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Accuracy of whole-genome sequence imputation using hybrid peeling in large pedigreed livestock populations.
Ros-Freixedes, Roger; Whalen, Andrew; Chen, Ching-Yi; Gorjanc, Gregor; Herring, William O; Mileham, Alan J; Hickey, John M.
Afiliação
  • Ros-Freixedes R; The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. roger.ros@roslin.ed.ac.uk.
  • Whalen A; Departament de Ciència Animal, Universitat de Lleida-Agrotecnio Center, Lleida, Spain. roger.ros@roslin.ed.ac.uk.
  • Chen CY; The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
  • Gorjanc G; The Pig Improvement Company, Genus plc, 100 Bluegrass Commons Blvd Ste 2200, Hendersonville, TN, 37075, USA.
  • Herring WO; The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
  • Mileham AJ; The Pig Improvement Company, Genus plc, 100 Bluegrass Commons Blvd Ste 2200, Hendersonville, TN, 37075, USA.
  • Hickey JM; Genus plc, 1525 River Road, Deforest, WI, 53532, USA.
Genet Sel Evol ; 52(1): 17, 2020 Apr 06.
Article em En | MEDLINE | ID: mdl-32248811
ABSTRACT

BACKGROUND:

The coupling of appropriate sequencing strategies and imputation methods is critical for assembling large whole-genome sequence datasets from livestock populations for research and breeding. In this paper, we describe and validate the coupling of a sequencing strategy with the imputation method hybrid peeling in real animal breeding settings.

METHODS:

We used data from four pig populations of different size (18,349 to 107,815 individuals) that were widely genotyped at densities between 15,000 and 75,000 markers genome-wide. Around 2% of the individuals in each population were sequenced (most of them at 1× or 2× and 37-92 individuals per population, totalling 284, at 15-30×). We imputed whole-genome sequence data with hybrid peeling. We evaluated the imputation accuracy by removing the sequence data of the 284 individuals with high coverage, using a leave-one-out design. We simulated data that mimicked the sequencing strategy used in the real populations to quantify the factors that affected the individual-wise and variant-wise imputation accuracies using regression trees.

RESULTS:

Imputation accuracy was high for the majority of individuals in all four populations (median individual-wise dosage correlation 0.97). Imputation accuracy was lower for individuals in the earliest generations of each population than for the rest, due to the lack of marker array data for themselves and their ancestors. The main factors that determined the individual-wise imputation accuracy were the genotyping status, the availability of marker array data for immediate ancestors, and the degree of connectedness to the rest of the population, but sequencing coverage of the relatives had no effect. The main factors that determined variant-wise imputation accuracy were the minor allele frequency and the number of individuals with sequencing coverage at each variant site. Results were validated with the empirical observations.

CONCLUSIONS:

We demonstrate that the coupling of an appropriate sequencing strategy and hybrid peeling is a powerful strategy for generating whole-genome sequence data with high accuracy in large pedigreed populations where only a small fraction of individuals (2%) had been sequenced, mostly at low coverage. This is a critical step for the successful implementation of whole-genome sequence data for genomic prediction and fine-mapping of causal variants.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Suínos / Cruzamento / Gado / Técnicas de Genotipagem / Sequenciamento Completo do Genoma Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Suínos / Cruzamento / Gado / Técnicas de Genotipagem / Sequenciamento Completo do Genoma Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article