Abstract
Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host–pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.
This is a preview of subscription content, access via your institution.
Buying options



References
Abad A, Victoria Fernández-Molina J, Bikandi J et al (2010) What makes Aspergillus fumigatus a successful pathogen? Genes and molecules involved in invasive aspergillosis. Rev Iberoam Micol 27:155–182. https://doi.org/10.1016/j.riam.2010.10.003
Adams MD, Kelley JM, Gocayne JD et al (1991) Complementary DNA sequencing: expressed sequence tags and human genome project. Science 252:1651–1656. https://doi.org/10.1126/science.2047873
Alwine JC, Kemp DJ, Stark GR (1977) Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes. Proc Natl Acad Sci 74:5350–5354. https://doi.org/10.1073/pnas.74.12.5350
Amorim-vaz S, Tran VDT, Pradervand S et al (2015) RNA enrichment method for quantitative transcriptional analysis of pathogens in vivo applied to the fungus Candida albicans. MBio 6:1–16. https://doi.org/10.1128/mBio.00942-15.Editor
Anders S, Pyl PT, Huber W (2015) HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics 31:166–169. https://doi.org/10.1093/bioinformatics/btu638
Andes D, Lepak A, Pitula A et al (2005) A simple approach for estimating gene expression in Candida albicans directly from a systemic infection site. J Infect Dis 192:893–900. https://doi.org/10.1086/432104
Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc
Aprianto R, Slager J, Holsappel S, Veening JW (2016) Time-resolved dual RNA-seq reveals extensive rewiring of lung epithelial and pneumococcal transcriptomes during early infection. Genome Biol 17. https://doi.org/10.1186/s13059-016-1054-5
Au KF, Sebastiano V, Afshar PT et al (2013) Characterization of the human ESC transcriptome by hybrid sequencing. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.1320101110
Avital G, Avraham R, Fan A et al (2017) scDual-Seq: Mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing. Genome Biol. https://doi.org/10.1186/s13059-017-1340-x
Avraham R, Haseley N, Brown D et al (2015) Pathogen Cell-to-Cell Variability Drives Heterogeneity in Host Immune Responses. Cell. https://doi.org/10.1016/j.cell.2015.08.027
Bainbridge MN, Warren RL, Hirst M et al (2006) Analysis of the prostate cancer cell line LNCaP transcriptome using a sequencing-by-synthesis approach. BMC Genomics 7. https://doi.org/10.1186/1471-2164-7-246
Baruzzo G, Hayer KE, Kim EJ et al (2017) Simulation-based comprehensive benchmarking of RNA-seq aligners. Nat Methods 14:135–139. https://doi.org/10.1038/nmeth.4106
Berenguer J, Buck M, Witebsky F et al (1993) Lysis-centrifugation blood cultures in the detection of tissue-proven invasive candidiasis disseminated versus single-organ infection. Diagn Microbiol Infect Dis 17:103–109. https://doi.org/10.1016/0732-8893(93)90020-8
Binkley J, Arnaud MB, Inglis DO et al (2014) The Candida Genome Database: the new homology information page highlights protein similarity and phylogeny. Nucleic Acids Res 42:D711–D716. https://doi.org/10.1093/nar/gkt1046
Bitar D, Lortholary O, Le Strat Y et al (2014) Population-based analysis of invasive fungal infections, France, 2001–2010. Emerg Infect Dis 20:1149–1155. https://doi.org/10.3201/eid2007.140087
Black MB, Parks BB, Pluta L et al (2014) Comparison of microarrays and RNA-Seq for gene expression analyses of dose-response experiments. Toxicol Sci 137:385–403. https://doi.org/10.1093/toxsci/kft249
Blackwell M (2011) The fungi: 1, 2, 3 … 5.1 million species? Am J Bot 98:426–438. https://doi.org/10.3732/ajb.1000298
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. https://doi.org/10.1093/bioinformatics/btu170
Borodina T, Adjaye J, Sultan M (2011) A Strand-Specific Library Preparation Protocol for RNA Sequencing. In: Methods in enzymology. pp 79–98
Brandão F, Esher SK, Ost KS et al (2018) HDAC genes play distinct and redundant roles in Cryptococcus neoformans virulence. Sci Rep. https://doi.org/10.1038/s41598-018-21965-y
Brandt ME, Lockhart SR (2012) Recent taxonomic developments with candida and other opportunistic yeasts. Curr Fungal Infect Rep 6:170–177. https://doi.org/10.1007/s12281-012-0094-x
Bray NL, Pimentel H, Melsted P, Pachter L (2016) Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34:525–527. https://doi.org/10.1038/nbt.3519
Brown GD, Denning DW, Gow NAR et al (2012) Hidden killers: human fungal infections. Sci. Transl, Med, p 4
Brown NA, Ries LNA, Reis TF et al (2016) RNAseq reveals hydrophobins that are involved in the adaptation of Aspergillus nidulans to lignocellulose. Biotechnol Biofuels 9. https://doi.org/10.1186/s13068-016-0558-2
Bruno VM, Shetty AC, Yano J et al (2015) Transcriptomic Analysis of Vulvovaginal Candidiasis Identifies a Role for the NLRP3 Inflammasome. MBio 6:1–15. https://doi.org/10.1128/mBio.00182-15
Bullard JH, Purdom E, Hansen KD, Dudoit S (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics 11:94. https://doi.org/10.1186/1471-2105-11-94
Byrne A, Beaudin AE, Olsen HE et al (2017) Nanopore long-read RNAseq reveals widespread transcriptional variation among the surface receptors of individual B cells. Nat Commun. https://doi.org/10.1038/ncomms16027
