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First Insights into the Guar (Cyamopsis tetragonoloba (L.) Taub.) Genome of the ‘Vavilovskij 130’ Accession, Using Second and Third-Generation Sequencing Technologies

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Abstract

Guar (Cyamopsis tetragonoloba (L.) Taub.) is becoming a popular industrial crop in response to industry demand for the guar gum extracted from seeds’ endosperm. Breeding efforts of new guar varieties would greatly benefit from genomic resources developed for marker assisted selection (MAS) purposes. We have undertaken the first steps to establish a whole-genome assembly of the guar ‘Vaviloskij 130’ accession, bred at VIR. Using a combination of second (Illumina short reads) and third generation (Oxford Nanopore long reads) sequencing methods, a dataset of approx. 5X of genome coverage was obtained. We tested assemblers for short reads, namely SOAPdenovo, AbySS and SGA, based on different algorithms. For short reads (Illumina MiSeq and HiSeq data), the better result in terms of total number of scaffolds and total assembly length were obtained with SGA (String Graph Assembler). For Oxford Nanopore dataset, we used the combination of minimap + miniASM assembly, then corrected the assembly with raw Illumina and Nanopore data. The current preliminary de novo assembly of the guar genome covers 1.2 Gb, corresponding to 50% of the genome. The data confirm the phylogeny position of C. tetragoloba as being highly related to the genus Vigna, Abrus, Glycine and Lupinus genomes. This preliminary reference genome paves the way to further detailed diversity and genetic analyses into that important agro-industrial crop.

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REFERENCES

  1. Aswathnarayana, N.K., Tiwari, P.B., Choudhary, M., et al., Genetic diversity study of cluster bean (Cyamopsis tetragonoloba (L.) Taub.) landraces using RAPD and ISSR markers, Int. J. Adv. Biotechnol. Res., 2013, vol. 4, no. 4, pp. 460—471.

    Google Scholar 

  2. Mudgil, D., Barak, S., and Khatkar, B.S., Guar gum: processing, properties and food applications—a review, J. Food Sci. Technol., 2014, vol. 51, no. 3, pp. 409—418. https://doi.org/10.1007/s13197-011-0522-x

    Article  CAS  PubMed  Google Scholar 

  3. Lubbers, E.L., Characterization and inheritance of photoperiodism on guar, Cyamopsis tetragonoloba (L.) Taub., PhD Thesis, University of Arizona. 1987.

  4. Whistler, R.L. and Hymowitz, T., Guar: Agronomy, Production, Industrial Use, and Nutrition, Purdue University Press, 1979.

    Google Scholar 

  5. Douglas, C.A., Evaluation of Guar Cultivars in Central and Southern Queensland: A Report for the Rural Industries Research and Development Corporation, Barton, Australia: Rural Industries Research and Development Corporation, 2005.

    Google Scholar 

  6. Boghara, M.C., Dhaduk, H.L., Kumar, et al., Genetic divergence, path analysis and molecular diversity analysis in cluster bean (Cyamopsis tetragonoloba L. Taub.), Ind. Crops Prod., 2016, vol. 89, pp. 468—477. https://doi.org/10.15389/agrobiology.2017.6.1116eng

    Article  CAS  Google Scholar 

  7. Gresta, F., Avola, G., Cannavò, S., et al., Morphological, biological, productive and qualitative characterization of 68 guar (Cyamopsis tetragonoloba (L.) Taub.) genotypes, Ind. Crops Prod., 2018, vol. 114, pp. 98—107. https://doi.org/10.1016/j.indcrop.2018.01.070

    Article  Google Scholar 

  8. Dzyubenko, N.I., Dzyubenko, E.A., Potokina, E.K., et al., Clusterbeans Cyamopsis tetragonoloba (L.) Taub.—properties, use, plant genetic resources and expected introduction in Russia, S.-kh. Biol., vol. 52, no. 6, pp. 1116—1128. https://doi.org/10.15389/agrobiology.2017.6.1116rus

  9. Kumar, S., Modi, A.R., Parekh, M.J., et al., Role of conventional and biotechnological approaches for genetic improvement of cluster bean, Ind. Crops Prod., 2017, vol. 97, pp. 639—648. https://doi.org/10.1016/j.indcrop.2017.01.008

    Article  CAS  Google Scholar 

  10. Naoumkina, M., Torres-Jerez, I., Allen, S., et al., Analysis of cDNA libraries from developing seeds of guar (Cyamopsis tetragonoloba (L.) Taub.), BMC Plant Biol., 2007, vol. 7, no. 1, p. 62. https://doi.org/10.1186/1471-2229-7-62

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Rawal, H.C., Kumar, S., Mithra, S.V.A., et al., High quality unigenes and microsatellite markers from tissue specific transcriptome and development of a database in clusterbean (Cyamopsis tetragonoloba L. Taub.), Genes, 2017, vol. 8, no. 11, p. 313. https://doi.org/10.3390/genes8110313

    Article  CAS  PubMed Central  Google Scholar 

  12. Tanwar, U.K., Pruthi, V., Randhawa, G.S., RNA-Seq of guar (Cyamopsis tetragonoloba L. Taub.) leaves: de novo transcriptome assembly, functional annotation and development of genomic resources, Front. Plant Sci., 2017, vol. 8, p. 91. https://doi.org/10.3389/fpls.2017.0009

    Article  PubMed  PubMed Central  Google Scholar 

  13. Thakur, O. and Randhawa, G.S., Identification and characterization of SSR, SNP and InDel molecular markers from RNA-Seq data of guar (Cyamopsis tetragonoloba L. Taub.) roots, BMC Genomics, 2018, vol. 19, no. 1, p. 951. https://doi.org/10.1186/s12864-018-5205-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Sahu, S., Rao, A.R., Pandey, J., et al., Genome-wide identification and characterization of lncRNAs and miRNAs in cluster bean (Cyamopsis tetragonoloba), Gene, 2018, vol. 667, pp. 112—12. https://doi.org/10.1016/j.gene.2018.05.027

    Article  CAS  PubMed  Google Scholar 

  15. Tyagi, A., Nigam, D., Solanke, A.U., et al., Genome-wide discovery of tissue-specific miRNAs in clusterbean (Cyamopsis tetragonoloba) indicates their association with galactomannan biosynthesis, Plant Biotechnol. J., 2018, vol. 16, no. 6, pp. 1241—1257. https://doi.org/10.1111/pbi.12866

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kaila, T., Chaduvla, P.K., Rawal, et al., Chloroplast genome sequence of clusterbean (Cyamopsis tetragonoloba L.): genome structure and comparative analysis, Genes, 2017, vol. 8, no. 9, p. 212. https://doi.org/10.3390/genes8090212

    Article  CAS  PubMed Central  Google Scholar 

  17. Patil, C.G., Nuclear DNA amount variation in Cyamopsis D.C. (Fabaceae), Cytologia, 2004, vol. 69, no. 1, pp. 59—62. https://doi.org/10.1508/cytologia.69.59

    Article  Google Scholar 

  18. Tyagi, A., Sandhya, S., Sharma, et al., The genome size of clusterbean (Cyamopsis tetragonoloba) is significantly smaller compared to its wild relatives as estimated by flow cytometry, Gene, 2019. https://doi.org/10.1111/pbi.12866

  19. Chang, Y., Liu, H., Liu, M., et al., The draft genomes of five agriculturally important African orphan crops, GigaScience, 2018, vol. 8, no. 3, р. 152. https://doi.org/10.1093/gigascience/giy152

  20. Bennett, M.D., Smith J.B., and Riley Ralph, Nuclear DNA amounts in angiosperms, R. Soc. Online J., 1976, vol. 274, pp. 227—274. https://doi.org/10.1098/rspb.1982.0069

    Article  CAS  Google Scholar 

  21. Metzker, M.L., Sequencing technologies—the next generation, Nat. Rev. Genet., 2010, vol. 11, no. 1, p. 31. https://doi.org/10.1038/nrg2626

    Article  CAS  PubMed  Google Scholar 

  22. van Dijk, E.L., Auger, H., Jaszczyszyn, Y., et al., Ten years of next-generation sequencing technology, Trends Genet., 2014, vol. 30, no. 9, pp. 418—426. https://doi.org/10.1016/j.tig.2014.07.001

