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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Investigating the accuracy of imputing autosomal variants in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

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Autor(es):
Hermisdorff, Isis da Costa [1, 2] ; Costa, Raphael Bermal [1] ; de Albuquerque, Lucia Galvao [3] ; Pausch, Hubert [2] ; Kadri, Naveen Kumar [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Fed Univ Bahia UFBA, Sch Vet Med & Anim Sci, Salvador, BA - Brazil
[2] Swiss Fed Inst Technol, Anim Genom, Zurich - Switzerland
[3] Sao Paulo State Univ Unesp, Sch Agr & Vet Sci, Anim Sci Dept, Jaboticabal, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: BMC Genomics; v. 21, n. 1 NOV 10 2020.
Citações Web of Science: 0
Resumo

BackgroundImputation accuracy among other things depends on the size of the reference panel, the marker's minor allele frequency (MAF), and the correct placement of single nucleotide polymorphism (SNP) on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50K to 777K SNP density using Minimac3, when map positions were determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to the empirical imputation accuracy.ResultsThe overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R(2)dose) was almost identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R(2)dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy increased from 0.903 to 0.913, and the marker density in the imputed data increased from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals. The model-based imputation quality scores from Minimac3 (Rsq) were systematically higher than empirically estimated accuracies. However, both metrics were positively correlated and the correlation increased with the size of the reference panel and MAF of imputed variants.ConclusionsAccurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel and MAF of the imputed variants. (AU)

Processo FAPESP: 09/16118-5 - Ferramentas genômicas no melhoramento genético de características de importância econômica direta em bovinos da raça Nelore
Beneficiário:Lucia Galvão de Albuquerque
Linha de fomento: Auxílio à Pesquisa - Temático