Journal Article

Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

Delomas, Thomas A., Willis, Stuart C.

2023

Overview

Background Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data. Results We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing. Conclusions These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq .

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Algorithms / Alleles / Allelomorphism / Analysis / Bioinformatics / Biomedical and Life Sciences / Computational Biology/Bioinformatics / Computer Appl. in Life Sciences / cost effectiveness / data collection / DNA sequencing / Estimation / Fishes / Forensic sciences / Gene frequency / Gene sequencing / Genetic aspects / Genomes / Genomics / Genotype / Genotype & phenotype / Genotype panel design / Haplotypes / Heterozygosity / Life Sciences / Low-depth whole genome sequencing / Methods / Microarrays / Microhaplotype / Natural resources / Nucleotide sequence / nucleotide sequences / Nucleotide sequencing / Panels / Pool-seq / Programming languages / Single-nucleotide polymorphism / Skim-seq / United States / Whole genome sequencing