A flexible Bayesian method for detecting allelic imbalance in RNA-seq data

BMC Genomics

Volumn 15, Issue 1, 2014, Pages

  León Novelo, Luis G ^a   McIntyre, Lauren M ^b   Fear, Justin M ^b   Graze, Rita M ^c  

^a UNIVERSITY OF LOUISIANA AT LAFAYETTE   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

^c AUBURN UNIVERSITY   (United States)

Author keywords

Allele specific expression; Allelic imbalance; Bayesian model; RNA seq; Systematic error

Indexed keywords

ALLELE; ALLELIC IMBALANCE; ANIMAL MODEL; DISEASE SIMULATION; EXPERIMENTAL DESIGN; FILTRATION; GENOME; HUMAN; STATISTICAL MODEL; SYSTEMATIC ERROR; BAYES THEOREM; POISSON DISTRIBUTION; PROCEDURES; SEQUENCE ANALYSIS;

ALLELIC IMBALANCE; BAYES THEOREM; MODELS, STATISTICAL; POISSON DISTRIBUTION; SEQUENCE ANALYSIS, RNA;

EID: 84964315271     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-15-920     Document Type: Article

References (64)

1. Conne B, Stutz A, Vassalli JD: The 3' untranslated region ofmessenger RNA: Amolecular 'hotspot' for pathology? NatMed 2000, 6(6):637-641.
2. Mendell JT, Dietz HC: When themessage goes awry: disease-producingmutations that influencemRNA content and performance. Cell 2001, 107(4):411-414.
3. Hollams EM, Giles KM, Thomson AM, Leedman PJ: MRNA stability and the control of gene expression: implications for human disease. Neurochem Res 2002, 27(10):957-980.
4. Faustino NA, Cooper TA: Pre-mRNA splicing and human disease. Genes Dev 2003, 17(4):419-437.
5. Buckland PR: The importance and identification of regulatory polymorphisms and theirmechanisms of action. BiochimBiophys Acta 2006, 1762(1):17-28.
6. Chen J-M, Férec C, Cooper DN: A systematic analysis of disease-associated variants in the 3' regulatory regions of human protein-coding genes I: general principles and overview. HumGenet 2006, 120(1):1-21.
7. Johnson AD, Wang D, Sadee W: Polymorphisms affecting gene regulation and mRNA processing: broad implications for pharmacogenetics. Pharmacol Ther 2005, 106(1):19-38.
8. Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, Carlson S, Helgason A, Walters GB, Gunnarsdottir S, Mouy M, Steinthorsdottir V, Eiriksdottir GH, Bjornsdottir G, Reynisdottir I, Gudbjartsson D, Helgadottir A, Jonasdottir A, Jonasdottir A, Styrkarsdottir U, Gretarsdottir S, Magnusson KP, Stefansson H, Fossdal R, Kristjansson K, Gislason HG, Stefansson T, Leifsson BG, Thorsteinsdottir U, Lamb JR, et al.: Genetics of gene expression and its effect on disease. Nature 2008, 452(7186):423-428.
9. Lai Z, Gross BL, Zou YI, Andrews J, Rieseberg LH: Microarray analysis reveals differential gene expression in hybrid sunflower species. Mol Ecol 2006, 15(5):1213-1227.
10. Jeong S, Rebeiz M, Andolfatto P, Werner T, True J, Carroll SB: The evolution of gene regulation underlies a morphological difference between two Drosophila sister species. Cell 2008, 132(5):783-793.
11. Martin-Coello J, Dopazo H, Arbiza L, Ausió J, Roldan ER, Gomendio M: Sexual selection drives weak positive selection in protamine genes and high promoter divergence, enhancing sperm competitiveness. Proc R Soc Biol Sci 2009, 276(1666):2427-2436.
12. Wittkopp PJ, Stewart EE, Arnold LL, Neidert AH, Haerum BK, Thompson EM, Akhras S, Smith-Winberry G, Shefner L: Intraspecific polymorphism to interspecific divergence: genetics of pigmentation in Drosophila. Science 2009, 326(5952):540-544.
13. Barbash DA, Siino DF, Tarone AM, Roote J: A rapidly evolving MYB-related protein causes species isolation in Drosophila. Proc Nat Acad Sci USA 2003, 100(9):5302-5307.
14. Michalak P, Noor MAF: Association of misexpression with sterility in hybrids of Drosophila simulansand D. mauritiana. JMol Evol 2004, 59(2):277-282.
15. Sun S, Ting CT, Wu CI: The normal function of a speciation gene, Odysseus, and its hybrid sterility effect. Science 2004, 305(5680):81-83.
16. Haerty W, Singh RS: Gene regulation divergence is a major contributor to the evolution of Dobzhansky-Muller incompatibilities between species of Drosophila.Mol Biol Evol 2006, 23(9):1707-1714.
17. Michalak P, Malone JH, Lee IT, Hoshino D, Ma D: Gene expression polymorphism in Drosophila populations. Mol Ecol 2007, 16(6):1179-1189.
