A full genome assembly reveals drought stress effects on gene expression and metabolite profiles in blackcurrant (Ribes nigrum L.)

Abstract

Blackcurrant (Ribes nigrum L., family Grossulariaceae) is a perennial shrub that is widely cultivated for its edible berries. These are rich in antioxidants, vitamin C, and anthocyanins, making them a valuable ingredient in the food and beverage industry. However, prolonged periods of drought during the fruiting season lead to drought stress, which has serious ecological and agricultural implications, inhibiting blackcurrant growth and reducing yields. To facilitate the analysis of underlying molecular processes, we present the first high-quality chromosome-scale and partially haplotype-resolved assembly of the blackcurrant genome (cv. Rosenthals Langtraubige), also the first in the family Grossulariaceae. We used this genomic reference to analyze the transcriptomic response of blackcurrant leaves and roots to drought stress, revealing differentially expressed genes with diverse functions, including those encoding the transcription factors bZIP, bHLH, MYB, and WRKY, and tyrosine kinase-like kinases such as PERK and DUF26. Gene expression was correlated with the abundance of primary metabolites, revealing 14 with significant differences between stressed leaves and controls indicating a metabolic response to drought stress. Amino acids such as proline were more abundant under stress conditions, whereas organic acids were depleted. The genomic and transcriptomic data from this study can be used to develop more robust blackcurrant cultivars that thrive under drought stress conditions.

Acknowledgements

This study was funded by the European Union’s Horizon 2020 program under grant agreement number 679303. We thank Dr. Elisa Senger and Dr. Richard M Twyman for manuscript proofreading.

Author contributions

F.M.R.Z. performed ONT sequencing, data analysis, and manuscript writing, supported and supervised by B.U. S.O. and JGV performed metabolite measurement, and V.R. helped with ONT PoreC sequencing. L.M. provided RNA-Seq data of the drought stress experiment. F.G. and S.S. performed qPCR of selected candidate genes. A.S., L.S., and S.K.P. provided RNA-Seq data for genome annotation. All authors read and approved the final manuscript.

Data availability

Processed data are available in the supplementary data including read data summaries (S12) and raw sequencing data, and the genome will be available on EMBL-EBI (PRJEB77865). In addition, we added in the supplementary data the genomes and their annotation to the PLANTdataHUB [141] https://git.nfdi4plants.org/usadellab/ribes_nigrum_genome to make them accessible before publication.

Conflict of interest statement

The authors declare no competing interest.

Supplementary Data

Supplementary data is available at Horticulture Research online.

References

[1] Abe H, Urao T, Ito T. et al. Arabidopsis AtMYC 2 (bHLH) and AtMYB2 (MYB) function as transcriptional activators in abscisic acid signaling. Plant Cell. 2003;15:63-78

[2] Russell JR, Bayer M, Booth C. et al. Identification, utilization and mapping of novel transcriptome-based markers from blackcur-rant (Ribes nigrum). BMC Plant Biol. 2011;11:147

[3] Čereković N, Pagter M, Kristensen HL. et al. Effects of drought stress during flowering of two pot-grown blackcurrant ( Ribes nigrum L.) cultivars. Sci Hortic. 2013;162:365-73

[4] Yang X, Lu M, Wang Y. et al. Response mechanism of plants to drought stress. Horticulturae. 2021;7:50

[5] Jan S, Abbas N, Ashraf M. et al. Roles of potential plant hor-mones and transcription factors in controlling leaf senescence and drought tolerance. Protoplasma. 2018;256:313-29

[6] Munné-Bosch S, Allegre L. Die and let live: leaf senescence contributes to plant survival under drought stress. Funct Plant Biol. 2004;31:203-16

[7] Kuromori T, Seo M, Shinozaki K. ABA transport and plant water stress responses. Trends Plant Sci. 2018;23:513-22

[8] Choi WG, Miller G, Wallace I. et al. Orchestrating rapid long-distance signaling in plants with Ca²⁺, ROS and electric sig-nals. Plant J. 2017;90:698-707

[9] Ozturk M, Unal BT, García-Carparrós P. et al. Osmoregulation and its actions during the drought stress in plants. Physiol Plant. 2020;172:1321-35

[10] Lawas LMF, Zuther E, Jagadish SVK. et al. Molecular mech-anisms of combined heat and drought stress resilience in cereals. Curr Opin Plant Biol. 2018;45:212-7

[11] Farooqi MQU, Nawaz G, Wani SH, CHoudhary JR, Rana M, Sah RP, Afzal M, Zahra Z, Ganie SA, Razzaq A, Reyes VR, Mahmoud EA, Elansary HO, El-Abedin TKZ, Siddique KHM (2022). Recent developments in multi-omics and breeding strategies for abi-otic stress tolerance in maize ( Zea mays L.). Frontiers in PLant Science 13:965878.

