Evidence map›Paper›PMID 38337024›Full record

ArticleBioinformatics (Oxford, England)2024

PanEffect: a pan-genome visualization tool for variant effects in maize.

Carson M Andorf, Olivia C Haley, Rita K Hayford, John L Portwood, Stephen Harding, Shatabdi Sen, Ethalinda K Cannon, Jack M Gardiner, Hye-Seon Kim, Margaret R Woodhouse

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. 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

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

2 citing papers in PubMed.

  1. Article
  2. Article
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

10 authors.

Carson M AndorfUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.ORCID 0000-0003-2380-6704
Olivia C HaleyUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
Rita K HayfordUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
John L PortwoodUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
Stephen HardingUSDA-ARS, Mycotoxin Prevention and Applied Microbiology Research Unit, National Center for Agricultural Utilization Research, Peoria, IL 61604, United States.
Shatabdi SenDepartment of Plant Pathology & Microbiology, Iowa State University, Ames, IA 50011, United States.
Ethalinda K CannonUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
Jack M GardinerDivision of Animal Sciences, University of Missouri, Columbia, MO 65211, United States.
Hye-Seon KimUSDA-ARS, Mycotoxin Prevention and Applied Microbiology Research Unit, National Center for Agricultural Utilization Research, Peoria, IL 61604, United States.
Margaret R WoodhouseUSDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.ORCID 0000-0003-2164-8300

Funding

Agricultural Research ServiceU.S. Department of Agriculture
6 · The paper itself

Abstract

summaryUnderstanding the effects of genetic variants is crucial for accurately predicting traits and functional outcomes. Recent approaches have utilized artificial intelligence and protein language models to score all possible missense variant effects at the proteome level for a single genome, but a reliable tool is needed to explore these effects at the pan-genome level. To address this gap, we introduce a new tool called PanEffect. We implemented PanEffect at MaizeGDB to enable a comprehensive examination of the potential effects of coding variants across 50 maize genomes. The tool allows users to visualize over 550 million possible amino acid substitutions in the B73 maize reference genome and to observe the effects of the 2.3 million natural variations in the maize pan-genome. Each variant effect score, calculated from the Evolutionary Scale Modeling (ESM) protein language model, shows the log-likelihood ratio difference between B73 and all variants in the pan-genome. These scores are shown using heatmaps spanning benign outcomes to potential functional consequences. In addition, PanEffect displays secondary structures and functional domains along with the variant effects, offering additional functional and structural context. Using PanEffect, researchers now have a platform to explore protein variants and identify genetic targets for crop enhancement. AVAILABILITY AND IMPLEMENTATION: The PanEffect code is freely available on GitHub (https://github.com/Maize-Genetics-and-Genomics-Database/PanEffect). A maize implementation of PanEffect and underlying datasets are available at MaizeGDB (https://www.maizegdb.org/effect/maize/).

Indexed as

Databases, GeneticZea maysArtificial IntelligenceGenome, PlantPhenotypeSoftware

Identifiers

PMID38337024
PMCPMC10881103

What OpenQuestion holds

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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.