Neo-functionalization of a Teosinte branched 1 homologue mediates adaptations of upland rice.

The rice orthologue of maize domestication gene Teosinte branched 1 (Tb1) affects tillering. But, unlike maize Tb1 gene, it was not selected during domestication. Here, we report that an OsTb1 duplicate gene (OsTb2) has been artificially selected during upland rice adaptation and that natural variation in OsTb2 is associated with tiller number. Interestingly, transgenic rice overexpressing this gene shows increased rather than decreased tillering, suggesting that OsTb2 gains a regulatory effect opposite to that of OsTb1 following duplication. Functional analyses suggest that the OsTb2 protein positively regulates tillering by interacting with the homologous OsTb1 protein and counteracts the inhibitory effect of OsTb1 on tillering. We further characterize two functional variations within OsTb2 that regulate protein function and gene expression, respectively. These results not only present an example of neo-functionalization that generates an opposite function following duplication but also suggest that the Tb1 homologue has been selected in upland rice.

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection.

Selection for water-soluble carbohydrate accumulation and investigation of genetic × environment interactions in an elite wheat breeding population.

KEY MESSAGE: Water-soluble carbohydrate accumulation can be selected in wheat breeding programs with consideration of genetic × environmental interactions and relationships with other important characteristics such as relative maturity and nitrogen concentration, although the correlation between WSC traits and grain yield is low and inconsistent. The potential to increase the genetic capacity for water-soluble carbohydrate (WSC) accumulation is an opportunity to improve the drought tolerance capability of rainfed wheat varieties, particularly in environments where terminal drought is a significant constraint to wheat production. A population of elite breeding germplasm was characterized to investigate the potential for selection of improved WSC concentration and total amount in water deficit and well-watered environments. Accumulation of WSC involves complex interactions with other traits and the environment. For both WSC concentration (WSCC) and total WSC per area (WSCA), strong genotype × environment interactions were reflected in the clear grouping of experiments into well-watered and water deficit environment clusters. Genetic correlations between experiments were high within clusters. Heritability for WSCC was larger than for WSCA, and significant associations were observed in both well-watered and water deficit experiment clusters between the WSC traits and nitrogen concentration, tillering, grains per m2, and grain size. However, correlations between grain yield and WSCC or WSCA were weak and variable, suggesting that selection for these traits is not a better strategy for improving yield under drought than direct selection for yield.

Genome-Wide Associations for Water-Soluble Carbohydrate Concentration and Relative Maturity in Wheat Using SNP and DArT Marker Arrays.

Improving water-use efficiency by incorporating drought avoidance traits into new wheat varieties is an important objective for wheat breeding in water-limited environments. This study uses genome wide association studies (GWAS) to identify candidate loci for water-soluble carbohydrate accumulation-an important drought-avoidance characteristic in wheat. Phenotypes from a multi-environment trial with experiments differing in water availability and separate single nucleotide polymorphism (SNP) and diversity arrays technology (DArT) marker sets were used to perform the analyses. Significant associations for water-soluble carbohydrate accumulation were identified on chromosomes 1A, 1B, 1D, 2D, and 4A. Notably, these loci did not collocate with the major loci identified for relative maturity. Loci on chromosome 1D collocated with markers previously associated with the high molecular weight glutenin Glu-D1 locus. Genetic × environmental interactions impacted the results strongly, with significant associations for carbohydrate accumulation identified only in the water-deficit experiments. The markers associated with carbohydrate accumulation may be useful for marker-assisted selection of drought tolerance in wheat.

Inorganic Nutrients Increase Humification Efficiency and C-Sequestration in an Annually Cropped Soil.

Removing carbon dioxide (CO2) from the atmosphere and storing the carbon (C) in resistant soil organic matter (SOM) is a global priority to restore soil fertility and help mitigate climate change. Although it is widely assumed that retaining rather than removing or burning crop residues will increase SOM levels, many studies have failed to demonstrate this. We hypothesised that the microbial nature of resistant SOM provides a predictable nutrient stoichiometry (C:nitrogen, C:phosphorus and C:sulphur-C:N:P:S) to target using supplementary nutrients when incorporating C-rich crop residues into soil. An improvement in the humification efficiency of the soil microbiome as a whole, and thereby C-sequestration, was predicted. In a field study over 5 years, soil organic-C (SOC) stocks to 1.6 m soil depth were increased by 5.5 t C ha-1 where supplementary nutrients were applied with incorporated crop residues, but were reduced by 3.2 t C ha-1 without nutrient addition, with 2.9 t C ha-1 being lost from the 0-10 cm layer. A net difference of 8.7 t C ha-1 was thus achieved in a cropping soil over a 5 year period, despite the same level of C addition. Despite shallow incorporation (0.15 m), more than 50% of the SOC increase occurred below 0.3 m, and as predicted by the stoichiometry, increases in resistant SOC were accompanied by increases in soil NPS at all depths. Interestingly the C:N, C:P and C:S ratios decreased significantly with depth possibly as a consequence of differences in fungi to bacteria ratio. Our results demonstrate that irrespective of the C-input, it is essential to balance the nutrient stoichiometry of added C to better match that of resistant SOM to increase SOC sequestration. This has implications for global practices and policies aimed at increasing SOC sequestration and specifically highlight the need to consider the hidden cost and availability of associated nutrients in building soil-C.

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems.

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb) and on chromosome 8 (20.3-21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

Use of genotype x environment interactions to understand rooting depth and the ability of wheat to penetrate hard soils.

BACKGROUND: Root systems are well-recognized as complex and a variety of traits have been identified as contributing to plant adaptation to the environment. A significant proportion of soil in south-western Australia is prone to the formation of hardpans of compacted soil that limit root exploration and thus access to nutrients and water for plant growth. Genotypic variation has been reported for root-penetration ability of wheat in controlled conditions, which has been related to field performance in these environments. However, research on root traits in field soil is recognized as difficult and labour intensive. Pattern analysis of genotype × environment (G × E) interactions is one approach that enables interpretation of these complex relationships, particularly when undertaken with probe genotypes with well-documented traits, in this case, for the ability to penetrate a wax layer. While the analytical approach is well-established in the scientific literature, there are very few examples of pattern analysis for G × E interactions applied to root traits of cereal crops. SCOPE: In this viewpoint, we aim to review the approach of pattern analysis for G × E interaction and the importance of environment and genotype characterization, with a focus on root traits. We draw on our research on G × E interaction for root depth and related studies on genotypic evaluation for root-penetration ability. In doing so, we wish to explore how pattern analysis can aid in the interpretation of complex root traits and their interaction with the environment and how this may explain patterns of adaptation and inform future research. CONCLUSIONS: With appropriate characterization of environments and genotypes, the G × E approach can be used to aid in the interpretation of the complex interactions of root systems with the environment, inform future research and therefore provide supporting evidence for selecting specific root traits for target environments in a crop breeding programme.