Transcriptome profile of pecan scab resistant and susceptible trees from a pecan provenance collection.
Carya
DEG
Fungal resistance
Pecan
Provenance
RNA-seq
Scab
Venturia
Journal
BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258
Informations de publication
Date de publication:
15 Feb 2024
15 Feb 2024
Historique:
received:
29
08
2023
accepted:
12
01
2024
medline:
15
2
2024
pubmed:
15
2
2024
entrez:
14
2
2024
Statut:
epublish
Résumé
Pecan scab is a devastating disease that causes damage to pecan (Carya illinoinensis (Wangenh.) K. Koch) fruit and leaves. The disease is caused by the fungus Venturia effusa (G. Winter) and the main management practice for controlling the disease is by application of fungicides at 2-to-3-week intervals throughout the growing season. Besides disease-related yield loss, application of fungicides can result in considerable cost and increases the likelihood of fungicide resistance developing in the pathogen. Resistant cultivars are available for pecan growers; although, in several cases resistance has been overcome as the pathogen adapts to infect resistant hosts. Despite the importance of host resistance in scab management, there is little information regarding the molecular basis of genetic resistance to pecan scab.The purpose of this study was to elucidate mechanisms of natural pecan scab resistance by analyzing transcripts that are differentially expressed in pecan leaf samples from scab resistant and susceptible trees. The leaf samples were collected from trees in a provenance collection orchard that represents the natural range of pecan in the US and Mexico. Trees in the orchard have been exposed to natural scab infections since planting in 1989, and scab ratings were collected over three seasons. Based on this data, ten susceptible trees and ten resistant trees were selected for analysis. RNA-seq data was collected and analyzed for diseased and non-diseased parts of susceptible trees as well as for resistant trees. A total of 313 genes were found to be differentially expressed when comparing resistant and susceptible trees without disease. For susceptible samples showing scab symptoms, 1,454 genes were identified as differentially expressed compared to non-diseased susceptible samples. Many genes involved in pathogen recognition, defense responses, and signal transduction were up-regulated in diseased samples of susceptible trees, whereas differentially expressed genes in pecan scab resistant samples were generally down-regulated compared to non-diseased susceptible samples.Our results provide the first account of candidate genes involved in resistance/susceptibility to pecan scab under natural conditions in a pecan orchard. This information can be used to aid pecan breeding programs and development of biotechnology-based approaches for generating pecan cultivars with more durable scab resistance.
Identifiants
pubmed: 38355402
doi: 10.1186/s12864-024-10010-0
pii: 10.1186/s12864-024-10010-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
180Subventions
Organisme : Agricultural Research Service
ID : 6042-21220-014-000-D
Organisme : Agricultural Research Service
ID : 6042-21220-014-000-D
Organisme : National Institute of Food and Agriculture
ID : 2016-51181-25408
Organisme : National Institute of Food and Agriculture
ID : 2016-51181-25408
Organisme : National Institute of Food and Agriculture
ID : 2016-51181-25408
Informations de copyright
© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
Références
USDA-NASS. Statistics by subject: Pecans, Utilized, In Shell - Production, Measured in $ [Available from: https://www.nass.usda.gov/Statistics_by_Subject/result.php?EB7A7D83-A799-32A3-836F-0C54A8513C38§or=CROPS&group=FRUIT%20%26%20TREE%20NUTS&comm=PECANS .
Grauke LJ, Payne JA, Wood BW. North American pecans: a provenance study. Ann Rep Northern Nut Growers Assoc. 1989;80:124–31.
Rüter B, Hamrick JL, Wood BW. Genetic diversity within provenance and cultivar germplasm collections versus natural populations of pecan (Carya illinoinensis). J Heredity. 1999;90(5):521–8.
Bock CH, Alarcon Y, Conner PJ, Young CA, Randall JJ, Pisani C, et al. Foliage and fruit susceptibility of a pecan provenance collection to scab, caused by Venturia effusa. CABI Agric Biosci. 2020;1(1):19.
