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Native chickens are endangered genetic resources that are kept by farmers for different purposes. Native chickens distributed in a wide range of altitudes, have developed adaptive mechanisms to deal with hypoxia. For the first time, we report variants associated with high-altitude adaptation in Iranian native chickens by whole genome sequencing of lowland and highland chickens. We found that these adaptive variants are involved in DNA repair, organs development, immune response and histone binding. Amazingly, signature selection analysis demonstrated that differential variants are adaptive in response to hypoxia and are not due to other evolutionary pressures. Cellular component analysis of variants showed that mitochondrion is the most important organelle for hypoxia adaptation. A total of 50 variants was detected in mtDNA for highland and lowland chickens. High-altitude associated with variant discovery highlighted the importance of COX3, a gene involved in cell respiration, in hypoxia adaptation. The results of study suggest that MIR6644-2 is involved in hypoxia and high-altitude adaptations by regulation of embryo development. Finally, 3877 novel SNVs including the mtDNA ones, were submitted to EBI (PRJEB24944). Whole-genome sequencing and variant discovery of native chickens provided novel insights about adaptation mechanisms and highlights the importance of valuable genomic variants in chickens.

In eukaryotes, different combinations of exons lead to multiple transcripts with various functions in protein level, in a process called alternative splicing (AS). Unfolding the complexity of functional genomics through genome-wide profiling of AS and determining the altered ultimate products provide new insights for better understanding of many biological processes, disease progress as well as drug development programs to target harmful splicing variants. The current available tools of alternative splicing work with raw data and include heavy computation. In particular, there is a shortcoming in tools to discover AS events directly from transcripts. Here, we developed a Windows-based user-friendly tool for identifying AS events from transcripts without the need to any advanced computer skill or database download. Meanwhile, due to online working mode, our application employs the updated SpliceGraphs without the need to any resource updating. First, SpliceGraph forms based on the frequency of active splice sites in pre-mRNA. Then, the presented approach compares query transcript exons to SpliceGraph exons. The tool provides the possibility of statistical analysis of AS events as well as AS visualization compared to SpliceGraph. The developed application works for transcript sets in human and model organisms.