Evidence map›Paper›PMID 31653677›Full record

ArticleGenetics2019

The Fate of Deleterious Variants in a Barley Genomic Prediction Population.

Thomas J Y Kono, Chaochih Liu, Emily E Vonderharr, Daniel Koenig, Justin C Fay, Kevin P Smith, Peter L Morrell

Abstract read
In one paragraph

Article in Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 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.

Thomas J Y KonoDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108.ORCID 0000-0002-1388-3194
Chaochih LiuDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108.ORCID 0000-0002-2179-9638
Emily E VonderharrDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108.ORCID 0000-0002-8147-9986
Daniel KoenigDepartment of Botany and Plant Sciences, University of California, Riverside, California 92521.ORCID 0000-0002-1037-5346
Justin C FayDepartment of Biology, University of Rochester, New York 14627.ORCID 0000-0003-1893-877X
Kevin P SmithDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108.ORCID 0000-0001-8253-3326
Peter L MorrellDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108 pmorrell@umn.edu.ORCID 0000-0001-6282-1582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a "cost of domestication." This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of

Indexed as

Genetic VariationGenomicsBiological Variation, PopulationCodonExomeGene FrequencyGenetics, PopulationGenotypeHomozygoteHordeumPlant BreedingPolymorphism, Single NucleotideSequence Analysis, DNACodondeleterious variantsgenomic predictionmultiparent population

Identifiers

PMID31653677
PMCPMC6893365

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.