Campbell JD, Liu G, Luo L et al (2015) Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data. RNA. https://doi.org/10.1261/rna.046060.114
Castel SE, Levy-Moonshine A, Mohammadi P et al (2015) Tools and best practices for data processing in allelic expression analysis. Genome Biol 16:195. https://doi.org/10.1186/s13059-015-0762-6
Cerqueira GC, Arnaud MB, Inglis DO et al (2014) The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations. Nucleic Acids Res 42:D705–D710. https://doi.org/10.1093/nar/gkt1029
Chalupová J, Raus M, Sedlářová M, Šebela M (2014) Identification of fungal microorganisms by MALDI-TOF mass spectrometry. Biotechnol Adv 32:230–241
Chapman B, Slavin M, Marriott D et al (2017) Changing epidemiology of candidaemia in Australia. J Antimicrob Chemother 72:1103–1108. https://doi.org/10.1093/jac/dkw422
Chen SY, Deng F, Jia X et al (2017) A transcriptome atlas of rabbit revealed by PacBio single-molecule long-read sequencing. Sci Rep. https://doi.org/10.1038/s41598-017-08138-z
Chen JJ, Hsueh HM, Delongchamp RR et al (2007) Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data. BMC Bioinformatics 8. https://doi.org/10.1186/1471-2105-8-412
Chen L, Kostadima M, Martens JHA et al (2014a) Transcriptional diversity during lineage commitment of human blood progenitors. Science. https://doi.org/10.1126/science.1251033
Chen Y, Toffaletti DL, Tenor JL et al (2014b) The Cryptococcus neoformans transcriptome at the site of human meningitis. MBio 5. https://doi.org/10.1128/mbio.01087-13
Chen F, Zhang C, Jia X et al (2015) Transcriptome profiles of human lung epithelial cells A549 interacting with Aspergillus fumigatus by RNA-Seq. PLoS One 10. https://doi.org/10.1371/journal.pone.0135720
Cheon SA, Thak EJ, Bahn YS, Kang HA (2017) A novel bZIP protein, Gsb1, is required for oxidative stress response, mating, and virulence in the human pathogen Cryptococcus neoformans. Sci Rep 7. https://doi.org/10.1038/s41598-017-04290-8
Chhangawala S, Rudy G, Mason CE, Rosenfeld JA (2015) The impact of read length on quantification of differentially expressed genes and splice junction detection. Genome Biol 16:131. https://doi.org/10.1186/s13059-015-0697-y
Chowdhary A, Sharma C, Meis JF (2017) Candida auris: A rapidly emerging cause of hospital-acquired multidrug-resistant fungal infections globally. PLoS Pathog. 13
Cock PJA, Fields CJ, Goto N et al (2009) The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 38:1767–1771. https://doi.org/10.1093/nar/gkp1137
Conesa A, Madrigal P, Tarazona S et al (2016) A survey of best practices for RNA-seq data analysis. Genome Biol 17:13. https://doi.org/10.1186/s13059-016-0881-8
Cottier F, Tan ASM, Chen J et al (2015) The transcriptional stress response of Candida albicans to weak organic acids. G3 (Bethesda) 5:497–505. https://doi.org/10.1534/g3.114.015941
D’Souza CA, Kronstad JW, Taylor G et al (2011) Genome variation in Cryptococcus gattii, an emerging pathogen of immunocompetent hosts. MBio 2. https://doi.org/10.1128/mbio.00342-10
Dagenais TRT, Keller NP (2009) Pathogenesis of Aspergillus fumigatus in invasive aspergillosis. Clin Microbiol Rev 22:447–465
Dijksterhuis J, Houbraken J, Samson RA (2013) Fungal spoilage of crops and food. In: Agricultural Applications, 2nd Edition. pp 35–56
Dinel S, Bolduc C, Belleau P et al (2005) Reproducibility, bioinformatic analysis and power of the SAGE method to evaluate changes in transcriptome. Nucleic Acids Res 33:1–8. https://doi.org/10.1093/nar/gni025
Dobin A, Davis CA, Schlesinger F et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21. https://doi.org/10.1093/bioinformatics/bts635
Dobin A, Gingeras TR (2013) Comment on “TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions” by Kim et al. bioRxiv 000851. https://doi.org/10.1101/000851
Dutton LC, Paszkiewicz KH, Silverman RJ et al (2016) Transcriptional landscape of trans-kingdom communication between Candida albicans and Streptococcus gordonii. Mol Oral Microbiol 31:136–161. https://doi.org/10.1111/omi.12111
Emmert-Streib F, Glazko GV (2011) Pathway analysis of expression data: deciphering functional building blocks of complex diseases. PLoS Comput Biol. https://doi.org/10.1371/journal.pcbi.1002053
Fan HC, Fu GK, Fodor SPA, Önnerfjord P (2015) Expression profiling. Combinatorial labeling of single cells for gene expression cytometry. Science. https://doi.org/10.1126/science.1258367
Ferrareze PAG, Streit RSA, dos Santos PR et al (2017) Transcriptional Analysis Allows Genome Reannotation and Reveals that Cryptococcus gattii VGII Undergoes Nutrient Restriction during Infection. Microorganisms 5:49. https://doi.org/10.3390/microorganisms5030049
Flevari A, Theodorakopoulou M, Velegraki A et al (2013) Treatment of invasive candidiasis in the elderly: a review. Clin Interv Aging 8:1199–1208
Francis WR, Christianson LM, Kiko R et al (2013) A comparison across non-model animals suggests an optimal sequencing depth for de novo transcriptome assembly. BMC Genom 14:1–12. https://doi.org/10.1186/1471-2164-14-167
Fuller KK, Cramer RA, Zegans ME et al (2016) Aspergillus fumigatus photobiology illuminates the marked heterogeneity between isolates. MBio 7. https://doi.org/10.1128/mbio.01517-16
