Transcriptome divergence during leaf development in two contrasting switchgrass (Panicum virgatum L.) cultivars
Autoři:
Nathan A. Palmer aff001; R. V. Chowda-Reddy aff001; Anthony A. Muhle aff002; Satyanarayana Tatineni aff001; Gary Yuen aff002; Serge J. Edmé aff001; Robert B. Mitchell aff001; Gautam Sarath aff001
Působiště autorů:
Wheat, Sorghum, and Forage Research Unit, USDA-ARS, Lincoln, Nebraska, United states of America
aff001; Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, Nebraska, United states of America
aff002
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0222080
Souhrn
The genetics and responses to biotic stressors of tetraploid switchgrass (Panicum virgatum L.) lowland cultivar ‘Kanlow’ and upland cultivar Summer are distinct and can be exploited for trait improvement. In general, there is a paucity of data on the basal differences in transcription across tissue developmental times for switchgrass cultivars. Here, the changes in basal and temporal expression of genes related to leaf functions were evaluated for greenhouse grown ‘Kanlow’, and ‘Summer’ plants. Three biological replicates of the 4th leaf pooled from 15 plants per replicate were harvested at regular intervals beginning from leaf emergence through senescence. Increases and decreases in leaf chlorophyll and N content were similar for both cultivars. Likewise, multidimensional scaling (MDS) analysis indicated both cultivar-independent and cultivar-specific gene expression. Cultivar-independent genes and gene-networks included those associated with leaf function, such as growth/senescence, carbon/nitrogen assimilation, photosynthesis, chlorophyll biosynthesis, and chlorophyll degradation. However, many genes encoding nucleotide-binding leucine rich repeat (NB-LRRs) proteins and wall-bound kinases associated with detecting and responding to environmental signals were differentially expressed. Several of these belonged to unique cultivar-specific gene co-expression networks. Analysis of genomic resequencing data provided several examples of NB-LRRs genes that were not expressed and/or apparently absent in the genomes of Summer plants. It is plausible that cultivar (ecotype)-specific genes and gene-networks could be one of the drivers for the documented differences in responses to leaf-borne pathogens between these two cultivars. Incorporating broad resistance to plant pathogens in elite switchgrass germplasm could improve sustainability of biomass production under low-input conditions.
Klíčová slova:
Biology and life sciences – Cell biology – Genetics – Gene expression – Genomics – Genome analysis – Biochemistry – Plant science – Computational biology – Physical sciences – Proteins – DNA-binding proteins – Plant pathology – Plant pathogens – Gene regulation – Developmental biology – Cellular types – Cellular structures and organelles – Materials science – Materials – Transcription factors – Regulatory proteins – Biosynthesis – Plant anatomy – Leaves – Transcriptome analysis – Pigments – Organic pigments – Plant cell biology – Chloroplasts – Chlorophyll – Plant cells – Plant growth and development – Plant development – Leaf development
Zdroje
1. Vogel KP. Switchgrass. In: Moser LE, Sollenberger L, Burson B, editors. Warm-season (C4) grasses. ASA-CSSA-SSSA Monograph No. 45. Madison, WI: ASA-CSSA-SSSA; 2004. p. 561–88.
2. Young HA, Lanzatella CL, Sarath G, Tobias CM. Chloroplast genome variation in upland and lowland switchgrass. PLoS One. 2011;6(8):e23980. Epub 2011/09/03. doi: 10.1371/journal.pone.0023980 21887356
3. Okada M, Lanzatella C, Saha MC, Bouton J, Wu R, Tobias CM. Complete switchgrass genetic maps reveal subgenome collinearity, preferential pairing and multilocus interactions. Genetics. 2010;185(3):745–60. Epub 2010/04/22. doi: 10.1534/genetics.110.113910 20407132
4. Ersoz ES, Wright MH, Pangilinan JL, Sheehan MJ, Tobias C, Casler MD, et al. SNP discovery with EST and NextGen sequencing in switchgrass (Panicum virgatum L.). PLoS One. 2012;7(9):e44112. Epub 2012/10/11. doi: 10.1371/journal.pone.0044112 23049744
5. Evans J, Sanciangco MD, Lau KH, Crisovan E, Barry K, Daum C, et al. Extensive Genetic Diversity is Present within North American Switchgrass Germplasm. Plant Genome. 2018;11(1). doi: 10.3835/plantgenome2017.06.0055 29505643.
