Dataset Information

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes.

ABSTRACT: Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of field assessed phenotypes of genetic variants and of the weight of associated markers across different environmental variables. Association models accounting for oat population structure were applied on either arithmetic means or best linear unbiased prediction (BLUPs) to ensure robust identification of associations with the agronomic traits evaluated. The meta-analysis of the six joint environments (mega-environment) identified several markers associated with several agronomic traits and crown rust severity. Five of these associated markers were located within expressed genes. These associations were only mildly influenced by climatic variables indicating that these markers are good candidates to improve the genetic potential of oat under Mediterranean conditions. The models also highlighted several marker-trait associations, strongly affected by particular climatic variables including high rain pre- or post-heading dates and high temperatures, revealing strong potential for oat adaptation to specific agro-climatic conditions. These results will contribute to increase oat resilience for particular climatic conditions and facilitate breeding for plant adaptation to a wider range of climatic conditions in the current scenario of climate change.

SUBMITTER: Rispail N

PROVIDER: S-EPMC6156136 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes.

Rispail Nicolas N Montilla-Bascón Gracia G Sánchez-Martín Javier J Flores Fernando F Howarth Catherine C Langdon Tim T Rubiales Diego D Prats Elena E

Frontiers in plant science 20180919

Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of f ...[more]

PMID: 30283476

Similar Datasets

Project description:Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models remains a challenge in the successful implementation of this approach. Multivariate models have shown promise when evaluated using diverse panels of unrelated accessions; however, limited information is available on their performance in advanced breeding trials. Here, we used multivariate GP models to predict multiple agronomic traits using 314 advanced and elite breeding lines of winter wheat evaluated in 10 site-year environments. We evaluated a multi-trait (MT) model with two cross-validation schemes representing different breeding scenarios (CV1, prediction of completely unphenotyped lines; and CV2, prediction of partially phenotyped lines for correlated traits). Moreover, extensive data from multi-environment trials (METs) were used to cross-validate a Bayesian multi-trait multi-environment (MTME) model that integrates the analysis of multiple-traits, such as G × E interaction. The MT-CV2 model outperformed all the other models for predicting grain yield with significant improvement in PA over the single-trait (ST-CV1) model. The MTME model performed better for all traits, with average improvement over the ST-CV1 reaching up to 19, 71, 17, 48, and 51% for grain yield, grain protein content, test weight, plant height, and days to heading, respectively. Overall, the empirical analyses elucidate the potential of both the MT-CV2 and MTME models when advanced breeding lines are used as a training population to predict related preliminary breeding lines. Further, we evaluated the practical application of the MTME model in the breeding program to reduce phenotyping cost using a sparse testing design. This showed that complementing METs with GP can substantially enhance resource efficiency. Our results demonstrate that multivariate GS models have a great potential in implementing GS in breeding programs.

Project description:An F6 : 8 recombinant inbred line (RIL) population derived from the cross between WAOAT2132 (Dw6) and Caracas along with the two parents were used to evaluate the genetic effects of Dw6 dwarfing gene on plant height and other agronomic traits in oat (Avena sativa L.) across three environments, and develop closely linked markers for marker-assisted selection (MAS) for Dw6. The two parents differed in all investigated agronomic traits except for the number of whorls. The RIL lines showed a bimodal distribution for plant height in all three tested environments, supporting the height of this population was controlled by a single gene. Dw6 significantly reduced plant height (37.66∼44.29%) and panicle length (13.99∼22.10%) but without compromising the coleoptile length which was often positively associated with the reduced stature caused by dwarfing genes. Dw6 has also strong negative effects on hundred kernel weight (14.00∼29.55%), and kernel length (4.21∼9.47%), whereas the effects of Dw6 on the kernel width were not uniform across three environments. By contrast, lines with Dw6 produced more productive tillers (10.11∼10.53%) than lines without Dw6. All these together suggested the potential yield penalty associated with Dw6 might be partially due to the decrease of kernel weight which is attributed largely to the reduction of kernel length. Eighty-one simple sequence repeat (SSR) primer pairs from chromosome 6D were tested, five of them were polymorphic in two parents and in two contrasting bulks, confirming the 6D location of Dw6. By using the five polymorphic markers, Dw6 was mapped to an interval of 1.0 cM flanked by markers SSR83 and SSR120. Caution should be applied in using this information since maker order conflicts were observed. The close linkages of these two markers to Dw6 were further validated in a range of oat lines. The newly developed markers will provide a solid basis for future efforts both in the identification of Dw6 in oat germplasm and in the determination of the nature of the gene through positional cloning.

Dataset Information

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes.

Publications

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure