Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.

Yield is one of the most important traits of arabica coffee. Plant breeders seek to maximize yield directly or indirectly, using other related traits. The standard multi-trait genome-wide association study (MTM-GWAS) does not accommodate the network structure of phenotypes, therefore, does not address how traits are interrelated. We applied structural equation modeling (SEM) to GWAS to explore interrelated dependencies between phenotypes related to morphology (fruit size and number of reproductive nodes), physiology (vegetative vigor), and productivity (yield) traits using 195 Coffea arábica individuals genotyped with 21,211 single-nucleotide polymorphism markers. We inferred the probabilistic phenotypic network by the Hill-Climbing algorithm to estimate the structural coefficients. The integration of multivariate GWAS and SEM (SEM-GWAS) identified a positive interrelationship between vegetative vigor and yield, and vegetative vigor and the number of reproductive nodes. Among those traits, yield and number of reproductive nodes presented indirect SNP effects. There was no evidence of a single quantitative trait locus controlling all the traits jointly. We identified three genes (Stress enhanced protein 1, Abscisic stress-ripening protein 5, and SAR?SNI1) that acted directly on yield. In summary, SEM-GWAS offered new insights into the relationship between the traits linked to coffee yield, providing useful information for arabica coffee breeding programs.

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Main Authors: SUELA, M. M., AZEVEDO, C. F., NASCIMENTO, A. C. C., MOMEN, M., OLIVEIRA, A. C. B. de, CAIXETA, E. T., MOROTA, G., NASCIMENTO, M.
Other Authors: MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; ANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MEHDI MOMEN, UNIVERSITY OF WISCONSIN-MADISON; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; GOTA MOROTA, VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY; MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA.
Format: Artigo de periódico biblioteca
Language:Ingles
English
Published: 2023-11-06
Subjects:Structural equation modeling, Genome-wide association study, Single nucleotide polymorphism, Coffea arabica var. arabica,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157822
https://doi.org/10.1007/s11295-023-01597-8
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spelling dig-alice-doc-11578222023-11-06T18:31:29Z Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models. SUELA, M. M. AZEVEDO, C. F. NASCIMENTO, A. C. C. MOMEN, M. OLIVEIRA, A. C. B. de CAIXETA, E. T. MOROTA, G. NASCIMENTO, M. MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; ANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MEHDI MOMEN, UNIVERSITY OF WISCONSIN-MADISON; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; GOTA MOROTA, VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY; MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA. Structural equation modeling Genome-wide association study Single nucleotide polymorphism Coffea arabica var. arabica Yield is one of the most important traits of arabica coffee. Plant breeders seek to maximize yield directly or indirectly, using other related traits. The standard multi-trait genome-wide association study (MTM-GWAS) does not accommodate the network structure of phenotypes, therefore, does not address how traits are interrelated. We applied structural equation modeling (SEM) to GWAS to explore interrelated dependencies between phenotypes related to morphology (fruit size and number of reproductive nodes), physiology (vegetative vigor), and productivity (yield) traits using 195 Coffea arábica individuals genotyped with 21,211 single-nucleotide polymorphism markers. We inferred the probabilistic phenotypic network by the Hill-Climbing algorithm to estimate the structural coefficients. The integration of multivariate GWAS and SEM (SEM-GWAS) identified a positive interrelationship between vegetative vigor and yield, and vegetative vigor and the number of reproductive nodes. Among those traits, yield and number of reproductive nodes presented indirect SNP effects. There was no evidence of a single quantitative trait locus controlling all the traits jointly. We identified three genes (Stress enhanced protein 1, Abscisic stress-ripening protein 5, and SAR?SNI1) that acted directly on yield. In summary, SEM-GWAS offered new insights into the relationship between the traits linked to coffee yield, providing useful information for arabica coffee breeding programs. 2023-11-06T18:31:29Z 2023-11-06T18:31:29Z 2023-11-06 2023 Artigo de periódico Tree Genetics & Genomes, v. 19, n. 3, 2023. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157822 https://doi.org/10.1007/s11295-023-01597-8 Ingles en openAccess 17 p.
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language Ingles
English
topic Structural equation modeling
Genome-wide association study
Single nucleotide polymorphism
Coffea arabica var. arabica
Structural equation modeling
Genome-wide association study
Single nucleotide polymorphism
Coffea arabica var. arabica
spellingShingle Structural equation modeling
Genome-wide association study
Single nucleotide polymorphism
Coffea arabica var. arabica
Structural equation modeling
Genome-wide association study
Single nucleotide polymorphism
Coffea arabica var. arabica
SUELA, M. M.
AZEVEDO, C. F.
NASCIMENTO, A. C. C.
MOMEN, M.
OLIVEIRA, A. C. B. de
CAIXETA, E. T.
MOROTA, G.
NASCIMENTO, M.
Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
description Yield is one of the most important traits of arabica coffee. Plant breeders seek to maximize yield directly or indirectly, using other related traits. The standard multi-trait genome-wide association study (MTM-GWAS) does not accommodate the network structure of phenotypes, therefore, does not address how traits are interrelated. We applied structural equation modeling (SEM) to GWAS to explore interrelated dependencies between phenotypes related to morphology (fruit size and number of reproductive nodes), physiology (vegetative vigor), and productivity (yield) traits using 195 Coffea arábica individuals genotyped with 21,211 single-nucleotide polymorphism markers. We inferred the probabilistic phenotypic network by the Hill-Climbing algorithm to estimate the structural coefficients. The integration of multivariate GWAS and SEM (SEM-GWAS) identified a positive interrelationship between vegetative vigor and yield, and vegetative vigor and the number of reproductive nodes. Among those traits, yield and number of reproductive nodes presented indirect SNP effects. There was no evidence of a single quantitative trait locus controlling all the traits jointly. We identified three genes (Stress enhanced protein 1, Abscisic stress-ripening protein 5, and SAR?SNI1) that acted directly on yield. In summary, SEM-GWAS offered new insights into the relationship between the traits linked to coffee yield, providing useful information for arabica coffee breeding programs.
author2 MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; ANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MEHDI MOMEN, UNIVERSITY OF WISCONSIN-MADISON; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; GOTA MOROTA, VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY; MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA.
author_facet MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; ANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MEHDI MOMEN, UNIVERSITY OF WISCONSIN-MADISON; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; GOTA MOROTA, VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY; MOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA.
SUELA, M. M.
AZEVEDO, C. F.
NASCIMENTO, A. C. C.
MOMEN, M.
OLIVEIRA, A. C. B. de
CAIXETA, E. T.
MOROTA, G.
NASCIMENTO, M.
format Artigo de periódico
topic_facet Structural equation modeling
Genome-wide association study
Single nucleotide polymorphism
Coffea arabica var. arabica
author SUELA, M. M.
AZEVEDO, C. F.
NASCIMENTO, A. C. C.
MOMEN, M.
OLIVEIRA, A. C. B. de
CAIXETA, E. T.
MOROTA, G.
NASCIMENTO, M.
author_sort SUELA, M. M.
title Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
title_short Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
title_full Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
title_fullStr Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
title_full_unstemmed Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models.
title_sort genome-wide association study for morphological, physiological, and productive traits in coffea arabica using structural equation models.
publishDate 2023-11-06
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157822
https://doi.org/10.1007/s11295-023-01597-8
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