The biggest challenge for jatropha breeding is to identify superior genotypes that present high seed yield and seed oil content with reduced toxicity levels. Therefore, the objective of this study ...was to estimate genetic parameters for three important traits (weight of 100 seed, oil seed content, and phorbol ester concentration), and to select superior genotypes to be used as progenitors in jatropha breeding. Additionally, the genotypic values and the genetic parameters estimated under the Bayesian multi-trait approach were used to evaluate different selection indices scenarios of 179 half-sib families. Three different scenarios and economic weights were considered. It was possible to simultaneously reduce toxicity and increase seed oil content and weight of 100 seed by using index selection based on genotypic value estimated by the Bayesian multi-trait approach. Indeed, we identified two families that present these characteristics by evaluating genetic diversity using the Ward clustering method, which suggested nine homogenous clusters. Future researches must integrate the Bayesian multi-trait methods with realized relationship matrix, aiming to build accurate selection indices models.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Genome-wide selection (GWS) has been becoming an essential tool in the genetic breeding of long-life species, as it increases the gain per time unit. This study had a hypothesis that GWS is ...a tool that can decrease the breeding cycle in Jatropha. Our objective was to compare GWS with phenotypic selection in terms of accuracy and efficiency over three harvests. Models were developed throughout the harvests to evaluate their applicability in predicting genetic values in later harvests. For this purpose, 386 individuals of the breeding population obtained from crossings between 42 parents were evaluated. The population was evaluated in random block design, with six replicates over three harvests. The genetic effects of markers were predicted in the population using 811 SNP's markers with
call rate
= 95% and minor allele frequency (MAF) > 4%. GWS enables gains of 108 to 346% over the phenotypic selection, with a 50% reduction in the selection cycle. This technique has potential for the Jatropha breeding since it allows the accurate obtaining of GEBV and higher efficiency compared to the phenotypic selection by reducing the time necessary to complete the selection cycle. In order to apply GWS in the first harvests, a large number of individuals in the breeding population are needed. In the case of few individuals in the population, it is recommended to perform a larger number of harvests.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Jatropha (Jatropha curcas) has become one of the most important species for producing biofuels. Currently, Genotype x Environment (GxE) interaction is the biggest challenge that breeders should solve ...to increase the section accuracy in the plant breeding. Therefore, the objectives in this study were to estimate the parameters in the 180 half-sib families in Jatropha evaluated for five production years, to verify the significance of the GxE interaction variance, to evaluate the adaptability and stability for each family based on three prediction methods, to select superior half-sib families based on the adaptability and stability analyses, and to predict the accuracy for the sixth production year. Jatropha half-sib families were classified and selected using the follow adaptability and stability methods: linear regression, bi-segmented linear regression and mixed models concepts called harmonic mean of the relative performance of genetic values (HMRPGV). The prediction accuracy was estimated by the Pearson correlation between the predicted genetic values by adaptability and stability methods and the phenotypic value in the sixth production year. In result, most half-sib families were classified as general adaptability and general stability for the evaluated traits. The selection gain obtained via HMRPGV was higher than other methods. The prediction accuracy for the sixth production year was 0.45. Therefore, HMRPGV is efficient to maximize the genetic gain, and it can be a useful strategy to select genotype with high adaptability and stability in Jatropha breeding as well as other species that should be evaluated for many years to take a suitable selection accuracy.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective ...accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low (ρg ≤ 0.33), moderate (0.34 ≤ ρg ≤ 0.66), and high magnitude (ρg ≥ 0.67) were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Jatropha (
Jatropha
curcas
L.) is an oleaginous potential, howetever, some studies report that there is low genetic diversity in Brazilian genotypes. Estimating genetic diversity are the essential ...factors to ensure success in the management of genetic resources, planning and adoption of strategies for genetic breeding. The hypothesis of our study is: do Brazilian Jatropha breeding populations have sufficient genetic variability to select individuals within? The objective of this paper is to determine the genetic diversity of 573 genotypes of five populations of Jatropha curcas structured based on the characteristics of yield, resistance to powdery mildew and toxicity, using Single-nucleotide polymorphism molecular markers. The results shows moderate variability among the genotypes analyzed, confirming the initial hypothesis of this study. We recommended using a greater number of individuals per family rather than the number of families in breeding programs in order to exploit the greater variability within populations and hence obtain higher gains with selection.
