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Additional file 2: Table S1. The results of 80 cultivated and wild rice genomes survey. Table S2. Summary of Nanopore Technologies sequencing data of JX1 and SL1 genome. Table S3. Summary of sequencing assembly data of JX1 and SL1 genome. Table S4. Details of the 12 pseudo-chromosomes of JX1 and SL1. Table S5. Summary of sequencing evaluation data of JX1 and SL1genome. Table S6. Repetitive elements in JX1 and SL1 genomes. Table S7. The information of full length transcriptome sequencing data of JX1 and SL1. Table S8. The transcriptome sequencing data from different tissues of JX1 and SL1 based on Illumina sequence. Table S9. Annotated predictions of gene structure. Table S10. Summary of the assembly of 13 cultivated and wild rice genomes. Table S11. The SV information for 13 cultivated and wild rice. Table S12. Sequence information for structural variation. Table S13. The annotation of SV. Table S14. The sample list for SV population analysis. Table S15. The significant association sites based on GWAS data. Table S16. 49 cloned genes overlapping with DELs (>10 kb) region.

Additional file 1: Fig. S1. (a) Geographic origins of cultivated and wild rice accessions in this study. (b) SNP-based phylogenetic tree based on short-read sequencing of more than 600 cultivated and wild rice accessions. Major taxonomic groups are marked by colored lines along the circumference. Colored dots indicate a subset of the 80 accessions selected for genome survey. Fig. S2. Chromosome karyotyping of JX1 (a) and SL1 (b) in meiosis period in the root tip. Fig. S3. Distribution of short reads mapped on corresponding genome assemblies. (a) is JX1 and (b) is SL1. Fig. S4. Dot plots of assembly comparisons between JX1 and Nipponbare (a) and between SL1 and Nipponbare (b). Fig. S5. Relationship between SVs and their surrounding genes. Fig. S6. Venn-like diagram presenting the numbers of SVs among indica, japonica, and wild rice. Fig. S7. For each SV, the distance to the telomeric (a) and centromeric regions (b) of each chromosome was calculated and divided into 100-kb bins. (c) SV densities of short/long chromosome arms in continuous 200-kb windows. Significance was tested by Fisher’s exact test; NA indicates p > 0.05. Fig. S8. PCA plots of cultivated and wild rice accessions based on SV diversities. The three subgroups are indicated in different colors at the top of the Fig. Fig. S9. Phenotypes of the rice population used for GWAS, include FLL (flag leaf length), FLW (flag leaf width), GL (grain length), GW (grain width), PB (primary branch), PH (plant height), SB (secondary branch), and TGW (1000 grain weight). Fig. S10. GWASs on FLL, FLW, GL, GW, PB, PH, SB, and TGW using the compressed MLM. Manhattan plots for these phenotypes. The log10-transformed P values from a genome-wide scan were plotted against the position on each of the 12 chromosomes. Quantile-quantile plot for these phenotypes. The horizontal axis shows log10-transformed expected P values, and the vertical axis indicates log10-transformed observed P values. Fig. S11. (a) XP-CLR scores calculated by SNPs comparing wild rice with cultivated rice. (b) XP-CLR scores calculated by SVs comparing wild rice with cultivated rice. Chromosomes are painted with either blue or orange and the black line is defined using the top 5% XP-CLR scores.

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Additional file 2: Figure S2. Confusion matrix from random forest model predictions of species identity based on FA composition for all Camelina species. Colored boxes represent the number of new observations categorized by the random forest model, such that correct determinations are represented along the diagonal, all other cells indicate incorrect determinations. Boxes are shaded such that boxes which are darker blue represent a higher proportion of the total number of samples for each species.