18. Shirangi TR, Dufour HD, Williams TM, Carroll SB: Rapid evolution of sex pheromone-producing enzyme expression in Drosophila. PLoS Biol 2009, 7(8):e1000168.
19. Brem RB, Yvert G, Clinton R, Kruglyak L: Genetic dissection of transcriptional regulation in budding yeast. Science 2002, 296(5568):752-755.
20. Yan H, Yuan W, Velculescu VE, Vogelstein B: Kinzler KW: Allelic variation in human gene expression. Science 2002, 297(5584):1143.
21. Lo HS, Wang Z, Hu Y, Yang HH, Gere S, Buetow KH, Lee MP: Allelic variation in gene expression is common in the human genome. Genome Res 2003, 13(8):1855-1862.
22. Wittkopp PJ, Haerum BK, Clark AG: Evolutionary changes in cis and trans gene regulation. Nature 2004, 430(6995):85-88.
23. Kirst M, Basten CJ, Myburg AA, Zeng ZB, Sederoff RR: Genetic architecture of transcript-level variation in differentiating xylem of a eucalyptus hybrid. Genetics 2005, 169(4):2295-2303.
24. Ronald J, Akey JM, Whittle J, Smith EN, Yvert G, Kruglyak L: Simultaneous genotyping, gene-expression measurement, and detection of allele-specific expression with oligonucleotide arrays. Genome Res 2005, 15(2):284-291.
25. Hughes KA, Ayroles JF, Reedy MM, Drnevich JM, Rowe KC, Ruedi EA, Cáceres CE, Paige KN: Segregating variation in the transcriptome: cis regulation and additivity of effects. Genetics 2006, 173(3):1347-1355.12.
26. Genissel A, McIntyre LM, Wayne ML, Nuzhdin SV: Cis and trans regulatory effects contribute to natural variation in transcriptome of Drosophila melanogaster. Mol Biol Evol 2008, 25(1):101-110.
27. Guo M, Yang S, Rupe M, Hu B, Bickel DR, Arthur L, Smith O: Genome-wide allele-specific expression analysis usingmassively parallel signature sequencing (MPSSâĎć) reveals cis-and trans-effects on gene expression in maize. Plant Mol Ecol 2008, 66(5):551-563.
28. Lemos B, Araripe LO, Fontanillas P, Hartl DL: Dominance and the evolutionary accumulation of cis-and trans-effects on gene expression. Proc Nat Acad Sci 2008, 105(38):14471-14476.
29. Graze RM, McIntyre LM, Main BJ, Wayne ML, Nuzhdin SV: Regulatory divergence in Drosophila melanogaster and D. simulans, a genomewide analysis of allele-specific expression. Genetics 2009, 183(2):547-61121.
30. Tirosh I, Reikhav S, Levy AA, Barkai N: A yeast hybrid provides insight into the evolution of gene expression regulation. Science 2009, 324(5927):659-662.
31. Zhang X, Borevitz JO: Global analysis of allele-specific expression in Arabidopsis thaliana. Genetics 2009, 182(4):943-954.
32. McManus CJ, Coolon JD, Duff MO, Eipper-Mains J, Graveley BR, Wittkopp PJ: Regulatory divergence in Drosophila revealed bymRNA-seq. Genome Res 2010, 20(6):816-825.
33. Zhang K, Li JB, Gao Y, Egli D, Xie B, Deng J, Li Z, Lee J-H, Aach J, Leproust EM, Eggan K, Church GM: Digital RNA allelotyping reveals tissue-specific and allele-specific gene expression in human. Nat Methods 2009, 6(8):613-618.
34. Yang Y, Graze RM, Walts BM, Lopez CM, Baker HV, Wayne ML, Nuzhdin SV, McIntyre LM: Partitioning transcript variation in Drosophila: abundance, isoforms, and alleles. G3 (Bethesda) 2011, 1(6):427-436.
35. Degner JF, Marioni JC, Pai AA, Pickrell JK, Nikadori E, Gilad Y, Pritchard JK: Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data. J Bioinformatics 2009, 25(24):3207-3212.
36. Main BJ, Bickel RD, McIntyre LM, Graze RM, Calabrese PP, Nuzhdin SV: Allele-specific expression assays using Solexa. BMC Genomics 2009, 10(1):422.
37. Emerson JJ, Hsieh LH, Sung HM, Wang TY, Huang CJ, Lu HH-S, Lu M-YJ, Wu S-H, Li W-H: Natural selection on cis and trans regulation in yeasts. Genome Res 2010, 20(6):826-836.
38. Fontanillas P, Landry CR, Wittkopp PJ, Russ C, Gruber JD, Nusbaum C, Hartl DL: Key considerations for measuring allelic expression on a genomic scale using high-throughput sequencing. Mol Ecol 2010, 19:212-227.
39. Gregg C, Zhang J, Weissbourd B, Luo S, Schroth GP, Haig D, Dulac C: High-resolution analysis of parent-of-origin allelic expression in the mouse brain. Science 2010, 329(5992):643-648.
