First-degree relationships and genotyping errors deciphered by a high-density SNP array in a Duroc × Iberian pig cross

BACKGROUND

Two individuals with a first-degree relationship share about 50 percent of their alleles. Parent-offspring relationships cannot be homozygous for alternative alleles (genetic exclusion).

METHODS

Applying the concept of genetic exclusion to HD arrays typed in animals for experimental purposes or genomic selection allows estimation of the rate of rejection of first-degree relationships as the rate at which two individuals typed for a large number of Single Nucleotide Polymorphisms (SNPs) do not share at least one allele. An Expectation-Maximization algorithm is applied to estimate parentage. In addition, genotyping errors are estimated in true parent-offspring relationships. Samples from nine candidate Duroc sires and 55 Iberian dams producing 214 Duroc × Iberian barrows were typed for the HD porcine Affymetrix array.

RESULTS

We were able to establish paternity and maternity of 75 and 85 piglets, respectively. Rate of rejection in true parent-offspring relationships was estimated as 0.000735. This is a lower bound of the genotyping error since rate of rejection depends on allele frequencies. After accounting for allele frequencies, our estimate of the genotyping error is 0.6%. A total of 7,744 SNPs were rejected in five or more true parent-offspring relationships facilitating identification of "problematic" SNPs with inconsistent inheritance in multiple parent-offspring relationships.

CONCLUSIONS

This study shows that animal experiments and routine genotyping in genomic selection allow to establish or to verify first-degree relationships as well as to estimate genotyping errors for each batch of animals or experiment.

Development and validation of a high-density SNP chip tailored for genomic analysis in Indian backyard chickens

1. Indian backyard chicken breeds are well adapted to local climatic conditions and possess distinct genetic characteristics, necessitating a dedicated SNP chip to address their unique genetic diversity, breed identification and conservation needs. In this study, a high-density SNP chip, Axiom_Kukkut was developed with SNP markers derived from genomes of 16 indigenous chicken breeds, Red Jungle Fowl and White Leghorn.2. A total of 622,376 markers and an inter-marker distance of 1.9 kb, the Axiom_Kukkut provided a denser marker distribution compared to existing arrays. The chip was validated by genotyping a set of samples from diverse Indian chicken breeds. All the SNPs were used for validation. An average call rate of 99.92% and 91.28%, as high resolution polymorphic markers, demonstrated the high precision of the designed array.3. Population stratification analysis revealed high genetic diversity and distinct linkage disequilibrium patterns among various breeds. Multivariate principal component analysis confirmed the genetic distinctiveness of Red Jungle Fowl and Uttara, suggesting low genetic diversity due to geographic isolation or specific breeding practices.4. The customised SNP chip allows a multitude of possibilities, including applications in genome-wide association analysis, identification of selection signatures, population genetics and breed improvement programmes for Indian chicken. Continued refinement will expand its utility to include exotic and commercial breeds as well, enhancing its overall applicability across a wider range of chicken populations.