Principal component analysis (PCA) plot of 1003 rice accessions including weedy, cultivated and wild rice by the first and second eigenvectors. Figure S2. Distribution of D-statistic (±s.e.) across 12 chromosomes for Malaysian weedy rice. Figure S3. Genetic diversity (π) of whole-genome and domestication-related genes in wild, cultivar and weedy rice populations. Figure S4. The ratio of allele frequency for SNPs targets of domestication selection versus non-targets for indica type. Figure S5. Comparisons of genetic diversity for domestication and improvement genes between weedy and cultivated rice. Figure S6. Effective population size change of indica and aus cultivated and weedy rice. Figure S7. Phylogenetic relationship of different weedy rice groups and possible introgression inferred from TreeMix analysis. Figure S8. Heterozygosity level evaluated by observed heterozygosity across wild, cultivated and weedy rice populations. Figure S9. Weedy rice with ALS-inhibiting herbicide resistance. Figure S10. Geographic origins of weedy rice traced by Kinship analysis. Figure S11. Genomic differentiation regions for different weedy populations compared to their counterparts in cultivated rice. Figure S12. Numbers of SNPs that are shared or unique among weedy and cultivated rice. Figure S13. Characterization of one of the genes (RAL6) encoding allergenic proteins in the de-domestication genomic block.

Additional file 4: Figure S4. ADMIXTURE results displayed with pong at a range of K = 1–10, with 10 iterations per K. Individuals are divided into subgroups based on country of origin.

Additional file 5: Fig\ure S5. PCA generated from the final SNP dataset of C. microcarpa accessions used in ADMIXTURE analyses. Colored dots represent individual’s country of origin, colored ellipses represent population identities as determined from ADMIXTURE.

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Additional file 7: Figure S7. PCA generated from 19 BioClim variables determined from GPS coordinates for all accessions of Camelina in which seed oil composition was also analyzed. Red arrows are drawn according to weight and direction of effect for each climatic variable.

Additional file 1: Figure S1. Random forest model importance plots for individual FAs comprising total seed oils in A) all Camelina species examined and B) populations of C. microcarpa. Mean decrease in accuracy is a measure of model accuracy decrease when individual factors are removed, with larger values indicative of more important factors.

Additional file 6: Figure S6. Box and whisker plot of fatty acid abundances detected in C. microcarpa genetic populations determined via gas chromatography.

Additional file 3: Figure S3. NDMS plot of environments for different species of Camelina. Geographical locations of C. microcarpa individuals indicated with shapes as follows, circle = Caucasus, triangle = Ukraine, square = USA. Euclidean distance was used to construct the plot, stress = 0.01399579.

Additional file 8: Figure S8. Fatty acid composition of three C. sativa accessions in 12 °C (blue) and 30 °C (orange) growth conditions as inferred by GC-MS. Error bars ±1 SD (n = 9).

