Figure S1. Data flow of de novo genome assembly using next generation sequencing data from multiple platforms.
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1 Supplemental Figures Figure S1. Data flow of de novo genome assembly using next generation sequencing data from multiple platforms. Figure S2. Factors effect on the quality of de novo genome assembly. (A) The influences of data coverage to assembled genome size and contig length. (B) The effect of Kmer size on contig length at given 15 coverage data. (C) The effect of add-on multiplex sequencing data in the de novo assembly. Figure S3. Length and quality distribution of PacBio reads. Ten SMRT Cell runs generated 513,084 reads with average length 3.1 kb and total ~1.4 Gb data. (A) Length distribution of PacBio long reads. (B) Quality distribution of PacBio long reads. Figure S4. PacBio reads rescue. Mapping accurate high quality high coverage Illumina short reads against the low quality PacBio reads generated consensus sequences. Figure S5. The benefit of including PacBio long reads in the de novo assembly. Contig length (A) and assembled genome size (B) increased after adding PacBio reads to 454 short reads. Contig length was increased (C) and contig number (D) was reduced after added PacBio reads to Illumina short pairedend reads. Figure S6. Distance distribution of true mate-paired reads (A) and false mate-paired reads (B). Figure S7. Repeats distribution of all SSR loci. Figure S8. Distribution of unique transcripts in the horseweed genome by gene ontology (GO) annotation. (A) Molecular function (MF). (B) Biological process (BP). (C) Cellular component (CC). (D) Enzyme code distribution. Figure S9. Enriched GO terms in transporter subgroup of molecular functional category in the horseweed genome compared with Arabidopsis by analysis with Fisher's Exact Test. The overrepresented terms are shown in green. Figure S10. Map of horseweed chloroplast genome. Two inverted repeats (IRs: 24,936 bp each); large single-copy (LSC: 84,634 bp) and small single-copy (SSC: 18,063 bp), contain 95 protein-coding genes (88 unique), 39 trna (28 unique) and 8 rrna (4 unique).
2 Figure S11. Syntenic dot plot analysis of the horseweed chloroplast genome compared with sunflower ( Helianthus annuus) and lettuce (Lactuca sativa). A. Lettuce vs. horseweed. B. Horseweed vs. sunflower. Each black dot represent locus variation between genomes. Figure S12. De novo assembly of the horseweed mitochondrial genome with N 50 = 7,943 bp. The largest contig was 43,498 bp and the smallest contig was 315 bp. The mean G/C content was 40.1%. Figure S13. Morphological variation among horseweed populations. The plants were grown together under the same conditions and the photos were taken at the same stage (the same number of days after germination). Figure S14. Distribution of specific variants in genomes of glyphosate susceptible horseweed biotypes (A) and in genomes of glyphosate resistant biotypes (B) by Fisher s Exact test. Figure S15. Alignment of EPSPS protein sequences from different horseweed biotypes. The variant residues are highlighted with red lines Supplemental Tables Table S1. Results of mapping mate-paired reads to de novo assembled contigs. Table S2. Average GC content of plant genomes. Table S3. Summary of SSR markers in the assembled horseweed genome. Table S4. Summary of plant mitochondrial genomes. Table S5. Matrix of nucleotide diversity (kb per variant) within genome among horseweed biotypes Supplemental file 1 HWCP annotation.txt Supplemental file 2 HWMT genome.fas 61 62
3 Figure S1. Data flow of de novo genome assembly using next generation sequencing data from multiple platforms
4 Figure S2. Factors effect on the quality of de novo genome assembly. (A) The influences of data coverage to assembled genome size and contig length. (B) The effect of Kmer size on contig length at given 15 x coverage data. (C) The effect of added multiplex sequencing data in de novo assembly
