Lipids, including the diterpenes cafestol and kahweol, are key compounds that contribute to the quality of coffee beverages. We determined total lipid content and cafestol and kahweol concentrations in green beans and genotyped 107 Coffea arabica accessions, including wild genotypes from the historical FAO collection from Ethiopia. A genome-wide association study was performed to identify genomic regions associated with lipid, cafestol and kahweol contents and cafestol/kahweol ratio. Using the diploid Coffea canephora genome as a reference, we identified 6,696 SNPs. Population structure analyses suggested the presence of two to three groups (K = 2 and K = 3) corresponding to the east and west sides of the Great Rift Valley and an additional group formed by wild accessions collected in western forests. We identified 5 SNPs associated with lipid content, 4 with cafestol, 3 with kahweol and 9 with cafestol/kahweol ratio. Most of these SNPs are located inside or near candidate genes related to metabolic pathways of these chemical compounds in coffee beans. In addition, three trait-associated SNPs showed evidence of directional selection among cultivated and wild coffee accessions. Our results also confirm a great allelic richness in wild accessions from Ethiopia, especially in accessions originating from forests in the west side of the Great Rift Valley.

Brazil is the world's largest producer of common bean. Knowledge of the genetic diversity and relatedness of accessions adapted to Brazilian conditions is of great importance for the conservation of germplasm and for directing breeding programs aimed at the development of new cultivars. In this context, the objective of this study was to analyze the genetic diversity, population structure, and linkage disequilibrium (LD) of a diversity panel consisting of 219 common bean accessions, most of which belonging to the Mesoamerican gene pool. Genotyping by sequencing (GBS) of these accessions allowed the identification of 49,817 SNPs with minor allele frequency > 0.05. Of these, 17,149 and 12,876 were exclusive to the Mesoamerican and Andean pools, respectively, and 11,805 SNPs could differentiate the two gene pools. Further the separation according to the gene pool, bayesian analysis of the population structure showed a subdivision of the Mesoamerican accessions based on the origin and color of the seed tegument. LD analysis revealed the occurrence of long linkage blocks and low LD decay with physical distance between SNPs (LD half decay in 249 kb, corrected for population structure and relatedness). The GBS technique could effectively characterize the Brazilian common bean germplasms, and the diversity panel used in this study may be of great use in future genome-wide association studies.

A few breeding companies dominate the maize (Zea mays L.) hybrid market in Brazil: Monsanto® (35%), DuPont Pioneer® (30%), Dow Agrosciences® (15%), Syngenta® (10%) and Helix Sementes (4%). Therefore, it is important to monitor the genetic diversity in commercial germplasms as breeding practices, registration and marketing of new cultivars can lead to a significant reduction of the genetic diversity. Reduced genetic variation may lead to crop vulnerabilities, food insecurity and limited genetic gains following selection. The aim of this study was to evaluate the genetic vulnerability risk by examining the relationship between the commercial Brazilian maize germplasms and the Nested Association Mapping (NAM) Parents. For this purpose, we used the commercial hybrids with the largest market share in Brazil and the NAM parents. The hybrids were genotyped for 768 single nucleotide polymorphisms (SNPs), using the Illumina Goldengate® platform. The NAM parent genomic data, comprising 1,536 SNPs for each line, were obtained from the Panzea data bank. The population structure, genetic diversity and the correlation between allele frequencies were analyzed. Based on the estimated effective population size and genetic variability, it was found that there is a low risk of genetic vulnerability in the commercial Brazilian maize germplasms. However, the genetic diversity is lower than those found in the NAM parents. Furthermore, the Brazilian germplasms presented no close relations with most NAM parents, except B73. This indicates that B73, or its heterotic group (Iowa Stiff Stalk Synthetic), contributed to the development of the commercial Brazilian germplasms.

