A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers

The development of sugarcane as a sustainable crop has unlimited applications. The crop is one of the most economically viable for renewable energy production, and CO2 balance. Linkage maps are valuable tools for understanding genetic and genomic organization, particularly in sugarcane due to its complex polyploid genome of multispecific origins. The overall objective of our study was to construct a novel sugarcane linkage map, compiling AFLP and EST-SSR markers, and to generate data on the distribution of markers anchored to sequences of scIvana_1, a complete sugarcane transposable element, and member of the Copia superfamily. The mapping population parents (‘IAC66-6’ and ‘TUC71-7’) contributed equally to polymorphisms, independent of marker type, and generated markers that were distributed into nearly the same number of co-segregation groups (or CGs). Bi-parentally inherited alleles provided the integration of 19 CGs. The marker number per CG ranged from two to 39. The total map length was 4,843.19 cM, with a marker density of 8.87 cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72 cM, with an estimated average length of 52.64 cM. The greatest distance between two adjacent markers was 48.25 cM. The scIvana_1-based markers (56) were positioned on 21 CGs, but were not regularly distributed. Interestingly, the distance between adjacent scIvana_1-based markers was less than 5 cM, and was observed on five CGs, suggesting a clustered organization. Results indicated the use of a NBS-profiling technique was efficient to develop retrotransposon-based markers in sugarcane. The simultaneous maximum-likelihood estimates of linkage and linkage phase based strategies confirmed the suitability of its approach to estimate linkage, and construct the linkage map. Interestingly, using our genetic data it was possible to calculate the number of retrotransposon scIvana_1 (~60) copies in the sugarcane genome, confirming previously reported molecular results. In addition, this research possibly will have indirect implications in crop economics e.g., productivity enhancement via QTL studies, as the mapping population parents differ in response to an important fungal disease13CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPnão temnão tem2010/51708-

Genetic diversity in cultivated carioca common beans based on molecular marker analysis

A wide array of molecular markers has been used to investigate the genetic diversity among common bean species. However, the best combination of markers for studying such diversity among common bean cultivars has yet to be determined. Few reports have examined the genetic diversity of the carioca bean, commercially one of the most important common beans in Brazil. In this study, we examined the usefulness of two molecular marker systems (simple sequence repeats – SSRs and amplified fragment length polymorphisms – AFLPs) for assessing the genetic diversity of carioca beans. The amount of information provided by Roger’s modified genetic distance was used to analyze SSR data and Jaccards similarity coefficient was used for AFLP data. Seventy SSRs were polymorphic and 20 AFLP primer combinations produced 635 polymorphic bands. Molecular analysis showed that carioca genotypes were quite diverse. AFLPs revealed greater genetic differentiation and variation within the carioca genotypes (Gst = 98% and Fst = 0.83, respectively) than SSRs and provided better resolution for clustering the carioca genotypes. SSRs and AFLPs were both suitable for assessing the genetic diversity of Brazilian carioca genotypes since the number of markers used in each system provided a low coefficient of variation. However, fingerprint profiles were generated faster with AFLPs, making them a better choice for assessing genetic diversity in the carioca germplasm

Development and application of genétic model for QTL mapping in a full sib family

A cana-de-açúcar é uma espécie de elevada importância econômica, uma vez que o país é o maior produtor mundial desta cultura. Atualmente, recebe importância maior devido as questões econômico-ambientais geradas pelo seu principal produto, o etanol. Neste contexto, há um cenário de potencial crescimento para cultura, em que o melhoramento genético pode contribuir com o desenvolvimento de cultivares mais produtivos e eficientes para diversas condições de cultivo. Os programas de melhoramento genético poderiam utilizar as informações obtidas com o mapeamento de QTLs para tornarem-se mais eficientes. Para tanto, faz-se necessário o desenvolvimento de abordagem que permita o mapeamento de QTLs em cana-de-açúcar com maior precisão. Os modelos genéticos-estatisticos desenvolvidos para o mapeamento de QTLs, normalmente são baseados em populações experimentais originárias de linhagens endogâmicas e espécies diplóides. No entanto, para espécies como cana-de-açúcar, eucalipto, maracujá, a obtenção deste tipo de material é impraticável pela alta depressão por endogamia existente. Dessa forma, estudos de mapeamento são conduzidos com uso de progênies de irmãos completos, normalmente fazendo adaptações para que as metodologias existentes possam ser usadas, o que induz a várias desvantagens. Assim, o trabalho apresentou dois objetivos: i) desenvolvimento de uma abordagem para mapeamento de QTLs em progênies de irmãos completos, utilizando mapa integrado e mapeamento por intervalo composto. ii) aplicação do presente modelo em caracteres relacionados a produtividade em cana-de-açúcar. Verificou-se que o novo modelo foi superior as abordagens já existentes na literatura, pois em estudos de simulação os QTLs foram detectados com maior poder estatístico e também com maior precisão. A aplicação do modelo em dados de cana-de-açúcar permitiu a identificação de maior número de QTLs do que a abordagem comumente utilizada para esta cultura. O maior poder estatístico desta metodologia contribuiu diretamente para detecção de novas regiões que apresentam associação com caracteres de produção. Vale destacar que o modelo detectou QTLs com diferentes padrões de segregação, além de indicar a provável existência de QTLs que se expressam ao longo dos cortes.Sugarcane has great economic importance to Brazil, which is worlds largest producer. Currently, sugarcane receives worldwide attention due to the economic and environmental issues generated by its main product, ethanol. In this context, there is a scenario of potential growth for the culture, in which breeding can contribute to the development of new cultivars, more productive and effective to explore environmental conditions. Breeding programs could use the information obtained form QTL mapping to become more efficient. Thus, it is necessary to develop new statistical methods that allow QTL mapping in sugarcane with more precision. Statistical models developed for QTL mapping are usually based on experimental populations obtained from inbred lines. However, for species such as sugarcane, eucalyptus, passion fruit, inbred lines are not avaliable and then and mapping studies are conducted using full-sib families, usually making adaptations to existing methodologies, leading to several disadvantages since the assumptions are usually unrealist. This work had two objectives: i) develop an approach for mapping QTLs in full-sibs, using integrated map and compositive interval mapping. ii) use this model to map QTL for traits related to productivity in sugarcane. Results showed that the new model provided better results then existing approaches in literature. In simulation studies, all QTL were detected with more statistical power and precision. The application of the model on data from sugarcane has allowed the identification of more QTLs than single marker analysis, which is commonly used. The statistical power contributed to detection of new regions were associated with variation of quantitative traits. The model also detected QTLs with different patterns of segregation, as well as QTL expressed across harvests