Using Conservation Genomics Inference and Prediction to Inform Future Management Decisions

Authors: Nicolas Alexandre, Alexander Cameron, David Tian, Faisal Alzaben, Sree Kolora, Manjusha Chintalapati, Kamalakar Chatla, Thomas Turner, Priya Moorjani, Peter Sudmant, Noah Whiteman, Peter Reinthal

Year: 2021

Abstract

Here we use reduced representation sequencing from Spikedace (Meda fulgida) sampled from across the species range. This has been done in tandem with sequencing of high coverage whole genomes from major population clusters for imputation of missing data to optimize comparative analyses. These samples are representative of wild vs. broodstock, time series, and extinct vs extant populations permitting inference of future local trajectories of genetic diversity in the wild and the historic context of extinction of the Verde River population. Allele frequency data further permits the estimation of connectivity among populations across the species range to disentangle the effects of local adaptation and migration while polymorphisms can additionally allow estimation of population-specific mutation rates, locally selected variants, and mutation load. The integrative nature of these analyses aim to better inform future management of local populations to maintain stable levels of genetic diversity in threatened freshwater fish.