Bock CH, Grauke LJ, Conner P, Burrell SL, Hotchkiss MW, Boykin D, et al. Scab susceptibility of a provenance collection of pecan in three different seasons in the Southeastern United States. Plant Dis. 2016;100(9):1937–45.
pubmed: 30682991
Adams JR, Bailey ME, Burkhead CE, Cook HT, Vermeer J, Wilson RC, et al. Losses in Agriculture. In: Agriculture USDo, editor. 1965.
Gottwald TR. Influence of temperature, leaf wetness period, leaf age, and spore concentration on infection of pecan leaves by conidia of Cladosporium caryigenum. Phytopathology. 1985;75(2):190–4.
Demaree JB. Pecan scab with special reference to sources of the early spring infections. 1924:p. 321-30. plates.-USDA.
Charlton ND, Yi M, Bock CH, Zhang M, Young CA. First description of the sexual stage of Venturia effusa, causal agent of pecan scab. Mycologia. 2020;112(4):711–21.
pubmed: 32469692
Bock CH, Hotchkiss MW, Young CA, Charlton ND, Chakradhar M, Stevenson KL, et al. Population genetic structure of Venturia effusa, cause of pecan scab, in the Southeastern United States. Phytopathology. 2017;107(5):607–19.
pubmed: 28414611
Young CA, Bock CH, Charlton ND, Mattupalli C, Krom N, Bowen JK, et al. Evidence for sexual reproduction: identification, frequency, and spatial distribution of Venturia effusa (pecan scab) mating type idiomorphs. Phytopathology. 2018;108(7):837–46.
pubmed: 29381450
Bock CH, Wells L, Hotchkiss MW. Effect of tractor speed and spray application volume on severity of scab and fruit weight at different heights in the canopy of tall pecan trees. Plant Dis. 2021;105(12):3909–24.
pubmed: 34129351
Standish JR, Brenneman TB, Bock CH, Stevenson KL. Fungicide resistance in Venturia effusa, cause of pecan scab: current status and practical implications. Phytopathology. 2020;111(2):244–52.
Andersen EJ, Ali S, Byamukama E, Yen Y, Nepal MP. Disease resistance mechanisms in plants. Genes (Basel). 2018;9(7).
Muthamilarasan M, Prasad M. Plant innate immunity: an updated insight into defense mechanism. J Biosci. 2013;38(2):433–49.
pubmed: 23660678
Jones JDG, Dangl JL. The plant immune system. Nature. 2006;444(7117):323–9.
pubmed: 17108957
Asai T, Tena G, Plotnikova J, Willmann MR, Chiu W-L, Gomez-Gomez L, et al. MAP kinase signalling cascade in Arabidopsis innate immunity. Nature. 2002;415(6875):977–83.
pubmed: 11875555
Selitrennikoff CP. Antifungal proteins. Appl Environ Microbiol. 2001;67(7):2883–94.
pubmed: 11425698
pmcid: 92957
Pradhan SK, Nayak DK, Mohanty S, Behera L, Barik SR, Pandit E, et al. Pyramiding of three bacterial blight resistance genes for broad-spectrum resistance in deepwater rice variety, Jalmagna. Rice (N Y). 2015;8(1):51.
pubmed: 26054243
Baumgartner IO, Patocchi A, Frey J, Peil A, Kellerhals M. Breeding elite lines of apple carrying pyramided homozygous resistance genes against apple scab and resistance against powdery mildew and fire blight. Plant Mol Biol Report. 2015;33:1573–83.
Qi L, Ma G. Marker-assisted gene pyramiding and the reliability of using SNP markers located in the recombination suppressed regions of sunflower (Helianthus annuus L.). Genes (Basel). 2019;11(1).
Jensen PJ, Rytter J, Detwiler EA, Travis JW, McNellis TW. Rootstock effects on gene expression patterns in apple tree scions. Plant Mol Biol. 2003;53(4):493–511.
pubmed: 15010615
Benjamin G, Tietel Z, Porat R. Effects of rootstock/scion combinations on the flavor of citrus fruit. J Agric Food Chem. 2013;61(47):11286–94.
pubmed: 24219601
Conner PJ. A detached leaf technique for studying race-specific resistance to Cladosporium caryigenum in pecan. J Am Soc Hortic Sci. 2002;127(5):781–5.
