Julian Ramirez-VillegasNora CastañedaColin KhouryPeter WenzlAndy Jarvis

Gap analysis for CGIAR crops

A gap analysis approach for CGIAR crops

1. Brief history of gap analysis2. Targets and outputs in the Genebank platform3. A simple method to assess the geography of

collections and their representativeness4. An opportunity to develop more

understanding of drivers of diversity at taxonomic, trait and genetic levels

Brief history of gap analysis• Term first coined for in situ wildlife conservation

• Various authors have adapted the concept for ex situ conservation analyses, most notably:• Maxted et al. (2008) –Vigna spp.• Ramirez-Villegas et al. (2010) –Phaseolus spp.• Shehadeh et al. (2013) –Lathyrus spp.

• 2008: Development of gap analysis methodology for crop wild relatives• 2008–2009: GPG2 analyses on key genepools (CWR + cultivated

materials)• 2011–2016: Global assessment of CWR conservation gaps

Gap analysis is a tool used in wildlife conservation to identify gaps in conservation lands (e.g., protected areas and nature reserves) or other wildlands where significant plant and animal species and their habitat or important ecological features occur (Scott and Schipper, 2006)

Gather occurrence

data

Make collecting

recommendations

Model distributions

Process data

Determine gaps in

collections

TaxonomicGeographicEcological

Choose species or

area81 crop

genepools 1076 crop wild relative taxa

(close relatives)

CWR gap analysis method

Lettuce Sunflower Sweet potato

PigeonpeaPotato Beans

81 crop genepools

Castañeda-Alvarez et al. (2016), Nat. Plants

Main findings – CWR gap analysis

Methodology for cultivated species

CIAT & IRRI (unpublished) –Sorghum bicolor – data from the ICRISAT genebank (through SINGER)

• Gather data from SINGER (Genesys), and GBIF

• Assess variation in density of accessions

• Assess environmental similarity between accessions and ref. dist.

1 2

3 • Mash out [2] and [3] to produce gap maps4

Genebank platform targets and outputsTargets• Representation of crop genepools in ex situ conservation quantified• Gaps in at least 5 crop genepools addressed

Outputs• Representation of genetic (G), taxonomic (T), geographical (Ge) and

environmental (E) diversity and traits improved

Key strategic points• Identification of duplicates using genomic information at accession level• Global analysis of diversity of collections and assess G, T, and Ge gaps• Use of GIS-based tools with focus on threatened germplasm

Part 1: simple method to assess geography of collections and their representativeness

Address major limitations in GPG2 approach by• Including other drivers of germplasm

distribution, e.g. language and culture, land-use change, seed and delivery systems• Use of more robust estimators of species

distributions through niche-based models• Enhance taxonomic resolution when

possible, e.g. look at races individually instead of at the entire species

Lasky et al. (2015) Sci. Adv.

Part 2: An opportunity to develop our understanding of drivers of diversity at taxonomic, trait and genetic levels • One key objective of ex situ conservation is to be able to have

material at hand for breeders to look for adaptive traits.• Hence, our approach should seek to address some key questions:• Which traits are priorities?• Which alleles control such traits?• What conditions the presence these alleles (geography, culture, environment)?• What is the ”global” (likely) and “conserved” distribution of the trait?• How is trait expression affected by environment (and management)? (i.e. GxExM)

• How important?• Where is it distributed?

Drivers of landrace genetic diversity

Sorghum in Africa• Evidence of cultural factors

shaping crop diversity.• Close association of linguistic

families and crop diversity.

Westengen et al 2014, PNAS

What conditions the presence these alleles (geography, culture, environment)?

Drivers of landrace genetic diversity

Maize in Oaxaca (México)• Traits vs genetics.• Culture and environment as

drivers of morphological and agronomic differences.• Genetic distance small.• Low population structure.

Perales et al 2005, PNAS

What conditions the presence these alleles (geography, culture, environment)?

• Analyzed 104 wild and 297 cultivated accessions• Drought stress indices and population

structure are useful for genome-wide genetic-environmental associations

Population structure and environmentWhat conditions the presence these alleles (geography, culture, environment)?

What is the global distribution of a trait and how is its expression affected by environment?

• Germplasm characterization provides “G” component of trait, with little “E” impact.• To predict distribution, we need “E”

impact on trait, too.• Analogues may help find areas with

characteristics which are similar to evaluation sites/years• Some traits may have small “E”

component• Breeding trials may help assessing

GxE for a sub-set of accessions

Sorghum 100-seed weight (CIAT & ICRISAT, unpublished)

100-seed weight

Climate analogues of Patancheru

Final remarks on approach

• Take stock on methods and current thinking on genetic diversity of CGIAR crops (e.g. a systematic literature review paper)• Need heavy input from genebank managers and their

groups, perhaps through visits (1-2 month) and joint work at their stations –key to tap into existing knowledge• Input from breeders for trait prioritization• Data organization will be key –a long-term investment• Too much we could do, and limited time, so need to

prioritize (e.g. at trait level)

Thanks!Julian Ramirez-Villegasj.r.villegas@cgiar.org