Evolutionary characteristics of intergenic transcribed regions indicate rare novel genes and widespread noisy transcription in the Poaceae

Lloyd, John P.; Bowman, Megan J.; Azodi, Christina B.; Sowers, Rosalie P.; Moghe, Gaurav D.; Childs, Kevin L.; Shiu, Shin-Han

doi:10.1038/s41598-019-47797-y

Title: Evolutionary characteristics of intergenic transcribed regions indicate rare novel genes and widespread noisy transcription in the Poaceae

Journal Article · Tue Aug 20 00:00:00 EDT 2019 · Scientific Reports

DOI:https://doi.org/10.1038/s41598-019-47797-y· OSTI ID:1619548

;

; Sowers, Rosalie P.; Moghe, Gaurav D.; Childs, Kevin L.;

Abstract Extensive transcriptional activity occurring in intergenic regions of genomes has raised the question whether intergenic transcription represents the activity of novel genes or noisy expression. To address this, we evaluated cross-species and post-duplication sequence and expression conservation of intergenic transcribed regions (ITRs) in four Poaceae species. Among 43,301 ITRs across the four species, 34,460 (80%) are species-specific. ITRs found across species tend to be more divergent in expression and have more recent duplicates compared to annotated genes. To assess if ITRs are functional (under selection), machine learning models were established in Oryza sativa (rice) that could accurately distinguish between phenotype genes and pseudogenes (area under curve-receiver operating characteristic = 0.94). Based on the models, 584 (8%) and 4391 (61%) rice ITRs are classified as likely functional and nonfunctional with high confidence, respectively. ITRs with conserved expression and ancient retained duplicates, features that were not part of the model, are frequently classified as likely-functional, suggesting these characteristics could serve as pragmatic rules of thumb for identifying candidate sequences likely to be under selection. This study also provides a framework to identify novel genes using comparative transcriptomic data to improve genome annotation that is fundamental for connecting genotype to phenotype in crop and model systems.

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Research Organization:: Michigan State Univ., East Lansing, MI (United States). Great Lakes Bioenergy Research Center

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: BER DE-SC0018409; SC0018409; IOS-1546617; DEB-1655386

OSTI ID:: 1619548

Alternate ID(s):: OSTI ID: 1579362

Journal Information:: Scientific Reports, Journal Name: Scientific Reports Vol. 9 Journal Issue: 1; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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Cited by: 2 works

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