Supplementary Information of the manuscript entitled "When West meets East: The origins and spread of weedy rice between continental and island Southeast Asia" Supplementary Information Figure S1. Representatives of five groups of weedy and cultivated rice accessions classified according to seed morphological features: (A) strawhulled, awnless (SH); (B) strawhulled, awned (SHA); (C) brown-striped-hulled, awnless types (BR); (D) brown-striped-hulled, awned (BRA); (E) cultivars. Figure S2. STRUCTURE analysis of the Sabah, Peninsular Malaysian, and other countries’ rice samples. (A) Plot of Ln P(D) vs. K. showed an increase in the posterior probability [Ln P(D); L(K)] for a K value up to 20 populations. (B) Plot of ΔK vs. K. Value of ΔK at K = 2 (511.7) was removed to ease illustrations of the second highest peak at K = 5 in the plot. (C) deltaK values calculated as a function of K. ΔK at K = 5 is highlighted in yellow (ΔK = 7.813). (D) Alternate outcomes at K = 4. (E) Alternate outcomes at K = 10.Figure S3. Principal Coordinate Analysis (PCoA) plot of Sabah, Peninsular Malaysia, and worldwide rice samples. (A) PCoA analysis of 358 rice accessions from Sabah (weedy, cultivated and landrace rice), Peninsular Malaysia (cultivars), Indonesian Kalimantan (landrace), Indonesian Java (landrace), Brunei (landrace), Philippines (landrace), East Malaysian Sarawak state (landrace), Thailand (wild rice), Myanmar (wild rice) and US (tropical japonica). (B) PCoA analysis of 478 rice accessions from Sabah (weedy, cultivated and landrace rice), Peninsular Malaysia (weedy and cultivated rice), Thailand (wild rice), Myanmar (wild rice) and US (tropical japonica). Keys to rice sample names: SbCV, Sabah cultivated rice; PMCV, Peninsular Malaysia cultivated rice; SbSH, Sabah weedy rice with strawhulls and no awns; PMSH, Peninsular Malaysia weedy rice with strawhulls and no awns; PMmSH, Peninsular Malaysia weedy rice with intermediate strawhull and no awns; PMmSHA, Peninsular Malaysia weedy rice with intermediate strawhulls and awns; SbSHA, Sabah weedy rice with strawhulls and awns; PMSHA, Peninsular Malaysia weedy rice with strawhulls and awns; SbBR, Sabah weedy rice with browhulls and no awns; PMBR, Peninsular Malaysia weedy rice with browhulls and no awns; SbBRA, Sabah weedy rice with browhulls and awns; PMBRA, Peninsular Malaysia weedy rice with browhulls and awns; PMBH, Peninsular Malaysia weedy rice with blackhulls and no awns; PMBHA, Peninsular Malaysia weedy rice with blackhulls and awns; TropJap, tropical japonica; SbLr, Sabah landrace accessions; PMOr, Peninsular Malaysia Oryza rufipogon; SEAOr, Southeast Easian O. rufipogon; KN, Indonesian Kalimantan; JV, Indonesian Java; BN, Brunei; PHI, Philippines; SW, Sarawak; TropJap, tropical japonica. Figure S4. Haplotype network relationships for the An-1 haplotypes identified in this study (Table S6). Each circle represents a haplotype and circle size is proportional to haplotype frequency. Vertical line indicates number of SNP. Supplementary Table S1. Population code, location, number of sample, range of coordinates, coexisting rice varieties of the weedy rice populations and cultivated rice samples used in this study. Supplementary Table S2. Distribution, morphotype code and number of sample of weedy rice accessions used according to hull color and awn presence. Supplementary Table S3. Oryza accession information, haplotype of the An-1 gene, and coefficents of ancestry inferred by STRUCTURE. Supplementary Table S4. Genetic diversity in Sabah weedy rice samples grouped by sampling location. Abbreviations of genetic diversity parameters are as follows: P, percentage of polymorphic loci; Ho, observed heterozygosity; He, expected heterozygosity; I, Shannon diversity index. Supplementary Table S5. Pairwise population FST values generated by location-based clustering.Supplementary Table S6. Compilation of the ten mutations identified in the sequenced region of An-1 gene. Mutations n2*, n4*, and n6* are functional nucleotide polymorphisms (FNPs) identified in Luo et al. (2013) study.

