High-quality sequence assembly and accurate gene annotation are critical to understanding gene evolution but are often complicated in regions of segmental duplications (SDs). Although such regions are particularly important for gene innovation, a basic understanding (e.g., gene structure and protein-coding potential) is still incomplete, incorrect, or lacking for many duplicate genes. We developed a method to yield full-length transcript information and confidently distinguish between nearly identical genes/paralogs. We used biotinylated probes to enrich for full-length cDNA from duplicated regions, which were then amplified, size-fractionated, and sequenced using single-molecule, long-read sequencing technology, permitting us to distinguish between highly identical genes by virtue of multiple paralogous sequence variants. We examined 19 gene families as expressed in developing and adult human brain, selected for their high sequence identity (average >99%) and overlap with human-specific SDs. We characterized the transcriptional differences between related paralogs to better understand the birth-death process of duplicate genes and particularly how the process leads to gene innovation. In 48% of the cases, we find that the expressed duplicates have changed substantially from their ancestral models due to novel sites of transcription initiation, splicing, and polyadenylation, as well as fusion transcripts that connect duplication-derived exons with neighboring genes. This transcriptional diversity occurs early during evolution likely in in the absence of selection. We detect unannotated open-reading frames in genes currently annotated as pseudogenes, while relegating other duplicates to pseudogene status. Our method significantly improves gene annotation, specifically defining full-length transcripts, isoforms, and open-reading frames for new genes in highly identical SDs. The approach will be more broadly applicable to genes in structurally complex regions of other genomes where the duplication process creates novel genes important for adaptive traits.
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