Gabaldón T, Carreté L (2016) The birth of a deadly yeast: tracing the evolutionary emergence of virulence traits in Candida glabrata. FEMS Yeast Res. 16
Gabaldón T, Naranjo-Ortíz MA, Marcet-Houben M (2016) Evolutionary genomics of yeast pathogens in the Saccharomycotina. FEMS Yeast Res. 16
Garalde DR, Snell EA, Jachimowicz D et al (2018) Highly parallel direct RN A sequencing on an array of nanopores. Nat Methods. https://doi.org/10.1038/nmeth.4577
Geiss GK, Bumgarner RE, Birditt B et al (2008) Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol 26:317–325. https://doi.org/10.1038/nbt1385
Gibbons JG, Beauvais A, Beau R et al (2012) Global transcriptome changes underlying colony growth in the opportunistic human pathogen Aspergillus fumigatus. Eukaryot Cell 11:68–78. https://doi.org/10.1128/EC.05102-11
Gonzalez-Hilarion S, Paulet D, Lee KT et al (2016) Intron retention-dependent gene regulation in Cryptococcus neoformans. Sci Rep. https://doi.org/10.1038/srep32252
Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17:333–351. https://doi.org/10.1038/nrg.2016.49
Griffin AT, Hanson KE (2014) Update on fungal diagnostics. Curr Infect Dis Rep 16. https://doi.org/10.1007/s11908-014-0415-z
Guinea J (2014) Global trends in the distribution of Candida species causing candidemia. Clin Microbiol Infect 20:5–10
Guo Y, Zhao S, Li C-I et al (2014) RNAseqPS: A Web Tool for Estimating Sample Size and Power for RNAseq Experiment. Cancer Inform 13:1–5. https://doi.org/10.4137/CIN.S17688
Haas BJ, Papanicolaou A, Yassour M et al (2013) De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 8:1494–1512. https://doi.org/10.1038/nprot.2013.084
Hart SN, Therneau TM, Zhang Y et al (2013) Calculating Sample Size Estimates for RNA Sequencing Data. J Comput Biol 20:970–978. https://doi.org/10.1089/cmb.2012.0283
Havlickova B, Czaika VA, Friedrich M (2008) Epidemiological trends in skin mycoses worldwide. Mycoses 51:2–15
Hawksworth DL, Lücking R (2017) Fungal Diversity Revisited: 2.2 to 3.8 Million Species. Microbiol Spectr 5. https://doi.org/10.1128/microbiolspec.funk-0052-2016
Heward JA, Lindsay MA (2014) Long non-coding RNAs in the regulation of the immune response. Trends Immunol
Hu G, Chen SH, Qiu J et al (2014) Microevolution during serial mouse passage demonstrates FRE3 as a virulence adaptation gene in Cryptococcus neoformans. MBio. https://doi.org/10.1128/mBio.00941-14
Hu B, Xie G, Lo C-C et al (2011) Pathogen comparative genomics in the next-generation sequencing era: genome alignments, pangenomics and metagenomics. Brief Funct Genomics 10:322–333. https://doi.org/10.1093/bfgp/elr042
Idnurm A, Walton FJ, Floyd A et al (2009) Identification of ENA1 as a virulence gene of the human pathogenic fungus Cryptococcus neoformans through signature-tagged insertional mutagenesis. Eukaryot Cell. https://doi.org/10.1128/EC.00375-08
Irmer H, Tarazona S, Sasse C et al (2015) RNAseq analysis of Aspergillus fumigatus in blood reveals a just wait and see resting stage behavior. BMC Genom 16:640. https://doi.org/10.1186/s12864-015-1853-1
Jain M, Koren S, Miga KH et al (2018) Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat Biotechnol. https://doi.org/10.1038/nbt.4060
Jamuar SS Tan EC (2015) Clinical application of next-generation sequencing for Mendelian diseases. Hum. Genomics
Janbon G, Ormerod KL, Paulet D et al (2014) Analysis of the Genome and Transcriptome of Cryptococcus neoformans var. grubii Reveals Complex RNA Expression and Microevolution Leading to Virulence Attenuation. PLoS Genet 10. https://doi.org/10.1371/journal.pgen.1004261
Jia X, Chen F, Pan W et al (2014) Gliotoxin promotes Aspergillus fumigatus internalization into type II human pneumocyte A549 cells by inducing host phospholipase D activation. Microbes Infect 16:491–501. https://doi.org/10.1016/j.micinf.2014.03.001
Jiang H, Lei R, Ding S-W, Zhu S (2014) Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads. BMC Bioinformatics 15:182. https://doi.org/10.1186/1471-2105-15-182
Jiang C, Li Z, Zhang L et al (2016) Significance of hyphae formation in virulence of Candida tropicalis and transcriptomic analysis of hyphal cells. Microbiol Res 192:65–72. https://doi.org/10.1016/j.micres.2016.06.003
Jiang M, Zhang S, Yang Z et al (2018) Self-Recognition of an Inducible Host lncRNA by RIG-I Feedback Restricts Innate Immune Response. Cell. https://doi.org/10.1016/j.cell.2018.03.064
Jung WH, Hu G, Kuo W, Kronstad JW (2009) Role of ferroxidases in iron uptake and virulence of Cryptococcus neoformans. Eukaryot Cell. https://doi.org/10.1128/EC.00166-09
Kale SD, Ayubi T, Chung D et al (2017) Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis. Sci Rep 7. https://doi.org/10.1038/s41598-017-17000-1
Kathiravan, MK, Salake AB, Chothe AS, Dudhe PB, Watode RP, Mukta MS, Gadhwe S (2012). The biology and chemistry of antifungal agents: A review. Bioorganic Med Chem 20(19):5678–5698. https://doi.org/10.1016/j.bmc.2012.04.045
Khot PD, Fredricks DN (2009) PCR-based diagnosis of human fungal infections. Expert Rev Anti Infect Ther 7:1201–1221. https://doi.org/10.1586/eri.09.104
Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12:357–360. https://doi.org/10.1038/nmeth.3317
Kim D, Pertea G, Trapnell C et al (2013) TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14:R36. https://doi.org/10.1186/gb-2013-14-4-r36
