Open Access

Functional intronic polymorphisms: Buried treasure awaiting discovery within our genes

Human Genomics20104:284

https://doi.org/10.1186/1479-7364-4-5-284

Published: 1 June 2010

'In Nature's infinite book of secrecy, a little I can read.'

Antony and Cleopatra [Act I, Scene 2], William Shakespeare

Pathological mutations occurring within the extended consensus sequences of exon-intron splice junctions account for ~10 per cent of all inherited lesions logged in The Human Gene Mutation Database (HGMD®; http://www.hgmd.org)[1] and are frequently encountered in mutation screening studies [2]. Mutations residing in other intronic locations (including the canonical branch-point sequence,[3] 5'-YURAY-3'), however, may often go undetected unless patient RNA can be analysed and the mutations in question induce aberrant splicing (eg exon skipping or cryptic splice site utilisation) that is readily distinguishable qualitatively or quantitatively from normal (and/or normal alternative) splicing. Indeed, introns probably represent a substantially larger mutational target than has hitherto been appreciated, on account of their containing a multiplicity of functional elements, including intron splice enhancers and silencers that regulate alternative splicing,[4, 5]trans-splicing elements [6] and other regulatory elements, some of which may be deeply embedded within very large introns [7].

In addition to pathological mutations sensu stricto, introns also harbour functional polymorphisms that can influence the expression of the genes that host them. Some of these intronic variants may also confer susceptibility to disease or otherwise modulate the genotype-phenotype relationship. For the reasons discussed above, it is very likely that such variants will have been seriously under-ascertained to date. Although most of these variants are single nucleotide polymorphisms (SNPs), others may be of the insertion/deletion type [8]. With the advent of genome-wide association studies (GWAS), an increasing number of potentially functional intronic variants are being identified [9]. In the majority of cases, however, it is unclear whether such variants are of direct functional significance, as opposed to simply being in linkage disequilibrium with another (as yet unidentified) functional SNP in the vicinity [10]. Even when GWAS studies deem a newly identified intronic polymorphism to be 'functional', it should be appreciated that such a term may often be ascribed solely on the basis of an observed association between a specific allele and a plasma protein level, enzymatic activity or a clinical/laboratory phenotype -- even although in reality such associations cannot readily distinguish a bona fide functional SNP from a linkage disequilibrium effect.

As has been noted with pathological mutations, the vast majority of known functional intronic polymorphisms are located within the extended consensus sequences of exon-intron splice junctions [2]. Some intronic polymorphic variants do not occur within the splice junctions, however, but nevertheless still act so as to change the splicing phenotype as a consequence of their being located within an intron splice enhancer or branchpoint site, or by activating a cryptic splice site [11, 12]. This is, from a biological point of view, a more interesting category of intronic SNP to study, since the mechanisms by which these variants exert their effects on the splicing phenotype are often unclear and may be quite subtle. In the pages of this issue, Millar et al.[13] report that a SNP, buried deep within intron 4 of the human growth hormone (GH1) gene, is of direct functional significance by virtue of its influence on the expression of this gene. This polymorphism therefore joins the ranks of the hitherto relatively small number of human intronic SNPs located outwith exon-intron splice junctions that have been shown by various methods of in vitro characterisation to be of direct functional significance. Table 1 lists some of the best characterised examples of such functional SNPs, most of which are located at least ~30 base pairs (bp) from the nearest splice site. These SNPs have been shown to influence either the transcriptional activity or the splicing efficiency of their host genes, or instead to alter the expression of alternative transcripts.
Table 1

Selected examples of in vitro characterised human functional intronic polymorphisms located more than ~30 bp from the nearest splice site

Gene

Disease/phenotype

Chromosomal location

Polymorphism, intronic location and dbSNP number

Consequences for gene expression or mRNA splicing

Reference

AGTR2

Predisposition to congenital anomalies of the kidney and urinary tract

Xq22-q23

IVS1, AS, A > G, -29

(rs1403543)

SNP occurs within branchpoint motif and alters splicing efficiency

Nishimura et al. (1999)a

BANK1

Susceptibility to systemic lupus erythematosus

4q23

IVS1, AS, T > C, -43

(rs17266594)

SNP occurs within branchpoint motif and risk allele alters expression of alternative transcripts

Kozyrev et al. (2008)b

CD244

Susceptibility to rheumatoid arthritis

1q23.1

IVS3, AS, T > C, -164

(rs6682654)

