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MusaRgeneDB: an online comprehensive database for disease resistance genes in Musa spp.

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Abstract

Banana is one of the major food crops and its production is subject to many pests and diseases. Banana breeding exploits wild relatives and progenitor species for the introgression of resistant genes (R) into cultivated varieties to overcome these hurdles. With advances in sequencing technologies, whole-genome sequences are available for many Musa spp. and many of them are potential donors of disease resistance genes. Considering their potential role, R genes from these species were explored to develop an user-friendly open-access database that will be useful for studying and implementing disease resistance in bananas. MusaRgene database is complemented with complete details of 3598 R genes identified from eight Musa spp. and rice, Arabidopsis, sorghum along with its classification and separate modules on its expression under various stresses in resistant and susceptible cultivars and corresponding SSRs are also provided. This database can be regarded as the primary resource of information on R genes from bananas and their relatives. R genes from other allele mining studies are also incorporated which will enable the identification of its homolog in related Musa spp. MusaRgene database will aid in the identification of genes and markers associated, cloning of full-length R genes, and genetic transformation or gene editing of the R genes in susceptible cultivars. Multiple R genes can also be identified for pyramiding the genes to increase the level of resistance and durability. Overall, this database will facilitate the understanding of defense mechanisms in bananas against biotic or abiotic stresses leading to the development of promising disease-resistant varieties.

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Data availability

The MusaRgeneDB is publicly accessible at http://musargene.byethost6.com/.

Abbreviations

PTI:

PAMP-triggered immunity

PRRs:

Pattern-recognition receptors

PAMP/MAMP:

Pathogen/microbe-associated molecule patterns

Avr:

Avirulence genes

ETI:

Effector-triggered immunity

RLPs:

Receptor-like proteins

RLKs:

Receptor-like protein kinases

CDD:

Conserved domain database

PRGdb:

Plant resistance genes database

HMM:

Hidden Markov model

References

  • Atkinson NJ, Urwin PE (2012) The interaction of plant biotic and abiotic stresses: from genes to the field. J Exp Bot 63(10):3523–3543

    Article  CAS  Google Scholar 

  • Babu BK, Dinesh P, Agrawal PK et al (2014) Comparative genomics and association mapping approaches for blast resistant genes in finger millet using SSRs. PLoS ONE 9(6):e99182

    Article  Google Scholar 

  • Backiyarani S, Uma S, Varatharj P et al (2013) Mining of EST-SSR markers of Musa and their transferability studies among the members of order the Zingiberales. Appl Biochem Biotechnol 169(1):228–238

    Article  CAS  Google Scholar 

  • Backiyarani S, Uma S, Arunkumar G et al (2014) Differentially expressed genes in incompatible interactions of Pratylenchus coffeae with Musa using suppression subtractive hybridization. Physiol Mol Plant Pathol 86:11–18

    Article  CAS  Google Scholar 

  • Backiyarani S, Uma S, Saraswathi MS et al (2015) Transcriptome analysis of banana (Musa balbisiana) based on next generation sequencing technology. Turk J Agric for 39(5):705–717

    Article  CAS  Google Scholar 

  • Backiyarani S, Chandrasekar A, Uma S et al (2019) MusatransSSRDB (A transcriptome derived SSR database)—an advanced tool for banana improvement. J Biosci 44(1):4

    Article  Google Scholar 

  • Backiyarani S, Anuradha C, Uma S (2022) Genomic designing for biotic stress resistant banana. In: Kole C (ed) Genomic designing for biotic stress resistant fruit crops. Springer Cham, Switzerland, pp 25–74

    Chapter  Google Scholar 

  • Bateman A, Velankar S, Tunyasuvakool K et al (2021) How to interpret AlphaFold structures. European Bioinformatics Institute (EMBL-EBI) 2021. https://doi.org/10.6019/tol.alphafold-w.2021.00001.1

  • Beier S, Thiel T, Münch T et al (2017) MISA-web: a web server for microsatellite prediction. Bioinformatics 33(16):2583–2585

