UCLA

Zebra finch (Taeniopygia guttata) is a representative songbird species that has been widely studied to investigate the neurobiological basis of vocal learning, a rare trait shared in only a few species including human. In December 2019, an updated zebra finch genome annotation (bTaeGut1_v1.p) was released from Ensembl database and is substantially more comprehensive than the first version published in 2010. In this study, we utilized the publicly available RNA-seq data generated from Illumina-based short-read method and PacBio single-molecule real-time (SMRT) long-read method to assess the bird transcriptome. To analyze the high-throughput RNA-seq data, we adopted a hybrid bioinformatic approach combining short and long read pipelines to investigate the new bird annotation for the first time. From our analysis, we added 220 novel genes and 8,134 transcript variants to the Ensembl annotation, and predicted a new proteome based on the refined annotation. Our results provide additional resources for future studies of zebra finches and other songbirds utilizing this improved annotation.