Evidence map›Paper›PMID 32032385›Full record

ArticlePloS one2020

On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids.

Giovanni Galli, Filipe Couto Alves, Júlia Silva Morosini, Roberto Fritsche-Neto

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In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Giovanni GalliUniversity of São Paulo, Luiz de Queiroz College of Agriculture, Department of Genetics, Piracicaba, São Paulo, Brazil.ORCID 0000-0002-3400-7978
Filipe Couto AlvesInstitute of Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan, United States of America.
Júlia Silva MorosiniUniversity of São Paulo, Luiz de Queiroz College of Agriculture, Department of Genetics, Piracicaba, São Paulo, Brazil.
Roberto Fritsche-NetoUniversity of São Paulo, Luiz de Queiroz College of Agriculture, Department of Genetics, Piracicaba, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) is one of the most popular methods of studying the genetic control of traits. This methodology has been intensely performed on inbred genotypes to identify causal variants. Nonetheless, the lack of covariance between the phenotype of inbred lines and their offspring in cross-pollinated species (such as maize) raises questions on the applicability of these findings in a hybrid breeding context. To address this topic, we incorporated previously reported parental lines GWAS information into the prediction of a low heritability trait in hybrids. This was done by marker-assisted selection based on significant markers identified in the lines and by genomic prediction having these markers as fixed effects. Additive-dominance GWAS of hybrids, a non-conventional procedure, was also performed for comparison purposes. Our results suggest that incorporating information from parental inbred lines GWAS led to decreases in the predictive ability of hybrids. Correspondingly, inbred lines and hybrids-based GWAS yielded different results. These findings do not invalidate GWAS on inbred lines for selection purposes, but mean that it may not be directly useful for hybrid breeding.

Indexed as

Genome-Wide Association StudyQuantitative Trait, HeritableCluster AnalysisGenome, PlantLinkage DisequilibriumPhenotypePlant BreedingPrincipal Component AnalysisZea mays

Identifiers

PMID32032385
PMCPMC7006934

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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.