RNA Dizileme (Transkriptom)
Özet
Transkriptom, hücre içinde RNA üretimini ve düzenlenmesini inceleyen bir bilim dalıdır. RNA dizileme ve RNA-seq teknolojileri, transkriptom çalışmalarının yapılmasında kullanılan başlıca yöntemlerdir. RNA dizileme, hücre içinde meydana gelen RNA moleküllerinin dizilerini elde etmek için kullanılırken RNA-seq ise, aynı zamanda hangi genlerin aktif olduğunu ve hangi genlerin hangi durumlarda ifade edildiğini belirlemek için kullanılmaktadır. RNA dizi verilerinin analizi, hangi genlerin aktifleştiğini ve ne gibi durumlarda ifade edildiğini ortaya çıkarmak için biyoinformatiğin kullanıldığı alandır. Bu analizler, hücre içinde meydana gelen biyolojik olayları anlamak, hastalıkların patogenezini ve tedavisini araştırmak, bitkilerde ürün kalitesini arttırmak, gen terapisi gibi birçok amaç için kullanılabilir. Özellikle RNA-seq teknolojisi, gen ekspresyon düzeylerini belirlemek ve bunların zaman içinde nasıl değiştiğini takip etmek için oldukça önemli bir araçtır. Bu bölümde transkriptom konusuna ve transkriptomun kullanım alanlarına değinilmiştir.
Referanslar
Crick F. Central dogma of Molecular Biology. Nature. 1970; 227: 561-563.
Crick FH. On protein synthesis. Symposia of the Society for Experimental Biology. 1958; 12: 138-163.
Mattick JS, Makunin IV. Non-coding RNA. Human Molecular Genetics. 2006; 15 (1): R17–R29. doi: 10.1093/hmg/ddl046
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Guttman M, Amit I, Garber M, et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature. 2009; 458: 223-227.
Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: Insights into functions. Nature Reviews Genetics. 2009; 10: 155-159.
Wilusz JE, Sunwoo H, Spector DL. Long noncoding RNAs: Functional surprises from the RNA world. Genes & Development. 2009; 23: 1494-1504.
Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 1995; 270: 467-470.
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Referanslar
Crick F. Central dogma of Molecular Biology. Nature. 1970; 227: 561-563.
Crick FH. On protein synthesis. Symposia of the Society for Experimental Biology. 1958; 12: 138-163.
Mattick JS, Makunin IV. Non-coding RNA. Human Molecular Genetics. 2006; 15 (1): R17–R29. doi: 10.1093/hmg/ddl046
Stefani G, Slack FJ. Small non-coding RNAs in animal development. Nature Reviews Molecular Cell Biology. 2008; 9: 219-230.
Okazaki Y, Furuno M, Kasukawa T, et al. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature. 2002; 420: 563-573.
Guttman M, Amit I, Garber M, et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature. 2009; 458: 223-227.
Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: Insights into functions. Nature Reviews Genetics. 2009; 10: 155-159.
Wilusz JE, Sunwoo H, Spector DL. Long noncoding RNAs: Functional surprises from the RNA world. Genes & Development. 2009; 23: 1494-1504.
Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 1995; 270: 467-470.
Casneuf T, Van de Peer Y, Huber W. In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation. BMC Bioinformatics. 2007; 8: 461.
Shendure J. The beginning of the end for microarrays? Nature Methods. 2008; 5: 585-587. doi: 10.1038/nmeth0708-585
Kukurba KR, Montgomery SB. RNA sequencing and analysis. Cold Spring Harbor Protocols. 2015; 2015(11): 951-969. doi: 10.1101/pdb.top084970
Shiraki T, Kondo S, Katayama S, et al. Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage. Proceedings of the National Academy of Sciences. 2003; 100: 15776-15781.
Wang Z, Gerstein M, Snyder M. RNA-Seq: A revolutionary tool for transcriptomics. Nature Reviews Genetics. 2009; 10: 57-63.
Emrich SJ, Barbazuk WB, Li L, et al. Gene discovery and annotation using LCM-454 transcriptome sequencing. Genome Research. 2007; 17: 69-73.
