轉錄組測序技術在癲癇中的應用_Journal of Epilepsy

Authors：

盧倩 ¹ ,  鄒麗萍 ^1,2

1. ;
2. ;

Corresponding?author：

鄒麗萍, Email: zouliping21@sina.com

Keywords：

RNA-seq; 轉錄組; 癲癇; 高通量測序; 基因芯片; Sanger 測序

DOI：

10.7507/2096-0247.20180023

Video：

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轉錄組測序（RNA sequencing，RNA-seq）技術作為一種新興的測序方法，利用高通量測序平臺，對特定狀態下的細胞內全部 RNA 進行測序分析，揭示不同物種的基因表達情況以及轉錄調控的規律。癲癇發病原因復雜，即使具有相同突變基因的癲癇患者，臨床表現嚴重程度不同，提示存在額外的影響因素，RNA-seq 技術通過對差異表達基因的分析，在癲癇病因的研究中發揮重要的作用。文章主要介紹 RNA-seq 技術與其他測序技術的比較以及不同的 RNA-seq 技術平臺特點，并敘述 RNA-seq 技術在癲癇中的應用。

Citation： 盧倩, 鄒麗萍. 轉錄組測序技術在癲癇中的應用. Journal of Epilepsy, 2018, 4(2): 112-116. doi: 10.7507/2096-0247.20180023 Copy

