Haplotype-resolved genome assembly and allele-specific gene expression in cultivated ginger

Abstract

Ginger (Zingiber officinale) is one of the most valued spice plants worldwide; it is prized for its culinary and folk medicinal applications and is therefore of high economic and cultural importance. Here, we present a haplotype-resolved, chromosome-scale assembly for diploid ginger anchored to 11 pseudochromosome pairs with a total length of 3.1 Gb. Remarkable structural variation was identified between haplotypes, and two inversions larger than 15 Mb on chromosome 4 may be associated with ginger infertility. We performed a comprehensive, spatiotemporal, genome-wide analysis of allelic expression patterns, revealing that most alleles are coordinately expressed. The alleles that exhibited the largest differences in expression showed closer proximity to transposable elements, greater coding sequence divergence, more relaxed selection pressure, and more transcription factor binding site differences. We also predicted the transcription factors potentially regulating 6-gingerol biosynthesis. Our allele-aware assembly provides a powerful platform for future functional genomics, molecular breeding, and genome editing in ginger.

References

[1] Ravindran, P. & Babu, K. N. Ginger: the genus Zingiber (CRC press, 2005).

[2] Chrubasik, S., Pittler, M. & Roufogalis, B. Zingiberis rhizoma: a comprehensive review on the ginger effect and efficacy profiles. Phytomedicine 12, 684-701 (2005).

[3] Govindarajan, V. & Connell, D. Ginger-chemistry, technology, and quality evaluation: part 1. Crit. Rev. Food Sci. Nutr. 17, 1-96 (1983).

[4] Wei, Q. Y., Ma, J. P., Cai, Y. J., Yang, L. & Liu, Z. L. Cytotoxic and apoptotic activities of diarylheptanoids and gingerol-related compounds from the rhizome of Chinese ginger. J. Ethnopharmacol. 102, 177-184 (2005).

[5] Tjendraputra, E., Tran, V. H., Liu-Brennan, D., Roufogalis, B. D. & Duke, C. C. Effect of ginger constituents and synthetic analogues on cyclooxygenase-2 enzyme in intact cells. Bioorg. Chem. 29, 156-163 (2001).

[6] Ficker, C. et al. Bioassay-guided isolation and identification of antifungal compounds from ginger. Phytother. Res. 17, 897-902 (2003).

[7] Das, P., Rai, S. & Das, A. B. Cytomorphological barriers in seed set of cultivated ginger (Zingiber officinale Rosc.). Iran. J. Med. Phys. 8, 119-129 (1999).

[8] Ratnambal, M. J. Cytological studies in ginger (Zingiber officinale Rosc.). Unpublished Ph. D thesis.(University of Bombay, India, 1979).

[9] Knight, J. C. Allele-specific gene expression uncovered. Trends Genet. 20, 113-116 (2004).

[10] Guo, M. et al. Allelic variation of gene expression in maize hybrids. Plant Cell 16, 1707-1716 (2004).

[11] Ni, Z. et al. Altered circadian rhythms regulate growth vigour in hybrids and allopolyploids. Nature 457, 327-331 (2009).

[12] Šmarda, P. et al. Ecological and evolutionary significance of genomic GC content diversity in monocots. Proc. Natl Acad. Sci. USA 111, E4096-E4102 (2014).

[13] Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).

[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).

[15] Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 1-14 (2019).

[16] D’Hont, A. et al. The banana (Musa acuminata) genome and the evolution of monocotyledonous plants. Nature 488, 213-217 (2012).

[17] Van de Peer, Y., Fawcett, J. A., Proost, S., Sterck, L. & Vandepoele, K. The flowering world: a tale of duplications. Trends Plant Sci. 14, 680-688 (2009).

[18] Feulner, P. & De-Kayne, R. Genome evolution, structural rearrangements and speciation. J. Evol. Biol. 30, 1488-1490 (2017).

[19] Ramachandran, K. Chromosome numbers in Zingiberaceae. Cytologia 34, 213-221 (1969).

[20] Ramachandran, K. Polyploidy induced in ginger by colchicine treatment. Curr. Sci. 51, 288-289 (1982).

[21] Ramachandran, K. & Nair, P. C. Induced tetraploids of ginger (Zingiber officinale Rosc.). J. Spices Aromat. Crops 1, 39-42 (1992).

[22] Ramachandran, K. & Nair, P. C. Cytological studies on diploid and autotetraploid ginger (Zingiber officinale Rosc.). J. Spices Aromat. Crops 1, 125-130 (1992).

