Biblioteca do Café
URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/1
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Resultados da Pesquisa
Item Single-locus inheritance and partial linkage map of Coffea arabica L.(Crop Breeding and Applied Biotechnology, 2004) Sakiyama, Ney Sussumu; Teixeira-Cabral, Terezinha Aparecida; Zambolim, Laércio; Pereira, Antonio Alves; Schuster, IvanIn a backcross population of the allotetraploid Coffea arabica L. the loci with diploid-like segregation were predominant, although a few loci with tetrassomic inheritance or distortion of the expected segregation were also observed. A partial genetic map of Coffea arabica L. was constructed with 82 RAPD loci scored in this backcross population of 104 individuals. It covered the estimated length of 540.6 cM in eight linkage groups. The linkage group size was highly correlated with the number of markers, indicating random distribution of the markers in the groups. The average distance between two markers was 7.3 cM.Item Reproducibility of the RAPD marker and its efficiency in coffee tree genotype grouping analysis(Crop Breeding and Applied Biotechnology, 2002) Sakiyama, Ney Sussumu; Teixeira-Cabral, Terezinha Aparecida; Zambolim, Laércio; Pereira, Antonio Alves; Barros, Everaldo Gonçalves; Sakiyama, Cássia Camargo HargerThe genetic diversity of Coffea arabic L. cultivars is relatively narrow and its assessment and increase is important for breeding. Fifty two arbitrary primers were used to evaluate the reproducibility and the influence of the number of RAPD (Random Amplified Polymorphic DNA) markers on the estimation of genetic distances among 40 genotypes of Coffea spp. The average number of polymorphic bands was 6.69 per primer among all genotypes, and 1.27 among arabica coffee genotypes. RAPD markers were efficient in estimating the genetic distances among the genotypes. The increase in RAPD loci number during grouping analysis did not affect the major groups’ composition; however, it affected the composition of subgroups. Marker reproducibility was 76.88% and replicated data was recommended for distinguishing genotypes with the same genetic background.Item Polymorphic information content of SSR markers for Coffea spp.(Crop Breeding and Applied Biotechnology, 2010) Caixeta, Eveline Teixera; Missio, Robson Fernando; Zambolim, Eunize Maciel; Zambolim, Laércio; Cruz, Cosme Damião; Sakiyama, Ney SussumuThirty-three coffee SSR primers from enriched genomic library with (GT)15 and (AGG)10 repeats were analyzed in 24 coffee tree accessions. Twenty-two primers were polymorphic among accessions; the number of alleles ranged from 2 to 13, with the mean number of 5.1 alleles per primer. PIC values ranged from 0.08 to 0.79. The highest mean PIC values were found for C. canephora (0.46), and the lowest values for C. arabica (0.22) and triploids (0.22) accessions. The polymorphic SSR markers used in this study were useful for genetic fingerprinting in the coffee tree, especially in the C. canephora and the leaf rust resistant arabica cultivars.Item Grafted young coffee tree growth in a greenhouse(Crop Breeding and Applied Biotechnology, 2002) Sakiyama, Ney Sussumu; Tomaz, Marcelo Antonio; Martinez, Hermínia Emília Pietro; Pereira, Antonio Alves; Zambolim, Laércio; Cruz, Cosme DamiãoGrafted young coffee trees were observed in a greenhouse to study the effect of different scions and rootstocks on plant growth. Four Coffea arabica L. genotypes were used as scions: the cultivars Catuaí Vermelho IAC 15 and Oeiras MG 6851, and the progenies H 419-10-3-1-5 and H 514-5-5-3. They were also used as nongrafted control plants. Four genotypes were used as rootstocks: ‘Apoatã IAC 2258’ (C. canephora), ‘Conillon’ (C. canephora), ‘Emcapa 8141’ (C. canephora), and ‘Mundo Novo IAC 376-4’ (C. arabica). ‘Mundo Novo IAC 376-4’ and ‘Apoatã IAC 2258’ were classified as good rootstocks, while ‘Oeiras MG 6851’ and “H 419- 10-3-1-5” performed well as non-grafted plants. The diallel analysis statistical model was efficient to evaluate the general combination ability of the rootstocks and, therefore, recommended for rootstock