The jigsaw puzzle of pedigree: whole-genome resequencing reveals genetic diversity and ancestral lineage in Sunong black pigs

The Sunong black pig is a new composite breed under development generated from Chinese indigenous pig breeds (i.e., Taihu and Huai) and intensive pig breeds (i.e., Landrace and Berkshire), which is an important genetic material for studying breeding mechanisms. However, there is currently limited knowledge about the genetic structure and germplasm characteristics of Sunong black pigs. To comprehensively understand their genetic composition and ancestry proportions, we performed population structure and local ancestry inference analysis based on whole-genome sequencing information. The results showed that Sunong black pigs could be clustered independently into a group, whose pedigree was intermediate between indigenous and commercial pig breeds, but closer to commercial pigs. Furthermore, local ancestry inference analysis revealed that Sunong black pigs inherited immune and reproductive traits from indigenous pig breeds, including CC and CXC chemokine family, Toll-like receptor family, IFN gene family, ESR1, AREG and EREG gene, while growth and development-related traits were inherited from commercial pig breeds, including IGF1 and GSY2 gene. Overall, Sunong black pigs have formed a relatively stable genome structure with some advantageous traits inherited from their ancestral breeds. This study deepened the understanding of the breeding mechanism of Sunong black pigs and provided a reference for cross-breeding programmes in livestock.

Anthropogenic hybridization and its influence on the adaptive potential of the Sardinian wild boar (Sus scrofa meridionalis)

The wild boar (Sus scrofa meridionalis) arrived in Sardinia with the first human settlers in the early Neolithic with the potential to hybridize with the domestic pig (S. s. domesticus) throughout its evolution on the island. In this paper, we investigated the possible microevolutionary effects of such introgressive hybridization on the present wild boar population, comparing Sardinian wild specimens with several commercial pig breeds and Sardinian local pigs, along with a putatively unadmixed wild boar population from Central Italy, all genotyped with a medium density SNP chip. We first aimed at identifying hybrids in the population using different approaches, then examined genomic regions enriched for domestic alleles in the hybrid group, and finally we applied two methods to find regions under positive selection to possibly highlight instances of domestic adaptive introgression into a wild population. We found three hybrids within the Sardinian sample (3.1% out of the whole dataset). We reported 11 significant windows under positive selection with a method that looks for overly differentiated loci in the target population, compared with other two populations. We also identified 82 genomic regions with signs of selection in the domestic pig but not in the wild boar, two of which overlapped with genomic regions enriched for domestic alleles in the hybrid pool. Genes in these regions can be linked with reproductive success. Given our results, domestic introgression does not seem to be pervasive in the Sardinian wild boar. Nevertheless, we suggest monitoring the possible spread of advantageous domestic alleles in the coming years.

Genome-wide admixture mapping identifies wild ancestry-of-origin segments in cultivated Robusta coffee

Humans have had a major influence on the dissemination of crops beyond their native range, thereby offering new hybridization opportunities. Characterizing admixed genomes with mosaic origins generates valuable insight into the adaptive history of crops and the impact on current varietial diversity. We applied the ELAI tool-an efficient local ancestry inference method based on a two-layer hidden Markov model to track segments of wild origin in cultivated accessions in the case of multiway admixtures. Source populations-which may actually be limited and partially admixed-must be generally specified when using such inference models. We thus developed a framework to identify local ancestry with admixed source populations. Using sequencing data for wild and cultivated Coffea canephora (commonly called Robusta), our approach was found to be highly efficient and accurate on simulated hybrids. Application of the method to assess elite Robusta varieties from Vietnam led to the identification of an accession derived from a likely backcross between two genetic groups from the Congo Basin and the western coastal region of Central Africa. Admixtures resulting from crop hybridization and diffusion could thus lead to the generation of elite high-yielding varieties. Our methods should be widely applicable to gain insight into the role of hybridization during plant and animal evolutionary history.

Putting RFMix and ADMIXTURE to the test in a complex admixed population

Background

Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios.

Results

Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses.

Conclusion

This study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in world-wide complex admixture scenarios particularly when including these estimates in association studies.

LAIT: a local ancestry inference toolkit

Background

Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience.

Results

We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used.

Conclusion

We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-017-0546-y) contains supplementary material, which is available to authorized users.