5 Figure S3. Length and quality distribution of PacBio reads. Ten SMRT Cell runs generated 513,084 reads with average length 3.1 kb and total ~1.4 Gb data. (A) Length distribution of PacBio long reads. (B) Quality distribution of PacBio long reads
6 Figure S4. PacBio reads rescue. Mapping accurate high quality high coverage Illumina short reads against the low quality PacBio reads generated consensus sequences
7 Figure S5. The benefit of including PacBio long reads in the de novo assembly. Contig length (A) and assembled genome size (B) increased after adding PacBio reads to 454 short reads. Contig length was increased (C) and contig number (D) was reduced after added PacBio reads to Illumina short paired-end reads
8 Figure S6. Distance distribution of true mate-paired reads (A) and false mate-paired reads (B)
9 Figure S7. Repeats distribution of all SSR loci
10 Figure S8. Distribution of unique transcripts in the horseweed genome by gene ontology (GO) annotation. (A) Molecular function (MF). (B) Biological process (BP). (C) Cellular component (CC). (D) Enzyme code distribution
11 Figure S9. Enriched GO terms in transporter subgroup of molecular functional category in the horseweed genome compared with Arabidopsis by Fisher's Exact test analysis. The overrepresented terms are shown in green
12 Figure S10. Map of horseweed chloroplast genome. Two inverted repeats (IRs: 24,936 bp each); large single-copy (LSC: 84,634 bp) and small single-copy (SSC: 18,063 bp), contain 95 protein-coding genes (88 unique), 39 trna (28 unique) and 8 rrna (4 unique)
13 Figure S11. Syntenic dot plot analysis of the horseweed chloroplast genome compared with sunflower (Helianthus annuus) and lettuce (Lactuca sativa). A. Lettuce vs. horseweed. B. Horseweed vs. sunflower. Each black dot represent locus variation between genomes. 211
14 Figure S12. De novo assembly horseweed mitochondrial genome with N 50 = 7,943 bp. The largest contig was 43,498 bp and the smallest contig was 315 bp. Mean G/C content was 40.1%
15 Figure S13. Morphological variation among horseweed populations. The plants were grown together under the same conditions and photographs were taken at the same stage (the same number of days after germination)
16 Figure S14. Distribution of specific variants in genomes of glyphosate susceptible horseweed biotypes (A) and in genomes of glyphosate resistant biotypes (B) by Fisher s Exact test
17 Figure S15. Alignment of EPSPS1 (A) EPSPS2 (B) protein sequences from different horseweed biotypes. The variant residues are highlighted with red lines
18 Table S1. Results of mapping mate-paired reads to de novo assembled contigs
19 Table S2. Average GC content of selected plant genomes. Species GC content (%) Arabidopsis thaliana 36.0 Brachypodium distachyon 46.3 Conyza canadensis 34.9 Fragaria vesca 35.8 Glycine max 34.2 Lotus japonicus 35.6 Malus domestica 27.6 Medicago truncatula 27.2 Oryza sativa 42.4 Populus trichocarpa 32.9 Solanum lycopersicum 32.1 Sorghum bicolor 41.5 Vitis vinifera 33.7 Zea mays
20 Table S3. Summary of SSR markers in the assembled horseweed genome. 287 SSR types Dimer Trimer Tetramer Pentamer Hexamer Total Counts (%) 44,589 (85.9) 6,864 (13.2) 299 (0.58) 60 (0.12) 80 (0.15) 51,892 (100)
21 Table S4. Summary of selected plant mitochondrial genomes Species Genome size (bp) G/C content (%) Brassica carinata 232, Silene latifolia 253, Helianthus annuus 300, Arabidopsis thaliana 366, Citrullus lanatus 379, Vigna radiata 401, Nicotiana tabacum 430, Triticum aestivum 452, Conyza canadensis 453, Sorghum bicolor 468, Carica papaya 476, Oryza sativa 490, Ricinus communis 502, Zea mays 569, Tripsacum dactyloides 704, Vitis vinifera 773, Cucurbita pepo 982,
22 Table S5. Matrix of nucleotide diversity (kb per variant) within genomes among horseweed biotypes. Biotypes CA-R CA-S DE-R DE-S IN-R IN-S TN-S CA-S 1.14 DE-R DE-S IN-R IN-S TN-S TN-R
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