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Barley Heads East: Genetic Analyses Reveal Routes of Spread Through Diverse Eurasian Landscapes

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Barley Heads East: Genetic Analyses Reveal Routes of Spread Through Diverse Eurasian Landscapes

Diane L Lister et al. PLoS One.

Abstract

One of the world's most important crops, barley, was domesticated in the Near East around 11,000 years ago. Barley is a highly resilient crop, able to grown in varied and marginal environments, such as in regions of high altitude and latitude. Archaeobotanical evidence shows that barley had spread throughout Eurasia by 2,000 BC. To further elucidate the routes by which barley cultivation was spread through Eurasia, simple sequence repeat (SSR) analysis was used to determine genetic diversity and population structure in three extant barley taxa: domesticated barley (Hordeum vulgare L. subsp. vulgare), wild barley (H. vulgare subsp. spontaneum) and a six-rowed brittle rachis form (H. vulgare subsp. vulgare f. agriocrithon (Åberg) Bowd.). Analysis of data using the Bayesian clustering algorithm InStruct suggests a model with three ancestral genepools, which captures a major split in the data, with substantial additional resolution provided under a model with eight genepools. Our results indicate that H. vulgare subsp. vulgare f. agriocrithon accessions and Tibetan Plateau H. vulgare subsp. spontaneum are closely related to the H. vulgare subsp. vulgare in their vicinity, and are therefore likely to be feral derivatives of H. vulgare subsp. vulgare. Under the eight genepool model, cultivated barley is split into six ancestral genepools, each of which has a distinct distribution through Eurasia, along with distinct morphological features and flowering time phenotypes. The distribution of these genepools and their phenotypic characteristics is discussed together with archaeological evidence for the spread of barley eastwards across Eurasia.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Heat map of pairwise genetic distances between three barley taxa.
Analysis included 351 vulgare, 142 spontaneum and 23 agriocrithon accessions, and was based on the allele frequencies of 19 SSR markers. Genetic distances were calculated with GenAlEx based on Nei's pairwise genetic distance (D) [57]. The paler colour (yellow) represents closer genetic distances, whereas darker colours (red) represent more distant relationships. The arrow indicates the Tibetan spontaneum accessions, which are genetically closer to all the cultivated barley accessions than to other spontaneum accessions.
Fig 2
Fig 2. Clustering of accessions of three barley taxa using InStruct analysis of SSR markers.
Based on allele frequencies for 19 SSR markers in 351 vulgare, 142 spontaneum and 23 agriocrithon accessions. Plots are of the most likely number of genepools, (K = 3 and K = 8) using probability measures and ΔK analysis (see S1 Fig). Each accession is represented by a vertical line with a proportion of its alleles derived from each modeled genepool, which are each represented by different colours. Accessions are ordered by taxon and then genepool.
Fig 3
Fig 3. Principle component analyses (PCAs) of individual accessions characterised by 19 SSR markers.
The results are based on allele frequencies for 19 SSR markers in 351 vulgare, 142 spontaneum and 23 agriocrithon accessions. Plots are of the first two components at (A) K = 3 and (B) K = 8 genepools. Each dot represents an accession (open circles, vulgare; closed circles, spontaneum; triangles, agriocrithon), coloured according to the genepool with the highest proportional membership ascribed in the K = 8 InStruct model.
Fig 4
Fig 4. Neighbour joining (N-J) tree constructed from SSR genotypes of three barley taxa.
Based on allele frequencies for 19 SSR markers in 351 vulgare, 142 spontaneum and 23 agriocrithon accessions, which were analysed using Nei’s genetic distance, and drawn using the prabclus package [60]. Accessions are coloured according to the genepool with the highest proportional membership ascribed in the K = 8 InStruct model (> 50%). Agriocrithon accessions are indicated as ‘+’. The green ellipse surrounds the spontaneum accessions.
Fig 5
Fig 5. Geographical distribution of genepools of three barley taxa, according to the K = 8 model.
Based on allele frequencies for 19 SSR markers in 351 vulgare, 142 spontaneum and 23 agriocrithon accessions. Each accession is depicted as a pie chart with the proportional membership of its alleles to each one of the eight genepools and was mapped according to its geographical coordinates. (A) vulgare (n = 351); spontaneum accessions (total n = 142) from (B) the Near East and Central Asia, and (C) Tibet; (D) agriocrithon accessions (n = 23). Maps generated using ArcMap v. 10.2, and NASA Blue Marble: Next Generation satellite imagery, which was produced by Reto Stöckli and obtained from NASA’s Earth Observatory (NASA Goddard Space Flight Center). See: http://earthobservatory.nasa.gov/Features/BlueMarble/.
Fig 6
Fig 6. Proposed routes of spread of six vulgare genepools, according to the K = 8 model.
Based on the geographical distribution of population structure in 351 vulgare accessions. Proposed routes of spread are indicated by solid or dashed lines, coloured according to the six vulgare genepools. Solid lines: barley genepool population structure clearly maps onto attested routes of agricultural spread. Dashed lines: routes of spread are more speculative, based on sparser distribution of barley genepools and/or archaeobotanical data. Map generated using ArcMap v. 10.2, and NASA Blue Marble: Next Generation satellite imagery, which was produced by Reto Stöckli and obtained from NASA’s Earth Observatory (NASA Goddard Space Flight Center). See: http://earthobservatory.nasa.gov/Features/BlueMarble/.

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Grant support

Funding source 1. "Food Globalization in Prehistory" project (FOGLIP), grant number 249642, awarded to Martin Kenneth Jones; funded by the European Research Council - FP7-IDEAS-ERC - Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013), url: http://cordis.europa.eu/programme/rcn/845_en.html. Funding source 2: “The Vavilov Institute and Cambridge: insights from historic crop resources”, grant number JP101321, awarded to Martin Kenneth Jones; funded by the Royal Society of London, International Joint Project 2010/R3 (Russia costshare), url: https://royalsociety.org/grants-schemes-awards/grants/international-exchanges/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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