6. Bhandari HS, Saha MC, Mascia PN, Fasoula VA, Bouton JH. Variation among half-sib families and heritability for biomass yield and other traits in lowland switchgrass (Panicum virgatum L.). Crop Science. 2010;50(6):2355–63. doi: 10.2135/cropsci2010.02.0109
7. Milano ER, Lowry DB, Juenger TE. The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum). G3 (Bethesda). 2016. doi: 10.1534/g3.116.032763 27613751
8. Casler MD, Sosa S, Hoffman L, Mayton H, Ernst C, Adler PR, et al. Biomass yield of switchgrass cultivars under high- versus low-input conditions. Crop Sci. 2017;57(2):821–32. doi: 10.2135/cropsci2016.08.0698
9. Casler MD. Heterosis and Reciprocal-cross Effects in Tetraploid Switchgrass. Crop Science. 2014;54(5):2063–9. doi: 10.2135/cropsci2013.12.0821
10. Vogel KP, Mitchell KB. Heterosis in Switchgrass: Biomass Yield in Swards. Crop Science. 2008;48(6):2159–64. doi: 10.2135/cropsci2008.02.0117
11. Martinez-Reyna JM, Vogel KP. Heterosis in switchgrass: Spaced plants. Crop Science. 2008;48(4):1312–20. doi: 10.2135/cropsci2007.12.0695
12. Serba DD, Sykes RW, Gjersing EL, Decker SR, Daverdin G, Devos KM, et al. Cell Wall Composition and Underlying QTL in an F-1 Pseudo-Testcross Population of Switchgrass. Bioenerg Res. 2016;9(3):836–50. doi: 10.1007/s12155-016-9733-3
13. Serba D, Wu LM, Daverdin G, Bahri BA, Wang XW, Kilian A, et al. Linkage Maps of Lowland and Upland Tetraploid Switchgrass Ecotypes. Bioenergy Research. 2013;6(3):953–65. doi: 10.1007/s12155-013-9315-6
14. Bartley L, Wu Y, Saathoff A, Sarath G. Switchgrass Genetics and Breeding Challenges. John Wiley and Sons; 2013. p. 7–31.
15. Palmer NA, Saathoff AJ, Tobias CM, Twigg P, Xia Y, Vogel KP, et al. Contrasting metabolism in perenniating structures of upland and lowland switchgrass plants late in the growing season. PLoS One. 2014;9(8):e105138. Epub 2014/08/19. doi: 10.1371/journal.pone.0105138 25133804.
16. Sarath G, Baird LM, Mitchell RB. Senescence, dormancy and tillering in perennial C4 grasses. Plant Science. 2014;217–218(0):140–51. doi: 10.1016/j.plantsci.2013.12.012 24467906
17. Serba DD, Uppalapati SR, Mukherjee S, Krom N, Tang YH, Mysore KS, et al. Transcriptome Profiling of Rust Resistance in Switchgrass Using RNA-Seq Analysis. Plant Genome. 2015;8(2). doi: 10.3835/plantgenome2014.10.0075
18. Uppalapati SR, Serba DD, Ishiga Y, Szabo LJ, Mittal S, Bhandari HS, et al. Characterization of the Rust Fungus, Puccinia emaculata, and Evaluation of Genetic Variability for Rust Resistance in Switchgrass Populations. Bioenergy Research. 2013;6(2):458–68. doi: 10.1007/s12155-012-9263-6
19. Stewart CL, Pyle JD, Jochum CC, Vogel KP, Yuen GY, Scholthof KBG. Multi-Year Pathogen Survey of Biofuel Switchgrass Breeding Plots Reveals High Prevalence of Infections by Panicum mosaic virus and Its Satellite Virus. Phytopathology. 2015;105(8):1146–54. doi: 10.1094/PHYTO-03-15-0062-R 25894317
20. Fike JH, Pease JW, Owens VN, Farris RL, Hansen JL, Heaton EA, et al. Switchgrass nitrogen response and estimated production costs on diverse sites. Gcb Bioenergy. 2017;9(10):1526–42. doi: 10.1111/gcbb.12444
21. Mitchell R, Schmer M. Switchgrass harvest and management. In: Monti A., editor. Switchgrass. London, U.K.: Springer-Verlag; 2012. p. 113–27.
22. Sykes VR, Allen FL, Mielenz JR, Stewart CN Jr., Windham MT, Hamilton CY, et al. Reduction of Ethanol Yield from Switchgrass Infected with Rust Caused by Puccinia emaculata. Bioenergy Research. 2015. doi: 10.1007/s12155-015-9680-4
23. Tsuda K, Katagiri F. Comparing signaling mechanisms engaged in pattern-triggered and effector-triggered immunity. Curr Opin Plant Biol. 2010;13(4):459–65. Epub 2010/05/18. doi: 10.1016/j.pbi.2010.04.006 20471306.
