Metabolic and microbial changes in light-vented bulbul during recent northward range expansion.

Endotherms recently expanding to cold environments generally exhibit strong physiological acclimation to sustain high body temperature. During this process, gut microbes likely play a considerable role in host physiological functions, including digestion and thermogenesis. The light-vented bulbul Pycnonotus sinensis represents one such species. It used to be restricted to the Oriental realm but expanded its distribution range north to the Palearctic areas during the past few decades. Here, we explored the seasonal dynamics of the resting metabolic rate (RMR) and microbiota for local and newly colonized populations of the species. Our results showed that the mass-adjusted RMR and body mass were positively correlated with latitude variations in both seasons. Consistently, the gut microbiota showed a corresponding variation to the northern cold environments. In the two northern populations, the alpha diversity decreased compared with those of the two southern populations. Significant differences were detected in dominant phyla, such as Firmicutes, Bacteroidetes, Proteobacteria, and Desulfobacterota in both seasons. The core microbiota showed geographic differences in the winter, including the elevated relative abundance of 5 species in northern populations. Finally, to explore the link between microbial communities and host metabolic thermogenesis, we conducted a correlation analysis between microbiota and mass-adjusted RMR. We found that more genera were significantly correlated with mass-adjusted RMR in the wintering season compared to the breeding season (71 vs. 23). These results suggest that microbiota of the lighted-vented bulbul linked with thermogenesis in diversity and abundance under northward expansion.

Haplotype analysis of genomic prediction by incorporating genomic pathway information based on high-density SNP marker in Chinese yellow-feathered chicken.

Genomic selection using single nucleotide polymorphism (SNP) markers is now intensively investigated in breeding and has been widely utilized for genetic improvement. Currently, several studies have used haplotype (consisting of multiallelic SNPs) for genomic prediction and revealed its performance advantage. In this study, we comprehensively evaluated the performance of haplotype models for genomic prediction in 15 traits, including 6 growth, 5 carcass, and 4 feeding traits in a Chinese yellow-feathered chicken population. We adopted 3 methods to define haplotypes from high-density SNP panels, and our strategy included combining Kyoto Encyclopedia of Genes and Genomes pathway information and considering linkage disequilibrium (LD) information. Our results showed an increase in prediction accuracy due to haplotypes ranging from -0.04∼27.16% in all traits, where the significant improvements were found in 12 traits. The estimates of haplotype epistasis heritability were strongly correlated with the accuracy increase by haplotype models. In addition, incorporating genomic annotation information could further increase the accuracy of the haplotype model, where the further increase in accuracy is significantly relative to the increase of relative haplotype epistasis heritability. The genomic prediction using LD information for constructing haplotypes has the best prediction performance among the 4 traits. These results uncovered that haplotype methods were beneficial for genomic prediction, and the accuracy could be further increased by incorporating genomic annotation information. Moreover, using LD information would potentially improve the performance of genomic prediction.

Genomic analyses of wild argali, domestic sheep, and their hybrids provide insights into chromosome evolution, phenotypic variation, and germplasm innovation.

Understanding the genetic mechanisms of phenotypic variation in hybrids between domestic animals and their wild relatives may aid germplasm innovation. Here, we report the high-quality genome assemblies of a male Pamir argali (O ammon polii, 2n = 56), a female Tibetan sheep (O aries, 2n = 54), and a male hybrid of Pamir argali and domestic sheep, and the high-throughput sequencing of 425 ovine animals, including the hybrids of argali and domestic sheep. We detected genomic synteny between Chromosome 2 of sheep and two acrocentric chromosomes of argali. We revealed consistent satellite repeats around the chromosome breakpoints, which could have resulted in chromosome fusion. We observed many more hybrids with karyotype 2n = 54 than with 2n = 55, which could be explained by the selfish centromeres, the possible decreased rate of normal/balanced sperm, and the increased incidence of early pregnancy loss in the aneuploid ewes or rams. We identified genes and variants associated with important morphological and production traits (e.g., body weight, cannon circumference, hip height, and tail length) that show significant variations. We revealed a strong selective signature at the mutation (c.334C > A, p.G112W) in TBXT and confirmed its association with tail length among sheep populations of wide geographic and genetic origins. We produced an intercross population of 110 F2 offspring with varied number of vertebrae and validated the causal mutation by whole-genome association analysis. We verified its function using CRISPR-Cas9 genome editing. Our results provide insights into chromosomal speciation and phenotypic evolution and a foundation of genetic variants for the breeding of sheep and other animals.

Genomic Prediction Using LD-Based Haplotypes in Combined Pig Populations.

The size of reference population is an important factor affecting genomic prediction. Thus, combining different populations in genomic prediction is an attractive way to improve prediction ability. However, combining multireference population roughly cannot increase the prediction accuracy as well as expected in pig. This may be due to different linkage disequilibrium (LD) pattern differences between population. In this study, we used the imputed whole-genome sequencing (WGS) data to construct LD-based haplotypes for genomic prediction in combined population to explore the impact of different single-nucleotide polymorphism (SNP) densities, variant representation (SNPs or haplotype alleles), and reference population size on the prediction accuracy for reproduction traits. Our results showed that genomic best linear unbiased prediction (GBLUP) using the WGS data can improve prediction accuracy in multi-population but not within-population. Not only the genomic prediction accuracy of the haplotype method using 80 K chip data in multi-population but also GBLUP for the multi-population (3.4-5.9%) was higher than that within-population (1.2-4.3%). More importantly, we have found that using the haplotype method based on the WGS data in multi-population has better genomic prediction performance, and our results showed that building haploblock in this scenario based on low LD threshold (r 2 = 0.2-0.3) produced an optimal set of variables for reproduction traits in Yorkshire pig population. Our results suggested that whether the use of the haplotype method based on the chip data or GBLUP (individual SNP method) based on the WGS data were beneficial for genomic prediction in multi-population, while simultaneously combining the haplotype method and WGS data was a better strategy for multi-population genomic evaluation.