[12] Powell AF, Feder A, Li J. et al. A Solanum lycopersicoides ref-erence genome facilitates insights into tomato specialized metabolism and immunity. Plant J. 2022;110:1791-810

[13] Hewitt S, Hernández-Montes E, Dhingra A. et al. Impact of heat stress, water stress, and their combined effects on the metabolism and transcriptome of grape berries. Sci Rep. 2023;13:9907

[14] Čerekovi ć N, Jarret D, Pagter M. et al. The effects of drought stress on leaf gene expression during flowering in blackcurrant (Ribes nigrum L.). Eur J Hortic Sci. 2015;80:39-46

[15] Russell JR, Hackett C, Hedley P. et al. The use of genotyping by sequencing in blackcurrant (Ribes nigrum): developing high-resolution linkage maps in species without reference genome sequences. Mol Breed. 2013;33:835-49

[16] Jarret D, Morris J, Cullen DW. et al. A transcriptome and metabolite atlas of blackcurrant fruit development highlights hormonal regulation and reveals the role of key transcription factors. Front Plant Sci. 2018;9:1235

[17] Thole V, Bassard JE, Ramírez-González R. et al. RNA-seq,de novo transcriptome assembly and flavonoid gene analysis in 13 wild and cultivated berry fruit species with high content of phenolics. BMC Genet. 2019;20:995

[18] Mažeikienė I, Juškyte˙ AD, Stanys V. De novo transcriptome analysis of R. nigrum cv. Aldoniai in response to blackcurrant reversion virus infection. Int J Mol Sci. 2022;23:3137

[19] Juškytė AD, Mažeikiene˙ I, Stanys V. Analysis of R genes related to blackcurrant reversion virus resistance in the compara-tive transcriptome of Ribes nigrum cv. Aldoniai. Plants (Basel). 2022;11:3137

[20] SunX, ZhanY, LiS. et al. Complete chloroplast genome assem-bly and phylogenetic analysis of blackcurrant (Ribes nigrum), red and white currant (Ribes rubrum), and gooseberry (Ribes uva-crispa) provide new insights into the phylogeny of Grossulari-aceae. PeerJ. 2023;11:e16272

[21] Chiche J, Brown SC, Leclerc JC. et al. Genome size, hete-rochromatin organisation, and ribosomal gene mapping in four species of Ribes. Can J Bot. 2003;81:191-296

[22] Cheng H, Asri M, Lucas J. et al. Scalable telomere-to-telomere assembly for diploid and polyploid genomes with double graph. Nat Methods. 2024;21:967-70

[23] Rhie A, Walenz BP, Koren S. et al. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol. 2020;21:245

[24] Ou S, Su W, Liao Y. et al. Benchmarking transposable element annotation methods for creation of streamlined, comprehen-sive pipeline. Genome Biol. 2019;20:275

[25] Li K, Xu P, Wang J. et al. Identification of errors in draft genome assemblies at single-nucleotide resolution for quality assess-ment and improvement. Nat Commun. 2023;14:6556

[26] Simão FA, Waterhouse RM, Ioannidis P. et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31:3210-2

[27] Schwacke R, Ponce-Soto GY, Krause K. et al. MapMan4: a refined protein classification and annotation framework applicable to multi-omics data analysis. Mol Plant. 2019;12:879-92

[28] Ulahannan N, Pendleton M, Deshpande A. et al. Nanopore sequencing of DNA concatemers reveals higher-order features of chromatin structure. 2019; bioRxiv preprint: 833590

[29] Cheng H, Asri M, Lucas J. et al. Scalable telomere-to-telomere assembly for diploid and polyploid with double graph. Nat Methods. 2023;21:967-70

