Dissecting the genetic basis of grain size in sorghum. Yongfu Tao DO NOT COPY. Postdoctoral Research Fellow

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1 Dissecting the genetic basis of grain size in sorghum Yongfu Tao Postdoctoral Research Fellow

2 Why study grain size? The importance of grain size: Key yield component Key quality issue for grain growers (% of small grains) Key quality issue for grain users (ease of processing) The objective of this study Identify genes for grain size Identify useful alleles for plant breeders to use to improve grain size of elite cultivars There is large variation in grain size in sorghum

3 Strategies for studying grain size P to G Phenotype G to P Mapping Populations Validating Gene

4 P High-density genetic markers G: mapping grain size genes GWAS Identify loci controlling grain size Manipulate grain size in sorghum breeding Grain size and weight phenotypic data Diversity panel population >900 genotypes Highly diverse population Comprises a large number of genotypes from sorghum conversion program Significant overlap with sorghum association panel in the USA Excellent point of entry to explore native variation Nested Association Mapping population >100 exotic parental lines back-crossed to a single elite genotype Less diversity than the diversity panel but provides more power and the opportunity to evaluate exotic alleles in an elite genetic background Whole genome sequence data available for parental lines providing the opportunity to impute an additional 1M SNPs

5 Materials and methods Population size Marker number Trials NAM Population 23 NAM families 1385 NAM progenys ~ 40K SNPs (1 SNP/16kb) 2014/15 season Hermitage: 1,508 plots Gatton: 900 plots 2015/2016 season Gatton: 1520 plots Diversity Panel 900 genotypes ~180K SNPs (1 SNP/3.5kb) 2015/2016 season Gatton: 880 plots Hermitage: 1400 plots

6 Trade-off between grain number and grain size Thousand kernel weight (g) Grain number per plant Environment types High yield low stress Low yield high stress Variation in grain weight independent of number still exists Some of this is due to the genetic potential to produce large grains and some of this is due to capacity to fill the grain Grain size is a function of potential maximum grain size and the capacity to fill it

7 Achieving maximum grain size Treatment Two heads within a plot were selected (having a similar maturity) and tagged at flowering For one of the panicles, half of the head was removed to achieve maximum grain size

8 PY Phenotypic evaluation pipeline Treatment C O SeedCount SC5000 Producer: Next Instruments Weighing O T Cleaning D O N Samples Measuring

9 Phenotypic evaluation pipeline Treatment SeedCount SC5000 Producer: Next Instruments Samples Cleaning Weighing Measuring thousand kernel weight seed thickness seed length seed width seed volume seed colour Phenotypic data

10 Phenotypic distribution of full head TKW Thousand kernel weight (g) Diversity panel 10+ fold of variation NAM population 5+ fold of variation Variation of full head TKW is larger in diversity panel than NAM

11 Phenotypic distribution in NAM TKW Volume Length Width Thickness Near normal distribution of these grain size related traits indicates multiple genetic loci underlying

12 Phenotypic evaluation Head type Thousand kernel weight (g) Volume (mm 3 ) Diversity panel NAM Increase of TKW and volume was observed after removal of half head

13 Variation in grain size increase in half heads +20% 0% +16% +6% The increase of grain size in half heads varies among genotypes Increase of TKW

14 Correlations among grain size related traits Length fh length Thickness fh thickne TKW fh tkw Volume Full head diversity panel fh volume 0.93 Width fh width High correlation among grain size traits indicates they share common genetic ground

15 Genome-wide association mapping GWAS analysis: FarmCPU (Liu et al., 2016) NAM: pedigree is used to control population structure Diversity panel: PCA calculated from pruned markers Significance threshold: 0.05/n, n represents the effective number of independent SNPs calculated by the GEC software tool (Li et al., 2012) Half head thousand kernel weight in diversity panel

16 QTL represented by green bars 19 HH TKW QTL identified in NAM population SBI-01 SBI-02 SBI-03 SBI-04 SBI-05 SBI-06 SBI-07 SBI-08 SBI-09 SBI-10 Effects are presented as deviations from the elite recurrent parent for lines carrying the exotic allele at the location of this QTL Thousand kernel weight (g) Average allelic effect across 23 NAM populations

17 QTLs detected in NAM and Diversity panel DP: diversity panel NAM: nested association mapping population HH FH In total, 59 thousand kernel weight QTLs were identified

18 QTLs detected in NAM and Diversity panel DP: diversity panel NAM: nested association mapping population QTLs detected in half heads and full heads are more likely to be associated with inherent genetic potential of grain size that is affected by source availability HH FH

19 QTLs detected in NAM and Diversity panel DP: diversity panel NAM: nested association mapping population QTLs detected only in full heads are more likely to be associated with the capacity to fill grain HH FH

20 Grain size related QTL Trait Half head Full head Unique regions TGW Volume Length Width Thickness Grain size is a complex trait affected by multiple genetic factors

21 Strategies for studying grain size P to G Phenotype G to P Mapping Populations Validating Gene

22 G P: identifying candidate genes for grain size A total of 114 grain size candidate genes were identified in sorghum A number of 56 grain size candidate genes were located within 2 cm vicinity of grain size QTL

23 GS3 orthologue in sorghum controlling grain size Thousand kernel weight (g) Diversity panel NAM GS3 is a well-known gene controlling grain size in rice (Ma et al., 2010). Sobic.001G (GS3 Orthologue in sorghum) affects grain size in sorghum and is: highly expressed in sorghum early inflorescence (Makita et al., 2015), under selection during sorghum domestication (Mace et al., 2013).

24 Acknowledgements Background IP and access to germplasm UQ QAAFI David Jordan Erik Van Oosterom Adrian Hathorn Emma Mace UQ Ian Godwin Jimmy Botella Yuri Trusov Bradley Campbell Stephen Mudge DAF Emma Mace Colleen Hunt Alan Cruickshank DAF technical team