Random monoallelic expression of autosomal genes: stochastic transcription and allele-level regulation

Key Points

  • Analyses of clonal cell populations have revealed fixed autosomal random monoallelic expression (aRME), in which allele-specific expression is conserved in daughter cells after division.

  • More recently, single-cell analyses have revealed dynamic aRME, in which stochastic transcription renders shorter-term periods of expression frequently from only one allele.

  • Distinguishing features of the two forms of aRME (clonally fixed and dynamic) are discussed, and literature on their nature, pervasiveness and regulation is revisited.

  • Open outstanding questions in this emerging field of research are highlighted.

  • Clonally fixed and dynamic aRME can be studied simultaneously via single-cell analyses of allelic transcription in clonal cells, and such analyses of in vivo cell types will propel our understanding of transcriptional regulation.

  • aRME increases the heterogeneity among cells and probably contributes to the variance of phenotypes — including disease manifestations — among individuals of identical genotype.

Abstract

Random monoallelic expression (RME) of genes represents a striking example of how stochastic molecular processes can result in cellular heterogeneity. Recent transcriptome-wide studies have revealed both mitotically stable and cell-to-cell dynamic forms of autosomal RME, with the latter presumably resulting from burst-like stochastic transcription. Here, we discuss the distinguishing features of these two forms of RME and revisit literature on their nature, pervasiveness and regulation. Finally, we explore how RME may contribute to phenotypic variation, including the incomplete penetrance and variable expressivity often seen in genetic disease.

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Figure 1: Modes of monoallelic gene expression.
Figure 2: Causes of fixed and dynamic aRME.
Figure 3: Models for phenotypic consequences of aRME.

References

  1. 1

    Reik, W. & Walter, J. Genomic imprinting: parental influence on the genome. Nat. Rev. Genet. 2, 21–32 (2001).

  2. 2

    Ferguson-Smith, A. C. Genomic imprinting: the emergence of an epigenetic paradigm. Nat. Rev. Genet. 12, 565–575 (2011).

  3. 3

    Lyon, M. F. Gene action in the X-chromosome of the mouse (Mus musculus L.). Nature 190, 372–373 (1961).

  4. 4

    Monk, M. & Harper, M. I. Sequential X chromosome inactivation coupled with cellular differentiation in early mouse embryos. Nature 281, 311–313 (1979).

  5. 5

    Hadjantonakis, A. K., Cox, L. L., Tam, P. P. & Nagy, A. An X-linked GFP transgene reveals unexpected paternal X-chromosome activity in trophoblastic giant cells of the mouse placenta. Genesis 29, 133–140 (2001).

  6. 6

    Wu, H. et al. Cellular resolution maps of X chromosome inactivation: implications for neural development, function, and disease. Neuron 81, 103–119 (2014).

  7. 7

    Gimelbrant, A., Hutchinson, J. N., Thompson, B. R. & Chess, A. Widespread monoallelic expression on human autosomes. Science 318, 1136–1140 (2007). This paper describes the first genome-wide study on aRME, which identified widespread fixed aRME.

  8. 8

    Deng, Q., Ramsköld, D., Reinius, B. & Sandberg, R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193–196 (2014). This study reveals and characterizes abundant dynamic aRME in early embryonic cells using single-cell RNA-seq analyses on outcrossed mouse embryos.

  9. 9

    Pernis, B., Chiappino, G., Kelus, A. S. & Gell, P. G. Cellular localization of immunoglobulins with different allotypic specificities in rabbit lymphoid tissues. J. Exp. Med. 122, 853–876 (1965).

  10. 10

    Hozumi, N. & Tonegawa, S. Evidence for somatic rearrangement of immunoglobulin genes coding for variable and constant regions. Proc. Natl Acad. Sci. USA 73, 3628–3632 (1976).

  11. 11

    Brady, B. L., Steinel, N. C. & Bassing, C. H. Antigen receptor allelic exclusion: an update and reappraisal. J. Immunol. 185, 3801–3808 (2010).

  12. 12

    Chess, A., Simon, I., Cedar, H. & Axel, R. Allelic inactivation regulates olfactory receptor gene expression. Cell 78, 823–834 (1994).

  13. 13

    Tasic, B. et al. Promoter choice determines splice site selection in protocadherin α and γ pre-mRNA splicing. Mol. Cell 10, 21–33 (2002).

  14. 14

    Wang, X., Su, H. & Bradley, A. Molecular mechanisms governing Pcdh-γ gene expression: evidence for a multiple promoter and cis-alternative splicing model. Genes Dev. 16, 1890–1905 (2002).