[30] van Rengs WMJ, Schmidt MH-W, Effgen S. et al. A chromosome scale tomato genome built from complementary PacBio and nanopore sequences alone reveals extensive linkage drag dur-ing breeding. Plant J. 2022;110:572-88

[31] Zielinski QB. Chromosome numbers and meiotic studies. Bot Gaz. 1953;114:265-74

[32] Feron R, Waterhouse RM. Assessing species coverage and assembly quality of rapidly accumulating sequenced genomes. GigaScience. 2022;11:giac006

[33] Michael TP, Jupe F, Bemm F. et al. High contiguity Arabidopsis thaliana genome assembly with a single nanopore flow cell. Nat Commun. 2018;9:541

[34] Ou S, Chen J, Jiang N (2018). Assessing genome assembly qual-ity using the LTR Assembly Index (LAI). Nucleic Acid Research 46:e126.

[35] Du H, Yu Y, Ma Y. et al. Sequencing and de novo assembly of a near complete indica rice genome. Nat Commun. 2017;8:15324

[36] Song JM, Xie WZ, Wang S. et al. Two gap-free reference genomes and global view of the centromere architecture in rice. Mol Plant. 2021;14:1757-67

[37] Sun R, Li S, Chang L. et al. Chromosome-level genome assembly of Fragaria pentaphylla using PacBio and hi-C technologies. Front Genet. 2022;13:873711

[38] Huang Y, Escalona M, Morrison G. et al. Reference genome assembly of the big berry Manzanita (Arctostaphylos glauca). J Hered. 2022;113:188-96

[39] Zhao SW, Gup JF, Kong L. et al. Haplotype-resolved genome assembly of Coriaria nepalensis a non-legume nitrogen-fixing shrub. Sci Data. 2023;10:259

[40] Soltis DE, Smith SA, Cellinese N. et al. Angiosperm phylogeny: 17 genes, 640 taxa. Am J Bot. 2011;98:704-30

[41] Liu L, Chen M, Folk RA. et al. Phylogenomic and syntenic data demonstrate complex evolutionary processes in early radiation of the rosids. Mol Ecol Resour. 2023;23:1673-88

[42] Yuan J, Jiang S, Liu M. et al. Genomic basis of the giga-chromosomes and giga-genome of tree peony Paeonia ostii. Nat Commun. 2022;13:7328

[43] Yu J, Hulse-Kemp AM, Babiker E. et al. High-quality reference genome and annotation aids understanding of berry develop-ment for evergreen blueberry (Vaccinium darrowii). Hortic Res. 2021;8:228

[44] Davik J, Røen D, Lysøe E. et al. A chromosome -level genome sequence assembly of the red raspberry ( Rubus idaeus L.). PLoS One. 2022;17:e0265096

[45] Zhu S, Chen J, Zhao J. et al. Genomic insights on the contribu-tion of balancing selection and local adaptation to the long-term survival of a widespread living fossil tree, Cercidiphyllum japonicum. New Phytol. 2020;228:1674-89

[46] Gish LA, Clark SE. The RLK/Pelle family of kinases. Plant J. 2011;66:117-27

[47] Ksouri N, Jiménez S, Wells CE. et al. Transcriptional responses in root and leaf of Prunus persica under drought stress using RNA sequencing. Front Plant Sci. 2016;7:1715

[48] Wei K, Wang Y, Zhong X. et al. Protein kinase structure, expres-sion and regulation in maize drought signaling. Mol Breed. 2014;34:583-602

[49] Lin W, Ma X, Shan L. et al. Big roles of small kinases: the complex functions of receptor-like cytoplasmic kinases in plant immunity and development. J Integr Plant Biol. 2013;55:1188-97

[50] He Y, Zhou J, Shan L. et al. Plant cell surface receptor-mediated signaling- a common theme amid diversity. J Cell Sci. 2018;131:jcs209353

[51] Liang X, Zhou JM (2018). Receptor-Like Cytoplasmic Kinases: Central Players in Plant Receptor Kinase-Mediated Signaling. Annual review of plant biology 69:267-99

[52] Forzani C, Carreri A, de la Fuente van Bentem S. et al. The Arabidopsis protein kinase Pto-interacting 1-4 is a common tar-get of the oxidative signal-inducible 1 and mitogen-activated protein kinases. FEBS J. 2011;278:1126-36

