Meeting Abstract
Advances in sequencing technology have allowed for greater amounts of genomic data to be obtained from organisms at an increasingly more feasible cost. However, the amount of processing power and time required for analysis of this information has simultaneously increased. While utilization of whole genomes from even a limited number of individual for population studies is not yet feasible, reduced representation genomic scans are becoming more and more common. In this study, the impact of reduction schemes on population genomic analyses of a non-modal organism, grass carp (Ctenopharyngodon idella), is investigated. A high coverage single nucleotide polymorphism (SNP) dataset was generated using 2b-RAD sequencing. Genome scans were generated from a small number (n=23) of grass carp collected from Lake Erie. Reads were then used to construct a de novo reference sequence, which subsequently identified SNPs throughout the genome. To determine the population structure of grass carp, analyses including a Discriminant Analysis of Principal Components (DAPC) were performed. To investigate the effect that sequence read number has on determining population structure, the number of reads was reduced in a stepwise fashion and re-analyzed. A single putative population was resolved, and this was corroborated in all dataset reductions that we analyzed. Often specimen quality and/or quantity can limit the amount of genetic material available for analysis, such as in conservation studies or those involving invasive species that are expanding into new habitats. Understanding how reductions in datasets can impact the accuracy of inferences made about populations provides insight into the mechanics and statistics of reduction schemes on large genomic datasets.