24. Zhu QH, Bennetzen JL, Smith SM. Isolation and Diversity Analysis of Resistance Gene Homologues from Switchgrass. G3-Genes Genom Genet. 2013;3(6):1031–42. doi: 10.1534/g3.112.005447 23589518
25. Keith R, Mitchell-Olds T. Genetic variation for resistance to herbivores and plant pathogens: hypotheses, mechanisms and evolutionary implications. Plant Pathology. 2013;62:122–32. doi: 10.1111/Ppa.12134
26. Kim J, Lim CJ, Lee BW, Choi JP, Oh SK, Ahmad R, et al. A genome-wide comparison of NB-LRR type of resistance gene analogs (RGA) in the plant kingdom. Molecules and Cells. 2012;33(4):385–92. doi: 10.1007/s10059-012-0003-8 22453776
27. Takken FL, Goverse A. How to build a pathogen detector: structural basis of NB-LRR function. Curr Opin Plant Biol. 2012;15(4):375–84. Epub 2012/06/05. doi: 10.1016/j.pbi.2012.05.001 22658703.
28. McHale L, Tan X, Koehl P, Michelmore RW. Plant NBS-LRR proteins: adaptable guards. Genome Biol. 2006;7(4):212. Epub 2006/05/09. doi: 10.1186/gb-2006-7-4-212 16677430
29. Maekawa T, Kufer TA, Schulze-Lefert P. NLR functions in plant and animal immune systems: so far and yet so close. Nature Immunology. 2011;12(9):818–26. doi: 10.1038/Ni.2083 21852785
30. Collier SM, Hamel LP, Moffett P. Cell Death Mediated by the N-Terminal Domains of a Unique and Highly Conserved Class of NB-LRR Protein. Molecular Plant-Microbe Interactions. 2011;24(8):918–31. doi: 10.1094/MPMI-03-11-0050 21501087
31. Maag D, Erb M, Kollner TG, Gershenzon J. Defensive weapons and defense signals in plants: some metabolites serve both roles. Bioessays. 2015;37(2):167–74. Epub 2014/11/13. doi: 10.1002/bies.201400124 25389065.
32. Frazier TP, Palmer NA, Xie F, Tobias CM, Donze-Reiner TJ, Bombarely A, et al. Identification, characterization, and gene expression analysis of nucleotide binding site (NB)-type resistance gene homologues in switchgrass. BMC Genomics. 2016;17(1):892. doi: 10.1186/s12864-016-3201-5 27821048
33. Rasool B, McGowan J, Pastok D, Marcus SE, Morris JA, Verrall SR, et al. Redox Control of Aphid Resistance through Altered Cell Wall Composition and Nutritional Quality. Plant Physiology. 2017;175(1):259–71. doi: 10.1104/pp.17.00625 28743764
34. Nissen KS, Willats WGT, Malinovsky FG. Understanding CrRLK1L Function: Cell Walls and Growth Control. Trends Plant Sci. 2016;21(6):516–27. doi: 10.1016/j.tplants.2015.12.004 26778775.
35. Demidchik V. Mechanisms of oxidative stress in plants: From classical chemistry to cell biology. Environmental and Experimental Botany. 2015;109:212–28. doi: 10.1016/j.envexpbot.2014.06.021
36. Rushton PJ, Somssich IE, Ringler P, Shen QJ. WRKY transcription factors. Trends Plant Sci. 2010;15(5):247–58. Epub 2010/03/23. doi: 10.1016/j.tplants.2010.02.006 20304701.
37. Rinerson CI, Scully ED, Palmer NA, Donze-Reiner T, Rabara RC, Tripathi P, et al. The WRKY transcription factor family and senescence in switchgrass. Bmc Genomics. 2015;16. doi: 10.1186/S12864-015-2057-4 26552372
38. Palmer NA, Donze-Reiner T, Horvath D, Heng-Moss T, Waters B, Tobias C, et al. Switchgrass (Panicum virgatum L) flag leaf transcriptomes reveal molecular signatures of leaf development, senescence, and mineral dynamics. Functional & Integrative Genomics. 2015;15(1):1–16. doi: 10.1007/s10142-014-0393-0 25173486
39. Yang J, Worley E, Ma Q, Li J, Torres-Jerez I, Li G, et al. Nitrogen remobilization and conservation, and underlying senescence-associated gene expression in the perennial switchgrass Panicum virgatum. New Phytol. 2016. Epub 2016/03/05. doi: 10.1111/nph.13898 26935010.