Kim J, Sudbery P (2011) Candida albicans, a major human fungal pathogen. J Microbiol 49:171–177. https://doi.org/10.1007/s12275-011-1064-7
Klingspor L, Tortorano AM, Peman J et al (2015) Invasive Candida infections in surgical patients in intensive care units: a prospective, multicentre survey initiated by the European Confederation of Medical Mycology (ECMM) (2006-2008). Clin Microbiol Infect 21:87.e1-87.e10. https://doi.org/10.1016/j.cmi.2014.08.011
Kolisko M, Boscaro V, Burki F et al (2014) Single-cell transcriptomics for microbial eukaryotes. Curr, Biol
Kolodziejczyk AA, Kim JK, Svensson V et al (2015) The Technology and Biology of Single-Cell RNA Sequencing. Mol. Cell
Kowalski CH, Beattie SR, Fuller KK et al (2016) Heterogeneity among isolates reveals that fitness in low oxygen correlates with Aspergillus fumigatus virulence. MBio 7. https://doi.org/10.1128/mbio.01515-16
Kozel TR, Wickes B (2014) Fungal diagnostics. Cold Spring Harb Perspect Med 4. https://doi.org/10.1101/cshperspect.a019299
Kwon-Chung KJ, Boekhout T, Wickes BL, Fell JW (2011). Systematics of the genus Cryptococcus and its type species C. neoformans. In Cryptococcus: 3–15. American Society of Microbiology
Kwon-Chung KJ, Fraser JA, Doering TÁL et al (2015) Cryptococcus neoformans and Cryptococcus gattii, the etiologic agents of cryptococcosis. Cold Spring Harb Perspect Med. https://doi.org/10.1101/cshperspect.a019760
Kwon-Chung KJ, Sugui JA (2013) Aspergillus fumigatus-What Makes the Species a Ubiquitous Human Fungal Pathogen? PLoS Pathog 9:1–4. https://doi.org/10.1371/journal.ppat.1003743
Latgé JP (1999) Aspergillus fumigatus and Aspergillosis. Clin Microbiol Rev 12:310–350
Levin JZ, Yassour M, Adiconis X et al (2010) Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat Methods 7:709–715. https://doi.org/10.1038/nmeth.1491
Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930. https://doi.org/10.1093/bioinformatics/btt656
Lin JQ, Zhao XX, Zhi QQ et al (2013) Transcriptomic profiling of Aspergillus flavus in response to 5-azacytidine. Fungal Genet Biol 56:78–86. https://doi.org/10.1016/j.fgb.2013.04.007
Lister R, O’Malley RC, Tonti-Filippini J et al (2008) Highly Integrated Single-Base Resolution Maps of the Epigenome in Arabidopsis. Cell 133:523–536. https://doi.org/10.1016/j.cell.2008.03.029
Liu Y, Ferguson JF, Xue C et al (2013) Evaluating the Impact of Sequencing Depth on Transcriptome Profiling in Human Adipose. PLoS One 8. https://doi.org/10.1371/journal.pone.0066883
Liu Y, Filler SG (2011) Candida albicans Als3, a multifunctional adhesin and invasin. Eukaryot Cell 10:168–173
Liu Y, Shetty AC, Schwartz JA et al (2015) New signaling pathways govern the host response to C. albicans infection in various niches. Genome Res 125:679–689. https://doi.org/10.1101/gr.187427.114
Liu TB, Subbian S, Pan W et al (2014a) Cryptococcus inositol utilization modulates the host protective immune response during brain infection. Cell Commun Signal 12:1–17. https://doi.org/10.1186/s12964-014-0051-0
Liu Y, Zhou J, White KP (2014b) RNA-seq differential expression studies: more sequence or more replication? Bioinformatics 30:301–304. https://doi.org/10.1093/bioinformatics/btt688
Lockhart DJ, Dong H, Byrne MC et al (1996) Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol 14:1675–1680. https://doi.org/10.1038/nbt1296-1675
Losada L, Barker BM, Pakala S et al (2014) Large-Scale Transcriptional Response to Hypoxia in Aspergillus fumigatus Observed Using RNAseq Identifies a Novel Hypoxia Regulated ncRNA. Mycopathologia 178:331–339. https://doi.org/10.1007/s11046-014-9779-8
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550. https://doi.org/10.1186/s13059-014-0550-8
Lowe R, Shirley N, Bleackley M et al (2017) Transcriptomics technologies. PLOS Comput Biol 13:e1005457. https://doi.org/10.1371/journal.pcbi.1005457
Lu H, Giordano F, Ning Z (2016) Oxford Nanopore MinION Sequencing and Genome Assembly. Genomics, Proteomics Bioinforma
Luthra R, Chen H, Roy-Chowdhuri S, Singh RR (2015) Next-generation sequencing in clinical molecular diagnostics of cancer: advantages and challenges. Cancers (Basel)
Marioni JC, Mason CE, Mane SM et al (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18:1509–1517. https://doi.org/10.1101/gr.079558.108
Martin R, Albrecht-Eckardt D, Brunke S et al (2013) A Core Filamentation Response Network in Candida albicans Is Restricted to Eight Genes. PLoS One 8. https://doi.org/10.1371/journal.pone.0058613
May RC, Stone NRH, Wiesner DL et al (2016) Cryptococcus: from environmental saprophyte to global pathogen. Nat Rev Microbiol 14:106–117
McCoy RC, Taylor RW, Blauwkamp TA et al (2014) Illumina TruSeq synthetic long-reads empower de novo assembly and resolve complex, highly-repetitive transposable elements. PLoS ONE. https://doi.org/10.1371/journal.pone.0106689
Metpally RPR, Nasser S, Courtright A et al (2013) Comparison of analysis tools for miRNA high throughput sequencing using nerve crush as a model. Front Genet. https://doi.org/10.3389/fgene.2013.00020
Mitrovich QM, Tuch BB, Guthrie C, Johnson AD (2007) Computational and experimental approaches double the number of known introns in the pathogenic yeast Candida albicans. Genome Res 17:492–502. https://doi.org/10.1101/gr.6111907