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8.	Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270(5235): 467-470.
9.	基因芯片與高通量 DNA 測序技術前景分析. 中國科學生命科學: 中國科學, 2008, 38(10): 891-899.
10.	Bradford JR, Hey Y, Yates T, et al. A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics, 2010, 11: 282.
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13.	Schuler GD, Boguski MS, Stewart EA, et al. A gene map of the human genome. Science, 1996, 274(5287): 540-546.
14.	王曉娜, 盧欣石. 表達序列標簽的應用現狀及分析方法研究. 草業科學, 2010, 27(5): 76-84.
15.	Qian X, Ba Y, Zhuang Q, et al. RNA-Seq technology and its application in fish transcriptomics. Omics, 2014, 18(2): 98-110.
16.	Morozova O, Hirst M, Marra MA. Applications of new sequencing technologies for transcriptome analysis. Annu Rev Genomics Hum Genet, 2009, 10: 135-151.
17.	Martin JA, Wang Z. Next-generation transcriptome assembly. Nat Rev Genet, 2011, 12(10): 671-682.
18.	Cloonan N, Forrest AR, Kolle G, et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods, 2008, 5(7): 613-619.
19.	Mardis ER. A decade's perspective on DNA sequencing technology. Nature, 2011, 470(7333): 198-203.
20.	Costa V, Angelini C, de Feis I, et al. Uncovering the complexity of transcriptomes with RNA-Seq. J Biomed Biotechnol, 2010, 2010: 853916.
21.	Nowrousian M. Next-generation sequencing techniques for eukaryotic microorganisms: sequencing-based solutions to biological problems. Eukaryot Cell, 2010, 9(9): 1300-1310.
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24.	Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet, 2008, 24(3): 133-141.
25.	Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet, 2008, 9: 387-402.
26.	Hossain MS, Azimi N, Skiena S. Crystallizing short-read assemblies around seeds. Bmc Bioinformatics, 2009, 10(Suppl 1): 16.
27.	Mutz KO, Heilkenbrinker A, Lonne M, et al. Transcriptome analysis using next-generation sequencing. Curr Opin Biotechnol, 2013, 24(1): 22-30.
28.	Pagani I, Liolios K, Jansson J, et al. The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res, 2012, 40(Database issue): 571-579.
29.	Robertson G, Schein J, Chiu R, et al. De novo assembly and analysis of RNA-seq data. Nat Methods, 2010, 7(11): 909-912.
30.	Trapnell C, Williams BA, Pertea G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 2010, 28(5): 511-515.
31.	張莉華. 基于 RNA-Seq 技術的尼古丁影響下大鼠大腦中的基因表達研究. 天津醫科大學碩士學位論文, 2014: 1-73.
32.	Young MD, Wakefield MJ, Smyth GK, et al. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol, 2010, 11(2): R14.
33.	Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000, 25(1): 25-29.
34.	Kanehisa M, Araki M, Goto S, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res, 2008, 36(Database issue): 480-484.
35.	Calhoun JD, Hawkins NA, Zachwieja NJ, et al. Cacna1g is a genetic modifier of epilepsy caused by mutation of voltage-gated sodium channel Scn2a. Epilepsia, 2016, 57(6): e103-107.
36.	Dravet C. The core Dravet syndrome phenotype. Epilepsia, 2011, 52(Suppl 2): 3-9.
37.	Miller AR, Hawkins NA, Mccollom CE, et al. Mapping genetic modifiers of survival in a mouse model of dravet syndrome. Genes Brain Behav, 2014, 13(2): 163-172.
38.	Kearney JA, Plummer NW, Smith MR, et al. A gain-of-function mutation in the sodium channel gene Scn2a results in seizures and behavioral abnormalities. Neuroscience, 2001, 102(2): 307-317.
39.	Hawkins NA, Kearney JA. Confirmation of an epilepsy modifier locus on mouse chromosome 11 and candidate gene analysis by RNA-Seq. Genes Brain Behav, 2012, 11(4): 452-460.
40.	Larsen J, Carvill GL, Gardella E, et al. The phenotypic spectrum of SCN8A encephalopathy. Neurology, 2015, 84(5): 480-489.
41.	Sprissler RS, Wagnon JL, Bunton-Stasyshyn RK, et al. Altered gene expression profile in a mouse model of SCN8A encephalopathy. Exp Neurol, 2017, 288: 134-141.
42.	Veeramah KR, O'brien JE, Meisler MH, et al. De novo pathogenic SCN8A mutation identified by whole-genome sequencing of a family quartet affected by infantile epileptic encephalopathy and SUDEP. Am J Hum Genet, 2012, 90(3): 502-510.
43.	Banerjee J, Tripathi M, Chandra PS. Understanding complexities of synaptic transmission in medically intractable seizures: a paradigm of epilepsy research. Indian J Neurosurg, 2013, 2(1): 71-76.
44.	Dixit AB, Banerjee J, Srivastava A, et al. RNA-seq analysis of hippocampal tissues reveals novel candidate genes for drug refractory epilepsy in patients with MTLE-HS. Genomics, 2016, 107(5): 178-188.
45.	Bernasconi A. Magnetic resonance imaging in intractable epilepsy: focus on structural image analysis. Adv Neurol, 2006, 97: 273-278.
46.	Blumcke I, Kistner I, Clusmann H, et al. Towards a clinico-pathological classification of granule cell dispersion in human mesial temporal lobe epilepsies. Acta Neuropathol, 2009, 117(5): 535-544.
47.	Kaalund SS, Veno MT, Bak M, et al. Aberrant expression of miR-218 and miR-204 in human mesial temporal lobe epilepsy and hippocampal sclerosis-convergence on axonal guidance. Epilepsia, 2014, 55(12): 2017-2027.
48.	Griffin NG, Wang Y, Hulette CM, et al. Differential gene expression in dentate granule cells in mesial temporal lobe epilepsy with and without hippocampal sclerosis. Epilepsia, 2016, 57(3): 376-385.
49.	Oldham MC, Konopka G, Iwamoto K, et al. Functional organization of the transcriptome in human brain. Nat Neurosci, 2008, 11(11): 1271-1282.
50.	Ziats MN, Rennert OM. Identification of differentially expressed microRNAs across the developing human brain. Mol Psychiatry, 2014, 19(7): 848-852.

1. Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature, 2001, 409(6822): 860-921.
2. Venter JC, Adams MD, Myers EW, et al. The sequence of the human genome. Science, 2001, 291(5507): 1304-1351.
3. Guerreiro CA. Epilepsy: Is there hope?. Indian J Med Res, 2016, 144(5): 657-660.
4. Scheffer IE, Berkovic S, Capovilla G, et al. ILAE classification of the epilepsies: Position paper of the ILAE Commission for classification and terminology. Epilepsia, 2017, 58(4): 512-521.
5. Hawkins NA, Zachwieja NJ, Miller AR, et al. Fine mapping of a Dravet Syndrome modifier locus on mouse chromosome 5 and candidate gene analysis by RNA-Seq. PLoS Genet, 2016, 12(10): e1006398.
6. Kukurba KR, Montgomery SB. RNA Sequencing and Analysis. Cold Spring Harb Protoc, 2015, 2015(11): 951-969.
7. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 2009, 10(1): 57-63.
8. Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270(5235): 467-470.
9. 基因芯片與高通量 DNA 測序技術前景分析. 中國科學生命科學: 中國科學, 2008, 38(10): 891-899.
10. Bradford JR, Hey Y, Yates T, et al. A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics, 2010, 11: 282.
11. Royce TE, Rozowsky JS, Gerstein MB. Toward a universal microarray: prediction of gene expression through nearest-neighbor probe sequence identification. Nucleic Acids Res, 2007, 35(15): e99.
12. 萬海偉, 杜立新. 表達序列標簽 (EST) 在基因組學研究中的應用. 生物技術通報, 2004, 2004(1): 35-38.
13. Schuler GD, Boguski MS, Stewart EA, et al. A gene map of the human genome. Science, 1996, 274(5287): 540-546.
14. 王曉娜, 盧欣石. 表達序列標簽的應用現狀及分析方法研究. 草業科學, 2010, 27(5): 76-84.
15. Qian X, Ba Y, Zhuang Q, et al. RNA-Seq technology and its application in fish transcriptomics. Omics, 2014, 18(2): 98-110.
16. Morozova O, Hirst M, Marra MA. Applications of new sequencing technologies for transcriptome analysis. Annu Rev Genomics Hum Genet, 2009, 10: 135-151.
17. Martin JA, Wang Z. Next-generation transcriptome assembly. Nat Rev Genet, 2011, 12(10): 671-682.
18. Cloonan N, Forrest AR, Kolle G, et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods, 2008, 5(7): 613-619.
19. Mardis ER. A decade's perspective on DNA sequencing technology. Nature, 2011, 470(7333): 198-203.
20. Costa V, Angelini C, de Feis I, et al. Uncovering the complexity of transcriptomes with RNA-Seq. J Biomed Biotechnol, 2010, 2010: 853916.
21. Nowrousian M. Next-generation sequencing techniques for eukaryotic microorganisms: sequencing-based solutions to biological problems. Eukaryot Cell, 2010, 9(9): 1300-1310.
22. van Vliet AH. Next generation sequencing of microbial transcriptomes: challenges and opportunities. Fems Microbiol Lett, 2010, 302(1): 1-7.
23. Margulies M, Egholm M, Altman WE, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 2005, 437(7057): 376-380.
24. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet, 2008, 24(3): 133-141.
25. Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet, 2008, 9: 387-402.
26. Hossain MS, Azimi N, Skiena S. Crystallizing short-read assemblies around seeds. Bmc Bioinformatics, 2009, 10(Suppl 1): 16.
27. Mutz KO, Heilkenbrinker A, Lonne M, et al. Transcriptome analysis using next-generation sequencing. Curr Opin Biotechnol, 2013, 24(1): 22-30.
28. Pagani I, Liolios K, Jansson J, et al. The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res, 2012, 40(Database issue): 571-579.
29. Robertson G, Schein J, Chiu R, et al. De novo assembly and analysis of RNA-seq data. Nat Methods, 2010, 7(11): 909-912.