Risk allele associated with increased transcriptional activity

Suzuki et al. (2008)c

CD244

Susceptibility to rheumatoid arthritis

1q23.1

IVS5, DS, G > A, +526 (rs3766379)

Risk allele associated with increased transcriptional activity

Suzuki et al. (2008)c

COL1A1

Reduced bone density/osteoporosis

17q21.33

IVS1, AS, G > T, -440

(rs1800012)

SNP occurs within Sp1-binding site; risk allele alters Sp1 binding and transcriptional activity

Mann et al. (2001)d

CXCR3

Variation in immune cell response to chemokine-cytokine signals

Xq13

IVS1, DS, G > A, +234

(rs2280964)

Risk allele associated with reduced CXCR3 gene expression

Choi et al. (2008)e

CYP2D6

Intermediate metaboliser (reduced expression of CYP2D6)

22q13.1

IVS6, DS, G > A, +39

(rs28371725)

Increased level (7.3-fold) of non-functional splice variant transcript lacking exon 6 and reduced level (2.9-fold) of functional transcript

Toscano et al.

(2006)f

DRD2

Reduced DRD2 expression

11q22-q23

IVS1, DS, A > G, +3850

(rs2734836)

Risk allele associated with increased binding of transcriptional repressor (Freud-1) leading to reduced DRD2 expression

Rogaeva

et al. (2007)g

DRD2

Reduced DRD2 expression

11q23

IVS6, AS, C > A, -83

(rs 1076560)

Risk allele alters expression of alternative transcripts

Zhang et al.

(2007)h

F2

Elevated prothrombin level/thrombosis

11p11-q12

IVS13, AS, A > G, -59

Risk allele influences splicing efficiency

von Ahsen & Oellerich (2004)i

FGFR2

Susceptibility to breast cancer

10q26

IVS2, DS, T > C,+ 12912

(rs2981578)

Risk allele alters binding affinity for transcription factors Oct-1/Runx2, leading to increased FGFR2 expression

Meyer et al.

(2008)j

FOXP3

Susceptibility to psoriasis

Xp11.23

IVS1, DS, A > C, +2882

(rs3761548)

Risk allele causes loss of binding of E47 and c-Myb, leading to reduced FOXP3 transcription

Shen et al.

(2010)k

GFPT1

Reduced GFPT1 expression

2p13

IVS1, DS, T > C, +36

(rs6720415)

SNP occurs within GC box and risk allele decreases transcriptional activity

Kunika et al.

(2006)[1]

GSK3B

Risk of Parkinson's disease

3q13.3

IVS5, AS, T > C, -157

(rs6438552)

Risk allele associated with increased level of GSK3B transcripts lacking exons 9 and 11

Kwok et al.

(2005)m

IRF4

Risk of childhood acute lymphoblastic leukaemia in males

6p25-p23

IVS4, DS, C > T, +386

(rs12203592)

Risk allele increases IRF4 promoter activity/expression

Do et al.

(2010)n

LTA

Susceptibility to myocardial infarction

6p21.3

IVS1, AS, G > A, -198

(rs909253)

Risk allele associated with increased transcriptional activity

Ozaki et al.

(2002)o

NLRP3

Susceptibility to food-induced anaphylaxis

1q44

IVS7, AS, C > T, -202

(rs4612666)

Risk allele increases enhancer activity by 20%

Hitomi et al.

(2009)p

SCG3

Association with obesity

15q21

IVS1, DS, G > A, +190

(rs16964476)

Risk allele alters transcriptional activity

Tanabe et al.

(2007)q

TH

Risk of essential tension

11p15.5

IVS12, DS, T > C, +127

(rs2070762)

Risk allele associated with increased transcriptional activity

Wang et al.

(2008)r

USF1

Association with familial combined hyperlipidaemia

1q22-q23

IVS7, AS, G > A, -100

(rs2073658)

SNP alleles exhibit differential binding to nuclear proteins.

USF1-regulated genes are differentially regulated, depending on the identity of the rs2073658 allele

Naukkarinen et al. (2005)s

Naukkarinen et al. (2009)t

Abbreviations: AS, acceptor splice site; DRD2, dopamine D2 receptor; DS, donor splice site; IVS, intron (number) Nucleotide numbering relative to specified splice site.

rs numbers are provided courtesy of dbSNP http://www.ncbi.nlm.nih.gov/projects/SNP/. For the sake of simplicity, only SNPs have been included in Table 1 (thus, for example, functional intronic microsatellite polymorphisms would require a separate treatment).