Mitsuhashi S, Kryukov K, Nakagawa S et al (2017) A portable system for metagenomic analyses using nanopore-based sequencer and laptop computers can realize rapid on-site determination of bacterial compositions. bioRxiv. https://doi.org/10.1038/s41598-017-05772-5
Mixão V, Gabaldón T (2017) Hybridization and emergence of virulence in opportunistic human yeast pathogens. Yeast. https://doi.org/10.1002/yea.3242
Morrissy AS, Morin RD, Delaney A et al (2009) Next-generation tag sequencing for cancer gene expression profiling. Genome Res 19:1825–1835. https://doi.org/10.1101/gr.094482.109
Moyes DL, Richardson JP, Naglik JR (2014). From: Human Pathogenic Fungi: Molecular Biology and Pathogenic Mechanisms. In: Sullivan DJ, Moran GP (eds). Caister Academic Press, U.K
Moyes DL, Wilson D, Richardson JP et al (2016) Candidalysin is a fungal peptide toxin critical for mucosal infection. Nature 532:64–68. https://doi.org/10.1038/nature17625
Naglik JR, Challacombe SJ, Hube B (2003) Candida albicans Secreted Aspartyl Proteinases in Virulence and Pathogenesis. Microbiol Mol Biol Rev 67:400–428. https://doi.org/10.1128/MMBR.67.3.400-428.2003
Nature Microbiology Editorial (2017) Stop neglecting fungi. Nat. Microbiol. 2:17120. https://doi.org/10.1038/nmicrobiol.2017.123
Niemiec MJ, Grumaz C, Ermert D et al (2017) Dual transcriptome of the immediate neutrophil and Candida albicans interplay. BMC Genom 18:696. https://doi.org/10.1186/s12864-017-4097-4
Ning G, Cheng X, Luo P et al (2017) Hybrid sequencing and map finding (HySeMaFi): optional strategies for extensively deciphering gene splicing and expression in organisms without reference genome. Sci Rep. https://doi.org/10.1038/srep43793
Nobile CJ, Nett JE, Andes DR, Mitchell AP (2006) Function of Candida albicans adhesin hwp1 in biofilm formation. Eukaryot Cell 5:1604–1610. https://doi.org/10.1128/EC.00194-06
Nuss AM, Beckstette M, Pimenova M et al (2017) Tissue dual RNA-seq allows fast discovery of infection-specific functions and riboregulators shaping host–pathogen transcriptomes. Proc Natl Acad Sci 114:E791–E800. https://doi.org/10.1073/pnas.1613405114
O’Brien HE, Parrent JL, Jackson JA et al (2005) Fungal Community Analysis by Large-Scale Sequencing of Environmental Samples. Appl Environ Microbiol 71:5544–5550. https://doi.org/10.1128/AEM.71.9.5544
O’Keeffe G, Hammel S, Owens RA et al (2014) RNA-seq reveals the pan-transcriptomic impact of attenuating the gliotoxin self-protection mechanism in Aspergillus fumigatus. BMC Genomics 15. https://doi.org/10.1186/1471-2164-15-894
O’Meara TR, Holmer SM, Selvig K et al (2013) Cryptococcus neoformans Rim101 is associated with cell wall remodeling and evasion of the host immune responses. MBio. https://doi.org/10.1128/mBio.00522-12
O’Meara TR, Norton D, Price MS et al (2010) Interaction of Cryptococcus neoformans Rim101 and protein kinase a regulates capsule. PLoS Pathog. https://doi.org/10.1371/journal.ppat.1000776
O’Neil D, Glowatz H, Schlumpberger M (2013) Ribosomal RNA Depletion for Efficient Use of RNA-Seq Capacity. In: Current Protocols in Molecular Biology. Wiley, Hoboken, NJ, USA, p Unit 4.19
Oren I, Paul M (2014) Up to date epidemiology, diagnosis and management of invasive fungal infections. Clin Microbiol Infect 20:1–4
Otto C, Stadler PF, Hoffmann S (2014) Lacking alignments? The next-generation sequencing mapper segemehl revisited. Bioinformatics 30:1837–1843. https://doi.org/10.1093/bioinformatics/btu146
Ouyang J, Hu J, Chen JL (2016) lncRNAs regulate the innate immune response to viral infection. Wiley Interdiscip Rev RNA 7:129–143. https://doi.org/10.1002/wrna.1321
Papon N, Courdavault V, Clastre M, Bennett RJ (2013) Emerging and Emerged Pathogenic Candida Species: Beyond the Candida albicans Paradigm. PLoS Pathog 9. https://doi.org/10.1371/journal.ppat.1003550
Park BJ, Wannemuehler KA, Marston BJ et al (2009) Estimation of the current global burden of cryptococcal meningitis among persons living with HIV/AIDS. AIDS. https://doi.org/10.1097/QAD.0b013e328322ffac
Parkhomchuk D, Borodina T, Amstislavskiy V et al (2009) Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Res 37:e123–e123. https://doi.org/10.1093/nar/gkp596
Patel RK, Jain M (2012) NGS QC toolkit: a toolkit for quality control of next generation sequencing data. PLoS ONE 7:e30619. https://doi.org/10.1371/journal.pone.0030619
Paterson RRM, Lima N (2017) Filamentous Fungal Human Pathogens from Food Emphasising Aspergillus. Fusarium Mucor Microorganisms 5:44. https://doi.org/10.3390/microorganisms5030044
Patro R, Duggal G, Love MI et al (2017) Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14:417–419. https://doi.org/10.1038/nmeth.4197
Pel HJ, De Winde JH, Archer DB et al (2007) Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol 25:221–231. https://doi.org/10.1038/nbt1282
Perfect JR, Cox GM, Lee JY et al (2001) The impact of culture isolation of Aspergillus species: a hospital-based survey of aspergillosis. Clin Infect Dis 33:1824–1833. https://doi.org/10.1086/323900
Pfaller MA, Diekema DJ (2007) Epidemiology of invasive candidiasis: a persistent public health problem. Clin Microbiol Rev 20:133–163