  15. 15

    Esumi, S. et al. Monoallelic yet combinatorial expression of variable exons of the protocadherin-α gene cluster in single neurons. Nat. Genet. 37, 171–176 (2005).

  16. 16

    Kaneko, R. et al. Allelic gene regulation of Pcdh-α and Pcdh-α clusters involving both monoallelic and biallelic expression in single Purkinje cells. J. Biol. Chem. 281, 30551–30560 (2006).

  17. 17

    Held, W. & Raulet, D. H. Expression of the Ly49A gene in murine natural killer cell clones is predominantly but not exclusively mono-allelic. Eur. J. Immunol. 27, 2876–2884 (1997).

  18. 18

    Bix, M. Independent and epigenetic regulation of the interleukin-4 alleles in CD4+ T cells. Science 281, 1352–1354 (1998).

  19. 19

    Rivière, I., Sunshine, M. J. & Littman, D. R. Regulation of IL-4 expression by activation of individual alleles. Immunity 9, 217–228 (1998).

  20. 20

    Holländer, G. A. et al. Monoallelic expression of the interleukin-2 locus. Science 279, 2118–2121 (1998).

  21. 21

    Nutt, S. L. et al. Independent regulation of the two Pax5 alleles during B-cell development. Nat. Genet. 21, 390–395 (1999).

  22. 22

    Rhoades, K. L. et al. Allele-specific expression patterns of interleukin-2 and Pax-5 revealed by a sensitive single-cell RT-PCR analysis. Curr. Biol. 10, 789–792 (2000).

  23. 23

    Kelly, B. L. & Locksley, R. M. Coordinate regulation of the IL-4, IL-13, and IL-5 cytokine cluster in Th2 clones revealed by allelic expression patterns. J. Immunol. 165, 2982–2986 (2000).

  24. 24

    Guo, L., Hu-Li, J. & Paul, W. E. Probabilistic regulation in TH2 cells accounts for monoallelic expression of IL-4 and IL-13. Immunity 23, 89–99 (2005).

  25. 25

    Sano, Y. et al. Random monoallelic expression of three genes clustered within 60 kb of mouse t complex genomic DNA. Genome Res. 11, 1833–1841 (2001).

  26. 26

    Ohlsson, R. et al. Random monoallelic expression of the imprinted IGF2 and H19 genes in the absence of discriminative parental marks. Dev. Genes Evol. 209, 113–119 (1999).

  27. 27

    Rodriguez, I., Feinstein, P. & Mombaerts, P. Variable patterns of axonal projections of sensory neurons in the mouse vomeronasal system. Cell 97, 199–208 (1999).

  28. 28

    Gimelbrant, A. A., Ensminger, A. W., Qi, P., Zucker, J. & Chess, A. Monoallelic expression and asynchronous replication of p120 catenin in mouse and human cells. J. Biol. Chem. 280, 1354–1359 (2005).

  29. 29

    Zwemer, L. M. et al. Autosomal monoallelic expression in the mouse. Genome Biol. 13, R10 (2012).

  30. 30

    Jeffries, A. R. et al. Stochastic choice of allelic expression in human neural stem cells. Stem Cells 30, 1938–1947 (2012).

  31. 31

    Eckersley-Maslin, M. A. et al. Random monoallelic gene expression increases upon embryonic stem cell differentiation. Dev. Cell 28, 351–365 (2014).

  32. 32

    Gendrel, A.-V. et al. Developmental dynamics and disease potential of random monoallelic gene expression. Dev. Cell 28, 366–380 (2014). References 31 and 32 identify fixed aRME using RNA-seq on outcrossed mouse cell lines and perform the most-comprehensive analyses to date of putative regulatory correlates and mechanisms.

  33. 33

    Li, S. M. et al. Transcriptome-wide survey of mouse CNS-derived cells reveals monoallelic expression within novel gene families. PLoS ONE 7, e31751 (2012).

  34. 34

    Nag, A. et al. Chromatin signature of widespread monoallelic expression. eLife 2, e01256 (2013).

  35. 35

    Marinov, G. K. et al. From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing. Genome Res. 24, 496–510 (2014).

  36. 36

    Borel, C. et al. Biased allelic expression in human primary fibroblast single cells. Am. J. Hum. Genet. 96, 70–80 (2015).

  37. 37

    Rodriguez, I. Singular expression of olfactory receptor genes. Cell 155, 274–277 (2013).

  38. 38

    Morey, C. & Avner, P. The demoiselle of X-inactivation: 50 years old and as trendy and mesmerising as ever. PLoS Genet. 7, e1002212 (2011).