40. Yang JD, Worley E, Torres-Jerez I, Miller R, Wang MY, Fu CX, et al. PvNAC1 and PvNAC2 Are Associated with Leaf Senescence and Nitrogen Use Efficiency in Switchgrass. Bioenergy Research. 2015;8(2):868–80. doi: 10.1007/s12155-014-9566-x
41. Serba DD, Uppalapati SR, Krom N, Mukherjee S, Tang YH, Mysore KS, et al. Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency. Bmc Genomics. 2016;17. doi: 10.1186/s12864-016-3377-8 27986076
42. Vogel K, Mitchell R, Sarath G, Casler MD. Registration of ‘Liberty’ switchgrass. Journal of Plant Registrations. 2014.
43. Palmer NA, Saathoff AJ, Scully ED, Tobias CM, Twigg P, Madhavan S, et al. Seasonal below-ground metabolism in switchgrass. Plant J. 2017;92(6):1059–75. doi: 10.1111/tpj.13742 29030891.
44. Alderson J, Sharp WC. Grass Varieties in the United States. 1995.
45. Sindelar AJ, Schmer MR, Jin VL, Wienhold BJ, Varvel GE. Crop Rotation Affects Corn, Grain Sorghum, and Soybean Yields and Nitrogen Recovery. Agron J. 2016;108(4):1592–602. doi: 10.2134/agronj2016.01.0005
46. Kellenberger RT, Byers K, De Brito Francisco RM, Staedler YM, LaFountain AM, Schonenberger J, et al. Emergence of a floral colour polymorphism by pollinator-mediated overdominance. Nat Commun. 2019;10(1):63. doi: 10.1038/s41467-018-07936-x 30622247
47. Ilias IA, Negishi K, Yasue K, Jomura N, Morohashi K, Baharum SN, et al. Transcriptome-wide effects of expansin gene manipulation in etiolated Arabidopsis seedling. J Plant Res. 2019;132(2):159–72. doi: 10.1007/s10265-018-1067-0 30341720.
48. Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12(4):357–60. doi: 10.1038/nmeth.3317 25751142
49. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. doi: 10.1093/bioinformatics/btp352 19505943
50. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30(7):923–30. Epub 2013/11/15. doi: 10.1093/bioinformatics/btt656 24227677.
51. Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens M, Oksanen M, et al. The vegan package. Community Ecology Package. R package version 2.5–2. 2018.
52. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing,. Vienna, Austria: R Foundation for Statistical Computing; 2018.
53. 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. Epub 2014/12/18. doi: 10.1186/s13059-014-0550-8 25516281
54. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. Bmc Bioinformatics. 2008;9:559. Epub 2008/12/31. doi: 10.1186/1471-2105-9-559 19114008
55. Shen L, Sinai M. GeneOverlap: Test and visualize gene overlaps. R package version 1.16.0. 2013.
56. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. Epub 2012/03/06. doi: 10.1038/nmeth.1923 22388286
57. Thorvaldsdottir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform. 2013;14(2):178–92. doi: 10.1093/bib/bbs017 22517427
58. Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6. doi: 10.1038/nbt.1754 21221095
59. Lehti-Shiu MD, Shiu SH. Diversity, classification and function of the plant protein kinase superfamily. Philos Trans R Soc Lond B Biol Sci. 2012;367(1602):2619–39. doi: 10.1098/rstb.2012.0003 22889912
60. Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 2014;42(1):D199–205. Epub 2013/11/12. doi: 10.1093/nar/gkt1076 24214961.
61. Vogel KP, Sarath G, Saathoff AJ, Mitchell RB. Switchgrass. Energy Crops. 2011;3:341–80. doi: 10.1039/9781849732048-00341
62. Thomas H. Senescence, ageing and death of the whole plant. New Phytologist. 2013;197(3):696–711. doi: 10.1111/nph.12047 23176101
63. Hortensteiner S, Krautler B. Chlorophyll breakdown in higher plants. Biochim Biophys Acta. 2011;1807(8):977–88. Epub 2010/12/21. doi: 10.1016/j.bbabio.2010.12.007 21167811.
