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Nature genetics
06, 2022;54 (6): 885-896.

Genomic insights into the recent chromosome reduction of autopolyploid sugarcane Saccharum spontaneum.

Qing Zhang, Yiying Qi, Haoran Pan, Haibao Tang, Gang Wang, Xiuting Hua, Yongjun Wang, Lianyu Lin, Zhen Li, Yihan Li, Fan Yu, Zehuai Yu, Yongji Huang, Tianyou Wang, Panpan Ma, Meijie Dou, Zongyi Sun, Yibin Wang, Hengbo Wang, Xingtan Zhang, Wei Yao, Yuntong Wang, Xinlong Liu, Maojun Wang, Jianping Wang, Zuhu Deng, Jingsheng Xu, Qinghui Yang, ZhongJian Liu, Baoshan Chen, Muqing Zhang, Ray Ming, Jisen Zhang
Author Information
  1. Qing Zhang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  2. Yiying Qi: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  3. Haoran Pan: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  4. Haibao Tang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China. ORCID
  5. Gang Wang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  6. Xiuting Hua: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  7. Yongjun Wang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  8. Lianyu Lin: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  9. Zhen Li: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  10. Yihan Li: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  11. Fan Yu: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  12. Zehuai Yu: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  13. Yongji Huang: Institute of Oceanography, Marine Biotechnology Center, Minjiang University, Fuzhou, China.
  14. Tianyou Wang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  15. Panpan Ma: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  16. Meijie Dou: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  17. Zongyi Sun: GrandOmics Biosciences, Beijing, China.
  18. Yibin Wang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  19. Hengbo Wang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  20. Xingtan Zhang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  21. Wei Yao: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  22. Yuntong Wang: Biomarker Technologies Corporation, Beijing, China.
  23. Xinlong Liu: Yunnan Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Yunnan Academy of Agricultural Sciences, Kaiyuan, China.
  24. Maojun Wang: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China. ORCID
  25. Jianping Wang: Department of Agronomy, University of Florida, Gainesville, FL, USA. ORCID
  26. Zuhu Deng: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  27. Jingsheng Xu: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
  28. Qinghui Yang: Sugarcane Research Institute, Yunnan Agricultural University, Kunming, China.
  29. ZhongJian Liu: Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou, China. ORCID
  30. Baoshan Chen: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  31. Muqing Zhang: Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
  32. Ray Ming: Department of Plant Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA. ORCID
  33. Jisen Zhang: Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Sugarcane Biology and Genetic Breeding, National Engineering Research Center for Sugarcane, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China. zjisen@fafu.edu.cn. ORCID
PMID: 35654976 DOI: 10.1038/s41588-022-01084-1

Abstract

Saccharum spontaneum is a founding Saccharum species and exhibits wide variation in ploidy levels. We have assembled a high-quality autopolyploid genome of S. spontaneum Np-X (2n = 4x = 40) into 40 pseudochromosomes across 10 homologous groups, that better elucidates recent chromosome reduction and polyploidization that occurred circa 1.5 million years ago (Mya). One paleo-duplicated chromosomal pair in Saccharum, NpChr5 and NpChr8, underwent fission followed by fusion accompanied by centromeric split around 0.80 Mya. We inferred that Np-X, with x = 10, most likely represents the ancestral karyotype, from which x = 9 and x = 8 evolved. Resequencing of 102 S. spontaneum accessions revealed that S. spontaneum originated in northern India from an x = 10 ancestor, which then radiated into four major groups across the Indian subcontinent, China, and Southeast Asia. Our study suggests new directions for accelerating sugarcane improvement and expands our knowledge of the evolution of autopolyploids.

