Population Structure and Genetic Diversity Analysis of “Yufen 1” H Line Chickens Using Whole-Genome Resequencing

Whole-Genome Resequencing Reveals Genetic Diversity and Wool Trait-Related Genes in Liangshan Semi-Fine-Wool Sheep

Understanding the genetic makeup of local sheep breeds is essential for their scientific conservation and sustainable utilization. The Liangshan semi-fine-wool sheep (LSS), a Chinese semi-fine-wool breed renowned for its soft wool, was analyzed using whole-genome sequencing data including 35 LSS, 84 sheep from other domestic breeds, and 20 Asiatic mouflons. We investigated the genetic composition of LSS by conducting analyses of the population structure, runs of homozygosity, genomic inbreeding coefficients, and selection signature. Our findings indicated that LSS shares greater genetic similarity with Border Leicester and Romney sheep than with Tibetan (TIB), Yunnan (YNS), and Chinese Merino sheep. Genomic analysis indicated low to moderate inbreeding coefficients, ranging from 0.014 to 0.154. In identifying selection signals across the LSS genome, we pinpointed 195 candidate regions housing 74 annotated genes (e.g., IRF2BP2, BVES, and ALOX5). We also found the overlaps between the candidate regions and several known quantitative trait loci related to wool traits, such as the wool staple length and wool fiber diameter. A selective sweep region, marked by the highest value of cross-population extended haplotype homozygosity, encompassed IRF2BP2-an influential candidate gene affecting fleece fiber traits. Furthermore, notable differences in genotype frequency at a mutation site (c.1051 + 46T > C, Chr25: 6,784,190 bp) within IRF2BP2 were observed between LSS and TIB and YNS sheep (Fisher's exact test, p < 2.2 × 10-16). Taken together, these findings offer insights crucial for the conservation and breeding enhancement of LSS.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BACKGROUND

Effective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.

RESULTS

Our results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.

CONCLUSIONS

Different kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.