64. Troncoso-Ponce MA, Cao X, Yang Z, Ohlrogge JB. Lipid turnover during senescence. Plant Sci. 2013;205–206:13–9. Epub 2013/03/19. doi: 10.1016/j.plantsci.2013.01.004 23498858.
65. Waters BM, Uauy C, Dubcovsky J, Grusak MA. Wheat (Triticum aestivum) NAM proteins regulate the translocation of iron, zinc, and nitrogen compounds from vegetative tissues to grain. J Exp Bot. 2009;60(15):4263–74. Epub 2009/10/28. doi: 10.1093/jxb/erp257 19858116.
66. Yang J, Worley E, Wang M, Lahner B, Salt D, Saha M, et al. Natural Variation for Nutrient Use and Remobilization Efficiencies in Switchgrass. Bioenergy Research. 2009;2(4):257–66. doi: 10.1007/s12155-009-9055-9
67. El-Nashaar HM, Banowetz GM, Griffith SM, Casler MD, Vogel KP. Genotypic variability in mineral composition of switchgrass. Bioresour Technol. 2009;100(5):1809–14. doi: 10.1016/j.biortech.2008.09.058 19019672
68. Smykowski A, Zimmermann P, Zentgraf U. G-Box binding factor1 reduces CATALASE2 expression and regulates the onset of leaf senescence in Arabidopsis. Plant Physiol. 2010;153(3):1321–31. Epub 2010/05/21. doi: 10.1104/pp.110.157180 20484024
69. Xiao S, Dai L, Liu F, Wang Z, Peng W, Xie D. COS1: an Arabidopsis coronatine insensitive1 suppressor essential for regulation of jasmonate-mediated plant defense and senescence. Plant Cell. 2004;16(5):1132–42. doi: 10.1105/tpc.020370 15075400
70. Zhang Y, Liu Z, Wang X, Wang J, Fan K, Li Z, et al. DELLA proteins negatively regulate dark-induced senescence and chlorophyll degradation in Arabidopsis through interaction with the transcription factor WRKY6. Plant Cell Rep. 2018;37(7):981–92. doi: 10.1007/s00299-018-2282-9 29574486.
71. Huang Y, Feng CZ, Ye Q, Wu WH, Chen YF. Arabidopsis WRKY6 Transcription Factor Acts as a Positive Regulator of Abscisic Acid Signaling during Seed Germination and Early Seedling Development. PLoS Genet. 2016;12(2):e1005833. doi: 10.1371/journal.pgen.1005833 26829043
72. Anderson NA, Bonawitz ND, Nyffeler K, Chapple C. Loss of FERULATE 5-HYDROXYLASE Leads to Mediator-Dependent Inhibition of Soluble Phenylpropanoid Biosynthesis in Arabidopsis. Plant Physiol. 2015;169(3):1557–67. doi: 10.1104/pp.15.00294 26048881
73. Tallis MJ, Lin Y, Rogers A, Zhang J, Street NR, Miglietta F, et al. The transcriptome of Populus in elevated CO reveals increased anthocyanin biosynthesis during delayed autumnal senescence. New Phytol. 2010;186(2):415–28. doi: 10.1111/j.1469-8137.2010.03184.x 20202130.
74. Zalapa JE, Price DL, Kaeppler SM, Tobias CM, Okada M, Casler MD. Hierarchical classification of switchgrass genotypes using SSR and chloroplast sequences: ecotypes, ploidies, gene pools, and cultivars. Theor Appl Genet. 2011;122(4):805–17. Epub 2010/11/26. doi: 10.1007/s00122-010-1488-1 21104398.
75. Morris GP, Grabowski PP, Borevitz JO. Genomic diversity in switchgrass (Panicum virgatum): from the continental scale to a dune landscape. Mol Ecol. 2011;20(23):4938–52. doi: 10.1111/j.1365-294X.2011.05335.x 22060816
76. Zhang YW, Zalapa JE, Jakubowski AR, Price DL, Acharya A, Wei YL, et al. Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences. Genetica. 2011;139(7):933–48. doi: 10.1007/s10709-011-9597-6 21786028
77. Milano ER, Lowry DB, Juenger TE. The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass (Panicum virgatum). G3 (Bethesda). 2016;6(11):3561–70. doi: 10.1534/g3.116.032763 27613751
78. Vogel KP, Mitchell RB, Casler MD, Sarath G. Registration of ‘Liberty’ Switchgrass. Journal of Plant Registrations. 2014;8(3):242–7. doi: 10.3198/jpr2013.12.0076crc
Článok vyšiel v časopise
PLOS One
2019 Číslo 9
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania