Quantitative genetics theory for genomic selection and efficiency of genotypic value prediction in open-pollinated populations

ABSTRACT: Quantitative genetics theory for genomic selection has mainly focused on additive effects. This study presents quantitative genetics theory applied to genomic selection aiming to prove that prediction of genotypic value based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance and epistasis. Based on simulated data, we provided information on dominance and genotypic value prediction accuracy, assuming mass selection in an open-pollinated population, all quantitative trait loci (QTLs) of lower effect, and reduced sample size. We show that the predictor of dominance value is proportional to the square of the LD value and to the dominance deviation for each QTL that is in LD with each marker. The weighted (by the SNP frequencies) dominance value predictor has greater accuracy than the unweighted predictor. The linear × linear, linear × quadratic, quadratic × linear, and quadratic × quadratic SNP effects are proportional to the corresponding linear combinations of epistatic effects for QTLs and the LD values. LD between two markers with a common QTL causes a bias in the prediction of epistatic values. Compared to phenotypic selection, the efficiency of genomic selection for genotypic value prediction increases as trait heritability decreases. The degree of dominance did not affect the genotypic value prediction accuracy and the approach to maximum accuracy is asymptotic with increases in SNP density. The decrease in the sample size from 500 to 200 did not markedly reduce the genotypic value prediction accuracy

Validação e correção de fenótipos na seleção genômica ampla

The objective of this work was to evaluate the effect of the distribution of QTL effects, of the type of validation population, and of phenotype adjustment in the accuracy of genome-wide selection. Two populations of full siblings with 500 individuals were simulated, with 1,000 loci markers being genotypically considered – 100 linked to QTL. The QTL effects had uniform or exponential distribution. For validation 1, a 100-individual sample constituted the validation population; in validation 2, cross validation was applied, with a 100-individual sample in five replicates; and in validation 3, a second generation formed the validation population. The analysis methodologies used were RR-Blup and Blasso, with mixed models for phenotype correction. Without phenotypic correction, the exponential distribution led to higher accuracies, and the Blasso method showed greater accuracy with this distribution; while RR-Blup was more accurate with uniform distribution. In this scenario without correction, validations 1 and 3 were more accurate. With phenotypic correction, exponential and uniform distributions led to similar accuracies, and the Blasso method proved more accurate for both of them. In this scenario, validations 1 and 2 were more accurate. Generally, the RR-Blup method was more accurate, and the Blasso method was less biased.O objetivo deste trabalho foi avaliar a influência da distribuição dos efeitos de QTL, do tipo de população de validação e da correção dos fenótipos sobre a acurácia da seleção genômica ampla. Duas populações de irmãos completos, com 500 indivíduos, foram simuladas, tendo-se considerado, genotipicamente, 1.000 locos marcadores – 100 ligados a QTL. Os efeitos de QTL apresentaram distribuição uniforme ou exponencial. Na validação 1, uma amostra com 100 indivíduos constituiu a população de validação; na validação 2, aplicou-se a validação cruzada, com amostra de 100 indivíduos em cinco repetições; e na 3, uma segunda geração constituiu a população de validação. As metodologias de análise utilizadas foram RR-Blup e Blasso, com modelos mistos para correção dos fenótipos. Sem correção fenotípica, a distribuição exponencial proporcionou maiores acurácias, e o método Blasso foi mais acurado com essa distribuição; enquanto o RR-Blup foi mais acurado com a distribuição uniforme. Nesse cenário sem correção, as validações 1 e 3 foram mais acuradas. Com correção, as distribuições exponencial e uniforme produziram acurácias similares, e o método Blasso mostrou-se mais acurado para ambas. Nesse cenário, as validações 1 e 2 foram mais acuradas. No geral, o método RR-Blup foi mais acurado, e o Blasso menos viciado

Phased, chromosome-scale genome assemblies of tetraploid potato reveals a complex genome, transcriptome, and predicted proteome landscape underpinning genetic diversity

Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome. Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity including altered coding and transcript sequences, preferential allele expression, and structural variation that collectively result in a highly complex transcriptome and predicted proteome which are distributed across the homologous chromosomes. Wild species contribute to the extensive allelic diversity in tetraploid cultivars, demonstrating ancestral introgressions predating modern breeding efforts. As a clonally propagated autotetraploid that undergoes limited meiosis, dysfunctional and deleterious alleles are not purged in tetraploid potato. Nearly a quarter of the loci bore mutations predicted to have a high negative impact on protein function, complicating breeder’s efforts to reduce genetic load. The StCDF1 locus controls maturity and analysis of six tetraploid genomes revealed 12 allelic variants correlated with maturity in a dosage dependent manner. Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous, diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids