Imputation for sequencing variants preselected to a customized low-density chip

The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary animals and old bulls in Danish Jersey. For contemporary animals, a two-step imputation which first imputed to 54 K and then to 54 K + DFS + FRA SNPs achieved highest accuracy. Correlations between observed and imputed genotypes were 91.6% for DFS SNPs and 87.6% for FRA SNPs, while concordance rates were 96.6% for DFS SNPs and 93.5% for FRA SNPs. The SNPs with lower minor allele frequency (MAF) tended to have lower correlations but higher concordance rates. For old bulls, imputation for DFS and FRA SNPs were relatively accurate even for bulls without progenies (correlations higher than 97.2% and concordance rates higher than 98.4%). For contemporary animals, given limited imputation accuracy of preselected sequencing SNPs especially for SNPs with low MAF, it would be a good strategy to directly genotype preselected sequencing SNPs with a customized SNP chip. For old bulls, given high imputation accuracy for preselected sequencing SNPs with all MAF ranges, it would be unnecessary to re-genotype preselected sequencing SNPs.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Scientific reports - 10(2020), 1 vom: 12. Juni, Seite 9524

Sprache:

Englisch

Beteiligte Personen:

Liu, Aoxing [VerfasserIn]
Lund, Mogens Sandø [VerfasserIn]
Boichard, Didier [VerfasserIn]
Mao, Xiaowei [VerfasserIn]
Karaman, Emre [VerfasserIn]
Fritz, Sebastien [VerfasserIn]
Aamand, Gert Pedersen [VerfasserIn]
Wang, Yachun [VerfasserIn]
Su, Guosheng [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 07.12.2020

Date Revised 12.06.2021

published: Electronic

Citation Status MEDLINE

doi:

10.1038/s41598-020-66523-7

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM311122183