Tatiana Barbosa Rosado

Genetic parameters and variability in physic nut accessions during early developmental stages

The objective of this work was to estimate the genetic parameters and variability among accessions (half-sib families) of physic nut (Jatropha curcas) during the early stages of development. For this study, 110 accessions in the first year of development of the physic nut germplasm bank, maintained at Embrapa Cerrados, DF, Brazil, were evaluated in situ. The experiment was established in a randomized complete block design, with two replicates and five plants per plot arranged in rows at 4x2 m spacing. Grain yield, total number of branches per plant, plant height, stem diameter, canopy projection on the row, canopy projection between rows, canopy volume, number of days until first flowering and height of the first inflorescence were evaluated. Estimates of vegetative genetic parameters showed the existence of genetic variability in the physic nut germplasm bank. Physic nut accessions of the germplasm bank were grouped into five similarity groups based on character divergence. Although preliminary, the obtained results are promising for showing potential for Jatropha improvement with selective efficiency.

Seleção simultânea de clones de eucalipto de acordo com produtividade, estabilidade e adaptabilidade

The objective of this work was to estimate genetic parameters and to determine the efficiency of the simultaneous selection of eucalyptus clones based on yield, stability, and adaptability. Twenty-one clones, with 36 months of age, from the genetic breeding program of the company Cenibra were used. The experiment was done in a randomized complete block design, in four environments, with 21 replicates of one plant per plot. The clones were evaluated as to the variables: diameter at breast height, plant height, and total volume with bark. The genetic parameters were estimated using the mixed model procedure (REML/BLUP), and selection was based on the harmonic mean of the relative performance of the genetic values (HMRPGV), with three strategies: selection based on the predicted genetic gain, considering the average performance of genotypes in all environments (without interaction effect) or the performance on each environment (with interaction effect); and simultaneous selection based on productivity, stability, and adaptability. Environment particularities influenced the phenotypic expression of the clones. The heritability estimates indicated good perspectives for selecting clones with high yield, stability, and adaptability. Simultaneous selection optimizes clone selection and can be used in the construction of breeding populations and in the recommendation of genetic materials for commercial plantations.

Estimates of genetic parameters for physic nut traits based in the germplasm two years evaluation

In spite of increasingly widespread interest in planting physic nut, breeding efforts are still in its infancy. In that context, an important resource recently established aiming future breeding efforts was the assembly of a germplasm bank with near 200 accessions. The objective of this study was to estimate genetic parameters, repeatibility coefficients and genetic correlation between seven traits, measured in 110 accessions (half sib families) of this germplasm bank in different stages of development. The results show that higher relative values of additive variance were only found for yield and height, and the existence of low environmental variation (either of temporary or permanent nature) among plots within blocks. Given the high repeatibility values found for all traits, on average three measurements are necessary to predict, accurately and efficiently, the true breeding value of an individual. Based on the results of genetic correlations, breeding effort should initially be use track trees with increased stem diameter, elevated number of branches and canopy volume so as to increase the chances of finding an exceptionally highly productive tree.

Genetic gains in physic nut using selection indexes

Abstract – The objective of this work was to estimate genetic gains in physic nut ( Jatropha curcas ) using selection indexes and to establish the best selection strategy for the species. Direct and indirect selection was carried out using different selection indexes, totalizing 14 strategies. One hundred and seventy five families from the active germplasm bank of Embrapa Agroenergy, Brasilia, Brazil, were analyzed in a randomized complete block design with two replicates. The evaluated traits were: grain yield; seeds per fruit; endosperm/seed ratio; seed weight, length, width, and thickness; branches per plant at 0.5, 1.0, and 1.5 m; plant height; stem diameter; canopy projection on rows and between lines; canopy volume; juvenility (days to the first flowering); and height of the first inflorescence. Evaluations were done during the second year of cultivation. The use of selection indexes is relevant to maximize the genetic gains in physic nut, favoring a better distribution of desirable traits. The multiplicative and restrictive indexes are considered the most promising for selection.Index terms:

Joint analysis of phenotypic and molecular diversity provides new insights on the genetic variability of the brazilian physic nut germplasm bank

The genetic variability of the Brazilian physic nut (Jatropha curcas) germplasm bank (117 accessions) was assessed using a combination of phenotypic and molecular data. The joint dissimilarity matrix showed moderate correlation with the original matrices of phenotypic and molecular data. However, the correlation between the phenotypic dissimilarity matrix and the genotypic dissimilarity matrix was low. This finding indicated that molecular markers (RAPD and SSR) did not adequately sample the genomic regions that were relevant for phenotypic differentiation of the accessions. The dissimilarity values of the joint dissimilarity matrix were used to measure phenotypic + molecular diversity. This diversity varied from 0 to 1.29 among the 117 accessions, with an average dissimilarity among genotypes of 0.51. Joint analysis of phenotypic and molecular diversity indicated that the genetic diversity of the physic nut germplasm was 156% and 64% higher than the diversity estimated from phenotypic and molecular data, respectively. These results show that Jatropha genetic variability in Brazil is not as limited as previously thought.