  39. 39

    Augui, S., Nora, E. P. & Heard, E. Regulation of X-chromosome inactivation by the X-inactivation centre. Nat. Rev. Genet. 12, 429–442 (2011).

  40. 40

    Lessing, D., Anguera, M. C. & Lee, J. T. X chromosome inactivation and epigenetic responses to cellular reprogramming. Annu. Rev. Genomics Hum. Genet. 14, 85–110 (2013).

  41. 41

    Pollex, T. & Heard, E. Recent advances in X-chromosome inactivation research. Curr. Opin. Cell Biol. 24, 825–832 (2012).

  42. 42

    Nguyen, M. Q., Zhou, Z., Marks, C. A., Ryba, N. J. P. & Belluscio, L. Prominent roles for odorant receptor coding sequences in allelic exclusion. Cell 131, 1009–1017 (2007).

  43. 43

    Lewcock, J. W. & Reed, R. R. A feedback mechanism regulates monoallelic odorant receptor expression. Proc. Natl Acad. Sci. USA 101, 1069–1074 (2004).

  44. 44

    Lyons, D. B. et al. An epigenetic trap stabilizes singular olfactory receptor expression. Cell 154, 325–336 (2013).

  45. 45

    Bartolomei, M. S. & Ferguson-Smith, A. C. Mammalian genomic imprinting. Cold Spring Harb. Perspect. Biol. 3, a002592 (2011).

  46. 46

    Lee, J. T. & Bartolomei, M. S. X-inactivation, imprinting, and long noncoding RNAs in health and disease. Cell 152, 1308–1323 (2013).

  47. 47

    Hübner, M. R., Eckersley-Maslin, M. A. & Spector, D. L. Chromatin organization and transcriptional regulation. Curr. Opin. Genet. Dev. 23, 89–95 (2013).

  48. 48

    Chow, J. C. & Heard, E. Nuclear organization and dosage compensation. Cold Spring Harb. Perspect. Biol. 2, a000604 (2010).

  49. 49

    Pandey, R. R. et al. Kcnq1ot1 antisense noncoding RNA mediates lineage-specific transcriptional silencing through chromatin-level regulation. Mol. Cell 32, 232–246 (2008).

  50. 50

    Mohammad, F. et al. Kcnq1ot1/Lit1 noncoding RNA mediates transcriptional silencing by targeting to the perinucleolar region. Mol. Cell. Biol. 28, 3713–3728 (2008).

  51. 51

    Skok, J. A. et al. Nonequivalent nuclear location of immunoglobulin alleles in B lymphocytes. Nat. Immunol. 2, 848–854 (2001).

  52. 52

    Kosak, S. T. et al. Subnuclear compartmentalization of immunoglobulin loci during lymphocyte development. Science 296, 158–162 (2002).

  53. 53

    Lomvardas, S. et al. Interchromosomal interactions and olfactory receptor choice. Cell 126, 403–413 (2006).

  54. 54

    Clowney, E. J. et al. Nuclear aggregation of olfactory receptor genes governs their monogenic expression. Cell 151, 724–737 (2012).

  55. 55

    Li, G.-W. & Xie, X. S. Central dogma at the single-molecule level in living cells. Nature 475, 308–315 (2011).

  56. 56

    Larson, D. R., Singer, R. H. & Zenklusen, D. A single molecule view of gene expression. Trends Cell Biol. 19, 630–637 (2009).

  57. 57

    Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002).

  58. 58

    Sandberg, R. Entering the era of single-cell transcriptomics in biology and medicine. Nat. Methods 11, 22–24 (2014).

  59. 59

    Yunger, S., Rosenfeld, L., Garini, Y. & Shav-Tal, Y. Quantifying the transcriptional output of single alleles in single living mammalian cells. Nat. Protoc. 8, 393–408 (2013).

  60. 60

    Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).

  61. 61

    Chubb, J. R., Trcek, T., Shenoy, S. M. & Singer, R. H. Transcriptional pulsing of a developmental gene. Curr. Biol. 16, 1018–1025 (2006).

  62. 62

    Suter, D. M. et al. Mammalian genes are transcribed with widely different bursting kinetics. Science 332, 472–474 (2011).

  63. 63

    Yunger, S., Rosenfeld, L., Garini, Y. & Shav-Tal, Y. Single-allele analysis of transcription kinetics in living mammalian cells. Nat. Methods 7, 631–633 (2010).

  64. 64

    Rabani, M. et al. Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells. Nat. Biotech. 29, 436–442 (2011).

  65. 65

    Tani, H. et al. Genome-wide determination of RNA stability reveals hundreds of short-lived noncoding transcripts in mammals. Genome Res. 22, 947–956 (2012).