40. Rozowsky J, Abyzov A, Wang J, Alves P, Raha D, Harmanci A, Leng J, Bjorson R, Kong Y, Kitabayashi N, Bhardwaj N, Rubin M, Snyder M, Gerstein M: AlleleSeq: analysis of allele-specific expression and binding in a network framework. Mol Syst Biol 2011, 7(1):522.
41. Robinson MD, Smyth GK: Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 2008, 9(2):321-332.
42. Anders S, Huber W: Differential expression analysis for sequence count data. Genome Biol 2010, 11(10):106.
43. Auer PL, Doerge RW: A two-stage Poissonmodel for testing RNA-seq data. Stat Appl Genet Mol Biol 2011, 10(1):1-26.
44. Langmead B, Hansen KD, Leek JT: Cloud-scale RNA-sequencing differential expression analysis with Myrna. Genome Biol 2010, 11(8):R83.
45. Oshlack A, Robinson MD, Young MD: From RNA-seq reads to differential expression results. Genome Biol 2010, 11(12):220.
46. Skelly DA, Johansson M, Madeoy J, Wakefield J, Akey JM: A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data. Genome Res 2011, 21(10):1728-1737.
47. Turro E, Su SY, Gonçalves â, Coin LJ, Richardson S, Lewin A: Haplotype and isoform specific expression estimation usingmulti-mapping RNA-seq reads. Genome Res 2011, 12(2):13.
48. Graze RM, Novelo LL, Amin V, Fear JM, Casella G, Nuzhdin SV, McIntyre LM: Allelic imbalance in Drosophila hybrid heads: exons, isoforms, and evolution. Mol Biol Evol 2012, 29(6):1521-1532.
49. DeVeale B, Kooy DVD, Babak T: Critical evaluation of imprinted gene expression by RNAâ ĂSSeq: a new perspective. PLoS Genet 2012, 8(3):e1002600.
50. Stevenson KR, Coolon JD, Wittkopp PJ: Sources of bias inmeasures of allele-specific expression derived fromrna-seq data aligned to a single reference genome. BMC Genomics 2013, 14(1):536.
51. Satya RV, Zavaljevski N, Reifman J: A new strategy to reduce allelic bias in RNA-Seq readmapping. Nucleic Acids Res 2012, 40:e127.
52. Heap GA, Yang JH, Downes K, Healy BC, Hunt KA, Bockett N, Franke L, Dubois PC, Mein CA, Dobson RJ, Albert TJ, Rodesch MJ, Clayton DG, Todd JA, van Heel DA, Plagnol V: Genome-wide analysis of allelic expression imbalance in human primary cells by high-throughput transcriptome resequencing. HumMol Genet 2010, 19(1):122-134.
53. Nothnagel M, Wolf A, Herrmann A, Szafranski K, Vater I, Brosch M, Huse K, Siebert R, Platzer M, Hampe J, Krawczak M: Statistical inference of allelic imbalance from transcriptome data. HumMutat 2011, 32(1):98-106.
54. Pandey RV, Franssen SU, Futschik A, Schlötterer C: Allelic imbalance metre (Allim), a new tool formeasuring allele-specific gene expression with RNA-seq data.Mol Ecol Resour 2013, 13(4):740-745.
55. Huang W, Massouras A, Inoue Y, Peiffer J, Ràmia M, Tarone AM, Turlapati L, Zichner T, Zhu D, Lyman RF, Magwire MM, Blankenburg K, Carbone MA, Chang K, Ellis LL, Fernandez S, Han Y, Highnam G, Hjelmen CE, Jack JR, Javaid M, Jayaseelan J, Kalra D, Lee S, Lewis L, Munidasa M, Ongeri F, Patel S, Perales L, Perez A, et al.: Natural variation in genome architecture among 205 drosophila melanogaster genetic reference panel lines. Genome Res 2014, 24:1193-1208.
56. Li H: Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. 2013, 1303.3997 arXiv Prepr. arXiv1303.3997.
57. Garrison E, Marth G: Haplotype-based variant detection from short-read sequencing. 2012, 1207.3907 arXiv Prepr. arXiv1207.3907.
58. Law CW, Chen Y, Shi W: Smyth GK: Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 2014, 15:29.
59. Montgomery SB, Sammeth M, Gutierrez-Arcelus M, Lach RP, Ingle C, Nisbett J, Guigo R, Dermitzakis ET: Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 2010, 464(7289):773-777.
60. Langmead B, Trapnell C, Pop M: Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009, 10(3):25.
61. Frith MC,Wan R,Horton P: Incorporating sequence quality data into alignment improves DNA readmapping. Nucleic Acids Res 2010, 38(7):e100-e100.
62. Lee H, Schatz MC: Genomic dark matter: the reliability of short read mapping illustrated by the genome mappability score. Bioinformatics 2012, 28(16):2097-2105.
63. McIntyre LM, Lopiano KK, Morse AM, Amin V, Oberg AL, Young LJ: Nuzhdin SV: RNA-seq: technical variability and sampling. BMC Genomics 2011, 12(1):293.
64. Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995, 57(1):289-300.