Estimate of genetic parameters and predicted gains with early selection of physic nut families.

An initial evaluation of early selection of physic nut genotypes based on phenotypic data is presented. In order to predict the genetic gains with early selection, genetic parameters, e.g. additive genetic variance, were first obtained for grain yield along with other numerous traits. The results demonstrated that additive genetic variance exists not only for grain yield, which is considered to be the most important trait for oil and biodiesel production, but also for numerous other traits. The predicted genetic gains for grain yield, considering the selection of the 30, 20, 10 and 5 best families in the second crop year are respectively, 40.47, 48.43, 61.78 and 70.28%. With the selection of highly yielding physic nut genotypes indirectly genotypes with enhanced volume would be also selected, because yield exhibits moderate to high genetic correlations with height e canopy volume. The results here presented demonstrate the potential of the population gathered in the Brazilian physic nut germplasm bank for genetic breeding purposes and that superior physic nut families can be selected with high accuracy based on the evaluation of its second crop.

Genome-wide SNP discovery from a pooled sample of accessions of the biofuel plant Jatropha curcas based on whole-transcriptome Illumina resequencing

Background Jatropha curcas(JC) is an oil-rich, drought-tolerant perennial shrub of the Euphorbiaceae family widely dispersed throughout the world. Thought to be native to Central America, it has been the object of an increasing number of studies in recent years for it exhibits a number of appealing attributes as a promising source of biodiesel. Although its undomesticated nature and preferential outcrossed mating system would suggest a high degree of genetic variation to be exploited in breeding, studies have shown limited genetic diversity in the existing germplasm collections [1]. In spite of the increased interest in this bioenergy plant, challenges still exist to turn this species into a genuine crop and improved varieties that consolidate desirable traits are not yet available, making JC large scale plantation an uncertain business [2]. Genomic studies to potentially assist JC breeding efforts have started in the last few years. JC is diploid (2n=22), with a haploid genome size estimated at 416 Mbp [3]. EST databases focusing on gene discovery were constructed [4]and a draft genome sequence was recently published covering 285 Mbp (~68%) of the genome in 120,586 contigs with 40,929 predicted gene models [5]. The focus of our work with JC is to provide effective tools to accelerate breeding through Genomic Selection (GS) [6] and to help assess the levels, organization and enrichment strategies of genetic diversity in germplasm banks and breeding populations. To this end we have started the development of SNP markers. Available EST databases built from single individual plants do not provide the necessary sequence diversity for SNP discovery.In this work we report on the discovery of a set of SNPs for JC derived from a pool of genetically diverse accessions using Illumina sequencing and a SNP selection pipeline recently described [7].

Phenology and biometry of physic nut in the brazilian savannah

Estudos fenologicos de tres acessos morfologicamente distintos de pinhao-manso (Jatropha curcas L.) foram conduzidos no bioma Cerrado brasileiro. A taxa de crescimento da planta, florescimento, formacao e desenvolvimento dos frutos foram medidos, a fim de se estabelecer praticas de manejo eficientes para o aumento de produtividade. Os acessos estudados foram: CNPAE-102 (toxico, susceptivel a oidio), CNPAE-169 (nao-toxico, susceptivel a oidio) e CNPAE-259 (toxico, resistente a oidio). Os materiais considerados nao-toxicos nao possuem esteres de forbol detectaveis nos graos. No periodo de um ano (agosto de 2009 a julho de 2010) registraram-se, quinzenalmente, as variaveis agronomicas (altura de plantas, numero de inflorescencias, numero de frutos verdes e maduros por planta) de cada acesso, correlacionando-as com as variaveis climaticas, por meio da analise de correlacao de Pearson. O acesso CNPAE-102 apresentou a maior taxa de crescimento (0,76 cm dia-1), incremento 1,10 m na altura e altura final de 2,60 m; o CNPAE-169 apresentou menor incremento (0,63 cm dia-1), atingindo altura final de 1,85 m. Os acessos CNPAE-259 e CNPAE-102 foram os mais precoces, e o CNPAE-169 o mais tardio. A temperatura minima foi a variavel climatica que determinou o maior numero de inflorescencias.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.