    Article  CAS  PubMed  Google Scholar 

  23. Ip, C.L.C., Loose, M., Tyson, J.R., et al., MinION Analysis and Reference Consortium: phase 1 data release and analysis, F1000Research, 2015, vol. 4. https://doi.org/10.12688/f1000research.7201.1

  24. de Lannoy, C., de Ridder, D., and Risse, J., The long reads ahead: de novo genome assembly using the MinION, F1000Research, 2017, vol. 6. https://doi.org/10.12688/f1000research.12012.2

  25. Simpson, J.T. and Pop, M., The theory and practice of genome sequence assembly, Annu. Rev. Genomics Hum. Genet., 2015, vol. 16, pp. 153—172. https://doi.org/10.1146/annurev-genom-090314-050032

    Article  CAS  PubMed  Google Scholar 

  26. Myers, E.W., Sutton, G.G., Delcher, A.L., et al., A whole-genome assembly of Drosophila,Science, 2000, vol. 287, no. 5461, pp. 2196—2204.

    Article  CAS  PubMed  Google Scholar 

  27. Compeau, P.E.C., Pevzner, P.A., and Tesler, G., Why are de Bruijn graphs useful for genome assembly?, Nat. Biotechnol., 2011, vol. 29, no. 11, p. 987. https://doi.org/10.1038/nbt.2023

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Myers, E.W., The fragment assembly string graph, Bioinformatics, 2005, vol. 21, suppl. 2, pp. ii79—ii85. https://doi.org/10.1093/bioinformatics/bti1114

    Article  CAS  PubMed  Google Scholar 

  29. Pevzner, P.A., Tang, H., and Waterman, M.S., An Eulerian path approach to DNA fragment assembly, Proc. Natl. Acad. Sci., U.S.A., 2001, vol. 98, no. 17, pp. 9748—9753. https://doi.org/10.1073/pnas.171285098

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Simpson, J.T. and Durbin, R., Efficient construction of an assembly string graph using the FM-index, Bioinformatics, 2010, vol. 26, no. 12, pp. i367—i373. https://doi.org/10.1093/bioinformatics/btq217

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Doyle, J., A rapid total DNA preparation procedure for fresh plant tissue, Focus, 1990, vol. 12, pp. 13—15. https://doi.org/10.1007/978-3-642-83962-7_18

    Article  Google Scholar 

  32. FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

  33. BBTools. https://jgi.doe.gov/data-and-tools/bbtools/.

  34. Luo, R., Liu, B., Xie, Y., et al., SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler, GigaScience, 2012, vol. 1, p. 18. https://doi.org/10.1186/2047-217X-1-18

    Article  PubMed  PubMed Central  Google Scholar 

  35. Jackman, S.D., Vandervalk, B.P., Mohamadi, H., et al., ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter, Genome Res., 2017, vol. 27, no. 5, pp. 768—777. https://doi.org/10.1101/gr.214346.116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Simpson, J.T. and Durbin, R., Efficient de novo assembly of large genomes using compressed data structures, Genome Res., 2012, vol. 22, no. 3, pp. 549—556. https://doi.org/10.1101/gr.126953.111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. De Coster, W., D’Hert, S., Schultz, D.T., et al., Bioinformatics, 2018, vol. 34, no. 15, pp. 2666—2669. https://doi.org/10.1093/bioinformatics/bty149

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li, H., Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences, Bioinformatics, 2016, vol. 32, no. 14, pp. 2103—2110. https://doi.org/10.1093/bioinformatics/btw152

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Walker, B.J., Abeel, T., Shea, T., et al., Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement, PLoS One, 2014, vol. 9, no. 11. e112963. https://doi.org/10.1371/journal.pone.0112963

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Antipov, D., Korobeynikov, A., McLean, J.S., et al., hybridSPAdes: an algorithm for hybrid assembly of short and long reads, Bioinformatics, 2015, vol. 32, no. 7, pp. 1009—1015. https://doi.org/10.1093/bioinformatics/btv68

    Article  PubMed  PubMed Central  Google Scholar 

  41. Gurevich, A., Saveliev, V., Vyahhi Tehler, G., et al., QUAST: quality assessment tool for genome assemblies, Bioinformatics, 2013, vol. 29, no. 8, pp. 1072—1075. https://doi.org/10.1093/bioinformatics/btt086