selection procedures in breeding programs.Item Characterization of differential coffee tree hostsfor Hemileia vastatrix Berk. et Br. with RAPD markers(Crop Breeding and Applied Biotechnology, 2004-03-12) Teixeira-Cabral, Terezinha Aparecida; Sakiyama, Ney Sussumu; Zambolim, Laércio; Barros, Everaldo Gonçalves de; Silva, Dalza Gomes daEighteen clones of differential coffee tree hosts for Hemileia vastatrix Berk. et Br. were characterized with RAPD markers. The genetic distances were estimated and the genealogical origin of the clones compared to data of markerbased clusters. Thirty-five primers identified 158 polymorphic loci of RAPD markers. The cluster based on the matrix of genetic dissimilarity values was compatible with information on the genealogical origin cited in literature. Specific markers for a number of clones were identified, and a combination of 12 RAPD markers allowed the characterization of the studied clones.Item Analysis of AFLP markers associated to the Mex-1 resistance locus in Icatu progenies(Crop Breeding and Applied Biotechnology, 2005-09-06) Diniz, Leandro E C; Sakiyama, Ney S; Caixeta, Eveline T; Oliveira, Antonio Carlos B de; Zambolim, Eunize M; Loureiro, Marcelo E; Pereira, Antonio A; Zambolim, LaércioThe root-knot nematode Meloidogyne exigua is a parasite which attacks the Arabica coffee tree (Coffea sp.) and its eradication from infested areas is practically impossible. The wide dissemination of this nematode across coffee plantations in the south of the state of Minas Gerais has been causing great damage to the coffee producers of the area. Previous studies showed that the simple inheritance gene present in C. canephora, designated Mex-1, controls M. exigua resistance. Some genetic breeding programs have developed resistant Arabica coffee lines through the introgression of this gene. To confirm the introgression, twenty-one Icatu lines were analyzed and compared to two resistant (“Iapar 59” and “Híbrido de Timor”) and one susceptible cultivar (Catuaí). Among the AFLP markers used, five confirmed the presence of the introgressed fragment associated to Mex-1 resistance, showing that this marker can be used in marker-assisted selection.Item Partial map of Coffea arabica L. and recovery of the recurrent parent in backcross progenies(Crop Breeding and Applied Biotechnology, 2007-06-30) Oliveira, Antonio Carlos Baião de; Sakiyama, Ney Sussumu; Caixeta, Eveline Teixeira; Zambolim, Eunize Maciel; Rufino, Raphael José Nascif; Zambolim, LaércioA partial map of Coffea arabica L. was constructed based on a backcross population and RAPD markers. From a total of 178 markers evaluated, only 134 that segregated 1:1 (P>0.05) were used to develop the map. Seventeen markers were not linked, while 117 formed 11 linkage groups, covering a genome distance of 803.2 cM. The maximum distance between adjacent markers was 26.9 cM, and only seven intervals exceeded 20 cM. The markers were further used for assisted selection of the plants closest to the recurrent parent, to accelerate the introgression of rust resistance genes in the coffee breeding program. Three BC1 plants resistant to coffee leaf rust and with high genetic similarity to ?Catuaí? were selected and integrated in the following backcross cycles.Item In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases(Sociedade Brasileira de Genética, 2010) Alvarenga, Samuel Mazzinghy; Caixeta, Eveline Teixeira; Hufnagel, Bárbara; Thiebaut, Flávia; Maciel-Zambolim, Eunize; Zambolim, Laércio; Sakiyama, Ney SussumuSequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and plant defense responses to diseases. The 140 EST-contigs identified through the keyword NBS-LRR were classified according to function. This classification allowed association of the predicted products of EST-contigs with biological processes, including host defense and apoptosis, and with molecular functions such as nucleotide binding and signal transducer activity. Fisher’s exact test was used to examine the significance of differences in contig expression between libraries representing the responses to biotic stress challenges and other libraries