  66. 66

    Clark, M. B. et al. Genome-wide analysis of long noncoding RNA stability. Genome Res. 22, 885–898 (2012).

  67. 67

    Irizarry, R. A. et al. Multiple-laboratory comparison of microarray platforms. Nat. Methods 2, 345–350 (2005).

  68. 68

    Zilliox, M. J. & Irizarry, R. A. A gene expression bar code for microarray data. Nat. Methods 4, 911–913 (2007).

  69. 69

    Lucito, R. et al. Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation. Genome Res. 13, 2291–2305 (2003).

  70. 70

    Zong, C., Lu, S., Chapman, A. R. & Xie, X. S. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338, 1622–1626 (2012).

  71. 71

    Gaztelumendi, N. & Nogués, C. Chromosome instability in mouse embryonic stem cells. Sci. Rep. 4, 5324 (2014).

  72. 72

    Macosko, E. Z. & McCarroll, S. A. Our fallen genomes. Science 342, 564–565 (2013).

  73. 73

    Handsaker, R. E. et al. Large multiallelic copy number variations in humans. Nat. Genet. 47, 296–303 (2015).

  74. 74

    Maitra, A. et al. Genomic alterations in cultured human embryonic stem cells. Nat. Genet. 37, 1099–1103 (2005).

  75. 75

    Baker, D. E. C. et al. Adaptation to culture of human embryonic stem cells and oncogenesis in vivo. Nat. Biotechnol. 25, 207–215 (2007).

  76. 76

    Picelli, S. et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat. Methods 10, 1096–1098 (2013).

  77. 77

    Islam, S. et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat. Methods 11, 163–166 (2014).

  78. 78

    Jaitin, D. A. et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776–779 (2014).

  79. 79

    Hashimshony, T., Wagner, F., Sher, N. & Yanai, I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2, 666–673 (2012).

  80. 80

    Cooper, D. N., Krawczak, M., Polychronakos, C., Tyler-Smith, C. & Kehrer-Sawatzki, H. Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease. Hum. Genet. 132, 1077–1130 (2013).

  81. 81

    van Regemorter, N., Milaire, J., Ramet, J., Haumont, D. & Rodesch, F. Familial ectrodactyly and polydactyly: variable expressivity of one single gene — embryological considerations. Clin. Genet. 22, 206–210 (1982).

  82. 82

    Danforth, C. H. Heredity of polydactyly in the cat. J. Hered. 38, 107–112 (1947).

  83. 83

    Lehner, B. Genotype to phenotype: lessons from model organisms for human genetics. Nat. Rev. Genet. 14, 168–178 (2013).

  84. 84

    Kaern, M., Elston, T. C., Blake, W. J. & Collins, J. J. Stochasticity in gene expression: from theories to phenotypes. Nat. Rev. Genet. 6, 451–464 (2005).

  85. 85

    Roberts, N. J. et al. The predictive capacity of personal genome sequencing. Sci. Transl. Med. 4, 133ra58 (2012).

  86. 86

    Pereira, R., Halford, K., Sokolov, B. P., Khillan, J. S. & Prockop, D. J. Phenotypic variability and incomplete penetrance of spontaneous fractures in an inbred strain of transgenic mice expressing a mutated collagen gene (COL1A1). J. Clin. Invest. 93, 1765–1769 (1994).

  87. 87

    Raj, A., Rifkin, S. A., Andersen, E. & van Oudenaarden, A. Variability in gene expression underlies incomplete penetrance. Nature 463, 913–918 (2010). This study demonstrates how the disruption of a gene could have phenotypic consequences through the destabilization of an otherwise well-buffered gene regulatory network.

  88. 88

    Eckersley-Maslin, M. A. & Spector, D. L. Random monoallelic expression: regulating gene expression one allele at a time. Trends Genet. 30, 237–244 (2014).

  89. 89

    Chess, A. Mechanisms and consequences of widespread random monoallelic expression. Nat. Rev. Genet. 13, 421–428 (2012).

  90. 90

    Chess, A. Random and non-random monoallelic expression. Neuropsychopharmacology 38, 55–61 (2013).

  91. 91

    Southard-Smith, E. M., Kos, L. & Pavan, W. J. Sox10 mutation disrupts neural crest development in Dom Hirschsprung mouse model. Nat. Genet. 18, 60–64 (1998).

  92. 92

    Paratore, C., Eichenberger, C., Suter, U. & Sommer, L. Sox10 haploinsufficiency affects maintenance of progenitor cells in a mouse model of Hirschsprung disease. Hum. Mol. Genet. 11, 3075–3085 (2002).