Lister R, O'Malley RC, Tonti-Filippini J, et al. Highly integrated single- base resolution maps of the epigenome in Arabidopsis. Cell. 2008; 133: 523-536.
Stark R, Grzelak M, Hadfield J. RNA sequencing: the teenage years. Nature Reviews Genetics. 2019; 20(11): 631-656.
Illumina. NGS Library Preparation- 3 Key Technologies. (23.12.2022 tarihinde https://www.illumina.com/techniques/sequencing/ngs-library-prep.html adresinden ulaşılmıştır).
Garalde DR, Snell, EA, Jachimowicz D, et al. Highly parallel direct RNA sequencing on an array of nanopores. Nature Methods. 2018; 15: 201-206.
Smith AM, Jain M, Mulroney L, et al. Reading canonical and modified nucleotides in 16S ribosomal RNA using nanopore direct RNA sequencing. bioRxiv. 2017; 132274. doi: 10.1101/132274
Byrne A, Beaudin AE, Olsen HE, et al. Nanopore long- read RNAseq reveals widespread transcriptional variation among the surface receptors of individual B cells. Nature Communications. 2017; 8: 16027.
Leinonen R, Sugawara H, Shumway M, et al. The sequence read archive. Nucleic Acids Research. 2011; 39: D19–D21.
Kono N, Arakawa K. Nanopore sequencing: Review of potential applications in functional genomics. Development, growth & Differentiation. 2019; 61(5): 316-326.
Hong M, Tao S, Zhang L, et al. (2020). RNA sequencing: new technologies and applications in cancer research. Journal of Hematology & Oncology. 2020; 13(1): 1-16.
Piovesan A, Caracausi M, Antonaros F, et al. GeneBase 1.1: a tool to summarize data from NCBI Gene datasets and its application to an update of human gene statistics. Database. 2016; 2016: baw153.
Frankish A, Diekhans M, Ferreira AM, et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Research. 2019; 47: D766-D773.
Ramsköld D, Luo S, Wang YC, et al. Full- length mRNA- Seq from single- cell levels of RNA and individual circulating tumor cells. Nature Biotechnology. 2012; 30: 777-782.
Bolisetty MT, Rajadinakaran G, Graveley BR. Determining exon connectivity in complex mRNAs by nanopore sequencing. Genome Biology. 2015; 16: 204.
Ardui S, Ameur A, Vermeesch JR, et al. Single molecule real- time (SMRT) sequencing comes of age: applications and utilities for medical. Nucleic Acids Research. 2018; 46. 2159-2168.
Jain M, Olsen HE, Paten B, et al. The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biology. 2016; 17: 239.
Workman RE, Tang AD, Tang PS, et al. Nanopore native RNA sequencing of a human poly(A) transcriptome. Nature Methods. 2019; 16: 1297-1305. doi: 10.1038/s41592-019-0617-2
Weirather JL, de Cesare M, Wang Y, et al. Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis. F1000Res. 2017; 6: 100.
Tomita H, Vawter MP, Walsh DM, et al. Effect of agonal and postmortem factors on gene expression profile: Quality control in microarray analyses of postmortem human brain. Biological Psychiatry. 2004; 55: 346-352.
Thompson KL, Pine PS, Rosenzweig BA, et al. Characterization of the effect of sample quality on high density oligonucleotide microarray data using progressively degraded rat liver RNA. BMC Biotechnology. 2007; 7: 57.
Rudloff U, Bhanot U, Gerald W, et al. Biobanking of human pancreas cancer tissue: Impact of ex-vivo procurement times on RNA quality. Annals of Surgical Oncology. 2010; 17: 2229-2236.
Griffith RD, Simmons BJ, Bray FN, et al. 1064 nm Q‐switched Nd: YAG laser for the treatment of Argyria: a systematic review. Journal of the European Academy of Dermatology and Venereology. 2015; 29(11): 2100-2103.