Canola is a product of traditional plant breeding techniques to remove from rapeseed the antinutritional components erucic acid. This crop proves to be a promising crop due to the diverse purposes of ...its oil, especially by its potential for biofuel production. This paper aimed to integrate the information available in the literature and report the most promising strategies for genetic and biotechnological progress in canola. Thus, we carried out a detailed review of the origin and uses of canola, its socioeconomic importance in the global and Brazilian aspects, tropicalization, with emphasis on genetic breeding. We demonstrate the main breeding strategies that can be used to increase your oil production. We propose here a breeding strategy for canola, in which some strategies previously mentioned are integrated. The purpose of this strategy is to enhance the selection and efficiency at the beginning of a breeding program. Among these, genome wide selection (GWS) is a suitable tool to help breeders to improve the efficiency selection in a canola breeding program increasing the selection accuracy or even reducing the cycle time. The proposed strategies must be analyzed for each situation, adjusting the GWS model to obtain highest selection accuracy.
Macauba palm
Acrocomia aculeata
(Jacq.) Lodd. ex Mart. is a perennial oil, it stands out for having several characteristics of commercial interest, mainly for producing oil for biodiesel, it has ...high oil productivity, about 2.5 to 4.5 L·year
-1
. Despite its great potential, o its cultivation is carried out mainly in an extractive way, so the domestication and breeding programs has been incipient. The study hypothesis is that macauba populations collected in different locations have sufficient genetic variability to initiate a breeding program. Thus, the aim of this study was to estimate the genetic diversity and population structure of macauba palm genotypes by using
single nucleotide polymorphism
(SNP) markers in order to reveal genetic diversity and distribution of genetic variation within and between populations and use the genetic information obtained to assist breeding strategies. Leaf tissues were collected from 566 macauba plants belonging to the Embrapa Cerrados Active Germplasm Bank, composed of genotypes from five states in Brazil: Minas Gerais, Goiás, Pará, São Paulo, and Distrito Federal. Molecular variance analysis estimated, the genetic diversity parameters, the population structure and principal coordinate analysis. The genetic diversity is higher within than between populations. The results provided by PCoA and STRUCTURE were in agreement and indicated that the evaluated genotypes can be grouped into two groups. Genetic diversity parameters reveal the presence of inbreeding and a low number of heterozygotes, evidencing that the reproduction system of the species is mixed. The information revealed of the genotypes using SNP markers will be important for future studies using genome-wide selection and genomic association to develop cultivars of macauba with desirable traits, such as high yield of fruits and oil production.
Due to shortages of fossil fuels, and the worldwide concern approximately climate change and global warming, biofuels have become an important source of sustainable energy. Several species can be ...used to produce biofuels such as soybeans (Glycine max), oil palm (Elaeis guineensis), and Jatropha (Jatropha curcas L.). Therefore, the objective of this paper was to integrate the information available in the literature and report the most promising strategies for genetic and biotechnological progress in Jatropha. Jatropha has become a potential crop to produce biofuel due to the high oil content found in the seeds, which can be transformed into biofuel. Jatropha has an average seed oil content of 35%, and the oil extracted from the seeds has 24.6% crude protein and 47.2% crude fat. Moreover, Jatropha has several agronomic morphological traits that make it a useful crop for biofuel production and animal feed, such as drought tolerance, rapid growth, and ease of propagation. It can be grown at almost any altitude, and plants can produce for more than 50 years. Additionally, Jatropha oil has good stability to oxidation, low viscosity, a low pour-point, which makes Jatropha oil better than soybean or palm oil. This paper presented an innovative and comprehensive literature review on all agronomic aspects of Jatropha, and the strategies that have been used to select superior genotypes for Jatropha breeding. Several important traits of Jatropha are affected by the environment and new strategies to select superior genotypes are required by breeders. Therefore, genomic wide selection associated with recurrent selection can be an appropriate strategy for Jatropha breeding.
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