Developing Methods for Construction of Population Pedigrees From Low Coverage Sequencing Data

A population pedigree is a graph that captures the totality of the family and genetic histories within a population. While pedigrees contain an abundance of advantageous information for genomic studies, assembling one is often tedious, time consuming, and fraught with error. A combination of highly multiplexed low-coverage sequencing, genotype imputation, and relationship inference software makes it feasible to develop a pedigree cheaply and efficiently. By applying this approach to an experimental admixed Drosophila melanogaster population we developed a dataset that contains genome-wide variants for thousands of individuals in our population. We were also able to confidently identify over one thousand parent-offspring relationships from almost four thousand sequenced samples. However, we were not able to construct a complete pedigree due to overestimates of relatedness resulting from our population’s mixed ancestry. Implementing software that account for population structure could rectify this issue and provide more accurate relationship inference within our population