References to table

a. Nishimura, H., Yerkes, E., Hohenfellner, K., Miyazaki, Y. et al. (1999), 'Role of the angiotensin type 2 receptor gene in congenital anomalies of the kidney and urinary tract, CAKUT, of mice and men', Mol. Cell Vol. 3, pp. 1-10.

b. Kozyrev, S.V., Abelson, A.K., Wojcik, J., Zaghlool, A. et al. (2008), 'Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus', Nat. Genet. Vol. 40, pp. 211-216.

c. Suzuki, A., Yamada, R., Kochi, Y., Sawada, T. et al. (2008), 'Functional SNPs in CD244 increase the risk of rheumatoid arthritis in a Japanese population', Nat. Genet. Vol. 40, pp. 1224-1229.

d. Mann, V., Hobson, E.E., Li, B., Stewart, T.L et al. (2001), 'A COL1A1 Sp1 binding site polymorphism predisposes to osteoporotic fracture by affecting bone density and quality', J. Clin. Invest. Vol. 107, pp. 899-907.

e. Choi, J.W., Park, C.S., Hwang, M., Nam, H.Y. et al. (2008), 'A common intronic variant of CXCR3 is functionally associated with gene expression levels and the polymorphic immune cell responses to stimuli', J. Allergy Clin. Immunol. Vol. 122, pp. 1119-1126.

f. Toscano, C., Klein, K., Blievernicht, J., Schaeffeler, E. et al. (2006), 'Impaired expression of CYP2D6 in intermediate metabolizers carrying the *41 allele caused by the intronic SNP 2988G > A: Evidence for modulation of splicing events', Pharmacogenet. Genomics Vol. 16, pp. 755-766.

g. Rogaeva, A., Ou, X.M., Jafar-Nejad, H., Lemonde, S. et al. (2007), 'Differential repression by freud-1/CC2D1A at a polymorphic site in the dopamine-D2 receptor gene'. J. Biol. Chem. Vol. 282, pp. 20897-20905.

h. Zhang, Y., Bertolino, A., Fazio, L., Blasi, G. et al. (2007), 'Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory', Proc. Natl. Acad. Sci. USA Vol. 104, pp. 20552-20557.

i. von Ahsen, N. and Oellerich, M. (2004), 'The intronic prothrombin 19911A > G polymorphism influences splicing efficiency and modulates effects of the 20210G > A polymorphism on mRNA amount and expression in a stable reporter gene assay system', Blood Vol. 103, pp. 586-593.

j. Meyer, K.B., Maia, A.T., O'Reilly, M., Teschendorff, A.E. et al. (2008), 'Allele-specific up-regulation of FGFR2 increases susceptibility to breast cancer', PLoS Biol. Vol. 6, p. e108.

k. Shen, Z., Chen, L., Hao, F., Wang, G. et al. (2010), 'Intron-1 rs3761548 is related to the defective transcription of Foxp3 in psoriasis through abrogating E47/c-Myb binding', J. Cell. Mol. Med. Vol. 14, pp. 226-241.

l. Kunika, K., Tanahashi, T., Kudo, E., Mizusawa, N. et al. (2006), 'Effect of þ36T > C in intron 1 on the glutamine: fructose-6-phosphate amido-transferase 1 gene and its contribution to type 2 diabetes in different populations', J. Hum. Genet. Vol. 51, pp. 1100-1109.

m. Kwok, J.B., Hallupp, M., Loy, C.T., Chan, D.K. et al. (2005), 'GSK3B polymorphisms alter transcription and splicing in Parkinson's disease', Ann. Neurol. Vol. 58, pp. 829-839.

n. Do, T.N., Ucisik-Akkaya, E., Davis, C.F., Morrison, B.A. et al. (2010), 'An intronic polymorphism of IRF4 gene influences gene transcription in vitro and shows a risk association with childhood acute lymphoblastic leukemia in males', Biochim. Biophys. Acta Vol. 1802, pp. 292-300.

o. Ozaki, K., Ohnishi, Y., Iida, A., Sekine, A. et al. (2002), 'Functional SNPs in the lymphotoxin-a gene that are associated with susceptibility to myocardial infarction', Nat. Genet. Vol. 32, pp. 650-654.

p. Hitomi, Y., Ebisawa, M., Tomikawa, M., Imai, T. et al. (2009), 'Associations of functional NLRP3 polymorphisms with susceptibility to food-induced anaphylaxis and aspirin-induced asthma', J. Allergy Clin. Immunol. Vol. 124, pp. 779-785.