[53] Majhi BB, Sobol G, Gachie S. et al. Brassinosteroid-signalling kinases 7 and 8 associate with the FLS2 immune receptor and are required for flg22-induced PTI responses. Mol Plant Pathol. 2021;22:786-99

[54] Wang J, Hu M, Wang J. et al. Reconstitution and structure of a plant NLR resistosome conferring immunity. Science. 2019a;364:eaav5870

[55] Wang J, Wang J, Hu M. et al. Ligand-triggered allosteric ADP release primes a plant NLR complex. Science. 2019b;364:eaav5868

[56] Bai L, Guozeng Z, Yun Z. et al. Plasma membrane-associated proline-rich extensin-like receptor kinase 4, a novel regulator of Ca²⁺ signaling, is required for abscisic acid responses in Arabidopsis thaliana. Plant J. 2009;60:314-27

[57] Shahid S, Sher MA, Ahmad F. et al. Prediction of RNA editing sites and genome-wide characterization of PERK gene family in maize (Zea mays L.) in response to drought stress. J King Saud Univ Sci. 2022;34:102293

[58] Wrzaczek M, Brosché M, Salojärvi J, Kangasjärvi S, Idän-heimo N, Mersmann S, Robatzek S, Karpìński S, Karpìńska B, Kangasjärvi J (2010). Transcriptional regulation of the CRK/DUF 26 group of receptor-like protein kinases by ozone and plant hormones in Arabidopsis. BMC Plant Biology 10, 95.

[59] Arellano-Villagómez FC, Guevara-Olvera L, Zuñiga-Mayo VM, Cerbantez-Bueno VE, Verdugo-Perales M, Medina HR, De Folter S,Gerardo Acosta-García G ( 2021). Arabidopsis cysteine-rich receptor-like protein kinase CRK33 affects stomatal density and drought tolerance. Plant Signal Behaviour 16:1905335.

[60] Kundu S, Gantait S. Abscisic acid signal crosstalk during abiotic stress response. Plant Gene. 2017;11:61-9

[61] Baena-González E, Rolland F, Thevelein JM. et al. A central integrator of transcription networks in plant stress and energy signalling. Nature. 2007;448:938-42

[62] Zhang Y, Shewry PR, Jones H. et al. Expression of antisense SnRK1 protein kinase sequence causes abnormal pollen devel-opment and male sterility in transgenic barley. Plant J. 2001;28:431-41

[63] Radchuk R, Radchuk V, Weschke W, Borisjuk L, Weber H (2006). Repressing the expression of the SUCROSE NONFERMENTING-1-RELATED PROTEIN KINASE gene in pea embryo causes pleiotropic defects of maturation similar to an abscisic acid-insensitive phenotype. Plant Physiology 140:263-78

[64] Yang R, Guo Q, Gu Z.GABA shunt and polyamine degradation pathway on γ-aminobutyric acid accumulation in germinating fava bean (Vicia faba L.) under hypoxia. Food Chem. 2013;136:152-9

[65] Hasan MM, Liu XD, Waseem M. et al. ABA activated AnRK 2 kinases: an emerging role in plant growth and physiology. Plant Signal Behav. 2022;17:2071024

[66] Chen K, Tang W, Zhou Y. et al. AP2/ERF transcription factor GmDREB1 confers drought tolerance in transgenic soybean by interacting with GmERFs. Plant Physiol Biochem. 2022;170:287-95

[67] Dubouzet JG, Sakuma Y, Ito Y. et al. OsDREB genes in rice, Oryza sativa L., encode transcription activators that function in drought-, high-salt- and cold-responsive gene expression. Plant J. 2003;33:751-63

[68] Huang XY, Chao DY, Gao JP. et al. A previously unknown zinc finger protein, DST, regulates drought and salt tolerance in rice via stomatal aperture control. Genes Dev. 2009a;23:1805-17

[69] Joshi R, Wani SH, Singh B. et al. Transcription factors and plants response to drought stress: current understanding and future directions. Front Plant Sci. 2016;7:1029

[70] Khoso MA, Hussain A, Ritonga FN. et al. WRKY transcription factors (TFs): molecular switches to regulate drought, temper-ature, and salinity stresses in plants. Front Plant Sci. 2022;13:3389

[71] Li Z, Liang F, Zhang FN. et al. Enhanced tolerance to drought stress resulting from Caragana korshinskii CkWRKY 33 in trans-genic Arabidopsis thaliana. BMC Genom Data. 2021;22:11

[72] Liu W, Tai H, Li S. et al. bHLH 122 is important for drought and osmotic stress resistance in Arabidopsis and in the repression of ABA catabolism. New Phytol. 2014;201:1192-204

[73] Qu X, Wang H, Chen M. et al. Drought stress-induced physiolog-ical and metabolic changes in leaves of two oil tea cultivars. J Am Soc Hortic Sci. 2019;144:439-47

[74] Qiu XM, Sun YY, Ye XY. et al. Signaling role of glutamate in plants. Front Plant Sci. 2020;10:1743

[75] Valliyodan B, Nguyen HT. Understanding regulatory networks and engineering for enhanced drought tolerance in plants. Plant Biol. 2006;9:189-95

[76] Takasaki H, Maruyama K, Kidokoro S. et al. The abiotic stress-responsive NAC-type transcription factor OsNAC5 regulates stress-inducible genes and stress tolerance in rice. Mol Genet Genomics. 2010;284:173-83

[77] Tran LS, Nakashima K, Sakuma Y. et al. Isolation and functional analysis of Arabidopsis stress-inducible NAC transcription fac-tors that bind to a drought-responsive cis-element in the early response to dehydration stress 1 promoter. Plant Cell. 2004;16:2481-98

[78] Huang J, Sun S, Xu D. et al. Increased tolerance of rice to cold, drought and oxidative stresses mediated by the overexpression of a gene that encodes the zinc finger protein ZFP245. Biochem Biophys Res Commun. 2009b;389:556-61

[79] Wang K, Ding Y, Cai C. et al. The role of C2H2 zinc finger proteins in plant response to abiotic stresses. Physiol Plant. 2018;165:690-700

[80] He X, Wang C, Wang H. et al. The function of MAPK cascades in response to various stresses in horticultural plants. Front Plant Sci. 2020;11:952

[81] Ku YS, Sintaha M, Cheung MY. et al. Plant hormone signaling crosstalks between biotic and abiotic stress responses. Int J Mol Sci. 2018;19:3206

[82] Lin L, Wu J, Jiang M. et al. Plant mitogen-activated protein kinase cascades in environmental stresses. Int J Mol Sci. 2021;22:1543

[83] Agalou A, Purwantomo S, Overnaes E. et al. A genome-wide sur-vey of HD-zip genes in rice and analysis of drought-responsive family members. Plant Mol Biol. 2008;66:87-103

[84] Himmelbach A, Hoffmann T, Leube M. et al. Homeodomain protein ATHB6 is a target of the protein phosphatase ABI1 and regulates hormone responses in Arabidopsis. EMBO J. 2002;21:3029-38

[85] Olsson AS, Engström P, Söderman E. The homeobox genes ATHB12 and ATHB7 encode potential regulators of growth in response to water deficit in Arabidopsis. Plant Mol Biol. 2004;55:663-77

[86] Perotti MF, Arce AL, Chan RL. The underground life of homeodomain-leucine zipper transcription factors. JExp Bot. 2021;72:4005-21

[87] Jiang F, Hartung W. Long-distance signaling of abscisic acid (ABA): the factors regulating the intensity of ABA signal. JExp Bot. 2008;59:37-43

[88] Ullah N, Yüce M, Gökçe ZNÖ. et al. Comparative metabolite profiling of drought stress in roots and leaves of seven Triticeae species. BMC Genomics. 2017;18:969

[89] Hildebrandt TM, Nesi AN, Araújo WL. et al. Amino acid catabolism in plants. Mol Plant. 2015;8:1563-79

[90] Pratelli R, Guillaume P. Regulation of amino acid metabolic enzymes and transporters in plants. JExp Bot. 2014;65:5535-56

[91] Huang T, Jander G. Abscisic acid-regulated protein degrada-tion causes osmotic stress-induced accumulation of branched-chain amino acids in Arabidopsis thaliana. Planta. 2017;246:737-47

[92] Rizhsky L, Liang H, Shuman J. et al. When defense pathways col-lide. The response of Arabidopsis to a combination of drought and heat stress. Plant Physiol. 2004;134:1683-96

[93] Szabados L, Savouré A. Proline: a multifunctional amino acid. Trends Plant Sci. 2010;15:89-97

[94] Wang B, Yang X, Jia Y. et al. High-quality Arabidopsis thaliana genome assembly with nanopore and hifi long reads. Genomics Proteomics Bioinformatics. 2021;20:4-13

[95] Hasan MM, Alabdallah NM, Alharbi BM. et al. GABA: a key player in drought stress resistance in plants. Int J Mol Sci. 2021;22:10136

[96] Mousavi SAR, Chauvin A, Pascaud F. et al. GLUTAMATE RECEPTOR-LIKE genes mediate leaf-to-leaf wound signalling. Nature. 2013;500:422-6

[97] Nguyen CT, Kurenda A, Stolz S. et al. Identification of cell populations necessary for leaf-to-leaf electrical signaling in a wounded plant. PNAS. 2018;115:10178-83

[98] Sun C, Gao X, Zhou J. et al. Metabolic response of maize ( Zea mays L.) plants to combined drought and salt stress. Plant and Soil. 2015;388:99-117

[99] Toyota M, Spencer D, Sawai-Toyota S. et al. Glutamate triggers long-distance, calcium-based plant defense signaling. Science. 2018;361:1112-5

[100] Degu A, Hatew B, Nunes-Nesi A. et al. Inhibition of aconitase in citrus fruit callus results in a metabolic shift towards amino acid biosynthesis. Planta. 2011;234:501-13

[101] Araújo WL, Martins AO, Fernie AR. et al. 2-oxoglutarate: linking TCA cycle function with amino acid, glucosinolate, flavonoid, alkaloid, and gibberellin biosynthesis. Front Plant Sci. 2014;5:552

[102] Wan T, Feng Y, Liang C. et al. Metabolomics and transcriptomics analysis of two contrasting cherry rootstocks in response to drought stress. Biology (Basel). 2021;10:201

[103] Joshi V, Joung JG, Fei Z. et al. Interdependence of threonine, methionine and isoleucine metabolism in plants: accumula-tion and transcriptional regulation under abiotic stress. Amino Acids. 2010;39:933-47

[104] Sanchez DH, Siahpoosh MR, Roessner U. et al. Plant metabolomics reveals conserved and divergent metabolic responses to salinity. Physiol Plant. 2008;132:209-19

[105] Székely G, Abrahám E, Cséplo A. et al. Duplicated P5CS genes of Arabidopsis play distinct roles in stress regulation and devel-opmental control of proline biosynthesis. Plant J. 2008;53:11-28

[106] Shim JS, Jeong HI, Bang SW. et al. Drought-induced branched-chain amino acid aminotransferase enhances drought toleran-cein rice. Plant Physiol. 2018;191:1435-47

[107] Suguiyama VF, Silva EA, Meirelles ST. et al. Leaf metabolite profile of the Brazilian resurrection plant Barbacenia purpurea hook. (Velloziaceae) shows two time-dependent responses dur-ing desiccation and recovering. Front Plant Sci. 2014;5:96

[108] Kumar M, Patel MK, Kumar N. et al. Metabolomics and molec-ular approaches reveal drought stress tolerance in plants. Int J Mol Sci. 2021;22:9108

[109] Wang C, Yang A, Yin H. et al. Influence of water stress on endogenous hormone contents and cell damage of maize seedlings. J Integr Plant Biol. 2008;50:427-34

[110] Bowne JB, Erwin TA, Jutter J. et al. Drought responses of leaf tissues from wheat cultivars of differing drought tolerance at the metabolite level. Mol Plant. 2012;5:418-29

[111] Kaur H, Manna M, Thakur T. et al. Imperative role of sugar signaling and transport during drought stress responses in plants. Physiol Plant. 2021;171:833-48

[112] Taji T, Ohsumi C, Iuchi S. et al. Important roles of drought- and cold-inducible genes for galactinol synthase in stress tolerance in Arabidopsis thaliana. Plant J. 2002;29:417-26

[113] You J, Zhang Y, Liu A. et al. Transcriptomic and metabolomic profiling of drought-tolerant and susceptible sesame genotypes in response to drought stress. BMC Plant Biol. 2019;19:267

[114] Dilokpimol A, Poulsen CP, Vereb G. et al. Galactosyltransferases from Arabidopsis thaliana in the biosynthesis of type II ara-binogalactan: molecular interaction enhances enzyme activity. BMC Plant Biol. 2014;14:90

[115] Hedley PE, Russel JR, Jorgensen L. et al. Candidate genes associ-ated with bud dormancy release in blackcurrant ( Ribes nigrum L.). BMC Plant Biol. 2010;10:202

[116] Ganger MT, Dietz GD, Erwing SJ. A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments. BMC Bioinformatics. 2017;18:534

[117] Zhao S, Fernald RD. Comprehensive algorithm for quantitative real-time polymerase chain reaction. JComputBiol. 2005;12:1047-64

[118] Wick RR, Judd LM, Cl G. et al. Completing bacterial genome assemblies with multiplex MinION sequencing. Microb Genom. 2017;3:e000132

[119] Cheng H, Jarvis ED, Fedrigo O. et al. Haplotype-resolved assem-bly of diploid genomes without parental data. Nat Biotechnol. 2022;40:1332-5

[120] Roach MJ, Schmidt SA, Bornemann AR. Purge Haplotigs_ allelic contig reassignment for third-gen diploid genome assemblies. BMC Bioinformatics. 2018;19:460

[121] Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics. 2018;34:3094-100

[122] Zhou C, McCarthy SA, Durbin R. YaHS: yet another Hi-C scaf-folding tool. BMC Bioinformatics. 2022;39:btac808

[123] Dudchenko O, Shamim MS, Batra SS. et al. The Juicebox assem-bly tools module facilitates de novo assembly of mammalian genomes with chromosome-length scaffolds for under $1000. 2018; bioRxiv 254797

[124] Gurevich A, Saveliev V, Vyahhi NT. et al. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29:1072-5

[125] Alonge M, Lebeigle L, Kirsche M. et al. Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing. Genome Biol. 2022;23:258

[126] Goel M, Sun H, Jiao WB. et al. SyRI: finding genomic rearrange-ments and local sequence differences from whole-genome assemblies. Genome Biol. 2019;20:277

[127] Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. 2012; arXiv preprint arXiv:1207.3907

[128] Cingolani P, Platts A, Wang le L. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012;2:80-92

[129] RStudio Team (2020). RStudio: Integrated Development for R.RStu-dio, PBC, Boston, MA URL

[130] Ou S, Jiang N. Assessing genome assembly quality using the LTR assembly index (LAI). Nucleic Acids Res. 2018; gky730

[131] Camacho C, Coulouris G, Avagyan V. et al.BLAST+: architecture and applications. BMC Bioinformatics. 2008;10:421

[132] Holst F, Bolger A, Günther C. et al. Helixer-de novo prediction of primary eukaryotic gene models combining deeep learning and a hidden markov model. 2023; bioRxiv, 2023. 02.06.527280v2

[133] Shumate A, Wong B, Pertea G. et al. Improved transcriptome assembly using a hybrid of long and short reads with StringTie. PLoS Comput Biol. 2022;18:e1009730

[134] Mapleson DL, Venturini L, Kaithakottil G. et al. Efficient and accurate detection of splice junctions from RNAseq with portcullis. GigaScience. 2018;7:giy131

[135] Pertea G, Pertea M. GFF utilities: GrrRead and GffCompare. F 1000 F1000 Res. 2020; ISCB Comm J-304

[136] PatroR, DuggalG, LoveMI. et al. Salmon: fast and bia-aware quantification of transcript expression using dual-phase infer-ence. Nat Methods. 2019;14:417.419

[137] Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139-40

[138] Osorio S, Alba R, Nikoloski Z. et al. Integrative comparative analyses of transcript and metabolite profiles from pepper and tomato ripening and development stages uncovers species-specific patterns of network regulatory behaviour. Plant Physiol. 2012;159:1713-29

[139] Vallarino JG, de Abreu e Lima F, Soria C. et al. Genetic diversity of strawberry germplams using metabolomic biomarkers. Sci Rep. 2018;8:14386

[140] Kopka J, Schauer N, Krueger S. et al. GMD@CSB. DB: the golm metabolome database. Bioinformatics. 2005;21:1635-8

[141] Weil HL, Schneider K, Tschöpe M. et al. PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research. Plant J. 2023;116:974-88