Plant breeding in the 21 st century Arun Shunmugam, Laura James, Babu Pandey, Hossein Kahrood, Janine Croser, Brian Cullis, Ky Mathews, Surya Kant, Joe Panozzo, Sally Norton, Sukhjiwan Kaur & Garry Rosewarne
Plant breeding in the 21st century
Arun Shunmugam, Laura James, Babu Pandey, Hossein Kahrood, Janine Croser, Brian Cullis, Ky Mathews, Surya Kant, Joe Panozzo, Sally Norton, Sukhjiwan Kaur & Garry Rosewarne
The problem
• Challenges faced by plant breeders in the 21st century
- changing climate- growing world population- resource availability
• Australian example (Mba et al. 2012)- much of SA & EA production will decline by 2030 - reduced winter chill; drop in temperate fruit & nut production
Image adapted from, Jorasch. Transgenic Res (2019) 28: 81-86
Plant breeding milestones
Key milestones1760 – 1st hybridization1910s – bulk and recurrent selection1920s – pedigree, backcross &
mutation breeding1930s – chromosome doubling1940s – reciprocal recurrent
selection1960s – Ideotype breeding2000s – genomics based breeding2010s – gene editing based breeding
Image adapted from International Seed Federation
Milestones: Hickey et al. 2019, 37: 744-754
The solution
Accelerating genetic gains
Genetic gain over time(Rt) =Genetic variation (σA) x Selection intensity (i) x Selection accuracy (r)
Years per cycle(y)
Falconer and Mackay, 1996. Introduction to Quantitative Genetics.
Who are we at Ag VIC ?
L: 22 K haP: 39 K ha
L: 150 K haP: 50 K ha
L: 175 K haP: 70 K ha
L: 6 K haP: 20 K ha
Source:Australian crop report-Feb 2018 &Pulse breeding Australia
Australian field pea market classes
Australian lentil market classes
Kaspa
Germplasm enhancement
• Australian Grains Genebank (AGG)- Grains Innovation Park, Horsham, VIC- approx. 5000 lentil accessions- approx. 7500 field pea accessions
• International germplasm- ICARDA, Canadian & Mediterranean lines- e.g. machine harvest, heat tolerant lines- focussed identification of germplasm strategy (FIGS)
How do we incorporate them into our breeding programs?
Image source: Australian Grains Gene Bank
Biometrics for breeding• In collaboration with BBAGI & UOW
Type Source Field pea Lentil
Genetic % AdditiveGenetic Variance
75 90 • Using Optimal Design (OD)
Degree of co-ancestry in the breeding programsRep 1
Rep 2
Rep 3
• Advantages of partial reps
• Increasing %additive genetic variance decreases reliability (accuracy)
• Under simulation (blue)• No difference between DiGGer and Alpha,
i.e. using spatial in designs is not important
• OD (pedigree) is significant • Accuracy improves with multiple trials
• No cost to the breeding program!!!
Increasing Accuracy, r, through improved designs
• Cullis et al (in prep, 2019) JABES• od is an R library available from
www.mmade.org
Field phenomics for breeding
Stage3 Stage2 Stage1 PHIST Stage0
• Ground & UAV based phenotyping platforms- field based- collaboration with Phenomics group, Horsham- handheld instruments- large no. of lines & less labour intensive
• Traits of interest- vigour, plant count- flowering phenology- herbicide damage, disease scores- photosynthetic parameters
Image source: PPV, Horsham
Field phenotyping
field pea trials
Seed phenomics for breeding
3D seed information
• Image based seed analysis platform- collaboration with seed phenomics & quality group- EyeFOSS technology- visual & biochemical characterization- stage 2, 3 and NVT lines
• Assessment- seed size, colour, shape, grain weight- market class differentiation- gradient, texture- biochemical profiling- historical lines characterisation
EyeFOSS technology, Seed Phenomics & Quality, Horsham
In-house algorithm development
Images: Seed phenomics & quality group, GIP
Assisted Single Seed Descent
• aSSD- in vitro assisted single seed descent- in collaboration with UWA- rapid floral initiation in vivo + in vitro seed culture
• Generation advancement- field peas and lentils early generation advancement- 3 to 6 generations in a cycle (F2 to F6)- marker/phenotypic based screening- 800 genotypes advanced
How the breeding programs have deployed aSSD?
Images: F. Ribalta & J. Croser
Genomic selection based breeding
• Genomic selection (GS) in lentil breeding program- yield data from 8 years of MET- stage 2 lines as training populations- 70,000 high quality SNPs generated- develop prediction equations
• Deployment of GS - generate Genomic Estimated Breeding Values (GEBVs)- lentil crossing blocks based on GEBVs in 2018 (300 crosses)
- first GS based lentil field trial in 2019 (Horsham, VIC)
Training population
Phenotyping &
Genotyping
Train the model
Predicted GEBV
Genotyping breeding
population
Population selection
Bhat et al. Front. Genet. 2016, 7:221
Trait-based approaches
Trait Average % yield gain
No. of trials
Prediction accuracy
Vigour 15 19Brodal 7 10Asco 25 16 0.5-0.7
BGM Field 34 9BGM B. fabae 9 10 0.3-0.9
Shattering 5 2Boron 9 4 0.6-0.9
Seed Size/weight 12 30 0.7-0.8
• Genomic selection index to weight prediction equations for yield, vigour, Brodal, Ascochyta and BGM
• More traits to be added to the prediction equations
Herbicide damage Boron toxicity Botrytis Grey Mould (BGM) Ascochyta blight
GS based breeding pipeline*
CrossingYr.1
F1 summer GHYr.1
Conventional Breeding Program
Crossing
F1 summer GHGenotype
F1:2 Families
Yr.1
Yr.1
Yr.2
GS Based Breeding
Preliminary Yield TrialYr.4
Stage 1 TrialsYr.5
Stage 2 TrialsYr.6
Stage 3 TrialsYr.7
Yr.3 Row Trial (F3:4)
Yr.2 F2 Pod selection
Yr.2 F3 summer GH
National Variety TrialsYr.8-10
Preliminary Yield TrialYr.4
Stage 1 TrialsYr.5
Stage 2 TrialsYr.6
Stage 3 TrialsYr.7
Yr.3 Row Trial (F3:4)
Yr.2 F3 summer GH
National Variety TrialsYr.8-10
5000 lines
1000 lines
500 populations
5000 seeds
1000 lines
100 populations
5000 lines
400 lines
*stylised pipelines
Germplasm enhancement
Innovations in biometrics
High-throughput phenomics
Rapid generation advancement Genomic selection
Conventional breeding program
Integrated breeding program
Genetic variation (σA) 1 2Selection accuracy (i) 1 3Selection intensity (r) 1 4Years/cycle (Y) 10 1Genetic gain over time (Rt) 0.1 24
The Grand Scheme
Acknowledgment
• DPIRD, WA• GRDC
• Alternative crop rotations• Ascochyta field screening
• SARDI• Herbicide tolerance• Ascochyta screening• Rhizobium screening• Water use efficiency
• Curtin University• Ascochyta mapping
populations development and germplasm screening
• University of WA– aSSD to fast-track breeding
germplasm
• NSW DPI– Virus screening, landrace
discovery
• University of Wollongong
- Biometrics
• Ag VIC
- Southern Pulse Agronomy
- Plant pathology group