We are drawn to the extraordinary adaptations of birds, which are result from natural selection. Genome data, transcriptome data and epigenomic profiling provide us insights to understand the microevolutionary context underlying the animal adaptation to specific environment. We usually scan for the selection signatures on specific genes or pathways in the context of the evolutionary history, study the dynamics of gene expression and regulation during development, and identify variations at the molecular level that are connected to unique biological traits shown to affect species fitness (Feng et al, Nature, 2020). We also study some particular events in evolution that could act on the phenotype inheritance in the species lineages, such as incomplete lineage sorting (Feng et al, Cell, 2022). In our lab, the research scale is an entire class of bird species. High throughput ‘-omics’ data and rich phenotypic data in birds makes it necessary to find the relationship between phenotypes and genotypes from such big data. Therefore, our research group also apply Artificial Intelligence technology in biology to decipher the network of phenotypes and genotypes.