Coffea arabica L. is a native coffee species probably originated in Abyssinia, now Ethiopia. The genetic diversity of C. arabica has economic implications directly related to profits by breeding for developing new varieties to a global market. The economic value of C. arabica genetic resources are estimated at US$ 420 million, considered a 10% discount rate. Understanding the extent of traits variability and genetic diversity is essential to guide crosses between genotypes, targeting the development of new varieties with high economic value. This chapter will present the C. arabica economic importance, primarily to Brazil, the most significant world producer; we will outline the origin and dispersion of arabica coffee and briefly show the leading germplasm banks. We will also point out contribution of genetic diversity studies based on morphological, agronomic traits, and molecular markers supporting the development of new varieties. Finally, we present an outline for the future.

Information about population structure and genetic relationships within and among wild and brazilian Coffea arabica L. genotypes is highly relevant to optimize the use of genetic resources for breeding purposes. In this study, we evaluated genetic diversity, clustering analysis based on Jaccard's coefficient and population structure in 33 genotypes of C. arabica and of three diploid Coffea species (C. canephora, C. eugenioides and C. racemosa) using 30 SSR markers. A total of 206 alleles were identified, with a mean of 6.9 over all loci. The set of SSR markers was able to discriminate all genotypes and revealed that Ethiopian accessions presented higher genetic diversity than commercial varieties. Population structure analysis indicated two genetic groups, one corresponding to Ethiopian accessions and another corresponding predominantly to commercial cultivars. Thirty-four private alleles were detected in the group of accessions collected from West side of Great Rift Valley. We observed a lower average genetic distance of the C. arabica genotypes in relation to C. eugenioides than C. canephora. Interestingly, commercial cultivars were genetically closer to C. eugenioides than C. canephora and C. racemosa. The great allelic richness observed in Ethiopian Arabica coffee, especially in Western group showed that these accessions can be potential source of new alleles to be explored by coffee breeding programs.

Soybean is one of the most important crops worldwide. Brazil and the United States (US) are the world’s two biggest producers of this legume. The increase of publicly available DNA sequencing data as well as high-density genotyping data of multiple soybean germplasms has made it possible to understand the genetic relationships and identify genomics regions that underwent selection pressure during soy domestication and breeding. In this study, we analyzed the genetic relationships between Brazilian (N = 235) and US soybean cultivars (N = 675) released in different decades and screened for genomic signatures between Brazilian and US cultivars. The population structure analysis demonstrated that the Brazilian germplasm has a narrower genetic base than the US germplasm. The US cultivars were grouped according to maturity groups, while Brazilian cultivars were separated according to decade of release. We found 73 SNPs that differentiate Brazilian and US soybean germplasm. Maturity-associated SNPs showed high allelic frequency differences between Brazilian and US accessions. Other important loci were identified separating cultivars released before and after 1996 in Brazil. Our data showed important genomic regions under selection during decades of soybean breeding in Brazil and the US that should be targeted to adapt lines from different origins in these countries.

Increasing low nitrogen (N) tolerance in maize is an important goal for food security and agricultural sustainability. In order to analyze the population structure of tropical maize lines and identify genomic regions associated with low-N tolerance, a set of 64 inbred lines were evaluated under low-N and optimal-N conditions. The low-N Agronomic Efficiency index (LNAE) of each line was calculated. The maize lines were genotyped using 417,112 SNPs markers. The grouping based on the LNAE values classified the lines into two phenotypic groups, the first comprised by genotypes with high LNAE (named H_LNAE group), while the second one comprised genotypes with low LNAE (named L_LNAE group). The H_LNAE and L_LNAE groups had LNAE mean values of 3,304 and 1,644, respectively. The population structure analysis revealed a weak relationship between genetic and phenotypic diversity. Pairs of lines were identified, having at the same time high LNAE and high genetic distance from each other. A set of 29 SNPs markers exhibited a significant difference in allelic frequencies (Fst > 0.2) between H_LNAE and L_LNAE groups. The Pearson's correlation between LNAE and the favorable alleles in this set of SNPs was 0.69. These SNPs could be useful for marker-assisted selection for low-N tolerance in maize breeding programs. The results of this study could help maize breeders identify accessions to be used in the development of low-N tolerant cultivars.

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