Using archaeogenomic and computational approaches to unravel the

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Using archaeogenomic and computational approaches to unravel the

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Using archaeogenomic and computational approaches to unravel the history of ... Cluster analysis of archaeological Gossyium barbadense read variants.

Using archaeogenomic and computational approaches to unravel the history of local adaptation in crops Robin G. Allaby1*, Rafal Gutaker1, Andrew C. Clarke1, Neil Pearson1, Roselyn Ware1, Sarah A. Palmer1, James L. Kitchen2 and Oliver Smith1.

1. School of Life Sciences, Gibbet Hill Campus, University of Warwick, United Kingdom, CV4 7AL 2. Rothamsted Research Station, Harpenden, Hertfordshire, United Kingdom, AL5 2JQ

Supplementary Figures

Figure S1. A. Probability landscape of population survival (p) for a given number of loci (g) under selection coefficient (s) for an inbreeding cereal such as barley. B. Linear regression of the maximum selection load (total amount of selection) carried across loci for different selection coefficients without any population extinction in simulations (from Allaby, Fuller & Kitchen 2014).

Figure S2. Genomic profiles of Gypsy-, Copia-, and LINE-type retrotransposons in modern and archaeobotanical cotton. (Palmer et al. 2012b).

Figure S3. Cluster analysis of archaeological Gossyium barbadense read variants mapped to Arabidopsis thaliana metabolic Pathways. Reads were mapped to the KEGG A. thaliana metabolic pathway. The number of major nodes between reads were used to create a distance metric between variants, which were then grouped by

K-median clustering using the “Pheatmap” package in R. Groupings have 7 nodes or fewer between all points.

Figure S4. Archaeological Gossyium barbadense read variants mapped to Arabidopsis thaliana metabolic Pathways. Variants are represented by stars, for colour key see Figure S3.

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