A 10-YEAR RESEARCH STRATEGYFOR PULSE CROPS

CHAPTER 1: BREEDING & GENETICS FOR IMPROVED PRODUCTIVITY & RESILIENCE

FAO, Rome22-23 November, 2016claire.domoney@jic.ac.uk

1. Defining research objectives

2. Tools & Approaches

3. Current capacities & competencies

Genetics to underpin breeding• Yield, resilience & other agricultural

production objectives• End uses………… exploiting synergies

Franke et al (2016)

Genetics to underpin breeding• End uses

- Nutrition- Processing & cooking preferences- On-farm use

Nature Rev Neurosci 14: 551-564

Normal villi

Villi in coeliac disease

Yield vs quality: increasing delivery of high quality nutrition per hectare

Beta-oxalylamino-L-alanine

Genetics to underpin breeding• End uses

- Nutrition- Processing & cooking preferences- On-farm use

Weed suppression

Standing ability

Mihailović et al. (2016) Legume Perspectives 13

Intercropping

Genetics to underpin breeding………… exploiting synergies

Cool seasonW

arm season

Adapted from Lavin et al (2005) Syst Biol 54: 575–594 by Foyer et al (2016) Nature Plants

1. Defining research objectives

2. Tools & Approaches

3. Current capacities & competencies

• Conserving & using genetic resources• Using sequence data in breeding

programmes• Crop modelling & foresight1.1 1.2 1.3 1.4 1.5 1.6 1U 2.1 2.2 U 3

Understanding germplasm & mutant resources- Novel mutant alleles of genes: fundamental & breeding

TTCGCCGCAAA--------------GTTTTGA

Sampson & Weiss (2013) Bioessays 36:34-38Lawrenson et al. (2015) Genome Biol. 16:258

- MAS/ SNP platforms/ KASPar assays- CRISPR/Cas9 genome editing (speed breed)

• Targeted mutagenesis• Gene insertion or replacement• Ease of design, flexible, affordable

& efficient

Non-homologous end joining

Homology-directed repair

• Conserving & using genetic resources• Using sequence data in breeding

programmes• Crop modelling & foresight

• Conserving & using genetic resources• Using sequence data in breeding

programmes• Crop modelling & foresight

Yield: integration of many traits• measure traits affecting yield in many agro-ecological

scenariosGhanem et al (2015) Agric Syst 137: 24–38

Probability of grain yield increase of simulating different sowing day-of-year (A) 201, (B) 229, (C) 243, and (D) 264 as compared to a sowing day of 152

• Crop modelling & foresight

1. Defining research objectives

2. Tools & Approaches

3. Current capacities & competencies

Diamond (2002) Nature 418: 700-707

Centres of pulse domestication

Implementing coherent breeding & genetics programmes to deliver productivity

Data from FAO (www.faostat.fao.org) & Foyer et al (2016) Nature Plants

GL species/category

severe drought risk normal low drought risk

Implementing coherent breeding & genetics programmes to deliver resilience

Dai (2013) Nature Climate Change 3: 52-58

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