Marcelo Mollinari

Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences

Managed environments in the form of well watered and water stressed trials were performed to study the genetic basis of grain yield and stay green in sorghum with the objective of validating previously detected QTL. As variations in phenology and plant height may influence QTL detection for the target traits, QTL for flowering time and plant height were introduced as cofactors in QTL analyses for yield and stay green. All but one of the flowering time QTL were detected near yield and stay green QTL. Similar co-localization was observed for two plant height QTL. QTL analysis for yield, using flowering time/plant height cofactors, led to yield QTL on chromosomes 2, 3, 6, 8 and 10. For stay green, QTL on chromosomes 3, 4, 8 and 10 were not related to differences in flowering time/plant height. The physical positions for markers in QTL regions projected on the sorghum genome suggest that the previously detected plant height QTL, Sb-HT9-1, and Dw2, in addition to the maturity gene, Ma5, had a major confounding impact on the expression of yield and stay green QTL. Co-localization between an apparently novel stay green QTL and a yield QTL on chromosome 3 suggests there is potential for indirect selection based on stay green to improve drought tolerance in sorghum. Our QTL study was carried out with a moderately sized population and spanned a limited geographic range, but still the results strongly emphasize the necessity of corrections for phenology in QTL mapping for drought tolerance traits in sorghum.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12xa0years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

SNP genotyping allows an in-depth characterisation of the genome of sugarcane and other complex autopolyploids

Many plant species of great economic value (e.g., potato, wheat, cotton, and sugarcane) are polyploids. Despite the essential roles of autopolyploid plants in human activities, our genetic understanding of these species is still poor. Recent progress in instrumentation and biochemical manipulation has led to the accumulation of an incredible amount of genomic data. In this study, we demonstrate for the first time a successful genetic analysis in a highly polyploid genome (sugarcane) by the quantitative analysis of single-nucleotide polymorphism (SNP) allelic dosage and the application of a new data analysis framework. This study provides a better understanding of autopolyploid genomic structure and is a sound basis for genetic studies. The proposed methods can be employed to analyse the genome of any autopolyploid and will permit the future development of high-quality genetic maps to assist in the assembly of reference genome sequences for polyploid species.

Efficient Exact Maximum a Posteriori Computation for Bayesian SNP Genotyping in Polyploids

The problem of genotyping polyploids is extremely important for the creation of genetic maps and assembly of complex plant genomes. Despite its significance, polyploid genotyping still remains largely unsolved and suffers from a lack of statistical formality. In this paper a graphical Bayesian model for SNP genotyping data is introduced. This model can infer genotypes even when the ploidy of the population is unknown. We also introduce an algorithm for finding the exact maximum a posteriori genotype configuration with this model. This algorithm is implemented in a freely available web-based software package SuperMASSA. We demonstrate the utility, efficiency, and flexibility of the model and algorithm by applying them to two different platforms, each of which is applied to a polyploid data set: Illumina GoldenGate data from potato and Sequenom MassARRAY data from sugarcane. Our method achieves state-of-the-art performance on both data sets and can be trivially adapted to use models that utilize prior information about any platform or species.

The Biotechnology Roadmap for Sugarcane Improvement

Due to the strategic importance of sugarcane to Brazil, FAPESP, the main São Paulo state research funding agency, launched in 2008 the FAPESP Bioenergy Research Program (BIOEN, http://bioenfapesp.org). BIOEN aims to generate new knowledge and human resources for the improvement of the sugarcane and ethanol industry. As part of the BIOEN program, a Workshop on Sugarcane Improvement was held on March 18th and 19th 2009 in São Paulo, Brazil. The aim of the workshop was to explore present and future challenges for sugarcane improvement and its use as a sustainable bioenergy and biomaterial feedstock. The workshop was divided in four sections that represent important challenges for sugarcane improvement: a) gene discovery and sugarcane genomics, b) transgenics and controlled transgene expression, c) sugarcane physiology (photosynthesis, sucrose metabolism, and drought) and d) breeding and statistical genetics. This report summarizes the roadmap for the improvement of sugarcane.

