Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models
Abstract Markers are an important tool in plant breeding, which can improve conventional phenotypic breeding, generating more accurate information outcoming better decision making. This study aimed to apply and compare the fit of different Bayesian models BRR, BayesA, BayesB, BayesB (setting the val...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-07-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-93120-z |
id |
doaj-ff0d0eda78084174bbd951a95836d65d |
---|---|
record_format |
Article |
spelling |
doaj-ff0d0eda78084174bbd951a95836d65d2021-07-04T11:30:50ZengNature Publishing GroupScientific Reports2045-23222021-07-0111111110.1038/s41598-021-93120-zBayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian modelsFlavia Alves da Silva0Alexandre Pio Viana1Caio Cezar Guedes Correa2Eileen Azevedo Santos3Julie Anne Vieira Salgado de Oliveira4José Daniel Gomes Andrade5Rodrigo Moreira Ribeiro6Leonardo Siqueira Glória7Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Plant Genetic Breeding (LMGV), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Laboratory of Animal Science (LZO), Center for Agricultural Sciences and Technologies (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)Abstract Markers are an important tool in plant breeding, which can improve conventional phenotypic breeding, generating more accurate information outcoming better decision making. This study aimed to apply and compare the fit of different Bayesian models BRR, BayesA, BayesB, BayesB (setting the value from very low to $$\pi$$ π = $${10}^{-5}$$ 10 - 5 ), BayesC and Bayesian Lasso (LASSO) for predictions of the genomic genetic values of productivity and quality traits of a guava population. The models were fitted for traits fruit mass, pulp mass, soluble solids content, fruit number, and production per plant in the genomic prediction with SSR markers, obtained through the CTAB extraction method with 200 primers. The Bayesian ridge regression model showed the best results for all traits and was chosen to predict the individual’s genomic values according to the cross-validation data. A good stabilization of the Markov and Monte Carlo chains was observed with the mean values close to the observed phenotypic means. Heritabilities showed good predictive accuracy. The model showed strong correlations between some traits, allowing indirect selection.https://doi.org/10.1038/s41598-021-93120-z |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Flavia Alves da Silva Alexandre Pio Viana Caio Cezar Guedes Correa Eileen Azevedo Santos Julie Anne Vieira Salgado de Oliveira José Daniel Gomes Andrade Rodrigo Moreira Ribeiro Leonardo Siqueira Glória |
spellingShingle |
Flavia Alves da Silva Alexandre Pio Viana Caio Cezar Guedes Correa Eileen Azevedo Santos Julie Anne Vieira Salgado de Oliveira José Daniel Gomes Andrade Rodrigo Moreira Ribeiro Leonardo Siqueira Glória Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models Scientific Reports |
author_facet |
Flavia Alves da Silva Alexandre Pio Viana Caio Cezar Guedes Correa Eileen Azevedo Santos Julie Anne Vieira Salgado de Oliveira José Daniel Gomes Andrade Rodrigo Moreira Ribeiro Leonardo Siqueira Glória |
author_sort |
Flavia Alves da Silva |
title |
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models |
title_short |
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models |
title_full |
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models |
title_fullStr |
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models |
title_full_unstemmed |
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models |
title_sort |
bayesian ridge regression shows the best fit for ssr markers in psidium guajava among bayesian models |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-07-01 |
description |
Abstract Markers are an important tool in plant breeding, which can improve conventional phenotypic breeding, generating more accurate information outcoming better decision making. This study aimed to apply and compare the fit of different Bayesian models BRR, BayesA, BayesB, BayesB (setting the value from very low to $$\pi$$ π = $${10}^{-5}$$ 10 - 5 ), BayesC and Bayesian Lasso (LASSO) for predictions of the genomic genetic values of productivity and quality traits of a guava population. The models were fitted for traits fruit mass, pulp mass, soluble solids content, fruit number, and production per plant in the genomic prediction with SSR markers, obtained through the CTAB extraction method with 200 primers. The Bayesian ridge regression model showed the best results for all traits and was chosen to predict the individual’s genomic values according to the cross-validation data. A good stabilization of the Markov and Monte Carlo chains was observed with the mean values close to the observed phenotypic means. Heritabilities showed good predictive accuracy. The model showed strong correlations between some traits, allowing indirect selection. |
url |
https://doi.org/10.1038/s41598-021-93120-z |
work_keys_str_mv |
AT flaviaalvesdasilva bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT alexandrepioviana bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT caiocezarguedescorrea bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT eileenazevedosantos bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT julieannevieirasalgadodeoliveira bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT josedanielgomesandrade bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT rodrigomoreiraribeiro bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels AT leonardosiqueiragloria bayesianridgeregressionshowsthebestfitforssrmarkersinpsidiumguajavaamongbayesianmodels |
_version_ |
1721320263508819968 |