The zebra finch (Taeniopygia guttata), a representative oscine songbird species, has been widely studied to investigate behavioral neuroscience, most notably the neurobiological basis of vocal learning, a rare trait shared in only a few animal groups including humans. In 2019, an updated zebra finch genome annotation (bTaeGut1_v1.p) was released from the 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-reads and PacBio single-molecule real-time (SMRT) long-reads 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. 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. We further validated 18 different novel proteins by using mass-spectrometry data generated from zebra finch caudal telencephalon tissue. Our results provide additional resources for future studies of zebra finches utilizing this improved bird genome annotation and proteome.
Keywords: RNA-seq; SMRT-seq; Song-system; Zebra finch.
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