References

  1. Masterson, J. Stomatal size in fossil plants: evidence for polyploidy in majority of angiosperms. Science 264, 421–424 (1994). pubmed:17836906; doi:10.1126/science.264.5157.421
  2. Irvine, J. E. Saccharum species as horticultural classes. Theor. Appl. Genet. 98, 186–194 (1999). doi:10.1007/s001220051057
  3. Piperidis, N. & D’Hont, A. Sugarcane genome architecture decrypted with chromosome-specific oligo probes. Plant J. 103, 2039–2051 (2020). pubmed:32537783; doi:10.1111/tpj.14881
  4. Garsmeur, O. et al. A mosaic monoploid reference sequence for the highly complex genome of sugarcane. Nat. Commun. 9, 2638 (2018). pubmed:29980662; pmcid:6035169; doi:10.1038/s41467-018-05051-5
  5. Zhang, J. et al. Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum L. Nat. Genet. 50, 1565–1573 (2018). pubmed:30297971; doi:10.1038/s41588-018-0237-2
  6. Souza, G. M. et al. Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world’s leading biomass crop. GigaScience 8, giz129 (2019). pubmed:31782791; pmcid:6884061; doi:10.1093/gigascience/giz129
  7. Wenger, A. M. et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol. 37, 1155–1162 (2019). pubmed:31406327; pmcid:6776680; doi:10.1038/s41587-019-0217-9
  8. Koren, S. et al. De novo assembly of haplotype-resolved genomes with trio binning. Nat. Biotechnol. 36, 1174–1182 (2018). doi:10.1038/nbt.4277
  9. Braz, G. T., Yu, F., do Vale Martins, L. & Jiang, J. in In Situ Hybridization Protocols (eds. Nielsen, B. S. & Jones, J.) 71–83 (Springer, 2020).
  10. Zhang, X., Zhang, S., Zhao, Q., Ming, R. & Tang, H. Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nat. Plants 5, 833–845 (2019). pubmed:31383970; doi:10.1038/s41477-019-0487-8
  11. Dudchenko, O. et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356, 92–95 (2017). pubmed:28336562; pmcid:5635820; doi:10.1126/science.aal3327
  12. Durand, N. C. et al. Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst. 3, 99–101 (2016). pubmed:27467250; pmcid:5596920; doi:10.1016/j.cels.2015.07.012
  13. Parra, G., Bradnam, K. & Korf, I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics 23, 1061–1067 (2007). pubmed:17332020; doi:10.1093/bioinformatics/btm071
  14. Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015). pubmed:26059717; doi:10.1093/bioinformatics/btv351
  15. Mitros, T. et al. Genome biology of the paleotetraploid perennial biomass crop Miscanthus. Nat. Commun. 11, 5442 (2020). pubmed:33116128; pmcid:7595124; doi:10.1038/s41467-020-18923-6
  16. Paterson, A. H. et al. The Sorghum bicolor genome and the diversification of grasses. Nature 457, 551–556 (2009). pubmed:19189423; doi:10.1038/nature07723
  17. Kim, C. et al. Comparative analysis of Miscanthus and Saccharum reveals a shared whole-genome duplication but different evolutionary fates. Plant Cell 26, 2420–2429 (2014). pubmed:24963058; pmcid:4114942; doi:10.1105/tpc.114.125583
  18. The Rice Chromosomes 11 and 12 Sequencing Consortia. The sequence of rice chromosomes 11 and 12, rich in disease resistance genes and recent gene duplications. BMC Biol. 3, 20 (2005). pmcid:1261165; doi:10.1186/1741-7007-3-20
  19. Wang, X., Tang, H. & Paterson, A. H. Seventy million years of concerted evolution of a homoeologous chromosome pair, in parallel, in major Poaceae lineages. Plant Cell 23, 27–37 (2011). pubmed:21266659; pmcid:3051248; doi:10.1105/tpc.110.080622
  20. Ouyang, S. et al. The TIGR Rice Genome Annotation Resource: improvements and new features. Nucleic Acids Res. 35, D883–D887 (2007). pubmed:17145706; doi:10.1093/nar/gkl976
  21. Dong, P. et al. 3D chromatin architecture of large plant genomes determined by local A/B compartments. Mol. Plant 10, 1497–1509 (2017). pubmed:29175436; doi:10.1016/j.molp.2017.11.005
  22. Dong, Q. et al. Genome-wide Hi-C analysis reveals extensive hierarchical chromatin interactions in rice. Plant J. 94, 1141–1156 (2018). pubmed:29660196; doi:10.1111/tpj.13925
  23. Fujino, K. et al. NARROW LEAF 7 controls leaf shape mediated by auxin in rice. Mol. Genet. Genomics 279, 499–507 (2008). pubmed:18293011; doi:10.1007/s00438-008-0328-3
  24. Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011). pubmed:21753753; pmcid:3154645; doi:10.1038/nature10231
