Estudo de associação genômica ampla aplicada ao conteúdo de macronutrientes em grãos de Coffea arabica L.
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Data
2020-04-02
Autores
Felicio, Mariane Silva
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Universidade Estadual Paulista (Unesp)
Resumo
O café é uma das commodities agrícolas tropicais mais comercializadas no mundo. Coffea arabica é a principal espécie utilizada para a produção comercial de café. A espécie é originária da Etiópia. Ela é única espécie alotetraploide do gênero (2n = 4x = 44) e se reproduz predominantemente por autofecundação. As cultivares comerciais de C. arabica possuem baixa diversidade genética, o que indica a necessidade de introgressão de alelos de germoplasma para o melhoramento dessas cultivares. Acessos do centro de origem da espécie possuem maior diversidade que as cultivares comerciais e podem ser utilizados para a identificação de novos alelos. O conteúdo de macronutrientes em grãos do cafeeiro tem impacto direto na qualidade do produto. No entanto, a base molecular da composição mineral de grãos de cafeeiro ainda é pouco conhecida. Com isso, o objetivo desse trabalho foi identificar marcadores SNP possivelmente associados com a composição de macronutrientes em grãos de C. arabica. Para alcance deste objetivo, foram comparados três métodos de imputação de genótipos, bem como foi realizado o mapeamento associativo em estudo de associação genômica ampla (GWAS). Foi utilizado um painel de 110 genótipos de C. arabica, composto por genótipos elite do programa de melhoramento do Instituto Agronômico do Paraná (3), cultivares comerciais (11) e acessos selvagens (96). Foram realizadas análises da composição de cinco macronutrientes (N, P, K, Ca e Mg) em grãos de cafeeiro coletados de 70 e 105 genótipos de C. arabica nos anos de 2017 e 2018, respectivamente. Foram calculados valores de BLUP para 65 genótipos, para os quais foram realizadas coletas nos dois anos. Foi identificado que os acessos selvagens de C. arabica possuem maior variabilidade genética e de composição de macronutrientes nos grãos que as cultivares comerciais. Foram identificados mais marcadores SNPs quando o mapeamento dos dados de GBS foi realizado com o genoma de referência da cultivar Caturra (11.230 SNPs) do que com o diaploide Et39 (9.991 SNPs). O método Beagle apresentou o melhor desempenho para a imputação dos painéis de marcadores e a imputação contribuiu para reduzir a taxa de associações espúrias identificadas nas análises de GWAS. Foram identificados 5, 12, 13, 6, 6 e 1 marcadores em regiões codificantes associados a composição de N, P, K, Ca, Mg, Mg e K em grãos de C. arabica, respectivamente. As regiões genômicas identificadas foram relacionadas a diversas rotas metabólicas em plantas, incluindo o transporte de nutrientes, a germinação de sementes, o controle da época de florescimento e algumas vias de resposta a estresses bióticos e abióticos. As proteínas identificadas nesse trabalho podem ser utilizadas como alvos em futuros estudos para a caracterização de vias metabólicas que atuam no controle do acúmulo de macronutrientes em plantas da espécie C. arabica. Além disso, os genótipos selvagens de C. arabica utilizados nesse trabalho podem ser utilizados para identificação de alelos favoráveis a serem introduzidos em cultivares comerciais.