Pfaller MA, Diekema DJ (2010) Epidemiology of Invasive Mycoses in North America. Crit Rev Microbiol 36:1–53. https://doi.org/10.3109/10408410903241444
Pfaller MA, Messer SA, Hollis RJ et al (2009) Variation in susceptibility of bloodstream isolates of Candida glabrata to fluconazole according to patient age and geographic location in the United States in 2001 to 2007. J Clin Microbiol 47:3185–3190. https://doi.org/10.1128/JCM.00946-09
Pruitt KD, Tatusova T, Maglott DR (2007) NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 35:D61–D65. https://doi.org/10.1093/nar/gkl842
Pryszcz LP, Németh T, Gácser A, Gabaldón T (2014) Genome comparison of candida orthopsilosis clinical strains reveals the existence of hybrids between two distinct subspecies. Genome Biol Evol 6:1069–1078. https://doi.org/10.1093/gbe/evu082
Pryszcz LP, Németh T, Saus E et al (2015) The Genomic Aftermath of Hybridization in the Opportunistic Pathogen Candida metapsilosis. PLoS Genet 11. https://doi.org/10.1371/journal.pgen.1005626
Quick J, Ashton P, Calus S et al (2015) Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella. Genome Biol. https://doi.org/10.1186/s13059-015-0677-2
Rapaport F, Khanin R, Liang Y et al (2013) Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol 14:R95. https://doi.org/10.1186/gb-2013-14-9-r95
Rappolee D A, Mark D, Banda MJ, Werb Z (1988) Wound macrophages express TGF-alpha and other growth factors in vivo: analysis by mRNA phenotyping. Science (80-) 241:708–12. https://doi.org/10.1126/science.3041594
Rasheed M, Battu A, Kaur R (2018) Aspartyl proteases in Candida glabrata are required for suppression of the host innate immune response. J Biol Chem jbc.M117.813741. https://doi.org/10.1074/jbc.m117.813741
Reuter S, Ellington MJ, Cartwright EJP et al (2013) Rapid bacterial whole-genome sequencing to enhance diagnostic and public health microbiology. JAMA Intern Med. https://doi.org/10.1001/jamainternmed.2013.7734
Rhoads A, Au KF (2015) PacBio Sequencing and Its Applications. Genomics, Proteomics Bioinforma
Rhodes J, Desjardins CA, Sykes SM et al (2017) Tracing genetic exchange and biogeography of cryptococcus neoformans var. Grubii at the global population level. Genetics 207:327–346. https://doi.org/10.1534/genetics.117.203836
Ritchie ME, Phipson B, Wu D et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47–e47. https://doi.org/10.1093/nar/gkv007
Rizzetto L, Giovannini G, Bromley M et al (2013) Strain Dependent Variation of Immune Responses to A. fumigatus: Definition of Pathogenic Species. PLoS One 8. https://doi.org/10.1371/journal.pone.0056651
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140. https://doi.org/10.1093/bioinformatics/btp616
Rosenbach A, Dignard D, Pierce JV et al (2010) Adaptations of Candida albicans for growth in the mammalian intestinal tract. Eukaryot Cell 9:1075–1086. https://doi.org/10.1128/EC.00034-10
Rosenberg AB, Roco CM, Muscat RA et al (2018) Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science (80-). https://doi.org/10.1126/science.aam8999
Rosenthal K, Oehling V, Dusny C, Schmid A (2017) Beyond the bulk: Disclosing the life of single microbial cells. FEMS Microbiol, Rev
Saliba AE, Li L, Westermann AJ et al (2016) Single-cell RNA-seq ties macrophage polarization to growth rate of intracellular Salmonella. Nat Microbiol. https://doi.org/10.1038/nmicrobiol.2016.206
Samson RA, Visagie CM, Houbraken J, Hong S-B, Hubka V, Klaassen CHW, Perrones G, Seifert KA, Susca A, Tanney JB, Varga J, Kocsube S, Szigeti G, Yaguchi T, Frisvad JC (2014) Phylogeny, identification and nomenclature of the genus Aspergillus. Stud Mycol 78:343–371. https://doi.org/10.1016/j.simyco.2014.09.001
Sanger F, Nicklen S, Coulson AR (1977) DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A 74:5463–5467
Sanglard D (2016) Emerging Threats in Antifungal-Resistant Fungal Pathogens. Front Med 3. https://doi.org/10.3389/fmed.2016.00011
Sarma S, Upadhyay S (2017) Current perspective on emergence, diagnosis and drug resistance in Candida auris. Infect Drug Resist 10:155–165
Satoh K, Makimura K, Hasumi Y et al (2009) Candida auris sp. nov., a novel ascomycetous yeast isolated from the external ear canal of an inpatient in a Japanese hospital. Microbiol Immunol 53:41–44. https://doi.org/10.1111/j.1348-0421.2008.00083.x
Saus E, Willis JR, Pryszcz LP et al (2018) nextPARS: parallel probing of RNA structures in Illumina. RNA 24:609–619. https://doi.org/10.1261/rna.063073.117
Schena M, Shalon D, Davis RW, Brown PO (1995) Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray. Science (80-) 270:467–470. https://doi.org/10.1126/science.270.5235.467
Schmidt K, Mwaigwisya S, Crossman LC et al (2017) Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. J Antimicrob Chemother. https://doi.org/10.1093/jac/dkw397
Schröder MS, Martinez de San Vicente K, Prandini THR et al (2016) Multiple Origins of the Pathogenic Yeast Candida orthopsilosis by Separate Hybridizations between Two Parental Species. PLoS Genet 12. https://doi.org/10.1371/journal.pgen.1006404
Schulze S, Henkel SG, Driesch D et al (2015) Computational prediction of molecular pathogen-host interactions based on dual transcriptome data. Front Microbiol. https://doi.org/10.3389/fmicb.2015.00065
