Evidence map›Paper›PMID 31431676›Full record

ArticleScientific reports2019

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

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

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

John P LloydDepartment of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.ORCID http://orcid.org/0000-0003-0454-4374
Megan J BowmanDepartment of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.ORCID http://orcid.org/0000-0001-5742-1779
Christina B AzodiDepartment of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.ORCID http://orcid.org/0000-0002-6097-606X
Rosalie P SowersDepartment of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, 16801, USA.
Gaurav D MogheSection of Plant Biology, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, 14853, USA.
Kevin L ChildsDepartment of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.
Shin-Han ShiuDepartment of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA. shius@msu.edu.ORCID http://orcid.org/0000-0001-6470-235X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DNA, IntergenicGenes, PlantTranscription, GeneticBiological EvolutionGenome, PlantMachine LearningModels, GeneticPhenotypePoaceaePseudogenesSpecies SpecificityDNA, Intergenic

Identifiers

PMID31431676
PMCPMC6702216

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.