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. 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. 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.

The transcriptional profiles of mammals during brain development and ageing have been characterized. However the global expression patterns of transcriptome in the chicken brain have not been explored. Here, we systematically investigated the temporal expression profiles of lncRNAs and mRNAs across 8 stages (including 3 embryonic stages, 2 growth stages and 3 adult stages) in the female chicken cerebrum. We identified 39,907 putative lncRNAs and 14,558 mRNAs, investigated the temporal expression patterns by tracking a set of age-dependent genes and predicted potential biological functions of lncRNAs based on co-expression network. The results showed that genes with functions in development, synapses and axons exhibited a progressive decay; genes related to immune response were up-regulated with age. These results may reflect changes in the regulation of transcriptional networks and provide non-coding RNA gene candidates for further studies and would contribute to a comprehensive understanding of the molecular mechanisms of chicken development and may provide insights or deeper understanding regarding the regulatory mechanisms of age-dependent protein coding and non-protein coding genes in chicken. In addition, as the chicken is an important model organism bridging the evolutionary gap between mammals and other vertebrates, these high resolution data may provide a novel evidence to improve our comprehensive understanding of the brain transcriptome during vertebrate evolution.