  93. 93

    Cook, D. L., Gerber, A. N. & Tapscott, S. J. Modeling stochastic gene expression: implications for haploinsufficiency. Proc. Natl Acad. Sci. USA 95, 15641–15646 (1998). This paper proposes that loss of an allele could have phenotypic consequences owing to increased noise in gene expression.

  94. 94

    López- Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. The hallmarks of aging. Cell 153, 1194–1217 (2013).

  95. 95

    Cai, L., Friedman, N. & Xie, X. S. Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358–362 (2006).

  96. 96

    Ozbudak, E. M., Thattai, M., Kurtser, I., Grossman, A. D. & van Oudenaarden, A. Regulation of noise in the expression of a single gene. Nat. Genet. 31, 69–73 (2002).

  97. 97

    Schwanhäusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011).

  98. 98

    Fatica, A. & Bozzoni, I. Long non-coding RNAs: new players in cell differentiation and development. Nat. Rev. Genet. 15, 7–21 (2014).

  99. 99

    Dekker, J., Marti-Renom, M. A. & Mirny, L. A. Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data. Nat. Rev. Genet. 14, 390–403 (2013).

  100. 100

    Li, J., Ishii, T., Feinstein, P. & Mombaerts, P. Odorant receptor gene choice is reset by nuclear transfer from mouse olfactory sensory neurons. Nature 428, 393–399 (2004).

  101. 101

    Eggan, K. et al. Mice cloned from olfactory sensory neurons. Nature 428, 44–49 (2004).

  102. 102

    Miyanari, Y. & Torres-Padilla, M.-E. Control of ground-state pluripotency by allelic regulation of Nanog. Nature 483, 470–473 (2012).

  103. 103

    Faddah, D. A. et al. Single-cell analysis reveals that expression of Nanog is biallelic and equally variable as that of other pluripotency factors in mouse ESCs. Cell Stem Cell 13, 23–29 (2013).

  104. 104

    Filipczyk, A. et al. Biallelic expression of Nanog protein in mouse embryonic stem cells. Cell Stem Cell 13, 12–13 (2013).

  105. 105

    DeChiara, T. M., Robertson, E. J. & Efstratiadis, A. Parental imprinting of the mouse insulin-like growth factor II gene. Cell 64, 849–859 (1991).

  106. 106

    Garfield, A. S. et al. Distinct physiological and behavioural functions for parental alleles of imprinted Grb10. Nature 469, 534–538 (2011).

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Acknowledgements

The authors are grateful to T. Perlmann and G. Winberg for their comments on the text, and to Q. Deng and D. Ramsköld for comments on the figures.

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Correspondence to Rickard Sandberg.

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The authors declare no competing financial interests.

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Glossary

Mosaic expression

When populations of cells within the organism express different alleles or genotypes, which can give rise to phenotypic patchiness.

Allelic exclusion

The process through which only one allele is expressed and the other is kept silent. Allelic exclusion most often, but not exclusively, refers to monoallelic expression of immunoglobulins in B cells or T cells and olfactory receptor expression in sensory neurons.

Fixed aRME

Clonally stable random monoallelic expression of an autosomal gene.

Dynamic aRME

Transient random monoallelic expression of an autosomal gene, resulting from stochastic allelic transcription.

Allele-biased expression

When the expression output of the two alleles is skewed towards higher expression of one of the parental copies, although both alleles are still expressed (in contrast to strict monoallelic expression).

Allelic dropout

The loss of allelic RNA species due to technical limitations in the sampling technique. This may result in a gene that is actually biallelically transcribed getting a false monoallelic call in the analysis of the data.

Allelic calls

The classification of allelic expression of genes by analysis of expression data. Gene expression can be classed as biallelic, maternal monoallelic, paternal monoallelic or not detected.

Lineage-tracing techniques

Methods that allow tracking of cell lineage from a given time-point, often by introducing or activating a fluorescent marker that is transmitted to each cell during mitotic division.

Split-cell experiments

Control experiments that estimate allelic dropout by dividing the cell lysate into two equal portions, which are independently processed, analysed and checked for coherence in the allelic calls (see Box 1).

RNA-dilution experiments

Control experiments that estimate allelic dropout by diluting bulk RNA in series and sampling for sequencing library preparation at amounts comparable to those of single cells.

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Reinius, B., Sandberg, R. Random monoallelic expression of autosomal genes: stochastic transcription and allele-level regulation. Nat Rev Genet 16, 653–664 (2015). https://doi.org/10.1038/nrg3888

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