Advancing Harvest Index in Winter Wheat in High Biomass Backgrounds through Genomics Enabled Breeding

Lead Research Organisation: University of Nottingham
Department Name: Sch of Biosciences


Wheat is one of the three major staple cereal crops globally, with excess of 700m tonnes produced per year. Global demand for wheat is set to grow to 900m tonnes by 2050, and in order to meet that target, yields must increase by 1.6% per year, up from current annual increases of 1%. Research to improve biomass, particularly through the avenue of enhancing wheat photosynthesis may generate some yield increases, however this is unlikely to help hit yield targets unless the additional biomass generated is "useful biomass", or grain. Harvest index, (HI, grain dry matter (DM) yield / aboveground DM) is a measure of the ratio of useful biomass to non-useful biomass, and is a key component of yield. For winter wheat, HI values rarely exceed 0.55, and have not increased significantly since the 1990's, despite a theoretical limit as high as 0.65. A better understanding of the genetic basis of HI would allow for the improvement and stable expression of HI in higher biomass varieties, leading to a step change in genetic yield potential. There is significant evidence that yield potential is a sink limited trait, where carbon accumulation is limited by grain sink strength. Therefore improving grains per m2 is an important avenue for increasing the HI and yield potential of modern winter wheat. Fruiting efficiency is a measure of the number of grains set per unit of spike dry weight as anthesis, and is another trait of particular interest. This project is in collaboration with Drs Ed Byrne and Jacob Lage at KWS UK Ltd and will phenotype an association panel of elite KWS UK winter wheat doubled-haploid lines for grain yield, HI, 1000 grain weight and grains per m2; and grain partitioning and photosynthetic traits, including spike and stem-internode dry matter partitioning indices, fruiting efficiency (grains per unto spike DM at anthesis), canopy NDVI and leaf chlorophyll content (SPAD). The panel (150 lines), representing a stratified sampling across the KWS programme, will be genotyped. Marker-trait analysis will be performed via GWAS to identify markers for grain partitioning traits that can be used in breeding programs to select for high HI, high biomass genotypes.Wider germplasm including synthetic-derived and landrace-derived lines in the BBSRC Breders' Toolkit panel will also be screened (100 lines) and marker-trait analysis carried out to gain a better understanding of the range of potential loci. .
The genetic and physiological basis of grain partitioning in the KWS panel will be investigated further with an RNAseq experiment on a subset of DH lines, in conjunction with spike hormone concentration analysis at booting.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M008770/1 30/09/2015 31/10/2024
2102620 Studentship BB/M008770/1 30/09/2017 30/12/2021 James Norton Garner
Description The work so far, though data analysis is still ongoing, has demonstrated that novel stem-internode dry matter partitioning traits in wheat lines are indicators of spike fertility and grain number in UK winter wheat. Specifically, we have observed a negative relationship between length and dry weight of internodes 2 and 3 of the stem and spike dry weight, supporting previous work suggesting these internodes as the main sinks competing for assimilate with the spike during stem elongation. In addition, genetic variation in fruiting efficiency, a measure of grain number per unit of spike dry weight at anthesis, was highly correlated with final grain number per unit area. Furthermore, significant genetic variation in harvest index was observed, and this also correlated with grains per unit are and grain yield. This is the first time these associations have been shown in modern UK winter wheat material.

An ongoing GWAS of the field trial data over two years has uncovered several significant marker trait associations for these grain partitioning traits, including fruiting efficiency and stem internode 2 and 3 lengths. This raises several new research questions. Firstly whether the identified markers are previously published or are novel, and what candidate genes they are linked to. Additionally what are mechanisms by which any candidate genes linked to these markers effect plant phenotype and whether they are related to plant hormone concentrations in the spike at key growth stages. These questions are being explored further with additional field data to refine the GWAS and an ongoing RNA seq study on a subset of 8 contrasting lines to further identify and validate candidate genes. Training in the relevant skills for GWAS was obtained at KWS UK and by attending a bioinformatics workshop at the John Innes Centre.
Exploitation Route The identification of novel traits and markers will be useful to the UK wheat breeding community as selection criteria in future breeding programs, with the aim of increasing grain number and yield. This will initially be through our collaborating company, KWS UK, however markers could be licensed out to other breeding companies through appropriate IP agreements.

Future BBSRC grant applications using the project data are also planned to build on the work, for example, validating and/or cloning candidate genes.
Sectors Agriculture, Food and Drink

Description KWS partnerhsip 
Organisation KWS UK
Country United Kingdom 
Sector Private 
PI Contribution Two fieod experiments located at KWS Cambridge have been carried out in the project. The bulk of phenotyping work in these experiments was carried out by JG as a key part of my project thesis data set. In addition, glasshouse experiments to examine traits in detail and to sample for RNAseq analysis and hormone analysis are conducted jointly with trait analaysis at Nottingham but samples submitted for transcriptomics analysis at KWS.
Collaborator Contribution Training in phenotyping and breeding techniques were provided at KWS UK. Field space, management and plot monitoring of the wheat association mapping field trials, financial contributions including both cash for consumables and the transcriptomics analysis in the RNAseq experiment.
Impact To date the main outputs are field datasets in 2017-8 and 2018-9 for wheat grain number traits. The collaboration is multidisciplinary: physiology, molecular genomics, Plant breeding.
Start Year 2017