Evidence map›Paper›PMID 30242197›Full record

ArticleScientific reports2018

Genome-wide discovery of DNA polymorphisms by whole genome sequencing differentiates weedy and cultivated rice.

Chenglin Chai, Rama Shankar, Mukesh Jain, Prasanta K Subudhi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.7field-weighted citation impact, top 6% of its field
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

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3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 26 citations in OpenAlex.

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  9. A Novel Mutation of theInternational journal of molecular sciences · 2020
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  11. Whole-genome sequencing reveals uniqueness of black-hulled and straw-hulled weedy rice genomes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020
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  13. Comprehensive Analysis of the Chitinase Gene Family in Cucumber (International journal of molecular sciences · 2019
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Chenglin ChaiSchool of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803, USA.
Rama ShankarSchool of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.
Mukesh JainSchool of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India. mjain@jnu.ac.in.ORCID 0000-0002-7622-1083
Prasanta K SubudhiSchool of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803, USA. psubudhi@agcenter.lsu.edu.
Jawaharlal Nehru University · INLouisiana State University Agricultural Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing the genome level DNA polymorphisms between weedy and cultivated rice is crucial to elucidate the molecular basis of weedy and agronomic traits, which in turn can enhance our ability to control weedy rice and its utilization for rice improvement. Here, we presented the genome-wide genetic variations between a weedy rice accession PSRR-1 and two cultivated rice accessions, Bengal and Nona Bokra, belonging to japonica and indica subspecies, respectively. The total number of SNPs and InDels in PSRR/Bengal was similar to that of Nona Bokra/Bengal, but was three times greater than that of PSRR/Nona Bokra. There were 11546 large-effect SNPs/InDels affecting 5673 genes, which most likely differentiated weedy rice from cultivated rice. These large effect DNA polymorphisms were mostly resulted in stop codon gain and least by start codon loss. Analysis of the molecular functions and biological processes of weedy rice specific SNPs/InDels indicated that most of these genes were involved in protein modification/phosphorylation, protein kinase activity, and protein/nucleotide binding. By integrating previous QTL mapping results with the DNA polymorphisms data, the candidate genes for seed dormancy and seed shattering were narrowed down. The genomic resource generated in this study will facilitate discovery of functional variants for weedy and agronomic traits.

Indexed as

Chromosome MappingCodonCrops, AgriculturalDNA, PlantEvolution, MolecularGenes, PlantGenome, PlantOryzaPlant WeedsPolymorphism, Single NucleotideSeedsWhole Genome SequencingCodonDNA, Plant

Identifiers

PMID30242197
PMCPMC6155081
OpenAlexW2892359519

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LicenceCC BY
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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.