Coffee is one of the most traded tropical commodities in the world. Coffea arabica is the main species used for commercial production. The species is originally from Ethiopia. In the Coffea genus, C. arabica is the only allotetraploid species (2n = 4x = 44) and it reproduces predominantly by self-fertilization. The commercial cultivars of C. arabica have a narrow genetic base that indicates the need for the introgression of new alleles from germplasm into coffee breeding programs. Wild accessions of C. arabica, from Ethiopia, have higher genetic diversity and can be used to identify new alleles. The macronutrient composition of the coffee grains has a direct impact on grain quality. However, the molecular basis for the mineral composition in coffee grains still poorly understood. Thus, the aim of this work was to perform mapping association analyses using the genome-wide association study (GWAS) technique to identify single nucleotide polymorphisms (SNPs) associated with macronutrient content in coffee grains from C. arabica. We also tested three imputation methods (haplotype missing allele imputation - Beagle, K-nearest neighbors, and Random Forest) in the genotypic data, and mapped it to two C. arabica reference genomes from the cultivar Caturra red and the spontaneous dihaploid Et39. We used a panel of 110 C. arabica genotypes, including elite landraces from the IAPAR coffee breeding program (3), commercial cultivars (11) and wild accessions (96). Analysis of the composition of five macronutrients (N, P, K, Ca and Mg) was carried out on coffee grains collected from 70 and 105 genotypes in the years 2017 and 2018, respectively. BLUP values were estimated for 65 genotypes in which the grains were collected in both years. Our results indicate that the C. arabica wild accessions have higher genetic variability and higher diversity for grains macronutrient content than the commercial cultivars. More SNPs markers were identified when the GBS data were mapped to the Caturra reference genome (11,230 SNPs) than to the Et39 reference genome (9,991 SNPs). Beagle presented the best performance in markers dataset imputation. The imputation reduced the false discovery rate in GWAS. We identified 5, 12, 13, 6, 6 and 1 markers in coding regions associated with the content of N, P, K, Ca, Mg, and Mg and K in coffee grains, respectively. The proteins identified participates in several metabolic pathways, including nutrient transport, seed germination, flowering time control and plant response to biotic and abiotic stresses. These proteins can be used as targets in further studies for the characterization of metabolic pathways controlling macronutrient accumulation in C. arabica plants. Also, the wild C. arabica genotypes used in this work can be used to identify favorable alleles to be introduced in commercial cultivars, and for the selection of promising genotypes with altered levels of macronutrients in their grains than the observed among C. arabica commercial cultivars.
Coffee is one of the most traded tropical commodities in the world. Coffea arabica is the main species used for commercial production. The species is originally from Ethiopia. In the Coffea genus, C. arabica is the only allotetraploid species (2n = 4x = 44) and it reproduces predominantly by self-fertilization. The commercial cultivars of C. arabica have a narrow genetic base that indicates the need for the introgression of new alleles from germplasm into coffee breeding programs. Wild accessions of C. arabica, from Ethiopia, have higher genetic diversity and can be used to identify new alleles. The macronutrient composition of the coffee grains has a direct impact on grain quality. However, the molecular basis for the mineral composition in coffee grains still poorly understood. Thus, the aim of this work was to perform mapping association analyses using the genome-wide association study (GWAS) technique to identify single nucleotide polymorphisms (SNPs) associated with macronutrient content in coffee grains from C. arabica. We also tested three imputation methods (haplotype missing allele imputation - Beagle, K-nearest neighbors, and Random Forest) in the genotypic data, and mapped it to two C. arabica reference genomes from the cultivar Caturra red and the spontaneous dihaploid Et39. We used a panel of 110 C. arabica genotypes, including elite landraces from the IAPAR coffee breeding program (3), commercial cultivars (11) and wild accessions (96). Analysis of the composition of five macronutrients (N, P, K, Ca and Mg) was carried out on coffee grains collected from 70 and 105 genotypes in the years 2017 and 2018, respectively. BLUP values were estimated for 65 genotypes in which the grains were collected in both years. Our results indicate that the C. arabica wild accessions have higher genetic variability and higher diversity for grains macronutrient content than the commercial cultivars. More SNPs markers were identified when the GBS data were mapped to the Caturra reference genome (11,230 SNPs) than to the Et39 reference genome (9,991 SNPs). Beagle presented the best performance in markers dataset imputation. The imputation reduced the false discovery rate in GWAS. We identified 5, 12, 13, 6, 6 and 1 markers in coding regions associated with the content of N, P, K, Ca, Mg, and Mg and K in coffee grains, respectively. The proteins identified participates in several metabolic pathways, including nutrient transport, seed germination, flowering time control and plant response to biotic and abiotic stresses. These proteins can be used as targets in further studies for the characterization of metabolic pathways controlling macronutrient accumulation in C. arabica plants. Also, the wild C. arabica genotypes used in this work can be used to identify favorable alleles to be introduced in commercial cultivars, and for the selection of promising genotypes with altered levels of macronutrients in their grains than the observed among C. arabica commercial cultivars.
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Palavras-chave
Imputação, Dados ausentes, Estresses bióticos e abióticos, Imputation, Missing genotypes, Non-model species, Biotic and abiotic stress, Espécies não-modelo