Publications by authors named "Rodrigo Iván Contreras-Soto"

4 Publications

  • Page 1 of 1

Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network.

Front Plant Sci 2020 27;11:593897. Epub 2020 Nov 27.

Departamento de Agronomia, Universidade Estadual de Maringá, Maringá, Brazil.

Genomic selection models were investigated to predict several complex traits in breeding populations of L. and Labill. For this, the following methods of Machine Learning (ML) were implemented: (i) Deep Learning (DL) and (ii) Bayesian Regularized Neural Network (BRNN) both in combination with different hyperparameters. These ML methods were also compared with Genomic Best Linear Unbiased Prediction (GBLUP) and different Bayesian regression models [Bayes A, Bayes B, Bayes Cπ, Bayesian Ridge Regression, Bayesian LASSO, and Reproducing Kernel Hilbert Space (RKHS)]. DL models, using Rectified Linear Units (as the activation function), had higher predictive ability values, which varied from 0.27 (pilodyn penetration of 6 years old eucalypt trees) to 0.78 (flowering-related traits of maize). Moreover, the larger mini-batch size (100%) had a significantly higher predictive ability for wood-related traits than the smaller mini-batch size (10%). On the other hand, in the BRNN method, the architectures of one and two layers that used only the pureline function showed better results of prediction, with values ranging from 0.21 (pilodyn penetration) to 0.71 (flowering traits). A significant increase in the prediction ability was observed for DL in comparison with other methods of genomic prediction (Bayesian alphabet models, GBLUP, RKHS, and BRNN). Another important finding was the usefulness of DL models (through an iterative algorithm) as an SNP detection strategy for genome-wide association studies. The results of this study confirm the importance of DL for genome-wide analyses and crop/tree improvement strategies, which holds promise for accelerating breeding progress.
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http://dx.doi.org/10.3389/fpls.2020.593897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728740PMC
November 2020

Plasticity of the Root System Architecture and Leaf Gas Exchange Parameters Are Important for Maintaining Bottle Gourd Responses under Water Deficit.

Plants (Basel) 2020 Dec 3;9(12). Epub 2020 Dec 3.

Instituto de Ciencias Agroalimentarias, Animales y Ambientales, Universidad de O'Higgins, San Fernando 3070000, Chile.

The evaluation of root system architecture (RSA) development and the physiological responses of crop plants grown under water-limited conditions are of great importance. The purpose of this study was to examine the short-term variation of the morphological and physiological plasticity of genotypes under water deficit, evaluating the changes in the relationship between the root system architecture and leaf physiological responses. Bottle gourd genotypes were grown in rhizoboxes under well-watered and water deficit conditions. Significant genotype-water regime interactions were observed for several RSA traits and physiological parameters. Biplot analyses confirmed that the drought-tolerant genotypes (BG-48 and GC) showed a high net CO assimilation rate, stomatal conductance, transpiration rates with a smaller length, and a reduced root length density of second-order lateral roots, whereas the genotypes BG-67 and Osorno were identified as drought-sensitive and showed greater values for average root length and the density of second-order lateral roots. Consequently, a reduced length and density of lateral roots in bottle gourd should constitute a response to water deficit. The root traits studied here can be used to evaluate bottle gourd performance under novel water management strategies and as criteria for breeding selection.
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http://dx.doi.org/10.3390/plants9121697DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761539PMC
December 2020

Genome-wide association mapping for flowering and maturity in tropical soybean: implications for breeding strategies.

Breed Sci 2017 Dec 16;67(5):435-449. Epub 2017 Nov 16.

Dow Agrosciences, Rod. Anhanguera S/N Km 330, Cravinhos SP, 14140-000, Brazil.

Knowledge of the genetic architecture of flowering and maturity is needed to develop effective breeding strategies in tropical soybean. The aim of this study was to identify haplotypes across multiple environments that contribute to flowering time and maturity, with the purpose of selecting desired alleles, but maintaining a minimal impact on yield-related traits. For this purpose, a genome-wide association study (GWAS) was undertaken to identify genomic regions that control days to flowering (DTF) and maturity (DTM) using a soybean association mapping panel genotyped for single nucleotide polymorphism (SNP) markers. Complementarily, yield-related traits were also assessed to discuss the implications for breeding strategies. To detect either stable or specific associations, the soybean cultivars (N = 141) were field-evaluated across eight tropical environments of Brazil. Seventy-two and forty associations were significant at the genome-wide level relating respectively to DTM and DTF, in two or more environments. Haplotype-based GWAS identified three haplotypes (Gm12_Hap12; Gm19_Hap42 and Gm20_Hap32) significantly co-associated with DTF, DTM and yield-related traits in single and multiple environments. These results indicate that these genomic regions may contain genes that have pleiotropic effects on time to flowering, maturity and yield-related traits, which are tightly linked with multiple other genes with high rates of linkage disequilibrium.
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http://dx.doi.org/10.1270/jsbbs.17024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5790042PMC
December 2017

A Genome-Wide Association Study for Agronomic Traits in Soybean Using SNP Markers and SNP-Based Haplotype Analysis.

PLoS One 2017 2;12(2):e0171105. Epub 2017 Feb 2.

Dow Agrosciences, Rod. Anhanguera, Cravinhos, SP, Brazil.

Mapping quantitative trait loci through the use of linkage disequilibrium (LD) in populations of unrelated individuals provides a valuable approach for dissecting the genetic basis of complex traits in soybean (Glycine max). The haplotype-based genome-wide association study (GWAS) has now been proposed as a complementary approach to intensify benefits from LD, which enable to assess the genetic determinants of agronomic traits. In this study a GWAS was undertaken to identify genomic regions that control 100-seed weight (SW), plant height (PH) and seed yield (SY) in a soybean association mapping panel using single nucleotide polymorphism (SNP) markers and haplotype information. The soybean cultivars (N = 169) were field-evaluated across four locations of southern Brazil. The genome-wide haplotype association analysis (941 haplotypes) identified eleven, seventeen and fifty-nine SNP-based haplotypes significantly associated with SY, SW and PH, respectively. Although most marker-trait associations were environment and trait specific, stable haplotype associations were identified for SY and SW across environments (i.e., haplotypes Gm12_Hap12). The haplotype block 42 on Chr19 (Gm19_Hap42) was confirmed to be associated with PH in two environments. These findings enable us to refine the breeding strategy for tropical soybean, which confirm that haplotype-based GWAS can provide new insights on the genetic determinants that are not captured by the single-marker approach.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171105PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289539PMC
August 2017