Genetic association of stomatal traits and yield in wheat grown in low rainfall environments

Published: 4 July 2016Background: In wheat, grain filling is closely related to flag leaf characteristics and function. Stomata are specialized leaf epidermal cells which regulate photosynthetic CO2 uptake and water loss by transpiration. Understanding the mechanisms controlling stomatal size, and their opening under drought, is critical to reduce plant water loss and maintain a high photosynthetic rate which ultimately leads to elevated yield. We applied a leaf imprinting method for rapid and non-destructive phenotyping to explore genetic variation and identify quantitative traits loci (QTL) for stomatal traits in wheat grown under greenhouse and field conditions. Results: The genetics of stomatal traits on the adaxial surface of the flag leaf was investigated using 146 double haploid lines derived from a cross between two Australian lines of Triticum aestivum, RAC875 and Kukri. The drought tolerant line RAC875 showed numerous small stomata in contrast to Kukri. Significant differences between the lines were observed for stomatal densitity and size related traits. A negative correlation was found between stomatal size and density, reflecting a compensatory relationship between these traits to maintain total pore area per unit leaf surface area. QTL were identified for stomatal traits on chromosomes 1A, 1B, 2B, and 7A under field and controlled conditions. Most importantly some of these loci overlap with QTL on chromosome 7A that control kernel number per spike, normalized difference vegetation index, harvest index and yield in the same population. Conclusions: In this first study to decifer genetic relationships between wheat stomatal traits and yield in response to water deficit, no significant correlations were observed among yield and stomatal traits under field conditions. However we found some overlaps between QTL for stomatal traits and yield across environments. This suggested that stomatal traits could be an underlying mechanism increasing yield at specific loci and used as a proxy to track a target QTL in recombinant lines. This finding is a step-forward in understanding the function of these loci and identifying candidate genes to accelerate positional cloning of yield QTL in wheat under drought.Fahimeh Shahinnia, Julien Le Roy, Benjamin Laborde, Beata Sznajder, Priyanka Kalambettu, Saba Mahjourimajd, Joanne Tilbrook and Delphine Fleur

Dissecting genetic variation for nitrogen use efficiency in wheat

Nitrogen (N) is essential for high grain yield (GY) in cereals. A major aim of breeding programs is to increase GY while minimising the level of external inputs, such as N fertilisation. Nitrogen Use Efficiency (NUE) is a complex trait controlled by both genetic and environmental factors resulting in variation depending on seasonal growth conditions. Only 30-50% of N supplied is actually taken up by the plants with the extra N lost through run-off, leaching, denitrification and gas emission. These losses have a negative environmental impact, leading to surface and underground water pollution, algae blooms and intensifying global warming. In addition, nitrogen (N) application is costly further emphasising the importance of NUE improvement to reduce the economic and environmental issues associated with N application. NUE of wheat is important in all production areas but little is known about genetic variation for NUE in low-yielding environments such the Mediterranean-type climate of Southern Australia with low rainfall and high temperatures during critical growth periods. Research described in this thesis evaluated variation in NUE in Australian wheat germplasm and then to identify loci regulating NUE traits in a bi-parental mapping population of RAC875/Kukri. Improvement in NUE will require the integration of physiological and molecular aspects of N status in plants under different growth conditions: the highly variable conditions of field trials and controlled environments such as under hydroponics. The assessment of NUE and N response under both field and controlled conditions could facilitate the identification of traits and QTL and lead to the discovery of candidate genes underlying the traits. The first step of this research involved NUE traits and N response assessment of Australian cultivars in different environments, with varying N input. Genetic variation for NUE was identified in Australian spring wheat cultivars, and the cultivars were ranked for their N-efficiency and responsiveness. The dissection of genetic variation for NUE was investigated in the RAC875/Kukri population across six field trials between 2011 and 2013 covering 16 environment by treatment combinations. Nitrogen responsiveness was compared with N efficiency and the genotypes were ranked for the consistency of a positive response and high efficiency of N use versus negative responsiveness and low efficiency. Quantitative Trait Loci (QTL) analysis identified the genome regions associated with GY, grain quality and responsiveness to N. In addition, specific-environment associated N QTL were identified. A QTL on chromosome 2A was detected for most of traits studied and across multiple environments. Further stable QTL were identified on chromosomes 1A, 1B, 2A, 3D, 7A and 7B for GY across environments. The physiological response to N was studied at the early stages of growth for selected lines in a hydroponics system that allowed the measurement of N uptake and utilisation. The aim of the experiments was to investigate the physiological basis for the effects seen in the field trials. However, no consistent response was seen in these studies suggesting that future work should focus on later growth stages. To conclude, the results showed significant genetic variation and transgressive segregation for NUE despite the complex nature of the effect of N on grain yield and quality traits. These genome regions can be used to support marker assistance selection (MAS) for improved NUE and for cloning genes underlying the loci affecting NUE in wheat. The results show that selection for improved NUE is possible and also provide a base for further molecular and physiological studies on efficient use of applied N.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Agriculture, Food and Wine, 2015