Conesa A, Madrigal P, Tarazona S, et al. A survey of best practices for RNA-seq data analysis. Genome Biology. 2016; 17(1): 1-19.
Morin RD, Zhao YJ, Prabhu AL, et al. Preparation and analysis of Micro-RNA libraries using the Illumina massively parallel sequencing technology. Methods in Molecular Biology. 2010; 650: 173–199.
Parkhomchuk D, Borodina T, Amstislavskiy V, et al. Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Research. 2009; 37: e123.
Vivancos AP, Guell M, Dohm JC, et al. Strand-specific deep sequencing of the transcriptome. Genome Research. 2010; 20: 989-999.
Mills JD, Kawahara Y, Janitz M. Strand-specific RNA-Seq provides greater resolution of transcriptome profiling. Current Genomics. 2013; 14: 173-181.
Borodina T, Adjaye J, Sultan MA. Strand-specific library preparation protocol for RNA sequencing. Methods in Enzymology. 2011; 500: 79-98. doi: 10.1016/B978-0-12-385118-5.00005-0
Jayaprakash AD, Jabado O, Brown BD, et al. Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing. Nucleic Acids Research. 2011; 39: e141. doi: 10.1093/nar/gkr693
Sun G, Wu X, Wang J, et al. A bias-reducing strategy in profiling small RNAs using Solexa. RNA. 2011; 17: 2256-2262. doi: 10.1261/rna.028621.111
Levin JZ, Yassour M, Adiconis X, et al. Comprehensive comparative analysis of strand specific RNA sequencing methods. Nature Methods. 2010; 7: 709-715. doi:10.1038/nmeth.1491.
Hrdlickova R, Toloue M, Tian B. RNA‐Seq methods for transcriptome analysis. Wiley Interdisciplinary Reviews: RNA. 2017; 8(1): e1364.
Emmert-Buck MR, Bonner RF, Smith PD, et al. Laser capture microdissection. Science. 1996; 274: 998-1001.
Kube DM, Savci-Heijink CD, Lamblin AF, et al. Optimization of laser capture microdissection and RNA amplification for gene expression profiling of prostate cancer. BMC Molecular Biology. 2007; 8: 25.
Cantor H, Simpson E, Sato VL, et al. Characterization of subpopulations of T lymphocytes. I. Separation and functional studies of peripheral T-cells binding different amounts of fluorescent anti-Thy 1.2 (theta) antibody using a fluorescence-activated cell sorter (FACS). Cellular Immunology. 1975; 15: 180-196.
Huang S. Non-genetic heterogeneity of cells in development: More than just noise. Development. 2009; 136: 3853-3862.
Kawasaki ES. Microarrays and the gene expression profile of a single cell. Annals of the New York Academy of Sciences. 2004; 1020: 92-100.
Islam S, Kjallquist U, Moliner A, et al. Highly multiplexed and strand-specific single-cell RNA 5′ end sequencing. Nature Protocols. 2012; 7: 813-828.
Hashimshony T, Wagner F, Sher N, et al. CEL-Seq: Single-cell RNA-Seq by multiplexed linear amplification. Cell Reports. 2012; 2: 666-673.
Chapman AR, He Z, Lu S, et al. Single cell transcriptome amplification with MALBAC. PLoS One. 2015; 10: e0120889. doi: 10.1371/journal.pone.0120889
Kivioja T, Vaharautio A, Karlsson K, et al. Counting absolute numbers of molecules using unique molecular identifiers. Nature Methods. 2012; 9: 72-74. doi: 10.1038/nmeth.1778
Islam S, Zeisel A, Joost S, et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nature Methods. 2014; 11: 163-166. doi: 10.1038/nmeth.2772
Grun D, Kester L, van Oudenaarden A. Validation of noise models for single-cell transcriptomics. Nature Methods. 2014; 11: 637–640. doi: 10.1038/nmeth.2930
Fan HC, Fu GK, Fodor SP. Expression profiling. Combinatorial labeling of single cells for gene expression cytometry. Science. 2015; 347: 1258367. doi: 10.1126/science.1258367
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