Martinelli F, Uratsu SL, Albrecht U, Reagan RL, Phu ML, Britton M, et al. Transcriptome profiling of citrus fruit response to Huanglongbing disease. PLOS One. 2012;7(5):e38039.
pubmed: 22675433
pmcid: 3364978
Chakraborty S, Britton M, Martínez-García PJ, Dandekar AM. Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues. AMB Express. 2016;6(1):12.
pubmed: 26883051
pmcid: 4755957
Acquadro A, Torello Marinoni D, Sartor C, Dini F, Macchio M, Botta R. Transcriptome characterization and expression profiling in chestnut cultivars resistant or susceptible to the gall wasp Dryocosmus kuriphilus. Mol Genet Genomics. 2020;295(1):107–20.
pubmed: 31506717
Thompson MY, Randall JJ, VanLeeuwen D, Heerema RJ. Differential expression of key floral initiation genes in response to plant growth regulator application and alternate bearing in pecan. J Am Soc Hortic Sci. 2021;146(3):206–14.
Xu Z, Ni J, Shah FA, Wang Q, Wang Z, Wu L, et al. Transcriptome analysis of pecan seeds at different developing stages and identification of key genes involved in lipid metabolism. PLoS One. 2018;13(4):e0195913.
pubmed: 29694395
pmcid: 5919011
Wang M, Xi D, Chen Y, Zhu C, Zhao Y, Geng G. Morphological characterization and transcriptome analysis of pistillate flowering in pecan (Carya illinoinensis). Scientia Horticulturae. 2019;257:108674.
Mattison CP, Rai R, Settlage RE, Hinchliffe DJ, Madison C, Bland JM, et al. RNA-Seq analysis of developing pecan (Carya illinoinensis) embryos reveals parallel expression patterns among allergen and lipid metabolism genes. J Agric Food Chem. 2017;65(7):1443–55.
pubmed: 28121438
Chen Y, Zhang S, Zhao Y, Mo Z, Wang W, Zhu C. Transcriptomic analysis to unravel potential pathways and genes involved in pecan (Carya illinoinensis) resistance to Pestalotiopsis microspora. Int J Mol Sci. 2022;23(19).
Lovell JT, Bentley NB, Bhattarai G, Jenkins JW, Sreedasyam A, Alarcon Y, et al. Four chromosome scale genomes and a pan-genome annotation to accelerate pecan tree breeding. Nat Commun. 2021;12(1):4125.
pubmed: 34226565
pmcid: 8257795
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.
pubmed: 24695404
pmcid: 4103590
Randall JJ, Schmutz J. Carya illinoinensis cv. 87MX3-2.11. Phytozome V13; 2021.
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9.
pubmed: 22388286
pmcid: 3322381
Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, et al. Twelve years of SAMtools and BCFtools. GigaScience. 2021;10(2):1–4.
Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14(4):417–9.
pubmed: 28263959
pmcid: 5600148
R Development Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing 2013.
Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res. 2015;4:1521.
pubmed: 26925227
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
pubmed: 25516281
pmcid: 4302049
Stephens M. False discovery rates: a new deal. Biostatistics. 2017;18(2):275–94.
pubmed: 27756721
Winter DJ, Charlton ND, Krom N, Shiller J, Bock CH, Cox MP, et al. Chromosome-level reference genome of Venturia effusa, causative agent of pecan scab. Mol Plant Microbe Interact. 2020;33(2):149–52.
pubmed: 31631770
Chen H, Boutros PC. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics. 2011;12(1):35.
pubmed: 21269502
pmcid: 3041657
Luo W, Pant G, Bhavnasi YK, Blanchard SG Jr, Brouwer C. Pathview Web: user friendly pathway visualization and data integration. Nucleic Acids Res. 2017;45(W1):W501–8.
pubmed: 28482075
pmcid: 5570256
Thimm O, Bläsing O, Gibon Y, Nagel A, Meyer S, Krüger P, et al. MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J. 2004;37:914–39.
Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics. 2009;10(1):48.
pubmed: 19192299
pmcid: 2644678
Kanehisa M, Furumichi M, Sato Y, Kawashima M, Ishiguro-Watanabe M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 2023;51(D1):D587-d92.
pubmed: 36300620
Osuna-Cruz CM, Paytuvi-Gallart A, Di Donato A, Sundesha V, Andolfo G, Aiese Cigliano R, et al. PRGdb 3.0: a comprehensive platform for prediction and analysis of plant disease resistance genes. Nucleic Acids Res. 2018;46(D1):D1197-d201.
pubmed: 29156057
Steuernagel B, Witek K, Krattinger SG, Ramirez-Gonzalez RH, Schoonbeek H-J, Yu G, et al. The NLR-Annotator tool enables annotation of the intracellular immune receptor Repertoire. Plant Physiol. 2020;183(2):468–82.
pubmed: 32184345
pmcid: 7271791
Kim GB, Gao Y, Palsson BO, Lee SY. DeepTFactor: A deep learning-based tool for the prediction of transcription factors. Proc Natl Acad Sci. 2021;118(2):e2021171118.
pubmed: 33372147
Jin J, Tian F, Yang D-C, Meng Y-Q, Kong L, Luo J, et al. PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Res. 2017;45(D1):D1040–5.
pubmed: 27924042
Meng X, Zhang S. MAPK cascades in plant disease resistance signaling. Annu Rev Phytopathol. 2013;51:245–66.
pubmed: 23663002
Zheng Z, Qamar SA, Chen Z, Mengiste T. Arabidopsis WRKY33 transcription factor is required for resistance to necrotrophic fungal pathogens. Plant J. 2006;48(4):592–605.
pubmed: 17059405
Kwon T, Young-Byung Y, Nam J. Overexpression of AtCAF1, CCR4-associated factor 1 homologue in Arabidopsis thaliana, negatively regulates wounding-mediated disease resistance. J Plant Biotechnol. 2011;38:278–84.
Mitsuhara I, Iwai T, Seo S, Yanagawa Y, Kawahigasi H, Hirose S, et al. Characteristic expression of twelve rice PR1 family genes in response to pathogen infection, wounding, and defense-related signal compounds (121/180). Mol Genet Genomics. 2008;279(4):415–27.
pubmed: 18247056
pmcid: 2270915
Samac DA, Hironaka CM, Yallaly PE, Shah DM. Isolation and characterization of the genes encoding basic and acidic chitinase in Arabidopsis thaliana. Plant Physiol. 1990;93(3):907–14.
pubmed: 16667600
pmcid: 1062608
Penninckx IAMA, Eggermont K, Terras FRG, Thomma BPHJ, De Samblanx GW, Buchala A, et al. Pathogen-induced systemic activation of a plant defensin gene in Arabidopsis follows a salicylic acid-independent pathway. Plant Cell. 1996;8:2309–23.
pubmed: 8989885
pmcid: 161354
Berrocal-Lobo M, Molina A. Ethylene response factor 1 mediates Arabidopsis resistance to the soilborne fungus Fusarium oxysporum. Mol Plant Microbe Interact. 2004;17(7):763–70.
pubmed: 15242170
El Oirdi M, Bouarab K. Plant signalling components EDS1 and SGT1 enhance disease caused by the necrotrophic pathogen Botrytis cinerea. N Phytologist. 2007;175(1):131–9.
Lorang J, Kidarsa T, Bradford CS, Gilbert B, Curtis M, Tzeng SC, et al. Tricking the guard: exploiting plant defense for disease susceptibility. Science. 2012;338(6107):659–62.
pubmed: 23087001
pmcid: 4125361
Chung LM, Ferguson JP, Zheng W, Qian F, Bruno V, Montgomery RR, et al. Differential expression analysis for paired RNA-seq data. BMC Bioinformatics. 2013;14(1):110.
pubmed: 23530607
pmcid: 3663822
He Q, McLellan H, Boevink PC, Birch PRJ. All roads lead to susceptibility: the many modes of action of fungal and oomycete intracellular effectors. Plant Commun. 2020;1(4):100050.
pubmed: 33367246
pmcid: 7748000
Niks RE, Marcel TC. Nonhost and basal resistance: how to explain specificity? New Phytologist. 2009;182(4):817–28.
pubmed: 19646067