Plant breeding in the 21st century - APC 2019 · 2019-11-05 · Plant breeding in the 21st century...

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