Progress 12/01/16 to 11/30/17
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Academic and research community of US and around the world. Representative for food industry globally. Agricultural extenion personnell within USA and globally. Changes/Problems:No major changes in objectives, goals, and research approaches anticipated for 2017-18. What opportunities for training and professional development has the project provided?Bethany Love (PhD student registered Nottingham University) started on the project on August 2017. She will carry out the glasshouse experiments at Nottingham and contribute to the phenotyping of the HiBAP population and wider germplasm and associated GWAS analysis under Objectives 1-3 as outlined in the proposal. Dr. Jia Guo is newly appointed post-doc at University of Florida and is responsible for phenotyping of US soft wheat association panel at two locations in Florida. In addition, Dr. Guo will phenotype two double haploid population for marker conversion and validation, haplotype analysis and introgression of QTLs in different genetic background at UF. Dipendra Shahi is a Ph.D. student started on the project from Nov of 2016. He is full time on the project for phenotyping of association panel. Dipendra is funded through University of Florida. His responsibility is aligned with objectives 1 and 3 in the proposal. Student assistant Abdul Halim and Smita Rayamajhi were also trained through the project at UF. How have the results been disseminated to communities of interest?The results of 2016-17 WIll be presented at PAG meeting at San Diego and IWYP project directors meeting in 2018. What do you plan to do during the next reporting period to accomplish the goals?Objective 1 Develop new breeder-friendly molecular markers for grain partitioning traits (GWAS) At the CIMMYT IWYP Hub the HiBAP wil be phenotyped in 2017-8. While US soft wheat will be phenotyped at PSREU and NFREC, Florida. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Analysis of marker-trait associations will be carried out using TASSEL and R software (GAPIT package). For each QTL identified through GWAS analysis, 2-3 KASP markers will be developed, their haplotypes will be determined and validated in at least one linkage mapping population, and the validated KASP markers will be used for selecting the target QTL regions in breeding and for pyramiding the QTLs for grain traits through marker-assisted selection. Dr. Guihua Bai will lead breeder friendly KASP marker development. Dr. Babar and post-doc Dr. Jia Guo will be responsible for phenotyping of two double haploid populations at Florida for marker conversion and validation. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 2. Screen wider resources: CIMMYT exotic panel and US soft and hard wheat panel Wider germplasmwill be screened at the CIMMYT IWYP Hub to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis. The panel of wider germplasm will comprise selected genotypes of three other CIMMYT panels: a) Primary Synthetics Diversity panel (n=160). b) Bread wheat diversity panel (n=370). c) 7Ag.7DL translocation lines panel. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 3. Identify mechanisms determining grain traits and quantify genotype-by-environment interaction A set of 20 genotypes (10 representative lines of each of the HiBAP and US association panels) will be used as common checks for the two association panels in Objective 1. A more detailed set of physiological measurements will be carried out on these 20 genotypes at both UFL and IWYP hub to identify the mechanisms determining the grain sink traits and to quantify G x E and the heritability of the traits. The measurements will include: Growth and partitioning: Stem structural and soluble DM in internode 1 (peduncle), internode 2, internode 3 and internode 4+ at GS65 Spike partitioning at harvest (awns, rachis, glume, palea, lemma). Stem water soluble carbohydrate % at harvest. Photosynthetic capacity: Flag-leaf stomatal conductance weekly measured from GS51 to mid-senescence (GS75) The subset of 10 genotypes from the CIMMYT HiBAP will be assessed in a glasshouse experiment at UoN in 2017-8 for fruiting efficiency, grain number and plant growth regulator profiles. These results will also provide the basis for future GWAS analysis for these plant signalling traits.
What was accomplished under these goals?
Objective 1): Develop new breeder-friendly molecular markers for grain partitioning traits that permit photosynthesis products to be consistently translated to grain yield through genome-wide association study (GWAS) using two association panels in high biomass backgrounds, one panel comprising of US southern, eastern, and southeastern facultative soft wheats, and one CIMMYT spring wheats Two association panels (one panel at UFL, Gainesville and another panel at the CIMMYT IWYP Hub, Ciudad Obregon) were characterized for physiological traits that determine spike, lamina, and stem partitioning, fruiting efficiency, HI, above ground biomass, and grain yield. At UFL, the panel is comprised of 248 US soft red facultative wheat genotypes developed by different public and private wheat breeding programs. The panel was planted at Plant Science Research and Education Unit (PSREU), Citra, FL and North Florida Research and Education Center (NFREC), Quincy, FL for phenotypic characterization, The High Biomass Association Panel (HiBAP) was characterized at the CIMMYT IWYP Hub at Obregon, Mexico. The HiBAP panel comprised of 150 spring lines has been assembled by systematic screening of: (i) recent CIMMYT international bread wheat nurseries targeted to high yield environments, (ii) outstanding pre-breeding lines crossed and selected for high yield and biomass, and (iii) elite synthetic-derived lines. The HiBAP (High Biomass Association Panel) panel with high biomass was sown on 2 November 2016, in an