[23] Adaniya, S. & Shoda, M. Meiotic irregularity of ginger (Zingiber officinale Roscoe). Chromosome Science 2, 141-144 (1998).

[24] Goel, M., Sun, H., Jiao, W. B. & Schneeberger, K. SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies. Genome Biol. 20, 277 (2019).

[25] Zhang, H. et al. Non-Robertsonian translocations involving chromosomes 13, 14, or 15 in male infertility: 28 cases and a review of the literature. Medicine 98, e14730 (2019).

[26] Chantot-Bastaraud, S. et al. Sperm-FISH analysis in a pericentric chromosome 1 inversion, 46, XY, inv (1)(p22q42), associated with infertility. Mol. Hum. Reprod. 13, 55-59 (2007).

[27] Griffiths, A. J. et al. An Introduction to Genetic Analysis (Macmillan, 2005).

[28] Chen, K., Wang, Y., Zhang, R., Zhang, H. & Gao, C. CRISPR/Cas genome editing and precision plant breeding in agriculture. Annu. Rev. Plant Biol. 70, 667-697 (2019).

[29] Wang, Y. P. et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 40, e49 (2012).

[30] Jiang, Y. et al. Transcriptome analysis provides insights into gingerol biosynthesis in ginger (Zingiber officinale). Plant Genome 11, 180034 (2018).

[31] Hollister, J. D. & Gaut, B. S. Epigenetic silencing of transposable elements: a trade-off between reduced transposition and deleterious effects on neighboring gene expression. Genome Res. 19, 1419-1428 (2009).

[32] Schnable, J. C., Springer, N. M. & Freeling, M. Differentiation of the maize subgenomes by genome dominance and both ancient and ongoing gene loss. Proc. Natl Acad. Sci. USA 108, 4069-4074 (2011).

[33] Nützmann, H. W., Huang, A. & Osbourn, A. Plant metabolic clusters-from genetics to genomics. N. Phytol. 211, 771-789 (2016).

[34] Doyle, J. & Doyle, J. L. Genomic plant DNA preparation from fresh tissue-CTAB method. Phytochem Bull. 19, 11-15 (1987).

[35] Xie, T. et al. De novo plant genome assembly based on chromatin interactions: a case study of Arabidopsis thaliana. Mol. Plant 8, 489-492 (2015).

[36] Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764-770 (2011).

[37] Liu, B. et al. Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects. arXiv 1308. Preprint at https://arxiv.org/abs/1308.2012 (2013).

[38] Ruan, J. Ultra-fast de novo assembler using long noisy reads (2016).

[39] Ruan, J. & Li, H. Fast and accurate long-read assembly with wtdbg2. Nat. Methods 17, 155-158 (2019).

[40] Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 27, 722-736 (2017).

[41] Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv 1303, Preprint at https://arxiv.org/abs/1303.3997 (2013).

[42] Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).

[43] Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95-98 (2016).

[44] Dudchenko, O. et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356, 92-95 (2017).

[45] Xu, G. C. et al. LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly. GigaScience 8, giy157 (2019).

[46] Hu, J., Fan, J., Sun, Z. & Liu, S. NextPolish: a fast and efficient genome polishing tool for long read assembly. Bioinformatics 36, 2253-2255 (2019).

[47] Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094-3100 (2018).

[48] Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884-i890 (2018).

[49] Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290-295 (2015).

[50] Grabherr, M. G. et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29, 644-652 (2011).

[51] Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150-3152 (2012).

[52] Ellinghaus, D., Kurtz, S. & Willhoeft, U. LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons. BMC Bioinforma. 9, 18 (2008).

[53] Steinbiss, S., Willhoeft, U., Gremme, G. & Kurtz, S. Fine-grained annotation and classification of de novo predicted LTR retrotransposons. Nucleic Acids Res. 37, 7002-7013 (2009).

[54] Lyu, H., He, Z., Wu, C. I. & Shi, S. Convergent adaptive evolution in marginal environments: unloading transposable elements as a common strategy among mangrove genomes. N. Phytol. 217, 428-438 (2018).

[55] Neumann, P., Novák, P., Hoštáková, N. & Macas, J. Systematic survey of plant LTR-retrotransposons elucidates phylogenetic relationships of their polyprotein domains and provides a reference for element classification. Mob. DNA 10, 1 (2019).

[56] SanMiguel, P., Gaut, B. S., Tikhonov, A., Nakajima, Y. & Bennetzen, J. L. The paleontology of intergene retrotransposons of maize. Nat. Genet. 20, 43-45 (1998).

