26 resultados para GENETIC-IMPROVEMENT


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Anthracnose, caused by Colletotrichum trifolii, is one of the most serious diseases influencing lucerne persistence and productivity in eastern Australia. The disease is largely controlled by plant resistance; however, new pathotypes of C. trifolii have developed in Australia, seriously limiting the productive life of susceptible cultivars. This paper describes an incompletely recessive and quantitatively inherited resistance to C. trifolii identified in a clone (W116) from cv. Sequel. S-1, F-1, F-2 and backcross populations of W116 and D (highly susceptible clone) were studied for their reaction to C. trifolii race 1. Resistance was found to be quantitatively inherited, and quantitative trait loci associated with resistance and susceptibility were identified in a backcross population (D x W116) x D using random amplified polymorphic DNA and amplified fragment length polymorphic markers. A multi-locus region on linkage group 4 was found to contribute significantly to the resistance phenotype. The application of DNA markers to allow exploitation of this quantitatively inherited resistance in lucerne breeding is discussed.

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The novel molecular marker technique Randomly Amplified DNA Fingerprinting (RAF) was used to survey genetic relationships between 37 accessions of the tropical fruit G. mangostana (mangosteen) and among 11 accessions from eight other Garcinia species. Although mangosteen is believed to reproduce exclusively through apomixis, our results show that considerable genetic diversity exists within G. mangostana and between other Garcinia species. Among the 37 G. mangostana accessions examined, nine different genotypes were identified which clustered into three distinct groups based on correspondence analysis (reciprocal averaging). For 26 (70%) of the accessions no marker variation was detected over 530 loci screened. A further eight (22%) accessions exhibited very low levels of variation (0.2-1%) suggesting at least one well conservedm angosteen genotype. The remaining three accessions (8%) showed extensive variation (22-31%) compared with the majority of accessions. The three mangosteen groups were 63-70% dissimilar to the other Garcinia species investigated. The genetic diversity identified in this research will assist in the conservation of Garcinia germplasm and provides a valuable framework for the genetic improvement of mangosteen.

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Guayule (Parthenium argentatum Gray) is a potential source of commercial natural rubber. Its commercialisation depends mainly on economical plant production. The objective of this study was to evaluate the performance of improved lines in Australia. Seeds from five improved lines (AZ-1, AZ-2, AZ-3, AZ-5 and AZ-6) and two previously developed guayule lines (N 565 and 11591) were obtained from the Agricultural Research Service (ARS) of the United States Department of Agriculture (USDA). Seedlings from these lines were grown in a glasshouse for 3 months and later transplanted in a field experiment in early September 2001. Plant height and width were monitored from transplanting to 62 weeks at regular intervals. After 62 weeks, plant dry matter production, rubber and resin content, and yields were analysed. Plant height and width of the improved lines were higher than N 565 and 11591. Plant dry matter, rubber and resin yields were significantly different among lines. Of the five lines, AZ-1 and AZ-2 produced rubber yields of 620 and 550 kg/ha, respectively and these yields were significantly greater than for N 565 (371 kg/ha) and 11591 (391 kg/ha). AZ-1 and AZ-2 also produced significantly higher resin yields, 727 and 668 kg/ha, respectively, than those for N 565 (436 kg/ha) and 11591 (325 kg/ha). Rubber and resin yield increase of lines, AZ-1 and AZ-2, were in the range of 41-68% and 53-123%, respectively over N 565 and 11591. AZ-1 tended to produce higher rubber and resin yields than AZ-2 but exhibited highly variable plant height (CV = 25%) and width (CV = 41%) indicating potential for further genetic improvement. AZ-2 offers the best combination of desirable characters including early vigour, uniformity and comparatively higher rubber and resin yields. (C) 2003 Published by Elsevier B.V.

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Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.