Schulze S, Schleicher J, Guthke R, Linde J (2016) How to predict molecular interactions between species?. Front, Microbiol
Schurch NJ, Schofield P, Gierliński M et al (2016) How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? RNA 22:839–851. https://doi.org/10.1261/rna.053959.115
Seqc/Maqc-Iii Consortium (2014) A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. Nat Biotechnol 32:903–914. https://doi.org/10.1038/nbt.2957
Seyednasrollah F, Laiho A, Elo LL (2015) Comparison of software packages for detecting differential expression in RNA-seq studies. Brief Bioinform 16:59–70. https://doi.org/10.1093/bib/bbt086
Shankar J, Cerqueira GC, Wortman JR et al (2018) RNA-Seq Profile Reveals Th-1 and Th-17-Type of Immune Responses in Mice Infected Systemically with Aspergillus fumigatus. Mycopathologia. https://doi.org/10.1007/s11046-018-0254-9
Sharon D, Tilgner H, Grubert F, Snyder M (2013) A single-molecule long-read survey of the human transcriptome. Nat Biotechnol. https://doi.org/10.1038/nbt.2705
Shaw WH, Lin Q, Muhammad ZZBR et al (2016) Identification of HIV mutation as diagnostic biomarker through next generation sequencing. J Clin Diagnostic Res. https://doi.org/10.7860/JCDR/2016/19760.8140
Sherry NL, Porter JL, Seemann T et al (2013) Outbreak investigation using high-throughput genome sequencing within a diagnostic microbiology laboratory. J Clin Microbiol. https://doi.org/10.1128/JCM.03332-12
Short DP, O’Donnell K, Geiser DM (2014) Clonality, recombination, and hybridization in the plumbing-inhabiting human pathogen Fusarium keratoplasticum inferred from multilocus sequence typing. BMC Evol Biol 14:91. https://doi.org/10.1186/1471-2148-14-91
Smeekens SP, van de Veerdonk FL, Netea MG (2016) An Omics Perspective on Candida Infections: toward Next-Generation Diagnosis and Therapy. Front Microbiol 7:154. https://doi.org/10.3389/fmicb.2016.00154
Soneson C (2013) Delorenzi M (2013) A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinforma 141(14):91. https://doi.org/10.1186/1471-2105-14-91
Soneson C, Love MI, Robinson MD (2015) Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research 4:1521. https://doi.org/10.12688/f1000research.7563.2
Stajich JE, Harris T, Brunk BP et al (2012) FungiDB: an integrated functional genomics database for fungi. Nucleic Acids Res 40:D675–D681. https://doi.org/10.1093/nar/gkr918
Stegle O, Teichmann SA, Marioni JC (2015) Computational and analytical challenges in single-cell transcriptomics. Nat. Rev, Genet
Stoesser N, Batty EM, Eyre DW et al (2013) Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data. J Antimicrob Chemother. https://doi.org/10.1093/jac/dkt180
Subramanian A, Tamayo P, Mootha VK et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.0506580102
Sudbery P, Gow N, Berman J (2004) The distinct morphogenic states of Candida albicans. Trends Microbiol 12:317–324
Sutcliffe JG, Milner RJ, Bloom FE, Lerner RA (1982) Common 82-nucleotide sequence unique to brain RNA. Proc Natl Acad Sci U S A 79:4942–4946. https://doi.org/10.1073/pnas.79.16.4942
Tarazona S, García-Alcalde F, Dopazo J et al (2011) Differential expression in RNA-seq: a matter of depth. Genome Res 21:2213–2223. https://doi.org/10.1101/gr.124321.111
Thänert R, Goldmann O, Beineke A, Medina E (2017) Host-inherent variability influences the transcriptional response of Staphylococcus aureus during in vivo infection. Nat Commun 8. https://doi.org/10.1038/ncomms14268
The Gene Ontology Consortium (2017) Expansion of the Gene Ontology knowledgebase and resources. Nucleic Acids Res. https://doi.org/10.1093/nar/gkw1108
Thewes S, Kretschmar M, Park H et al (2007) In vivo and ex vivo comparative transcriptional profiling of invasive and non-invasive Candida albicans isolates identifies genes associated with tissue invasion. Mol Microbiol 63:1606–1628. https://doi.org/10.1111/j.1365-2958.2007.05614.x
Tierney L, Linde J, Müller S et al (2012) An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells. Front Microbiol 3:85. https://doi.org/10.3389/fmicb.2012.00085
Tóth R, Cabral V, Thuer E et al (2018) Investigation of Candida parapsilosis virulence regulatory factors during host-pathogen interaction. Sci Rep 8:1–14. https://doi.org/10.1038/s41598-018-19453-4
Turabelidze G, Lawrence SJ, Gao H et al (2013) Precise dissection of an escherichia coli o157:H7 outbreak by single nucleotide polymorphism analysis. J Clin Microbiol. https://doi.org/10.1128/JCM.01930-13
Turner SA, Butler G (2014) The Candida pathogenic species complex. Cold Spring Harb Perspect Med 4. https://doi.org/10.1101/cshperspect.a019778
Velculescu VE, Zhang L, Vogelstein B, Kinzler KW (1995) Serial Analysis of Gene Expression. Science (80-) 270:484–487. https://doi.org/10.1126/science.270.5235.484
Wain J, Mavrogiorgou E (2013) Next-generation sequencing in clinical microbiology. Expert Rev. Mol, Diagn
Wan Y, Qu K, Ouyang Z, Chang HY (2013) Genome-wide mapping of RNA structure using nuclease digestion and high-throughput sequencing. Nat Protoc 8:849–869. https://doi.org/10.1038/nprot.2013.045
Wang J, Chen L, Chen Z, Zhang W (2015a) RNA-seq based transcriptomic analysis of single bacterial cells. Integr Biol (United Kingdom). https://doi.org/10.1039/c5ib00191a
Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63
Wang B, Regulski M, Tseng E et al (2018) A comparative transcriptional landscape of maize and sorghum obtained by single-molecule sequencing. Genome Res. https://doi.org/10.1101/gr.227462.117
Wang K, Zhang Z, Chen X et al (2015b) Transcription factor ADS-4 regulates adaptive responses and resistance to antifungal azole stress. Antimicrob Agents Chemother 59:5396–5404. https://doi.org/10.1128/AAC.00542-15
Warner JR (1999) The economics of ribosome biosynthesis in yeast. Trends Biochem Sci 24:437–440
Watkins TN, Liu H, Chung M et al (2018) Comparative transcriptomics of Aspergillus fumigatus strains upon exposure to human airway epithelial cells. Microb Genomics 1–9. https://doi.org/10.1099/mgen.0.000154
Weinreb C, Wolock S, Tusi BK et al (2018) Fundamental limits on dynamic inference from single-cell snapshots. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.1714723115
Westermann AJ, Barquist L, Vogel J (2017) Resolving host–pathogen interactions by dual RNA-seq. PLoS Pathog 13:e1006033. https://doi.org/10.1371/JOURNAL.PPAT.1006033
Westermann AJ, Gorski SA, Vogel J (2012) Dual RNA-seq of pathogen and host. Nat Rev Microbiol 10:618–630. https://doi.org/10.1038/nrmicro2852
Whaley SG, Caudle KE, Simonicova L et al (2018) Jjj1 Is a Negative Regulator of Pdr1-Mediated Fluconazole Resistance in Candida glabrata. mSphere 3:1–11. https://doi.org/10.1128/msphere.00466-17
Williams CR, Baccarella A, Parrish JZ, Kim CC (2016) Trimming of sequence reads alters RNA-Seq gene expression estimates. BMC Bioinformatics 17:103. https://doi.org/10.1186/s12859-016-0956-2
Wilson D, Hube B (2014). From: Human Pathogenic Fungi: Molecular Biology and Pathogenic Mechanisms. Sullivan DJ, Moran GP (eds). Caister Academic Press, U.K
Wolf T, Kämmer P, Brunke S, Linde J (2018) Two’s company: studying interspecies relationships with dual RNA-seq. Curr Opin Microbiol 42:7–12. https://doi.org/10.1016/j.mib.2017.09.001
Wu Y, Li Y, Yu S et al (2016) A Genome-Wide Transcriptional Analysis of Yeast-Hyphal Transition in Candida tropicalis by RNA-Seq. PLoS ONE 11:e0166645. https://doi.org/10.1371/journal.pone.0166645
Wu G, Zhao H, Li C et al (2015) Genus-Wide Comparative Genomics of Malassezia Delineates Its Phylogeny, Physiology, and Niche Adaptation on Human Skin. PLoS Genet 11. https://doi.org/10.1371/journal.pgen.1005614
Xie Y, Wu G, Tang J et al (2014) SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads. Bioinformatics 30:1660–1666. https://doi.org/10.1093/bioinformatics/btu077
Yang Q, Gao L, Tao M et al (2016) Transcriptomics Analysis of Candida albicans Treated with Huanglian Jiedu Decoction Using RNA-seq. Evidence-based Complement Altern Med 2016. https://doi.org/10.1155/2016/3198249
Yang X, Liu D, Liu F et al (2013) HTQC: a fast quality control toolkit for Illumina sequencing data. BMC Bioinformatics 14:33. https://doi.org/10.1186/1471-2105-14-33
Yu L, Fernandez S, Brock G (2017) Power analysis for RNA-Seq differential expression studies. BMC Bioinformatics 18:234. https://doi.org/10.1186/s12859-017-1648-2
Zhang N, Park YD, Williamson PR (2014) New technology and resources for cryptococcal research. Fungal Genet Biol. https://doi.org/10.1016/j.fgb.2014.11.001
Zhao W, He X, Hoadley KA et al (2014) Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling. BMC Genom 15:419. https://doi.org/10.1186/1471-2164-15-419
Zhao S, Zhang Y, Gordon W et al (2015) Comparison of stranded and non-stranded RNA-seq transcriptome profiling and investigation of gene overlap. BMC Genom 16:675. https://doi.org/10.1186/s12864-015-1876-7
Zheng GXY, Terry JM, Belgrader P et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun. https://doi.org/10.1038/ncomms14049
Zhu YY, Machleder EM, Chenchik A et al (2001) Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. Biotechniques 30:892–897
Zoll J, Snelders E, Verweij PE, Melchers WJG (2016) Next-Generation Sequencing in the Mycology Lab. Curr Fungal Infect Rep 10:37–42. https://doi.org/10.1007/s12281-016-0253-6
Acknowledgements
TG group acknowledges support from the Spanish Ministry of Economy, Industry, and Competitiveness (MEIC) for the EMBL partnership and grants “Centro de Excelencia Severo Ochoa 2013–2017” SEV-2012-0208, and BFU2015-67107 cofounded by European Regional Development Fund (ERDF), from the CERCA Programme/Generalitat de Catalunya, from the Catalan Research Agency (AGAUR) SGR857, and grant from the European Union’s Horizon 2020 research and innovation programme under the grant agreement ERC-2016-724173 the Marie Sklodowska-Curie grant agreement No. H2020-MSCA-ITN-2014-642095.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Hovhannisyan, H., Gabaldón, T. (2018). Transcriptome Sequencing Approaches to Elucidate Host–Microbe Interactions in Opportunistic Human Fungal Pathogens. In: Rodrigues, M. (eds) Fungal Physiology and Immunopathogenesis . Current Topics in Microbiology and Immunology, vol 422. Springer, Cham. https://doi.org/10.1007/82_2018_122
Download citation
DOI: https://doi.org/10.1007/82_2018_122
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30236-8
Online ISBN: 978-3-030-30237-5
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)