Tapping Diversity From the Wild: From Sampling to Implementation

Abstract

The diversity observed among crop wild relatives (CWRs) and their ability to flourish in unfavorable and harsh environments have drawn the attention of plant scientists and breeders for many decades. However, it is also recognized that the benefit gained from using CWRs in breeding is a potential rose between thorns of detrimental genetic variation that is linked to the trait of interest. Despite the increased interest in CWRs, little attention was given so far to the statistical, analytical, and technical considerations that should guide the sampling design, the germplasm characterization, and later its implementation in breeding. Here, we review the entire process of sampling and identifying beneficial genetic variation in CWRs and the challenge of using it in breeding. The ability to detect beneficial genetic variation in CWRs is strongly affected by the sampling design which should be adjusted to the spatial and temporal variation of the target species, the trait of interest, and the analytical approach used. Moreover, linkage disequilibrium is a key factor that constrains the resolution of searching for beneficial alleles along the genome, and later, the ability to deplete linked deleterious genetic variation as a consequence of genetic drag. We also discuss how technological advances in genomics, phenomics, biotechnology, and data science can improve the ability to identify beneficial genetic variation in CWRs and to exploit it in strive for higher-yielding and sustainable crops.

Keywords: breeding; crop wild relative; genetic drag; introgression; sampling design.

FIGURE 1

Types of sampling designs for creating CWR germplasm collections. (A) Random sampling to obtain an uniform and unbiased representation of a heterogeneous environment, (B) transect sampling to represent the variation along an environmental gradient, (C) paired sampling in a heterogeneous environment to reduce the demographic effect on differentiation between populations, (D) clustered sampling to represent the within-site variation in comparison between sites, and (E) sampling at the same geographic location over different seasons or time points to represent changes in allele frequencies over time.

FIGURE 2

The process of implementing beneficial genetic variation identified in CWR in breeding. (A) Expected breeding timeline for different breeding strategies leveraging beneficial genetic variation that was already targeted in CWR. The given time frames are for annual crop breeding without the use of accelerating conditions such as greenhouse or winter nursery. (B) A conceptual pipeline for leveraging genetic variation identified in CWR in breeding, from sampling design and collection, followed with a common garden experiment for phenotyping, analysis of genomic, phenomic, and environmental data to target the causative mutation or tightly linked polymorphism. Once the trait was targeted gnomically, implementation into breeding material could be conducted through direct genome editing (CRISPR) or introgression.