Genetic variation for fusarium crown rot tolerance in durum wheat.

Tolerance to the cereal disease Fusarium crown rot (FCR) was investigated in a set of 34 durum wheat genotypes, with Suntop, (bread wheat) and EGA Bellaroi (durum) as tolerant and intolerant controls, in a series of replicated field trials over four years with inoculated (FCR-i) and non-inoculated (FCR-n) plots of the genotypes. The genotypes included conventional durum lines and lines derived from crossing durum with 2-49, a bread wheat genotype with the highest level of partial resistance to FCR. A split plot trial design was chosen to optimize the efficiency for the prediction of FCR tolerance for each genotype. A multi-environment trial (MET) analysis was undertaken which indicated that there was good repeatability of FCR tolerance across years. Based on an FCR tolerance index, Suntop was the most tolerant genotype and EGA Bellaroi was very intolerant, but some durum wheats had FCR tolerance indices which were comparable to Suntop. These included some conventional durum genotypes, V101030, TD1702, V11TD013*3X-63 and DBA Bindaroi, as well as genotypes from crosses with 2-49 (V114916 and V114942). The correlation between FCR tolerance and FCR-n yield predictions was moderately negative indicating it could be somewhat difficult to develop FCR-tolerant genotypes that are high yielding under low disease pressure. However, FCR tolerance showed a positive correlation with FCR-i yield predictions in seasons of high disease expression indicating it could be possible to screen for FCR tolerance using only FCR-i treatments. These results are the first demonstration of genetic diversity in durum germplasm for FCR tolerance and they provide a basis for breeding for this trait.

Use of Contemporary Groups in the Construction of Multi-Environment Trial Datasets for Selection in Plant Breeding Programs.

Plant breeding programs use multi-environment trial (MET) data to select superior lines, with the ultimate aim of increasing genetic gain. Selection accuracy can be improved with the use of advanced statistical analysis methods that employ informative models for genotype by environment interaction, include information on genetic relatedness and appropriately accommodate within-trial error variation. The gains will only be achieved, however, if the methods are applied to suitable MET datasets. In this paper we present an approach for constructing MET datasets that optimizes the information available for selection decisions. This is based on two new concepts that characterize the structure of a breeding program. The first is that of "contemporary groups," which are defined to be groups of lines that enter the initial testing stage of the breeding program in the same year. The second is that of "data bands," which are sequences of trials that correspond to the progression through stages of testing from year to year. MET datasets are then formed by combining bands of data in such a way as to trace the selection histories of lines within contemporary groups. Given a specified dataset, we use the A-optimality criterion from the model-based design literature to quantify the information for any given selection decision. We demonstrate the methods using two motivating examples from a durum and chickpea breeding program. Datasets constructed using contemporary groups and data bands are shown to be superior to other forms, in particular those that relate to a single year alone.

Genome-wide delineation of natural variation for pod shatter resistance in Brassica napus.

Resistance to pod shattering (shatter resistance) is a target trait for global rapeseed (canola, Brassica napus L.), improvement programs to minimise grain loss in the mature standing crop, and during windrowing and mechanical harvest. We describe the genetic basis of natural variation for shatter resistance in B. napus and show that several quantitative trait loci (QTL) control this trait. To identify loci underlying shatter resistance, we used a novel genotyping-by-sequencing approach DArT-Seq. QTL analysis detected a total of 12 significant QTL on chromosomes A03, A07, A09, C03, C04, C06, and C08; which jointly account for approximately 57% of the genotypic variation in shatter resistance. Through Genome-Wide Association Studies, we show that a large number of loci, including those that are involved in shattering in Arabidopsis, account for variation in shatter resistance in diverse B. napus germplasm. Our results indicate that genetic diversity for shatter resistance genes in B. napus is limited; many of the genes that might control this trait were not included during the natural creation of this species, or were not retained during the domestication and selection process. We speculate that valuable diversity for this trait was lost during the natural creation of B. napus. To improve shatter resistance, breeders will need to target the introduction of useful alleles especially from genotypes of other related species of Brassica, such as those that we have identified.