Supplementary Information of the manuscript entitled "When West meets East: The origins and spread of weedy rice between continental and island Southeast Asia" Supplementary Information Figure S1. Representatives of five groups of weedy and cultivated rice accessions classified according to seed morphological features: (A) strawhulled, awnless (SH); (B) strawhulled, awned (SHA); (C) brown-striped-hulled, awnless types (BR); (D) brown-striped-hulled, awned (BRA); (E) cultivars. Figure S2. STRUCTURE analysis of the Sabah, Peninsular Malaysian, and other countries’ rice samples. (A) Plot of Ln P(D) vs. K. showed an increase in the posterior probability [Ln P(D); L(K)] for a K value up to 20 populations. (B) Plot of ΔK vs. K. Value of ΔK at K = 2 (511.7) was removed to ease illustrations of the second highest peak at K = 5 in the plot. (C) deltaK values calculated as a function of K. ΔK at K = 5 is highlighted in yellow (ΔK = 7.813). (D) Alternate outcomes at K = 4. (E) Alternate outcomes at K = 10.Figure S3. Principal Coordinate Analysis (PCoA) plot of Sabah, Peninsular Malaysia, and worldwide rice samples. (A) PCoA analysis of 358 rice accessions from Sabah (weedy, cultivated and landrace rice), Peninsular Malaysia (cultivars), Indonesian Kalimantan (landrace), Indonesian Java (landrace), Brunei (landrace), Philippines (landrace), East Malaysian Sarawak state (landrace), Thailand (wild rice), Myanmar (wild rice) and US (tropical japonica). (B) PCoA analysis of 478 rice accessions from Sabah (weedy, cultivated and landrace rice), Peninsular Malaysia (weedy and cultivated rice), Thailand (wild rice), Myanmar (wild rice) and US (tropical japonica). Keys to rice sample names: SbCV, Sabah cultivated rice; PMCV, Peninsular Malaysia cultivated rice; SbSH, Sabah weedy rice with strawhulls and no awns; PMSH, Peninsular Malaysia weedy rice with strawhulls and no awns; PMmSH, Peninsular Malaysia weedy rice with intermediate strawhull and no awns; PMmSHA, Peninsular Malaysia weedy rice with intermediate strawhulls and awns; SbSHA, Sabah weedy rice with strawhulls and awns; PMSHA, Peninsular Malaysia weedy rice with strawhulls and awns; SbBR, Sabah weedy rice with browhulls and no awns; PMBR, Peninsular Malaysia weedy rice with browhulls and no awns; SbBRA, Sabah weedy rice with browhulls and awns; PMBRA, Peninsular Malaysia weedy rice with browhulls and awns; PMBH, Peninsular Malaysia weedy rice with blackhulls and no awns; PMBHA, Peninsular Malaysia weedy rice with blackhulls and awns; TropJap, tropical japonica; SbLr, Sabah landrace accessions; PMOr, Peninsular Malaysia Oryza rufipogon; SEAOr, Southeast Easian O. rufipogon; KN, Indonesian Kalimantan; JV, Indonesian Java; BN, Brunei; PHI, Philippines; SW, Sarawak; TropJap, tropical japonica. Figure S4. Haplotype network relationships for the An-1 haplotypes identified in this study (Table S6). Each circle represents a haplotype and circle size is proportional to haplotype frequency. Vertical line indicates number of SNP. Supplementary Table S1. Population code, location, number of sample, range of coordinates, coexisting rice varieties of the weedy rice populations and cultivated rice samples used in this study. Supplementary Table S2. Distribution, morphotype code and number of sample of weedy rice accessions used according to hull color and awn presence. Supplementary Table S3. Oryza accession information, haplotype of the An-1 gene, and coefficents of ancestry inferred by STRUCTURE. Supplementary Table S4. Genetic diversity in Sabah weedy rice samples grouped by sampling location. Abbreviations of genetic diversity parameters are as follows: P, percentage of polymorphic loci; Ho, observed heterozygosity; He, expected heterozygosity; I, Shannon diversity index. Supplementary Table S5. Pairwise population FST values generated by location-based clustering.Supplementary Table S6. Compilation of the ten mutations identified in the sequenced region of An-1 gene. Mutations n2*, n4*, and n6* are functional nucleotide polymorphisms (FNPs) identified in Luo et al. (2013) study.

The response of plant traits to global change is of fundamental importance to understanding anthropogenic impacts on natural systems. Nevertheless, little is known about plant genetic variation in such responses or the indirect effect of environmental change on higher trophic levels. In a three-year common garden experiment, we grew the shrub Artemisia californica from five populations sourced along a 700 km latitudinal gradient under ambient and nitrogen (N) addition (20 kg N ha-1) and measured plant traits and associated arthropods. N addition increased plant biomass to a similar extent among all populations. In contrast, N addition effects on most other plant traits varied among plant populations; N addition reduced specific leaf area and leaf percent N and increased carbon to nitrogen ratios in the two northern populations, but had the opposite or no effect on the three southern populations. N addition increased arthropod abundance to a similar extent among all populations in parallel with an increase in plant biomass, suggesting that N addition did not alter plant resistance to herbivores. N addition had no effect on arthropod diversity, richness, or evenness. In summary, genetic variation among A. californica populations mediated leaf-trait responses to N addition, but positive direct effects of N addition on plant biomass and indirect effects on arthropod abundance were consistent among all populations.