Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes

Computer simulation of a selection strategy to accommodate genotype-environment interactions in a wheat recurrent selection programme

Multi-environment trials (METs) are used in plant breeding programmes to evaluate genotypes (lines/families) as a basis for selection on expected performance (yield and/or quality) in a target population of environments (TPE). When a large component of the genotype-environment (G x E) interactions results from crossover interactions, samples of environments in METs that deviate From the TPE provide a suboptimal basis for selection of genotypes on performance expected in the TPE. To adjust for the negative effects of these deviations, a selection strategy that weights the data from the MET according to their expected frequency of occurrence in the TPE (i.e. a weighted selection strategy)was investigated. Computer simulation methodology was used to obtain preliminary information on the weighted selection strategy and compare it to the traditional unweighted selection strategy For a range of MET scenarios and G x E interaction models. The evaluation of the weighted selection strategy was conducted in context with the germplasm enhancement programme (GEP) of the Northern Wheat Improvement Programme in Australia. The results indicated that when the environments sampled in the MET matched those expected in the TPE, the unweighted and weighted selection strategies achieved a similar response to selection in the TPE. However. when the environments sampled in the MET did not match the expectations in the TPE and a large component of the G x E interactions resulted from crossover interactions, the weighted selection strategy achieved a greater response to selection in the TPE. The advantage of the weighted strategy increased as the amount of crossover G x E interaction increased or fewer environments were sampled in the METs

Rainfed lowland rice breeding strategies for northeast Thailand. II. Comparison of interstation and intrastation selection

The physical environment of the rainfed lowland ecosystem is often characterised and grouped according to the surface hydrology of rice paddies and rice cultivars have been developed for each subecosystem. Rainfall is an important determinant of the yield of rainfed lowland rice, but other factors such as topography and soil fertility also affect grain yield and choice of cultivars. The growing environment and also rice yield vary greatly within small areas as well as across seasons. This causes great difficulty in determining the target population of environments for a rice breeding program. This paper reviews past work on characterising the variability in the physical environment, and rice production in the rainfed lowland ecosystem. It examines possible connections between this variability and slow progress in developing new cultivars that are widely adapted to the rainfed lowland rice ecosystem

Flapjack-graphical genotype visualization

Summary: New software tools for graphical genotyping are required that can routinely handle the large data volumes generated by the high-throughput single-nucleotide polymorphism (SNP) platforms, genotyping-by-sequencing and other comparable genotyping technologies. Flapjack has been developed to facilitate analysis of these data, providing real time rendering with rapid navigation and comparisons between lines, markers and chromosomes, with visualization, sorting and querying based on associated data, such as phenotypes, quantitative trait loci or other mappable features. Availability: Flapjack is freely available for Microsoft Windows, Mac OS X, Linux and Solaris, and can be downloaded from http://bioinf.scri.ac.uk/flapjack Contact: [email protected]

Rainfed lowland rice breeding strategies for Northeast Thailand. II. Comparison of intrastation and interstation selection

There has been limited progress for grain yield of rainfed lowland rice in Northeast Thailand since the 1960s. The current breeding strategy operates as a series of six semi-independent pedigree programs, each at a different site. Each program has three major phases of selection: (1) intrastation selection, (2) interstation selection, and (3) on-farm selection. The expected selection response for grain yield based on intrastation and interstation selection was examined using a combination of experimental results, prediction equation theory and computer simulation. Experiments were conducted to estimate genetic, genotype-by-environment interaction and error components of variance as inputs for estimation of heritability on a number of bases and also to obtain estimates of realised response from selection. Estimates of line-mean heritability for grain yield based on intrastation evaluation of lines suggest that it is low, ranging from 0.07 to 0.13, for one to four replicates, respectively, at a single site in 1 year. Line-mean heritability for intrastation evaluation based on two replicates and 2 years was estimated to be 0.18, only slightly higher than for 1 year and four replicates. In contrast, estimates of line-mean heritability for interstation testing were intermediate, e.g. 0.32 and 0.48 for two replicates at six sites for 1 year and 2 years, respectively. Estimates of realised selection response for grain yield from intrastation and interstation selection were consistent with the low to intermediate heritability estimates. Interstation selection, based on two replicates, eight sites and 1 year, showed an advantage over intrastation selection, based on two replicates and 1 year, when response was measured as the mean yield of selected lines across environments. The present breeding strategy applies intense selection during the intrastation phase of the breeding programs. Consequently, only a small number of lines (ca. 70 lines from all stations) are advanced from the intrastation selection phase to the interstation selection phase. Therefore, for most lines generated by the breeding program there is limited opportunity to evaluate the contributions of broad and specific adaptation to higher yield. The presence of large genotype-by-environment interactions, in combination with limited yield evaluation of lines in multi-environment trials (until the final stages of testing), is identified as a major factor contributing to the slow genetic progress for grain yield. The proposed breeding strategy replaces the intrastation testing phase with a coordinated early generation interstation testing based on F bulks. Evaluation of the proposed breeding strategy by computer simulation demonstrated an advantage from modifying the current breeding strategy to give greater emphasis to interstation selection in place of intrastation selection

Developments in breeding cereals for organic agriculture

The need for increased sustainability of performance in cereal varieties, particularly in organic agriculture (OA), is limited by the lack of varieties adapted to organic conditions. Here, the needs for breeding are reviewed in the context of three major marketing types, global, regional, local, in European OA. Currently, the effort is determined, partly, by the outcomes from trials that compare varieties under OA and CA (conventional agriculture) conditions. The differences are sufficiently large and important to warrant an increase in appropriate breeding. The wide range of environments within OA and between years, underlines the need to try to select for specific adaptation in target environments. The difficulty of doing so can be helped by decentralised breeding with farmer participation and the use of crops buffered by variety mixtures or populations. Varieties for OA need efficient nutrient uptake and use and weed competition. These and other characters need to be considered in relation to the OA cropping system over the whole rotation. Positive interactions are needed, such as early crop vigour for nutrient uptake, weedcompetition and disease resistance. Incorporation of all characteristics into the crop can be helped by diversification within the crop, allowing complementation and compensation among plants. Although the problems of breeding cereals for organic farming systems are large, there is encouraging progress. This lies in applications of ecology to organic crop production, innovations in plant sciences, and the realisation that such progress is central to both OA and CA, because of climate change and the increasing costs of fossil fuels