitative genetics
Population genomics
Transcriptome
candidate genes.
Presentation Type: Oral Paper
Session: PGG4, Population Genetics and Genomics IV
Location: /
Date: Wednesday, July 21st, 2021
Time: 3:00 PM(EDT)
Number: PGG4001
Abstract ID:320
Candidate for Awards:Margaret Menzel Award |