The Genetic Control of Grain Protein Content under Variable Nitrogen Supply in an Australian Wheat Mapping Population

<div><p>Genetic variation has been observed in both protein concentration in wheat grain and total protein content (protein yield). Here we describe the genetic analysis of variation for grain protein in response to nitrogen (N) supply and locate significant genomic regions controlling grain protein components in a spring wheat population. In total, six N use efficiency (NUE) field trials were carried out for the target traits in a sub-population of doubled haploid lines derived from a cross between two Australian varieties, RAC875 and Kukri, in Southern and Western Australia from 2011 to 2013. Twenty-four putative Quantitative Trait Loci (QTL) for protein-related traits were identified at high and low N supply and ten QTL were identified for the response to N for the traits studied. These loci accounted for a significant proportion of the overall effect of N supply. Several of the regions were co-localised with grain yield QTL and are promising targets for further investigation and selection in breeding programs.</p></div

The Genetic Control of Grain Protein Content under Variable Nitrogen Supply in an Australian Wheat Mapping Population - Fig 1

<p>Grain protein concentration (GPC, %) (A) and Protein yield (PY, kg ha-1) (B) of RAC875 and Kukri in nitrogen (N) use efficiency field trials across Australian sites. The vertical error bars represent the standard errors of the predicted means after spatial analysis.</p

Phenotypic performance of RAC875 × Kukri population for protein-related traits across southern Australian trial sites in three seasons (2011–2013).

<p>Phenotypic performance of RAC875 × Kukri population for protein-related traits across southern Australian trial sites in three seasons (2011–2013).</p

The location, climate and basic soil characteristics, growing conditions and average grain yield (GY, kg ha^-1) of five southern Australian trial sites used for nitrogen use efficiency field trials in this study.

<p>The location, climate and basic soil characteristics, growing conditions and average grain yield (GY, kg ha^-1) of five southern Australian trial sites used for nitrogen use efficiency field trials in this study.</p

Comparison of the loci identified in this study with previous reports of loci associated with grain protein or nitrogen content.

<p>The loci identified in this study are shown on the right of each stylized chromosome while those found in previous studies are labelled as GNC (Grain nitrogen/protein content) on the left. The positions are only approximate since a direct alignment of the loci is not possible since the markers and maps are very different and the studies vary greatly in their level of genetic resolution. The superscript numbers before each GCN loci refer to the reference.</p

Phenotypic correlation coefficients of grain yield (GY, kg ha^-1) and grain protein concentration (GPC, %) for all genotypes, parental lines and doubled haploid lines, in nitrogen use efficiency field trials in southern Australia, 2011–2012.

<p>Correlation coefficients of GY and GPC in the trials are in bold.</p

Additional file 4: Figure S3. of Genetic association of stomatal traits and yield in wheat grown in low rainfall environments

Morphological features of a single stomata. Arrows indicate aperture length (APL) and width (APW) and guard cell length (GCL) and width (GCW). Aperture area (APA) and guard cell area (GCL) were calculated by multiplying the length and width of the rectangle. (DOCX 261 kb

Additional file 1: Figure S1. of Genetic association of stomatal traits and yield in wheat grown in low rainfall environments

Frequency distribution of phenotypes for stomatal size related traits and yield in the RAC875/Kukri DH lines based on means obtained over each experiment. a) Lameroo, b) Roseworthy, c) Well watered conditions in the glasshouse, d) Drought conditions in the glasshouse. Arrows indicate phenotypic values of RAC875 (R) and Kukri (K). (PPTX 264 kb