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The ability to track large numbers of individuals and families is a key determinant of the power and precision of breeding programs, including the capacity to quantify interactions between genotypes and their environment. Until recently, most family based selective breeding programs for shrimp, and other highly fecund aquaculture species, have been restricted by the number of animals that can be physically tagged and individually selected. Advances in the development of molecular markers, such as microsatellite loci, are now providing the means to track large numbers of individuals and families in commercial production systems. In this study microsatellites, coupled with DNA parentage analyses, were used to determine the relative performance of 22 families of R japonicus reared in commercial production ponds. In the experimental design 6000 post-larvae from each of 22 families, whose maternal parents had been genotyped at 8 microsatellite loci, were stocked into each of four I ha ponds. After 6 months the ponds were harvested and a total of 6000 individuals were randomly weighed from each pond. Mean wet weight of the shrimp from one pond was significantly lower than that of the other three ponds demonstrating a possible pond effect on growth rate. The representation of families in the top 10% of each pond's weight distribution was then determined by randomly genotyping up to 300 individuals from this upper weight class. Parentage analyses based on individual genotypic data demonstrated that some families were over-represented in the top 10% in all ponds, while others were under-represented due to slower growth rates. The results also revealed some weak, but significant, male genotype x environment (G x E) interactions in the expression of shrimp growth for some families. This indicates that G x E effects may need to be factored into future R japonicus selective breeding programs. This study demonstrated the utility of DNA parentage analyses for tracking individual family performance in communally stocked shrimp pond populations and, its application to examining G x E effects on trait expression under commercial culture conditions. Crown Copyright (c) 2005 Published by Elsevier B.V. All rights reserved.

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Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

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Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

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New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

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Genetic control of adventitious rooting was characterised in two unrelated Pinus elliottii x P. caribaea families, an outbred F-1 (n = 287) and an inbred F-2 ( n = 357). Rooting percentage was assessed in three settings and root biomass was measured on a sub-set of clones ( n = 50) from each family in the third setting. On average, clones in the outbred F-1 had a higher rooting percentage (mean +/- SE; 59 +/- 1.9%) and biomass (mean +/- SD; 0.41 +/- 0.24 g) than clones in the inbred F-2 family ( mean +/- SE; 48 +/- 1.8% and mean +/- SD; 0.19 +/- 0.13 g). Genetic determination for rooting percentage was strong in both families, as indicated by high individual setting clonal repeatabilities ( e. g. Setting 3; outbred F-1 0.62 +/- 0.03 and inbred F-2 0.68 +/- 0.02 (H-2 +/- SE)) and the moderate-to-high genetic correlations amongst the three settings. For root biomass, clonal repeatabilities for both families were lower (outbred F-1 0.35 +/- 0.09 and inbred F-2 0.44 +/- 0.10 (H-2 +/- SE)). Weak positive genetic correlations between rooting percentage and root biomass in both families suggested a concomitant gain in root biomass would be insignificant when selecting solely on the more easily assessable rooting percentage.

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New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.

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The magnitude and nature of genotype-by-environment interactions (G×E) for grain yield (GY) and days to flower (DTF) in Cambodia were examined using a random population of 34 genotypes taken from the Cambodian rice improvement program. These genotypes were evaluated in multi-environment trials (MET) conducted across three years (2000 to 2002) and eight locations in the rainfed lowlands. The G×E interaction was partitioned into components attributed to genotype-by-location (G×L), genotype-by-year (G×Y) and genotype-by-location-by-year (G×L×Y) interactions. The G×L×Y interaction was the largest component of variance for GY. The G×L interaction was also significant and comparable in size to the genotypic component (G). The G×Y interaction was small and non significant. A major factor contributing to the large G×L×Y interactions for GY was the genotypic variation for DTF in combination with environmental variation for the timing and intensity of drought. Some of the interactions for GY associated with timing of plant development and exposure to drought were repeatable across the environments enabling the identification of three-target populations of environments (TPE) for consideration in the breeding program. Four genotypes were selected for wide adaptation in the rainfed lowlands in Cambodia.