Evolutionary History of Wild Barley (Hordeum vulgare subsp. spontaneum) Analyzed Using Multilocus Sequence Data and Paleodistribution Modeling

Abstract

Studies of Hordeum vulgare subsp. spontaneum, the wild progenitor of cultivated barley, have mostly relied on materials collected decades ago and maintained since then ex situ in germplasm repositories. We analyzed spatial genetic variation in wild barley populations collected rather recently, exploring sequence variations at seven single-copy nuclear loci, and inferred the relationships among these populations and toward the genepool of the crop. The wild barley collection covers the whole natural distribution area from the Mediterranean to Middle Asia. In contrast to earlier studies, Bayesian assignment analyses revealed three population clusters, in the Levant, Turkey, and east of Turkey, respectively. Genetic diversity was exceptionally high in the Levant, while eastern populations were depleted of private alleles. Species distribution modeling based on climate parameters and extant occurrence points of the taxon inferred suitable habitat conditions during the ice-age, particularly in the Levant and Turkey. Together with the ecologically wide range of habitats, they might contribute to structured but long-term stable populations in this region and their high genetic diversity. For recently collected individuals, Bayesian assignment to geographic clusters was generally unambiguous, but materials from genebanks often showed accessions that were not placed according to their assumed geographic origin or showed traces of introgression from cultivated barley. We assign this to gene flow among accessions during ex situ maintenance. Evolutionary studies based on such materials might therefore result in wrong conclusions regarding the history of the species or the origin and mode of domestication of the crop, depending on the accessions included.

Evolution of the Grain Dispersal System in Barley

“…The wild barley accessions most closely related to btr1-type cultivars were recovered from the southern Levant region and from Central Asia. The most genetically diverse extant stands of wild barley, along with the location of the most ancient archaeological finds, map to the southern portion of the Levant (Jakob et al, 2014;Zohary et al, 2013). One of the earliest finds of non-brittle barley was at Tell Aswad in modern day Syria, a site that dates from some 10,500 years ago (Tanno and Willcox, 2012).…”

“…One of the earliest finds of non-brittle barley was at Tell Aswad in modern day Syria, a site that dates from some 10,500 years ago (Tanno and Willcox, 2012). The southern Levant was a refugium for wild barley during the last glacial maximum (Jakob et al, 2014). Wild barley populations in Central Asia are not as genetically diverse as those in the Levant (Jakob et al, 2014) and archaeological finds are rare.…”

Correlations between Circadian Rhythms and Growth in Challenging Environments

“…For this study, we chose to focus on barley; as we note in the introduction, barley is an important crop and wild barley shows rich genetic variation. We used the Barley 1K (B1K) collection of wild barley accessions (Hübner et al, 2009(Hübner et al, , 2013 collected from a narrow range of latitudes, between 29°N and 33°N, in the southwestern part of the Fertile Crescent, an area with a high proportion of the total genetic variation of wild barley (Nevo, 1998;Jakob et al, 2014). It is one of the few collections of wild barley that comes directly from the wild without long-term storage, and the germplasm has been single seed descent propagated.…”

“…vulgare), and the subspecies readily cross. The richest genetic variation is found in wild barley (Jakob et al, 2014), which typically grows in areas with harsh environmental conditions (e.g. low water, poor soils, and heat stress).…”

Association mapping for morphological traits relevant to registration of barley varieties

“…The most probable number of sub-populations (clusters) was determined by plotting the quantity of ∆K as a function of K (Evanno et al, 2005) using the online software STRUCTURE HARVESTER (Earl & vonHoldt, 2012) to generate membership coefficient (Q) matrix. In order to assign each individual to a particular group a cut-off limit of 60% membership (Q-matrix) was considered (Jakob et al, 2014). Accessions with values below this threshold were considered as admixed individuals.…”