from the BCGP. This analysis revealed seven contigs highly similar to catalase, chitinase, protein with a BURP domain and unknown proteins. The involvement of these coffee proteins in plant responses to disease is discussed.Item Receptor-Like Kinase (RLK) as a candidate gene conferring resistance to Hemileia vastatrix in coffee(Escola Superior de Agricultura "Luiz de Queiroz", 2021) Almeida, Dênia Pires de; Castro, Isabel Samila Lima; Mendes, Tiago Antônio de Oliveira; Alves, Danúbia Rodrigues; Barka, Geleta Dugassa; Barreiros, Pedro Ricardo Rossi Marques; Zambolim, Laércio; Sakiyama, Ney Sussumu; Caixeta, Eveline TeixeiraThe biotrophic fungus Hemileia vastatrix causes coffee leaf rust (CLR), one of the most devastating diseases in Coffea arabica. Coffee, like other plants, has developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs) have been identified in certain plants as candidates for resistance (R) genes or membrane receptors that activate the R genes. The RGAs identified in different plants possess conserved domains that play specific roles in the fight against pathogens. Despite the importance of RGAs, in coffee plants these genes and other molecular mechanisms of disease resistance are still unknown. This study aimed to sequence and characterize candidate genes from coffee plants with the potential for involvement in resistance to H. vastatrix. Sequencing was performed based on a library of bacterial artificial chromosomes (BAC) of the coffee clone ‘Híbrido de Timor’ (HdT) CIFC 832/2 and screened using a functional marker. Two RGAs, HdT_ LRR_RLK1 and HdT_LRR_RLK2, containing the motif of leucine-rich repeat-like kinase (LRR-RLK) were identified. Based on the presence or absence of the HdT_LRR_RLK2 RGA in a number of differential coffee clones containing different combinations of the rust resistance gene, these RGAs did not correspond to any resistance gene already characterized (SH1-9). These genes were also analyzed using qPCR and demonstrated a major expression peak at 24 h after inoculation in both the compatible and incompatible interactions between coffee and H. vastatrix. These results are valuable information for breeding programs aimed at developing CLR-resistant cultivars, in addition to enabling a better understanding of the interactions between coffee and H. vastatrix.Item Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms(Escola Superior de Agricultura "Luiz de Queiroz", 2021) Sousa, Ithalo Coelho de; Nascimento, Moysés; Silva, Gabi Nunes; Nascimento, Ana Carolina Campana; Cruz, Cosme Damião; Silva, Fabyano Fonseca e; Almeida, Dênia Pires de; Pestana, Kátia Nogueira; Azevedo, Camila Ferreira; Zambolim, Laércio; Caixeta, Eveline TeixeiraGenomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such methodologies require certain assumptions about the data, such as the normality of the distribution of phenotypic values. To circumvent the non-normality of phenotypic values, the literature suggests the use of Bayesian Generalized Linear Regression (GBLASSO). Another alternative is the models based on machine learning, represented by methodologies such as Artificial Neural Networks (ANN), Decision Trees (DT) and related possible refinements such as Bagging, Random Forest and Boosting. This study aimed to use DT and its refinements for predicting resistance to orange rust in Arabica coffee. Additionally, DT and its refinements were used to identify the importance of markers related to the characteristic of interest. The results were compared with those from GBLASSO and ANN. Data on coffee rust resistance of 245 Arabica coffee plants genotyped for 137 markers were used. The DT refinements presented equal or inferior values of Apparent Error Rate compared to those obtained by DT, GBLASSO, and ANN. Moreover, DT refinements were able to identify important markers for the characteristic of interest. Out of 14 of the most important markers analyzed in each methodology, 9.3 markers on average were in regions of quantitative trait loci (QTLs) related to resistance to disease listed in the literature.
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