30. Trapnell C, Williams BA, Pertea G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 2010, 28(5): 511-515.
31. 張莉華. 基于 RNA-Seq 技術的尼古丁影響下大鼠大腦中的基因表達研究. 天津醫科大學碩士學位論文, 2014: 1-73.
32. Young MD, Wakefield MJ, Smyth GK, et al. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol, 2010, 11(2): R14.
33. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000, 25(1): 25-29.
34. Kanehisa M, Araki M, Goto S, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res, 2008, 36(Database issue): 480-484.
35. Calhoun JD, Hawkins NA, Zachwieja NJ, et al. Cacna1g is a genetic modifier of epilepsy caused by mutation of voltage-gated sodium channel Scn2a. Epilepsia, 2016, 57(6): e103-107.
36. Dravet C. The core Dravet syndrome phenotype. Epilepsia, 2011, 52(Suppl 2): 3-9.
37. Miller AR, Hawkins NA, Mccollom CE, et al. Mapping genetic modifiers of survival in a mouse model of dravet syndrome. Genes Brain Behav, 2014, 13(2): 163-172.
38. Kearney JA, Plummer NW, Smith MR, et al. A gain-of-function mutation in the sodium channel gene Scn2a results in seizures and behavioral abnormalities. Neuroscience, 2001, 102(2): 307-317.
39. Hawkins NA, Kearney JA. Confirmation of an epilepsy modifier locus on mouse chromosome 11 and candidate gene analysis by RNA-Seq. Genes Brain Behav, 2012, 11(4): 452-460.
40. Larsen J, Carvill GL, Gardella E, et al. The phenotypic spectrum of SCN8A encephalopathy. Neurology, 2015, 84(5): 480-489.
41. Sprissler RS, Wagnon JL, Bunton-Stasyshyn RK, et al. Altered gene expression profile in a mouse model of SCN8A encephalopathy. Exp Neurol, 2017, 288: 134-141.
42. Veeramah KR, O'brien JE, Meisler MH, et al. De novo pathogenic SCN8A mutation identified by whole-genome sequencing of a family quartet affected by infantile epileptic encephalopathy and SUDEP. Am J Hum Genet, 2012, 90(3): 502-510.
43. Banerjee J, Tripathi M, Chandra PS. Understanding complexities of synaptic transmission in medically intractable seizures: a paradigm of epilepsy research. Indian J Neurosurg, 2013, 2(1): 71-76.
44. Dixit AB, Banerjee J, Srivastava A, et al. RNA-seq analysis of hippocampal tissues reveals novel candidate genes for drug refractory epilepsy in patients with MTLE-HS. Genomics, 2016, 107(5): 178-188.
45. Bernasconi A. Magnetic resonance imaging in intractable epilepsy: focus on structural image analysis. Adv Neurol, 2006, 97: 273-278.
46. Blumcke I, Kistner I, Clusmann H, et al. Towards a clinico-pathological classification of granule cell dispersion in human mesial temporal lobe epilepsies. Acta Neuropathol, 2009, 117(5): 535-544.
47. Kaalund SS, Veno MT, Bak M, et al. Aberrant expression of miR-218 and miR-204 in human mesial temporal lobe epilepsy and hippocampal sclerosis-convergence on axonal guidance. Epilepsia, 2014, 55(12): 2017-2027.
48. Griffin NG, Wang Y, Hulette CM, et al. Differential gene expression in dentate granule cells in mesial temporal lobe epilepsy with and without hippocampal sclerosis. Epilepsia, 2016, 57(3): 376-385.
49. Oldham MC, Konopka G, Iwamoto K, et al. Functional organization of the transcriptome in human brain. Nat Neurosci, 2008, 11(11): 1271-1282.
50. Ziats MN, Rennert OM. Identification of differentially expressed microRNAs across the developing human brain. Mol Psychiatry, 2014, 19(7): 848-852.

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轉錄組測序技術在癲癇中的應用

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