alpha-lattice design with 4 replicates, at the International Maize and Wheat Improvement Center (CIMMYT) experimental station Norman E. Borlaug located in Yaqui Valley in Mexico. Physiological traits were measured at anthesis (GS65) +7d, when a full DM partitioning analysis was carried out (spike, leaf lamina and stem and leaf sheath DM proportions) including stem internode lengths: internode 2 and 3 (peduncle -1 and -2, respectively). At harvest, machine harvested yield, HI and yield components were assessed. The same traits were measured for US soft wheat panel at two locations (NFREC and PSREU) at anthesis+7d. Soft wheat panel was planted in a modified augmented design using three commercial varieties as repeated checks. HiBAP panel: Overall yields that ranged from 437 to 618 g m-2 (P<0.001) and above-ground biomass from 1123 to 1552 g m-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong relations were found amongst genotypes between grain yield and AGDM (r =0.46, P< 0.001) and HI (r = 0.35, P< 001). There was strong a trade-off between AGDM and HI (r = -0.57, P<0.001) There was an association between enhanced grains m-2 and reduced length of true-stem internode 3 (peduncle -2) (r = -0.29, P<0.01) at anthesis (GS65 +7d) and reduced length of true-stem internode 2 (peduncle -1) (r = -0.32; P<0.01). Internode 2 and 3 lengths were also negatively associated with SPI (P< 0.001; Fig.1a) There was a positive linear association between fruiting efficiency (grain per unit spike DM at GS65+7d; FE) and grains m-2 (r = 0.46, P<0.001). Considering the partitioning indices at GS65+7d, there was a strong negative linear association between spike PI and stem PI (R2 = -0.58, P< 0.001) but a weak negative association between spike PI and lamina PI (R2 = -0.04; P< 0.05). US Soft wheat panel: Gneotypes showed significant genetic variations for grain yield(P<0.001) and for above-ground biomassm-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong relations were found amongst genotypes between grain yield and AGDM (r =0.35***) and HI (r = 0.64***). There was signififcant trade-off between AGDM and HI (r = -0.21**). There was an association between enhanced grains m-2 and reduced length of true-stem internode 3 (peduncle -2) (r = -0.23**) at anthesis (GS65 +7d) . Spike partitioning index was strongly associated with grain yield (0.23**), HI (0.30***) and grains m-2 (0.25**). There was a positive linear association between fruiting efficiency and grains m-2 (r = 0.49***) and with harvest index (0.402***). Considering the partitioning indices at GS65+7d, there was a strong negative association between spike PI and stem PI (R2 = 0.42***) and between spike PI and lamina PI (R2 = 0.29***). These preliminary results suggest that genotypes with a longer internode 2 and 3 compete more with the spike for assimilate at GS65+7d and this is related to decreased Spike PI, grain number per unit area and HI. The genotyping of both panel is in progress by using the GBS (US soft wheat panel) and exom capture (CIMMYT HiBAP panel).The genotyping data will be used to identify QTLs for different traits. The genotyping information will be used for GWAS analysis. Genetic data will be analyzed using the TASSEL 5 software package to evaluate traits associations, evolutionary patterns, and linkage disequilibrium (GWAS). The genotyping of both panel is in progress and expected to completed by end of October. SNPs identified from Exon Capture and GBS that link to these QTLs will be converted into breeder-friendly KASP markers for breeding. Objective 2: Screen diverse sets of genetic resources including CIMMYT primary synthetic lines and US soft wheats for markers for grain traits determining grain partitioning in high biomass backgrounds. Wider germplasmwill be screened at the CIMMYT IWYP Hub to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis in 2017-18. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 3): Identify mechanisms determining grain partitioning traits and genotype-by-environment interaction through physiological dissection of subsets of wheat genotypes. A more detailed analysis was carried out on a subset of 30 genotypes in the HiBAP and 10 genotypes in the US soft wheat panel for true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2 and internode 3) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d.Genetic variation among genotypes was found for true stem (TS) and leaf sheath (LS) DM partitioning indices at each internode (internode PI) with a strong negative association between Spike PI and true-stem internode 3 PI.Genetic variation was found for all spike component partitioning indices (spike component DM/total spike DM, excluding grain) (P< 0.05). There were negative linear associations between FE and DM partitioning to each component (glumes, lemma, palea, awns PIs). This likely reflected that overall smaller spikes and spike growth was associated with higher FE. The strongest trade-off appeared to be between FE with lemma PI.Seed for a subset of 10 HiBAP lines has been sent to University of Nottingham and a glasshouse experiment is currently ongoing at Nottingham to investigate genetic variation in grain number and fruiting efficiency and associations with plant growth regulator profiles. 4) Design ideal plant ideotypes and establish pre-breeding crosses in the USA and CIMMYT wheat breeding programs. This research will be conducted at year 2018-19.
1. C. Li, C. Li, B. F. Carver, R. Bowden, Z. Su, Z. Wang, and G. Bai. 2017. Mapping of Quantitative Trait Loci for Leaf Rust Resistance in the Wheat Population Ning7840 � Clark. Plant Dis. https://doi.org/10.1094/PDIS-12-16-1743-RE
2. Y. Lu, R. L. Bowden, G. Zhang, X. Xu, A. K. Fritz, and G. Bai. 2017. Quantitative Trait Loci for Slow-Rusting Resistance to Leaf 1 Rust in Doubled Haploid Wheat Population CI13227 x Lakin. Phytopathology https://doi.org/10.1094/PHYTO-09-16-0347-R