Genomic data for 78 chickens from 14 populations

Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to~10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ~21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ~6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens.Peer reviewedAnimal Scienc

Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives

Abstract Background: Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown. Findings: We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression–based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation. Conclusions: These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments

Reference ranges and trajectories for blood pressure in pregnancy: findings from a follow-up study based on China Maternal and Newborn’s Health Monitoring System

Objectives: This study aimed to establish normal blood pressure reference ranges across gestation and maternal characteristics. Methods: We conducted a follow-up study including 29,200 Chinese normal pregnant women. Multilevel restrictive cubic spline models were used to calculate normal blood pressure reference ranges among all population and stratified groups. Results: In all normal pregnancies, the normal reference range of systolic blood pressure were 93.94-118.74 mmHg(2.5th-97.5th) and 97.35-124.63 mmHg at 12 and 37 weeks gestation, respectively while 58.79-74.21 mmHg and 59.19-78.25 mmHg were for diastolic blood pressure at 12 and 37 weeks gestation, which differed in subgroups stratified by prepregnancy body mass index and maternal age. Conclusion: This study provides evidence for blood pressure management in Chinese pregnant women

Genome-wide analysis reveals selection for Chinese Rongchang pigs

Livestock have undergone domestication and consequently strong selective pressure on genes or genomic regions that control desirable traits. To identify selection signatures in the genome of Chinese Rongchang pigs, we generated a total of about 170 Gb of DNA sequence data with about 6.4-fold coverage for each of six female individuals. By combining these data with the publically available genome data of 10 Asian wild boars, we identified 449 protein-coding genes with selection signatures in Rongchang pigs, which are mainly involved in growth and hormone binding, nervous system development, and drug metabolism. The accelerated evolution of these genes may contribute to the dramatic phenotypic differences between Rongchang pigs and Chinese wild boars. This study illustrated how domestication and subsequent artificial selection have shaped patterns of genetic variation in Rongchang pigs and provides valuable genetic resources that can enhance the use of pigs in agricultural production and biomedical studies

Time-series modules and co-expression network of lncRNAs and protein-coding genes.

<p>(A) Time-series modules of protein-coding genes and lncRNAs. The top panel shows protein-coding genes and the second panel shows lncRNAs. Numbers in the top left corner indicate module number. Numbers in lower left corners indicate numbers of protein-coding genes or lncRNAs in each module. The same color was used to represent each cluster. Functional categories of genes in green (B) and red modules (C). Benjamini adjusted <i>P</i> values were transformed by ‒log₁₀. (D) Heat map showing the largest two co-expression networks of protein-coding genes. Values represent log₂(FPKM+1) of each gene in each sample minus the mean value of each gene across all samples.</p

Expression profile and PCA of protein-coding genes.

<p>(A) Heat map showing the expression profile of protein-coding genes. The top panel is the tree constructed by Pearson correlation. (B) Two-way PCA plot of protein-coding genes based on expression profile.</p

Temporal expression profiles of protein-coding genes and lncRNAs.

<p>(A) Dynamic changes in expression profiles of protein-coding genes and lncRNAs. The top panel shows protein-coding genes and the bottom panel shows lncRNAs. Values represent the pairwise Pearson correlation. Correlation between every two samples was calculated by log₂-transformed (FPKM+1) gene expression values. Three main expression patterns can be distinguished. (B) Distributions of Shannon entropy-based temporal specificity scores were calculated for distinct classes of lncRNAs and protein-coding genes.</p

Differentially expressed protein-coding genes and lncRNAs, and PCA of PSI values.

<p>Venn diagram of common differentially expressed protein-coding genes (A) and lncRNAs (B) in five developmental stages. (C) Dynamic expression profiles of <i>CP</i> and TU78568. (D) Two-way PCA plot of protein-coding genes based on PSI values.</p

Population genomics identifies patterns of genetic diversity and selection in chicken

Abstract Background There are hundreds of phenotypically distinguishable domestic chicken breeds or lines with highly specialized traits worldwide, which provide a unique opportunity to illustrate how selection shapes patterns of genetic variation. There are many local chicken breeds in China. Results Here, we provide a population genome landscape of genetic variations in 86 domestic chickens representing 10 phenotypically diverse breeds. Genome-wide analysis indicated that sex chromosomes have less genetic diversity and are under stronger selection than autosomes during domestication and local adaptation. We found an evidence of admixture between Tibetan chickens and other domestic population. We further identified strong signatures of selection affecting genomic regions that harbor genes underlying economic traits (typically related to feathers, skin color, growth, reproduction and aggressiveness) and local adaptation (to high altitude). By comparing the genomes of the Tibetan and lowland fowls, we identified genes associated with high-altitude adaptation in Tibetan chickens were mainly involved in energy metabolism, body size maintenance and available food sources. Conclusions The work provides crucial insights into the distinct evolutionary scenarios occurring under artificial selection for agricultural production and under natural selection for success at high altitudes in chicken. Several genes were identified as candidates for chicken economic traits and other phenotypic traits