Monik Evelin Leite

Seleção de famílias de feijoeiro baseada na produtividade, no tipo de grãos e informações de QTLs

Objetivou-se neste trabalho, selecionar familias de feijoeiro promissoras para a produtividade de graos com tipo de graos ideal utilizando informacoes fenotipicas e de marcadores moleculares ligados a QTLs. Foram utilizadas 100 familias F3:7, avaliadas em tres safras, com dois experimentos/safra, totalizando seis experimentos. A primeira safra foi a da seca/2007, na qual conduziu-se um experimento em Lavras-MG e o outro em Ijaci-MG. Nas safras de inverno/2007 e aguas 2007/2008, foram conduzidos, em cada uma, um experimento em Lavras-MG e outro em Lambari-MG. Em todos eles foi utilizado o delineamento latice triplo 10x10, com parcelas de duas linhas de dois metros. As familias foram avaliadas pela sua produtividade de graos. Em apenas um dos experimentos de cada safra foi avaliado o tipo de grao. Os dados foram submetidos a analise de variância individual e conjunta, por local e por safra. 480 marcadores microssatelites foram testados para identificar polimorfismo entre os genitores. Os oito marcadores polimorficos identificados foram utilizados para a genotipagem das familias. Entre esses, cinco explicaram parte da variacao da produtividade de graos. Os marcadores explicaram pequena porcentagem da variacao fenotipica e apresentaram alta interacao QTLs x ambientes. O ganho com a selecao fenotipica para produtividade de graos foi de 7,4%, e de 9,6% para tipo de graos, adotando a intensidade de selecao de 5%. A selecao assistida por marcadores foi equivalente a fenotipica para produtividade de graos, porque apenas um marcador mais estavel contribuiu para a selecao com base na media dos ambientes.

Seleção assistida por marcadores para teor de matéria seca e açúcares redutores em tubérculos de batata

Early generation selection for clones with high content of tuber dry matter and low levels of reducing sugars is required for potato (Solanum tuberosum L.) processing. Selection of superior clones at early generations became possible with the deployment of genetic markers, and can precisely identify the superior individuals. Therefore, it is necessary to identify genetic markers closely linked to genes of interest to do assisted selection. The aim of this research was to evaluate the efficiency of marker assisted selection with genetic markers previously identified by ANDREU (2004), which are assumed to be associated with dry matter and reducing sugars content in potato tubers. Clones from 20 families were evaluated during the seedling generation (S), first clonal generation (C1) and second clonal generation (C2). The estimated coefficients of correlation for all traits among generations were significant, even though of low magnitude, confirming that selection at early generation based only on phenotypic traits is inviable. A total of sixteen bands were amplified using these markers. However, by multiple stepwise regression, only seven of these bands showed association with the evaluated traits. Moreover, no markers associated with dry matter and reducing sugars content in the C1 were significantly associated with these traits in the C2, suggesting the existence of QTLs x environment interactions. The marker assisted selection resulted less efficient than the phenotypic selection in all cases studied, and thus is not recommended for early generation selection of clones for the processing industry. These results suggest that the markers used are not closely linked to the genes controlling the traits most important for processing. Therefore, it is important to identify new markers closely linked with such traits of interest that could improve the efficiency of marker assisted selection.

Increasing the resistance of common bean to white mold through recurrent selection

White mold, caused by Sclerotinea sclerotiorum (Lib.) de Bary is one of the most important diseases of the common bean (Phaseolus vulgaris L.) worldwide. Physiological resistance and traits related to disease avoidance such as architecture contribute to field resistance. The aim of this study was to verify the efficiency of recurrent selection in physiological resistance to white mold, “Carioca” grain type and upright habit in common bean. Thirteen common bean lines with partial resistance to white mold were intercrossed by means of a circulant diallel table, and seven recurrent selection cycles were obtained. Of these cycles, progenies of the S0:1, S0:2 and S0:3 generations of cycles III, IV, V and VI were evaluated. The best (8 to 10) progenies of the seven cycles were also evaluated, in two experiments, one in the greenhouse and one in the field. Lattice and/or randomized block experimental designs were used. The traits evaluated were: resistance to white mold by the straw test method, growth habit and grain type. The most resistant progenies were selected based on the average score of resistance to white mold. Subsequently, they were evaluated with regard to grain type and growth habit. Recurrent selection allowed for genetic progress of about 11 % per year for white mold resistance and about 15 % per year for the plant architecture. There was no gain among cycles for grain type. Progeny selection and recurrent selection were efficient for obtaining progenies with a high level of resistance to white mold with “Carioca” grain type and upright habit.

Identification of QTLs for Resistance to Sclerotinia sclerotiorum in Carioca Common Bean by the Moving Away Method.

The aim of this study was to use multiple DNA markers for detection of QTLs related to resistance to white mold in an F2 population of common bean evaluated by the straw test method. The DNA from 186 F2 plants and from the parents was extracted for genotypic evaluation using SSR, AFLP, and SRAP markers. For phenotypic analysis, 186 F2:4 progenies and ten lines were evaluated, in a 14 × 14 triple lattice experimental design. The adjusted mean values of the F2:4 progenies were used for identification of QTLs by Bayesian shrinkage analysis. Significant differences were observed among the progenies for reaction to white mold. In identification of QTLs, 17 markers identified QTLs for resistance—13 SSRs and 4 AFLPs. The moving away method under the Bayesian approach proved to be efficient in the identification of QTLs when a genetic map is not used due to the low density of markers. The ME1 and BM211 markers are near the QTLs, with the effect of increasing resistance to white mold, and they have high heritability. They are thus promising for marker-assisted selection.