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

Autor: Delomas TA; Agricultural Research Service, United States Department of Agriculture, National Cold Water Marine Aquaculture Center, 483 CBLS, 120 Flagg Road, Kingston, RI, 02881, USA. thomas.delomas@usda.gov., Willis SC; Hagerman Genetics Laboratory, Columbia River Inter-Tribal Fish Commission, Hagerman, ID, USA.
Jazyk: angličtina
Zdroj: BMC bioinformatics [BMC Bioinformatics] 2023 Nov 03; Vol. 24 (1), pp. 415. Date of Electronic Publication: 2023 Nov 03.
DOI: 10.1186/s12859-023-05554-z
Abstrakt: 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 .
(© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Databáze: MEDLINE
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