Functional markers for gene mapping and genetic diversity studies in sugarcane.

BackgroundThe database of sugarcane expressed sequence tags (EST) offers a great opportunity for developing molecular markers that are directly associated with important agronomic traits. The development of new EST-SSR markers represents an important tool for genetic analysis. In sugarcane breeding programs, functional markers can be used to accelerate the process and select important agronomic traits, especially in the mapping of quantitative traits loci (QTL) and plant resistant pathogens or qualitative resistance loci (QRL). The aim of this work was to develop new simple sequence repeat (SSR) markers in sugarcane using the sugarcane expressed sequence tag (SUCEST database).FindingsA total of 365 EST-SSR molecular markers with trinucleotide motifs were developed and evaluated in a collection of 18 genotypes of sugarcane (15 varieties and 3 species). In total, 287 of the EST-SSRs markers amplified fragments of the expected size and were polymorphic in the analyzed sugarcane varieties. The number of alleles ranged from 2-18, with an average of 6 alleles per locus, while polymorphism information content values ranged from 0.21-0.92, with an average of 0.69. The discrimination power was high for the majority of the EST-SSRs, with an average value of 0.80. Among the markers characterized in this study some have particular interest, those that are related to bacterial defense responses, generation of precursor metabolites and energy and those involved in carbohydrate metabolic process.ConclusionsThese EST-SSR markers presented in this work can be efficiently used for genetic mapping studies of segregating sugarcane populations. The high Polymorphism Information Content (PIC) and Discriminant Power (DP) presented facilitate the QTL identification and marker-assisted selection due the association with functional regions of the genome became an important tool for the sugarcane breeding program.

Evaluation of algorithms used to order markers on genetic maps.

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3u2009cM between them. In all, 700 F2 populations were randomly simulated with 100 and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results.

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

BackgroundThe 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.ResultsThe 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 4,843.19u2009cM, with a marker density of 8.87u2009cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72u2009cM, with an estimated average length of 52.64u2009cM. The greatest distance between two adjacent markers was 48.25u2009cM. 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 5u2009cM, and was observed on five CGs, suggesting a clustered organization.ConclusionsResults 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 disease.

A model for quantitative trait loci mapping, linkage phase, and segregation pattern estimation for a full-sib progeny

Quantitative trait loci (QTL) mapping is an important approach for the study of the genetic architecture of quantitative traits. For perennial species, inbred lines cannot be obtained due to inbreed depression and a long juvenile period. Instead, linkage mapping can be performed by using a full-sib progeny. This creates a complex scenario because both markers and QTL alleles can have different segregation patterns as well as different linkage phases between them. We present a two-step method for QTL mapping using full-sib progeny based on composite interval mapping (i.e., interval mapping with cofactors), considering an integrated genetic map with markers with different segregation patterns and conditional probabilities obtained by a multipoint approach. The model is based on three orthogonal contrasts to estimate the additive effect (one in each parent) and dominance effect. These estimatives are obtained using the EM algorithm. In the first step, the genome is scanned to detect QTL. After, segregation pattern and linkage phases between QTL and markers are estimated. A simulated example is presented to validate the methodology. In general, the new model is more effective than existing approaches, because it can reveal QTL present in a full-sib progeny that segregates in any pattern present and can also identify dominance effects. Also, the inclusion of cofactors provided more statistical power for QTL mapping.

Mendelian inheritance, linkage and linkage disequilibrium in microsatellite loci of Copaifera langsdorffii Desf.

Copaifera langsdorffii is a Neotropical tree with wide distribution in the Brazilian Atlantic rain forest and savanna. Although eight microsatellite loci (SSR) were developed in 2000 and have been widely used since then, there is yet no information about their inheritance, linkage and linkage disequilibrium (LD). Through the analysis of 28 open-pollinated (OP) progenies, the SSR loci revealed Mendelian inheritance and independent assortment. Using these progenies, young and adult trees LD was mainly detected in OP progenies. Our results show clear evidence that the eight SSR loci can be used without restriction in genetic diversity, mating system and parentage analysis.