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Bioinformatics (Oxford, England)
02 01, 2024;40 (2):

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
Author Information
  1. Carson M Andorf: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States. ORCID
  2. Olivia C Haley: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
  3. Rita K Hayford: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
  4. John L Portwood: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
  5. Stephen Harding: USDA-ARS, Mycotoxin Prevention and Applied Microbiology Research Unit, National Center for Agricultural Utilization Research, Peoria, IL 61604, United States.
  6. Shatabdi Sen: Department of Plant Pathology & Microbiology, Iowa State University, Ames, IA 50011, United States.
  7. Ethalinda K Cannon: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States.
  8. Jack M Gardiner: Division of Animal Sciences, University of Missouri, Columbia, MO 65211, United States.
  9. Hye-Seon Kim: USDA-ARS, Mycotoxin Prevention and Applied Microbiology Research Unit, National Center for Agricultural Utilization Research, Peoria, IL 61604, United States.
  10. Margaret R Woodhouse: USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, United States. ORCID
PMID: 38337024 DOI: 10.1093/bioinformatics/btae073

Abstract

SUMMARY: Understanding 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/).

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Grants

  1. /U.S. Department of Agriculture
  2. /Agricultural Research Service

MeSH Term

Zea mays
Databases, Genetic
Artificial Intelligence
Genome, Plant
Phenotype
Software
Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, Non-U.S. Gov't

Word Cloud

Created with Highcharts 10.0.0effectsPanEffectmaizevariantsfunctionalvarianttoolpan-genomeproteingeneticoutcomeslanguagescorepossiblelevelgenomeexploreMaizeGDBpotentialmillionB73availableSUMMARY:UnderstandingcrucialaccuratelypredictingtraitsRecentapproachesutilizedartificialintelligencemodelsmissenseproteomesinglereliableneededaddressgapintroducenewcalledimplementedenablecomprehensiveexaminationcodingacross50genomesallowsusersvisualize550aminoacidsubstitutionsreferenceobserve23naturalvariationseffectcalculatedEvolutionaryScaleModelingESMmodelshowslog-likelihoodratiodifferencescoresshownusingheatmapsspanningbenignconsequencesadditiondisplayssecondarystructuresdomainsalongofferingadditionalstructuralcontextUsingresearchersnowplatformidentifytargetscropenhancementAVAILABILITYANDIMPLEMENTATION:codefreelyGitHubhttps://githubcom/Maize-Genetics-and-Genomics-Database/PanEffectimplementationunderlyingdatasetshttps://wwwmaizegdborg/effect/maize/PanEffect:visualization

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