-The objectives of this work were to investigate the genetic variation in 79 soybean (Glycine max) accessions from different regions of the world, to cluster the accessions based on their similarity, and to test the correlation between the two types of markers used. Simple sequence repeat markers present in genomic (SSR) and in expressed regions (EST-SSR) were used. Thirty SSR primer-pairs were selected (20 genomic and 10 EST-SSR) based on their distribution on the 20 genetic linkage groups of soybean, on their trinucleotide repetition unit and on their polymorphism information content. All analyzed loci were polymorphic, and 259 alleles were found. The number of alleles per locus varied from 2-21, with an average of 8.63. The accessions exhibit a significant number of rare alleles, with genotypes 19, 35, 63 and 65 carrying the greater number of exclusive alleles. Accessions 75 and 79 were the most similar and accessions 31 and 35, and 40 and 78, were the most divergent ones. A low correlation between SSR and EST-SSR data was observed, thus genomic and expressed microsatellite markers are required for an appropriate analysis of genetic diversity in soybean. The genetic diversity observed was high and allowed the formation of five groups and several subgroups. A moderate relationship between genetic divergence and geographic origin of accessions was observed.Index terms: Glycine max, molecular marker, plant breeding, plant germplasm, polymorphism information content. Termos para indexação: Glycine max, marcadores moleculares, melhoramento de plantas, germoplasma vegetal, conteúdo de informação polimórfica. Diversidade genética em germoplasma de soja identificada por marcadores SSR e EST-SSR

Caffeine inheritance was investigated in F 2 and BC 1 F 1 generations between Coffea arabica var. Bourbon Vermelho (BV) and Coffea canephora var. Robusta 4x (R4x). The caffeine content of seeds and leaves was determined during 2004 and 2005. Microsatellite loci-markers were used to deduce the meiotic pattern of chromosome pairing of tetraploid interspecific hybrids. Genetic analysis indicated that caffeine content in seeds was quantitatively inherited and controlled by genes with additive effects. The estimates of broad-sense heritability of caffeine content in seeds were high for both generations. In coffee leaves, the caffeine content (BSH) from the same populations showed transgressive segregants with enhanced levels and high BSH. Segregation of loci-markers in BC 1 F 1 populations showed that the ratios of the gametes genotype did not differ significantly from those expected assuming random associations and tetrasomic inheritance. The results confirm the existence of distinct mechanisms controlling the caffeine content in seeds and leaves, the gene exchange between the C. arabica BV and C. canephora R4x genomes and favorable conditions for improving caffeine content in this coffee population.

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The shrub species Psychotria tenuinervis (Rubiaceae) is native to the Brazilian Atlantic forest and is largely found within natural and disturbed forest fragments. Aiming to develop studies on population genetic structure of forest fragment species, eigth microsatellite markers were developed for P. tenuinervis. Also, 15 loci already developed for Coffea (Rubiaceae) were tested for transferability to this species. We utilized 45 individuals from natural populations of three different fragments-anthropic edge, interior fragment and natural edge, within the Brazilian Atlantic forest. The average number of alleles per locus was 2.5 (two-four alleles/locus). These loci will be useful for future population genetic studies aiming to the conservation and management of this species.

QTL identification in soybean related to stink bug resistance and agronomic traits using the multivariate multiple interval mapping approach Soybean is the Brazilian crop with the most expansion along the past three decades. Currently, it is a commodity commercialized in large scale as grain, bran and oil. Because it is an important source of protein, it plays a fundamental role in the food industry, both human and animal. Soybean monoculture in large areas has increased crop vulnerability to pathogens and insect pests, with significant consequences on grain production. Among such pest insects, stink bugs are considered a major pest of soybean crop, feeding directly on seeds, reducing yield and seed quality. Losses in crop yield due to stink bugs attack are greater than 30% and seed germination compromising can be greater than 50%. This study aimed to identify QTL (Quantitative Trait Loci), for stink bug resistance traits and agronomic traits using the multivariate multiple interval mapping. An F2 mapping population of 228 plants derived from a biparental cross between IAC-100 and CD-215 was used for genotyping. An F2:3 population was developed to evaluate eight stink bug resistant traits such as graining period, leaf retention, pod number per plant, percentage of pod damage, number of seeds, hundred seed weight, weight of healthy seeds and spotted seed weight. Other seven agronomic traits were evaluated such as number of days to flowering, plant height at flowering, number of days to maturity, plant height at maturity, lodging, agronomic value and grain yield. A total of 417 SNP (Single Nucleotide Polymorphism) markers, 61 SSR (Simple Sequence Repeat), 30 AFLP (Amplified Fragment Length Polymorphism) and 8 TRAP (Target Region Amplification Polymorphism) markers were mapped into 20 soybean linkage groups. The total map length was 2,814.82 cM with an average of 5.46 cM between markers. QTL mapping for those traits was performed using univariate (MIM) and multivariate (MT-MIM) multiple interval mapping, with main QTL effects estimates. MIM analysis identified a total of 60 QTL, through 13 soybean linkage groups, with 29 QTL related to stink bug resistant traits and 31 QTL related to agronomic traits. Phenotypic variation explained by QTL ranged from 14.27% for lodging to 65.45% for number of days to maturity. The traits were divided into nine groups for MT-MIM analysis considering their correlation coefficient. Twenty different genomic regions were identified showing a very high QTL clustering. For most of the traits phenotypic variation estimates for MT-MIM models were higher than MIM models, ranging from 27.98% to 65.30% for plant height at flowering and number of days to maturity, respectively. MT-MIM analysis showed 13 genomic regions controlling at least one of the evaluated traits which were not identified at MIM analysis. Comparison between identified QTL and QTL database at Soybase demonstrated that some QTL were similar to those described in different genetic background. However, 56 QTL detected in the pre...