  25. Fujita, D. et al. NAL1 allele from a rice landrace greatly increases yield in modern indica cultivars. Proc. Natl. Acad. Sci. USA 110, 20431–20436 (2013). pubmed:24297875; pmcid:3870739; doi:10.1073/pnas.1310790110
  26. Takai, T. et al. A natural variant of NAL1, selected in high-yield rice breeding programs, pleiotropically increases photosynthesis rate. Sci. Rep. 3, 2149 (2013). pubmed:23985993; pmcid:3756344; doi:10.1038/srep02149
  27. Kubo, F. C., Yasui, Y., Kumamaru, T., Sato, Y. & Hirano, H.-Y. Genetic analysis of rice mutants responsible for narrow leaf phenotype and reduced vein number. Genes Genet. Syst. 91, 235–240 (2016). pubmed:27522959; doi:10.1266/ggs.16-00018
  28. Zhao, J., Luo, H., Jiang, Y., Yang, X. & Zha, R. Gene mapping for rice narrow leaf mutant Narrow leaf 11 (nal11). J. South. Agric. 48, 1133–1138 (2017).
  29. Imbrie, J. et al. in Milankovitch and Climate Part 1 (eds Berger A. L. et al.) 269–305 (D. Reidel, 1984).
  30. Martinson, D. G. et al. Age dating and the orbital theory of the ice ages: development of a high-resolution 0 to 300,000-year chronostratigraphy. Quat. Res. 27, 1–29 (1987). doi:10.1016/0033-5894(87)90046-9
  31. Sarnthein, M. & Tiedemann, R. Younger Dryas-style cooling events at glacial terminations I-VI at ODP site 658: associated benthic δ13C anomalies constrain meltwater hypothesis. Paleoceanography 5, 1041–1055 (1990). doi:10.1029/PA005i006p01041
  32. Szabo, B. J., Ludwig, K. R., Muhs, D. R. & Simmons, K. R. Thorium-230 ages of corals and duration of the last interglacial sea-level high stand on Oahu, Hawaii. Science 266, 93–96 (1994). pubmed:17814002; doi:10.1126/science.266.5182.93
  33. Stirling, C. H., Esat, T. M., McCulloch, M. T. & Lambeck, K. High-precision U-series dating of corals from Western Australia and implications for the timing and duration of the Last Interglacial. Earth Planet. Sci. Lett. 135, 115–130 (1995). doi:10.1016/0012-821X(95)00152-3
  34. Alley, R. B. et al. Holocene climatic instability: a prominent, widespread event 8200 yr ago. Geology 25, 483–486 (1997). doi:10.1130/0091-7613(1997)025<0483:HCIAPW>2.3.CO;2
  35. Mayewski, P. A. et al. Major features and forcing of high-latitude northern hemisphere atmospheric circulation using a 110,000-year-long glaciochemical series. J. Geophys. Res.: Oceans 102, 26345–26366 (1997). doi:10.1029/96JC03365
  36. Severinghaus, J. P., Sowers, T., Brook, E. J., Alley, R. B. & Bender, M. L. Timing of abrupt climate change at the end of the Younger Dryas interval from thermally fractionated gases in polar ice. Nature 391, 141–146 (1998). doi:10.1038/34346
  37. Jacques, F. M. B. et al. Quantitative reconstruction of the Late Miocene monsoon climates of southwest China: a case study of the Lincang flora from Yunnan Province. Palaeogeogr., Palaeoclimatol., Palaeoecol. 304, 318–327 (2011). doi:10.1016/j.palaeo.2010.04.014
  38. Winnepenninckx, B., Backeljau, T. & De Wachter, R. Extraction of high molecular weight DNA from molluscs. Trends Genet. 9, 407 (1993). pubmed:8122306; doi:10.1016/0168-9525(93)90102-N
  39. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014). pubmed:24695404; pmcid:4103590; doi:10.1093/bioinformatics/btu170
  40. Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011). pubmed:21217122; pmcid:3051319; doi:10.1093/bioinformatics/btr011
  41. Nurk, S. et al. HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. Genome Res. 30, 1291–1305 (2020). pubmed:32801147; pmcid:7545148; doi:10.1101/gr.263566.120
  42. Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat. Methods 18, 170–175 (2021). pubmed:33526886; pmcid:7961889; doi:10.1038/s41592-020-01056-5
  43. Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010). pubmed:20080505; pmcid:2828108; doi:10.1093/bioinformatics/btp698
  44. Langdon, W. B. Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks. BioData Min. 8, 1 (2015). pubmed:25621011; pmcid:4304608; doi:10.1186/s13040-014-0034-0
  45. Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015). pubmed:25751142; pmcid:4655817; doi:10.1038/nmeth.3317
  46. Stanke, M., Steinkamp, R., Waack, S. & Morgenstern, B. AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res. 32, W309–W312 (2004). pubmed:15215400; pmcid:441517; doi:10.1093/nar/gkh379
