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Revisiting avian ‘missing’ genes from de novo assembled transcripts
- Source :
- BMC Genomics, Vol 20, Iss 1, Pp 1-10 (2019)
- Publication Year :
- 2019
- Publisher :
- BMC, 2019.
-
Abstract
- Abstract Background Argument remains as to whether birds have lost genes compared with mammals and non-avian vertebrates during speciation. High quality-reference gene sets are necessary for precisely evaluating gene gain and loss. It is essential to explore new reference transcripts from large-scale de novo assembled transcriptomes to recover the potential hidden genes in avian genomes. Results We explored 196 high quality transcriptomic datasets from five bird species to reconstruct transcripts for the purpose of discovering potential hidden genes in the avian genomes. We constructed a relatively complete and high-quality bird transcript database (1,623,045 transcripts after quality control in five birds) from a large amount of avian transcriptomic data, and found most of the presumed missing genes (83.2%) could be recovered in at least one bird species. Most of these genes have been identified for the first time in birds. Our results demonstrate that 67.94% genes have GC content over 50%, while 2.91% genes are AT-rich (AT% > 60%). In our results, 239 (53.59%) genes had a tissue-specific expression index of more than 0.9 in chicken. The missing genes also have lower Ka/Ks values than average (genome-wide: Ka/Ks = 0.99; missing gene: Ka/Ks = 0.90; t-test = 1.25E-14). Among all presumed missing genes, there were 135 for which we did not find any meaningful orthologues in any of the 5 species studied. Conclusion Insufficient reference genome quality is the major reason for wrongly inferring missing genes in birds. Those presumably missing genes often have a very strong tissue-specific expression pattern. We show multi-tissue transcriptomic data from various species are necessary for inferring gene family evolution for species with only draft reference genomes.
Details
- Language :
- English
- ISSN :
- 14712164
- Volume :
- 20
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Genomics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.fd542f71792347d59b07ed27c825f566
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12864-018-5407-1