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang, Z., Schwartz, S., Wagner, L., et al., Greedy algorithm for aligning DNA sequences, J. Comput. Biol., 2000, vol. 7, nos. 1—2, pp. 203—214. https://doi.org/10.1089/10665270050081478

    Article  CAS  PubMed  Google Scholar 

  43. Cock, P.J.A., Antao, T., Chang, J.T., et al., Biopython: freely available Python tools for computational molecular biology and bioinformatics, Bioinformatics, 2009, vol. 25, no. 11, pp. 1422—1423. https://doi.org/10.1093/bioinformatics/btp163

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. R Core Team, R: A Language and Environment for Statistical Computing, Vienna: R Foundation for Statistical Computing, 2019.

  45. Zimin, A.V., Marçais, G., Puiu, D., et al., The MaSuRCA genome assembler, Bioinformatics, 2013, vol. 29, no. 21, pp. 2669—2677. https://doi.org/10.1093/bioinformatics/btt476

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Peters, W.S., Haffer, D., Hanakam, C.B., et al., Legume phylogeny and the evolution of a unique contractile apparatus that regulates phloem transport, Am. J. Bot., 2010, vol. 97, no. 5, pp. 797—808. https://doi.org/10.3732/ajb.0900328

    Article  PubMed  Google Scholar 

  47. Pratap, A. and Kumar, J., Biology and Breeding of Food Legumes, CABI, 2011. https://doi.org/10.1017/S0014479712000312

    Book  Google Scholar 

  48. Wang, J., Sun, P., Li, Y., Cheng, R., Duan, X., et al., Hierarchically aligning 10 legume genomes establishes a family-level genomics platform, Plant Physiol., 2017, vol. 174, no. 1, pp. 284—300. https://doi.org/10.1104/pp.16.01981

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Belser, C., Istace, B., Denis, E., et al., Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps, Nat. Plants, 2018, vol. 4, no. 11, p. 879. https://doi.org/10.1038/s41477-018-0289-4

    Article  CAS  PubMed  Google Scholar 

  50. Schmidt, M.H.-W., Vogel, A., Denton, A.K., et al., De novo assembly of a new Solanum pennellii accession using nanopore sequencing, plant cell, Plant Cell, 2017, vol. 29, no. 10, pp. 2336—2348. https://doi.org/10.1105/tpc.17.00521

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Chaisson, M.J.P., Wilson, R.K., and Eichler, E.E., Genetic variation and the de novo assembly of human genomes, Nat. Rev. Genet., 2015, vol. 16, no. 11, p. 627. https://doi.org/10.1038/nrg3933

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ellinghaus, D., Kurtz, S., and Willhoeft, U., LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons, BMC Bioinf., 2008, vol. 9, no. 1, p. 18. https://doi.org/10.1186/1471-2105-9-18

    Article  CAS  Google Scholar 

  53. RepeatMasker Open-4.0. http://repeatmasker.org.

  54. Sohn, J. and Nam, J.-W., The present and future of de novo whole-genome assembly, Briefings Bioinf., 2016, vol. 19, no. 1, pp. 23—40. https://doi.org/10.1093/bib/bbw096

    Article  CAS  Google Scholar 

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ACKNOWLEDGMENTS

The reported study was funded by RFBR according to the research project no. 17-29-08027. We are grateful to the Genotoul bioinformatics platform Toulouse Midi-Pyrenees (Bioinfo Genotoul) for providing computing resources. Sequencing was performed at the Biobank of Research Park of St. Petersburg State University (no. 1259502495). E. Potokina was supported by a “Visiting Scholar” fellowship from Toulouse INP for a short scientific stay at Toulouse INP.

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Correspondence to L. Gentzbittel or E. Potokina.

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Grigoreva, E., Ulianich, P., Ben, C. et al. First Insights into the Guar (Cyamopsis tetragonoloba (L.) Taub.) Genome of the ‘Vavilovskij 130’ Accession, Using Second and Third-Generation Sequencing Technologies. Russ J Genet 55, 1406–1416 (2019). https://doi.org/10.1134/S102279541911005X

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