  47. Finn, R. D. et al. Pfam: the protein families database. Nucleic Acids Res. 42, D222–D230 (2014). pubmed:24288371; doi:10.1093/nar/gkt1223
  48. Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309–D314 (2019). pubmed:30418610; doi:10.1093/nar/gky1085
  49. Bleasby, A. J., Akrigg, D. & Attwood, T. K. OWL–a non-redundant composite protein sequence database. Nucleic Acids Res. 22, 3574–3577 (1994). pubmed:7937061; pmcid:308323
  50. Boeckmann, B. et al. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res. 31, 365–370 (2003). pubmed:12520024; pmcid:165542; doi:10.1093/nar/gkg095
  51. Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014). pubmed:24451626; pmcid:3998142; doi:10.1093/bioinformatics/btu031
  52. Wang, Y. et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 40, e49 (2012). pubmed:22217600; pmcid:3326336; doi:10.1093/nar/gkr1293
  53. Zhang, T., Liu, G., Zhao, H., Braz, G. T. & Jiang, J. Chorus2: design of genome-scale oligonucleotide-based probes for fluorescence in situ hybridization. Plant Biotechnol. J. 19, 1967–1978 (2021). pubmed:33960617; pmcid:8486243; doi:10.1111/pbi.13610
  54. Huang, Y. et al. The formation and evolution of centromeric satellite repeats in Saccharum species. Plant J. 106, 616–629 (2021). pubmed:33547688; doi:10.1111/tpj.15186
  55. Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015). pubmed:26619908; pmcid:4665391; doi:10.1186/s13059-015-0831-x
  56. Servant, N. et al. HiTC: exploration of high-throughput ‘C’ experiments. Bioinformatics 28, 2843–2844 (2012). pubmed:22923296; pmcid:3476334; doi:10.1093/bioinformatics/bts521
  57. Bao, Z. & Eddy, S. R. Automated de novo identification of repeat sequence families in sequenced genomes. Genome Res. 12, 1269–1276 (2002). pubmed:12176934; pmcid:186642; doi:10.1101/gr.88502
  58. Price, A. L., Jones, N. C. & Pevzner, P. A. De novo identification of repeat families in large genomes. Bioinformatics 21, i351–i358 (2005). pubmed:15961478; doi:10.1093/bioinformatics/bti1018
  59. Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999). pubmed:9862982; pmcid:148217; doi:10.1093/nar/27.2.573
  60. Abrusán, G., Grundmann, N., DeMester, L. & Makalowski, W. TEclass—a tool for automated classification of unknown eukaryotic transposable elements. Bioinformatics 25, 1329–1330 (2009). pubmed:19349283; doi:10.1093/bioinformatics/btp084
  61. Xu, Z. & Wang, H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, W265–W268 (2007). pubmed:17485477; pmcid:1933203; doi:10.1093/nar/gkm286
  62. Ellinghaus, D., Kurtz, S. & Willhoeft, U. LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons. BMC Bioinf. 9, 18 (2008). doi:10.1186/1471-2105-9-18
  63. Ou, S. & Jiang, N. LTR_retriever: a highly accurate and sensitive program for identification of long terminal repeat retrotransposons. Plant Physiol. 176, 1410–1422 (2018). pubmed:29233850; doi:10.1104/pp.17.01310
  64. Huang, G. et al. Genome sequence of Gossypium herbaceum and genome updates of Gossypium arboreum and Gossypium hirsutum provide insights into cotton A-genome evolution. Nat. Genet. 52, 516–524 (2020). pubmed:32284579; pmcid:7203013; doi:10.1038/s41588-020-0607-4
  65. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009). pubmed:19505943; pmcid:2723002; doi:10.1093/bioinformatics/btp352
  66. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011). pubmed:21653522; pmcid:3137218; doi:10.1093/bioinformatics/btr330
  67. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007). pubmed:17701901; pmcid:1950838; doi:10.1086/519795
  68. Ginestet, C. ggplot2: elegant graphics for data analysis. J. R. Stat. Soc.: Ser. A 174, 245–246 (2011). doi:10.1111/j.1467-985X.2010.00676_9.x
  69. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009). pubmed:19648217; pmcid:2752134; doi:10.1101/gr.094052.109
  70. Raj, A., Stephens, M. & Pritchard, J. K. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197, 573–589 (2014). pubmed:24700103; pmcid:4063916; doi:10.1534/genetics.114.164350
  71. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014). pubmed:24451623; pmcid:3998144; doi:10.1093/bioinformatics/btu033

MeSH Term

Chromosomes
Genome, Plant
Genomics
Ploidies
Saccharum
Journal Article Research Support, Non-U.S. Gov't

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