**1. Introduction: Common bean – a model to explore the usefulness of wild relatives and landraces as a resource for the future**

In this chapter, we review the utility of genome-environment association approaches to infer the potential of wild accessions and landraces to make tropical crops more resistant to climate change, using the food crop common bean (*Phaseolus vulgaris* L.) as a model.

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**Figure 1.** Geographic distribution of wild relatives (light gray) and landraces (dark gray) of common bean and its diversity in terms of seed size, colors, and patterns. Modified from Cortés *et al*. [12].

Wild beans are thought to have diversified and adapted locally in South and Central

the southern and northern ends of each region gave origin to Andean and Mesoamerican

dissemination through the world, generating new secondary centers of diversity in Africa

Common bean is a source of nutrients and protein for over 500 million people in Latin America and Africa, and more than 4.5 out of 23 million hectares are grown in zones where drought is severe, such as in northeastern Brazil, coastal Peru, the central and northern high

increased drought due to climate change will reduce global crop production in greater than 10% by 2050 [11]. Increasing drought tolerance in common bean varieties is therefore needed. Characterizing geo-referenced landraces and wild accessions of common bean at the genetic

tions with a bioclimatic-based drought index offer an efficient path to identify adaptive varia

In the following two sections, we fist explain the theoretical bases behind genome-environment associations, as well as its caveats (Section 2), and later we exemplify it with concrete cases that used geo-referenced landraces and wild accessions of common bean to infer naturally available

**2. Strategies to infer adaptability of wild relatives and landraces to their** 

Understanding the genomic signatures associated with environmental variation provides insights

have demonstrated that genome-environment associations, which are associations between SNP alleles and accessions' environment of origin, can indeed be used to identify adaptive loci and predict phenotypic variation. For instance, Turner *et al*. [16] predicted genetic adaptive variation to serpentine soils in *Arabidopsis lyrata;* Hancock *et al*. [17] identified climate-adaptive genetic loci among a set of geographically diverse *Arabidopsis thaliana;* Fischer *et al*. [18] predicted adap

tive variation to topoclimatic factors in *Arabidopsis halleri;* Pluess *et al*. [19] predicted genetic local adaptation to climate at a regional scale in *Fagus sylvatica;* and Yeaman *et al*. [20] detected

This genome-environment association approach has also been explored in some crop acces

sions as a prospection strategy of germplasm, alternative to traditional phenotyping. For example, Yoder *et al*. [21] was able to capture adaptive variation to thermal tolerance, drought tolerance, and resistance to pathogens in *Medicago truncatula;* Lasky *et al*. [22] predicted geno

type-by-environment interactions to drought stress and aluminum toxicity in *Sorghum bicolor;* and Berthouly-Salazar *et al*. [23] uncovered genomic regions involved in adaption to abiotic

convergent local adaptation in two distantly related species of conifers.

and biotic stress on two climate gradients in *Cenchrus americanus*

1,

Lessons from Common Bean on How Wild Relatives and Landraces Can Make Tropical Crops...

**1**) and quantifying single-nucleotide polymorphism (SNP) allelic associa

7]. Both gene pools followed somewhat parallel pathways of

2], after which domestication in

http://dx.doi.org/10.5772/intechopen.71669

9, 10]. This situation may worsen as

–15]. Recent genomic studies in wild populations

.


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America from an original range in Central America [

3 –

lands of Mexico, and in Eastern and Southern Africa [

tions suitable to breed new drought-tolerant varieties.

into how species adapt to their environment [13

domesticates, respectively [

8].

level (e.g., **Figure**

**natural habitats**

adaptive variations (Section 3).

and Asia [

Wild beans are thought to have diversified and adapted locally in South and Central America from an original range in Central America [1, 2], after which domestication in the southern and northern ends of each region gave origin to Andean and Mesoamerican domesticates, respectively [3–7]. Both gene pools followed somewhat parallel pathways of dissemination through the world, generating new secondary centers of diversity in Africa and Asia [8].

Common bean is a source of nutrients and protein for over 500 million people in Latin America and Africa, and more than 4.5 out of 23 million hectares are grown in zones where drought is severe, such as in northeastern Brazil, coastal Peru, the central and northern highlands of Mexico, and in Eastern and Southern Africa [9, 10]. This situation may worsen as increased drought due to climate change will reduce global crop production in greater than 10% by 2050 [11]. Increasing drought tolerance in common bean varieties is therefore needed. Characterizing geo-referenced landraces and wild accessions of common bean at the genetic level (e.g., **Figure 1**) and quantifying single-nucleotide polymorphism (SNP) allelic associations with a bioclimatic-based drought index offer an efficient path to identify adaptive variations suitable to breed new drought-tolerant varieties.

In the following two sections, we fist explain the theoretical bases behind genome-environment associations, as well as its caveats (Section 2), and later we exemplify it with concrete cases that used geo-referenced landraces and wild accessions of common bean to infer naturally available adaptive variations (Section 3).
