WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants
Abstract The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrate...
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
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BMC
2019-05-01
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Series: | Genome Biology |
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Online Access: | http://link.springer.com/article/10.1186/s13059-019-1697-0 |
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author | Laurent Gentzbittel Cécile Ben Mélanie Mazurier Min-Gyoung Shin Todd Lorenz Martina Rickauer Paul Marjoram Sergey V. Nuzhdin Tatiana V. Tatarinova |
author_facet | Laurent Gentzbittel Cécile Ben Mélanie Mazurier Min-Gyoung Shin Todd Lorenz Martina Rickauer Paul Marjoram Sergey V. Nuzhdin Tatiana V. Tatarinova |
author_sort | Laurent Gentzbittel |
collection | DOAJ |
description | Abstract The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method’s prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes. |
first_indexed | 2024-12-11T13:52:30Z |
format | Article |
id | doaj.art-5b581194cf0f419baf77c6d80d5d6993 |
institution | Directory Open Access Journal |
issn | 1474-760X |
language | English |
last_indexed | 2024-12-11T13:52:30Z |
publishDate | 2019-05-01 |
publisher | BMC |
record_format | Article |
series | Genome Biology |
spelling | doaj.art-5b581194cf0f419baf77c6d80d5d69932022-12-22T01:04:13ZengBMCGenome Biology1474-760X2019-05-0120112010.1186/s13059-019-1697-0WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plantsLaurent Gentzbittel0Cécile Ben1Mélanie Mazurier2Min-Gyoung Shin3Todd Lorenz4Martina Rickauer5Paul Marjoram6Sergey V. Nuzhdin7Tatiana V. Tatarinova8EcoLab, Université de Toulouse, CNRSEcoLab, Université de Toulouse, CNRSEcoLab, Université de Toulouse, CNRSUniversity of Southern CaliforniaUniversity of La VerneEcoLab, Université de Toulouse, CNRSUniversity of Southern CaliforniaUniversity of Southern CaliforniaUniversity of La VerneAbstract The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method’s prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes.http://link.springer.com/article/10.1186/s13059-019-1697-0Genomic predictionMolecular ecologyAdaptationQuantitative disease resistanceBreedingMedicago truncatula |
spellingShingle | Laurent Gentzbittel Cécile Ben Mélanie Mazurier Min-Gyoung Shin Todd Lorenz Martina Rickauer Paul Marjoram Sergey V. Nuzhdin Tatiana V. Tatarinova WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants Genome Biology Genomic prediction Molecular ecology Adaptation Quantitative disease resistance Breeding Medicago truncatula |
title | WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants |
title_full | WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants |
title_fullStr | WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants |
title_full_unstemmed | WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants |
title_short | WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants |
title_sort | whogem an admixture based prediction machine accurately predicts quantitative functional traits in plants |
topic | Genomic prediction Molecular ecology Adaptation Quantitative disease resistance Breeding Medicago truncatula |
url | http://link.springer.com/article/10.1186/s13059-019-1697-0 |
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