Evidence map›Paper›PMID 31641024›Full record

ArticleThe Plant cell2020

Transcriptome-Based Prediction of Complex Traits in Maize.

Christina B Azodi, Jeremy Pardo, Robert VanBuren, Gustavo de Los Campos, Shin-Han Shiu

Abstract read
In one paragraph

Article in The Plant cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

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  12. Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Christina B AzodiDepartment of Plant Biology, Michigan State University, East Lansing, Michigan 48824.ORCID 0000-0002-6097-606X
Jeremy PardoDepartment of Plant Biology, Michigan State University, East Lansing, Michigan 48824.ORCID 0000-0003-3419-095X
Robert VanBurenPlant Resilience Institute, Michigan State University, East Lansing, Michigan 48824.ORCID 0000-0003-2133-2760
Gustavo de Los CamposEpidemiology and Biostatistics and Statistics and Probability Departments, Michigan State University, East Lansing, Michigan 48824.ORCID 0000-0001-5692-7129
Shin-Han ShiuDepartment of Plant Biology, Michigan State University, East Lansing, Michigan 48824 shius@msu.edu.ORCID 0000-0001-6470-235X

Funding

Plant Biotechnology for Health and SustainabilityT32GM110523 · NIGMS · MICHIGAN STATE UNIVERSITY · PI LAST, ROBERT LOUIS · 2014 to 2023
$2.2M
NIGMS NIH HHS T32 GM110523
6 · The paper itself

Abstract

The ability to predict traits from genome-wide sequence information (i.e., genomic prediction) has improved our understanding of the genetic basis of complex traits and transformed breeding practices. Transcriptome data may also be useful for genomic prediction. However, it remains unclear how well transcript levels can predict traits, particularly when traits are scored at different development stages. Using maize (

Indexed as

Multifactorial InheritanceTranscriptomeGenetic MarkersGenetic VariationGenome, PlantGenome-Wide Association StudyGenomicsModels, GeneticPhenotypeZea maysGenetic Markers

Identifiers

PMID31641024
PMCPMC6961623

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.