    Article  CAS  Google Scholar 

  • Czislowski E, Fraser-Smith S, Zander M et al (2018) Investigation of the diversity of effector genes in the banana pathogen, Fusarium oxysporum f. sp. cubense, reveals evidence of horizontal gene transfer. Mol Plant Pathol 19(5):1155–1171

    Article  CAS  Google Scholar 

  • Dong OX, Ronald PC (2019) Genetic engineering for disease resistance in plants: recent progress and future perspectives. Plant Physiol 180(1):26–38

    Article  CAS  Google Scholar 

  • Gadaleta A, Giancaspro A, Giove SL et al (2009) Genetic and physical mapping of new EST-derived SSRs on the A and B genome chromosomes of wheat. Theor Appl Genet 118(5):1015–1025

    Article  CAS  Google Scholar 

  • Goodstein DM, Shu S, Howson R et al (2012) Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res 40(D1):D1178–D1186

    Article  CAS  Google Scholar 

  • Guidetti-Gonzalez S, Carrer H (2007) Putative resistance genes in the CitEST database. Genet Mol Biol 30(3):931–942

    Article  CAS  Google Scholar 

  • Guo WZ, Sang ZQ, Zhou BL et al (2007) Genetic relationships of D-genome species based on two types of EST-SSR markers derived from G. arboreum and G. raimondii in Gossypium. Plant Sci 172:808–814

    Article  CAS  Google Scholar 

  • Hunter S, Apweiler R, Attwood TK et al (2009) InterPro: the integrative protein signature database. Nucleic Acids Res 37(Database issue):211–215

    Article  Google Scholar 

  • Johnson LS, Eddy SR, Portugaly E (2010) Hidden Markov model speed heuristic and iterative HMM search procedure. BMC Bioinform 11:431

    Article  Google Scholar 

  • Jones JD, Dangl JL (2006) The plant immune system. Nature 444(7117):323–329

    Article  CAS  Google Scholar 

  • Li J, Ding J, Zhang W et al (2010) Unique evolutionary pattern of numbers of gramineous NBS-LRR genes. Mol Genet Genomics 283:427–438

    Article  CAS  Google Scholar 

  • Li F, Han Y, Feng Y et al (2013) Expression of wheat expansin driven by the RD29 promoter in tobacco confers water-stress tolerance without impacting growth and development. J Biotechnol 163(3):281–291

    Article  CAS  Google Scholar 

  • Li J, Cocker JM, Wright J et al (2016) Genetic architecture and evolution of the S locus supergene in Primula vulgaris. Nat Plants 2(12):16188

    Article  CAS  Google Scholar 

  • MathiThumilan B, Sajeevan RS, Biradar J et al (2016) Development and characterization of genic SSR markers from Indian mulberry transcriptome and their transferability to related species of Moraceae. PLoS ONE 11(9):e0162909

    Article  CAS  Google Scholar 

  • MusaNet (2016) Global strategy for the conservation and use of Musa genetic resources (B.Laliberté, compiler). Bioversity International, Montpellier

    Google Scholar 

  • Mushtaq M, Sakina A, Wani SH et al (2019) Harnessing genome editing techniques to engineer disease resistance in plants. Front Plant Sci 10:550

    Article  Google Scholar 

  • Muthusamy M, Uma S, Backiyarani S et al (2016) Transcriptomic changes of drought-tolerant and sensitive banana cultivars exposed to drought stress. Front Plant Sci 7:1609

    PubMed  PubMed Central  Google Scholar 

  • Nansamba M, Sibiya J, Tumuhimbise R et al (2020) Breeding banana (Musa spp.) for drought tolerance: a review. Plant Breed 139(4):685–696

    Article  Google Scholar 

  • Osuna-Cruz CM, Gallart AP, Donato AD et al (2018) PRGdb 3.0: a comprehensive platform for prediction and analysis of plant disease resistance genes. Nucleic Acids Res 46:D1197–D1201

    Article  CAS  Google Scholar 

  • Pan Q, Wendel J, Fluhr R (2000) Divergent evolution of plant NBS-LRR resistance gene 31 homologues in dicot and cereal genomes. J Mol Evol 50:203–213

    Article  CAS  Google Scholar 

  • Saravanakumar AS, Uma S, Thangavelu R et al (2016) Preliminary analysis on the transcripts involved in resistance responses to eumusae leaf spot disease of banana caused by Mycosphaerella eumusae, a recent add-on of the sigatoka disease complex. Turk J Bot 40:461–471

    Article  CAS  Google Scholar 

  • Singh J, Kalberer SR, Belamkar V et al (2017) A transcriptome-SNP-derived linkage map of Apios americana (potato bean) provides insights about genome re-organization and synteny conservation in the phaseoloid legumes. Theor Appl Genet 131(2):333–351

    Article  Google Scholar 

  • Tabbasam N, Zafar Z, Mehboob-ur-Rahman (2014) Pros and cons of using genomic SSRs an EST-SSRs for resolving phylogeny of the genus Gossypium. Plant Syst Evol 300:559–575

    Article  Google Scholar 

  • Tan S, Wu S (2012) Genome wide analysis of nucleotide-binding site disease resistance genes in Brachypodium distachyon. Comp Funct Genomics 2012:418208

    Article  Google Scholar 

  • Thiel T, Michalek W, Varshney R et al (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet 106(3):411–422

    Article  CAS  Google Scholar 

  • Toda N, Rustenholz C, Baud A et al (2020) NLGenomeSweeper: a tool for genome-wide NBS-LRR resistance gene identification. Genes 11(3):333

    Article  CAS  Google Scholar 

  • Van der Biezen EA, Jones JD (1998) Plant disease-resistance proteins and the gene-for-gene concept. Trends Biochem Sci 23(12):454–456

    Article  Google Scholar 

  • Visser RGF, Bachem CWB, de Boer JM et al (2009) Sequencing the potato genome: outline and first results to come from the elucidation of the sequence of the world’s third most important food crop. Am J Potato Res 86:417–429

    Article  CAS  Google Scholar 

  • Vleeshouwers VG, Finkers R, Budding D et al (2011) SolRgene: an online database to explore disease resistance genes in tuber-bearing Solanum species. BMC Plant Biol 11:116

    Article  CAS  Google Scholar 

  • Wang RK, Li LL, Cao ZH et al (2012) Molecular cloning and functional characterization of a novel apple MdCIPK6L gene reveals its involvement in multiple abiotic stress tolerance in transgenic plants. Plant Mol Biol 79(1–2):123–135

    Article  CAS  Google Scholar 

  • Zhang YM, Shao ZQ, Wang Q et al (2016) Uncovering the dynamic evolution of nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes in Brassicaceae. J Integr Plant Biol 58(2):165–177

    Article  CAS  Google Scholar 

  • Zhou T, Wang Y, Chen JQ et al (2004) Genome-wide identification of NBS genes in japonica rice reveals significant expansion of divergent non-TIR NBS-LRR genes. Mol Genet Genom 271(4):402–415

    Article  CAS  Google Scholar 

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Acknowledgements

The financial support received from the Indian Council of Agricultural Research, New Delhi is greatly acknowledged.

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Author notes

  1. Chelliah Anuradha and Arumugam Chandrasekar have contributed equally to this work.

Authors and Affiliations

  1. ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India

    Chelliah Anuradha, Arumugam Chandrasekar, Suthanthiram Backiyarani & Subbaraya Uma

Authors
  1. Chelliah Anuradha
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  2. Arumugam Chandrasekar
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  3. Suthanthiram Backiyarani
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  4. Subbaraya Uma
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Contributions

Project administration, conceptualization, work design, data curation, methodology, writing—original draft, review and editing, and formatting: CA; developed the web interface and implemented other modules in the database: AC; validation: SB; supervision and validation: SU.

Corresponding author

Correspondence to Chelliah Anuradha.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Anuradha, C., Chandrasekar, A., Backiyarani, S. et al. MusaRgeneDB: an online comprehensive database for disease resistance genes in Musa spp.. 3 Biotech 12, 222 (2022). https://doi.org/10.1007/s13205-022-03285-1

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