[57] Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772-780 (2013).

[58] Miele, V., Penel, S. & Duret, L. Ultra-fast sequence clustering from similarity networks with SiLiX. BMC Bioinforma. 12, 116 (2011).

[59] Stanke, M., Diekhans, M., Baertsch, R. & Haussler, D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics 24, 637-644 (2008).

[60] Boratyn, G. M. et al. Domain enhanced lookup time accelerated BLAST. Biol. Direct 7, 12 (2012).

[61] Droc, G. et al. The Banana Genome Hub Database (Oxford, 2013).

[62] Ouyang, S. et al. The TIGR rice genome annotation resource: improvements and new features. Nucleic Acids Res. 35, D883-D887 (2007).

[63] Singh, R. et al. Oil palm genome sequence reveals divergence of interfertile species in Old and New worlds. Nature 500, 335-339 (2013).

[64] Cai, J. et al. The genome sequence of the orchid Phalaenopsis equestris. Nat. Genet. 47, 65-72 (2015).

[65] Ming, R. et al. The pineapple genome and the evolution of CAM photosynthesis. Nat. Genet. 47, 1435-1442 (2015).

[66] Lowe, T. M. & Eddy, S. R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25, 955-964 (1997).

[67] Lagesen, K. et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 35, 3100-3108 (2007).

[68] Nawrocki, E. P. et al. Rfam 12.0: updates to the RNA families database. Nucleic Acids Res. 43, D130-D137 (2015).

[69] Bairoch, A. & Apweiler, R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res. 28, 45-48 (2000).

[70] Finn, R. D. et al. Pfam: the protein families database. Nucleic Acids Res. 42, D222-D230 (2014).

[71] Kent, W. J. BLAT-the BLAST-like alignment tool. Genome Res. 12, 656-664 (2002).

[72] Quevillon, E. et al. InterProScan: protein domains identifier. Nucleic Acids Res. 33, W116-W120 (2005).

[73] Marçais, G. et al. MUMmer4: a fast and versatile genome alignment system. PLoS Comp. Biol. 14, e1005944 (2018).

[74] Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome Biol. 5, R12 (2004).

[75] Zhao, H. et al. The chromosome-level genome assemblies of two rattans (Calamus simplicifolius and Daemonorops jenkinsiana). GigaScience 7, giy097 (2018).

[76] Costa, M. D. et al. A footprint of desiccation tolerance in the genome of Xerophyta viscosa. Nat. Plants 3, 1-10 (2017).

[77] Tamiru, M. et al. Genome sequencing of the staple food crop white Guinea yam enables the development of a molecular marker for sex determination. BMC Biol. 15, 1-20 (2017).

[78] Olsen, J. L. et al. The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea. Nature 530, 331-335 (2016).

[79] Jaillon, O. et al. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature 449, 463-467 (2007).

[80] Nguyen, L. T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268-274 (2015).

[81] Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972-1973 (2009).

[82] Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586-1591 (2007).

[83] Wang, D., Zhang, Y., Zhang, Z., Zhu, J. & Yu, J. KaKs_Calculator 2.0: a toolkit incorporating gamma-series methods and sliding window strategies. Genomics, Proteom. Bioinforma. 8, 77-80 (2010).

[84] Vanneste, K., Van de Peer, Y. & Maere, S. Inference of genome duplications from age distributions revisited. Mol. Biol. Evol. 30, 177-190 (2012).

[85] Li, Z. et al. Gene duplicability of core genes is highly consistent across all angiosperms. Plant Cell 28, 326-344 (2016).

[86] Kim, D., Landmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357-360 (2015).

[87] Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923-930 (2013).

[88] Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

[89] Jin, J. et al. PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Res. 4, D1040-D1045 (2016).

[90] Grant, C. E., Bailey, T. L. & Noble, W. S. FIMO: scanning for occurrences of a given motif. Bioinformatics 27, 1017-1018 (2011).

[91] Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 9, 559 (2008).

[92] Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16, 284-287 (2012).

[93] Deng, W., Zhang, K., Busov, V. & Wei, H. Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways. PloS One 12, e0171532 (2017).

[94] Yu, J. et al. The genomes of Oryza sativa: a history of duplications. PLoS Biol. 3, e38 (2005).

[95] Jiao, Y. et al. A genome triplication associated with early diversification of the core eudicots. Genome Biol. 13, R3 (2012).