Genetic evaluation of Jatropha curcas: an important oilseed for biodiesel production

Jatropha curcas, internationally and locally known, respectively, as physic nut and pinhão manso, is a highly promising species for biodiesel production in Brazil and other countries in the tropics. It is rustic, grows in warm regions and is easily cultivated. These characteristics and high-quality oil yields from the seeds have made this plant a priority for biodiesel programs in Brazil. Consequently, this species merits genetic investigations aimed at improving yields. Some studies have detected genetic variability in accessions in Africa and Asia. We have made the first genetic evaluation of J. curcas collected from Brazil. Our objective was to quantify genetic diversity and to estimate genetic parameters for growth and production traits and seed oil content. We evaluated 75 J. curcas progenies collected from Brazil and three from Cambodia. The mean oil content in the seeds was 31%, ranging from 16 to 45%. No genetic correlation between growth traits and seed oil content was found. However, high coefficients of genetic variation were found for plant height, number of branches, height of branches, and stem diameter. The highest individual narrow-sense heritabilities were found for leaf length (0.35) and width (0.34), stem diameter (0.24) and height of branches (0.21). We used a clustering algorithm to genetically identify the closest and most distant progenies, to assist in the development of new cultivars. Geographical diversity did not necessarily represent the genetic diversity among the accessions collected. These results are important for the continuity of breeding programs, aimed at obtaining cultivars with high grain yield and high oil content in seeds

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs

Genetic diversity and coefficient of parentage between clones and sugarcane varieties in Brazil

The success of the development of new sugarcane varieties is associated with the ability to correctly select the genitor. The aim of this study was to evaluate the genetic diversity between 113 clones and sugarcane varieties using the Ward-modified location model procedure with added information about the coefficient of parentage and endogamy. In this study, data was used from 100 experiments that evaluated clones; the experimental phase was conducted in 70 places between the years 2002 and 2009 on the outlining in random blocks. According to the diversity analysis, 3 groups formed: G1, G2, and G3, which were composed of 58, 8, and 47 genotypes, respectively. The clones of groups G1 and G3 were the most outstanding. Thus, biparental crossbreeding involving clones and varieties of these 2 groups can efficiently obtain transgressive genotypes. Knowledge of the heterotypic groups indicated by the Ward-modified location model method, along with the parentage information, will make it a lot easier to define the desirable and undesirable crossbreeds for public and private breeding programs that develop sugarcane varieties

Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information

Knowledge of dominance effects should improve ge-netic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of het-erosis in crossbreeds. In this study, we combined genomic and pedi-gree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respec-tively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age