q. Tanabe, A., Yanagiya, T., Iida, A., Saito, S. et al. (2007), 'Functional single-nucleotide polymorphisms in the secretogranin III (SCG3) gene that form secretory granules with appetite-related neuropeptides are associated with obesity', J. Clin. Endocrinol. Metab. Vol. 92, pp. 1145-1154.

r. Wang, L., Li, B., Lu, X., Zhao, Q. et al. (2008), 'A functional intronic variant in the tyrosine hydroxylase (TH) gene confers risk of essential hypertension in the Northern Chinese Han population', Clin. Sci. Vol. 115, pp. 151-158.

s. Naukkarinen, J., Gentile, M., Soro-Paavonen, A., Saarela, J. et al. (2005), 'USF1 and dyslipidemias: Converging evidence for a functional intronic variant', Hum. Mol. Genet. Vol. 14, pp. 2595-2605.

t. Naukkarinen, J., Nilsson, E., Koistinen, H.A., Söderlund, S. et al. (2009), 'Functional variant disrupts insulin induction of USF1: Mechanism for USF1-associated dyslipidemias', Circ. Cardiovasc. Genet. Vol. 2, pp. 522-529.

How should we go about increasing the number of identified functional intronic polymorphisms? One approach would be to employ exon-tiling microarrays to perform genome-wide scans to identify intronic SNPs responsible for inter-individual differences in the splicing phenotype [11, 14, 15]. Since currently available bioinformatics tools are inadequate to the task of predicting splicing consequences,[14] however, all SNPs identified in this way would have to be further validated using mini-gene constructs to determine the resulting splicing phenotype [14]. One feature that might prove helpful in identifying intronic SNPs is that such variants are often located within gene regions that are characterised by a reduced level of genetic variation [16].

Precisely because we invariably adopt a gene-centric approach to screening introns for functional polymorphisms, we should be wary of the existence of overlapping genes, a not infrequent occurrence in our complex genome. Thus, for example, the functional SNP rs4988235, located 13.9 kilobases upstream of the lactase (LCT) gene and associated with adult-type hypolactasia, actually resides deep within intron 13 of the minichromosome maintenance complex component 6 (MCM6) gene [1719]. In addition, since disease-associated intronic SNPs that play a role in long-range gene regulation have also recently been identified,[20, 21] we should be aware that some SNPs may influence the expression of remote genes at distance, rather than the expression of those genes which actually host them. These caveats notwithstanding, new techniques such as chromosome conformational capture [22] and chromatin immunoprecipitation followed by deep sequencing (ChIP-seq)[23] promise greatly to increase the number of functional intronic polymorphisms identified, thereby potentially pinpointing the locations of a whole new lexicon of intron-located regulatory elements, which will increase our understanding of intron structure and function.

Authors’ Affiliations

(1)
Institute of Medical Genetics, School of Medicine Cardiff University

References

  1. Stenson PD, Mort M, Ball EV, Howells K, et al: 'The Human Gene Mutation Database: 2008 update'. Genome Med. 2009, 1: 13-10.1186/gm13.PubMed CentralView ArticlePubMedGoogle Scholar
  2. Krawczak M, Thomas NS, Hundrieser B, Mort M, et al: 'Single base-pair substitutions in exon-intron junctions of human genes: Nature, distribution, and consequences for mRNA splicing'. Hum Mutat. 2007, 28: 150-158. 10.1002/humu.20400.View ArticlePubMedGoogle Scholar
  3. Královicová J, Lei H, Vorechovský I: 'Phenotypic consequences of branch point substitutions'. Hum Mutat. 2006, 27: 803-813. 10.1002/humu.20362.View ArticlePubMedGoogle Scholar
  4. Wang X, Wang K, Radovich M, Wang Y, et al: 'Genome-wide prediction of cis-acting RNA elements regulating tissue-specific pre-mRNA alternative splicing'. BMC Genomics. 2009, 10 (Suppl 1): S4-10.1186/1471-2164-10-S1-S4.PubMed CentralView ArticlePubMedGoogle Scholar
  5. Tress ML, Martelli PL, Frankish A, Reeves GA, et al: 'The implications of alternative splicing in the ENCODE protein complement'. Proc Natl Acad Sci USA. 2007, 104: 5495-5500. 10.1073/pnas.0700800104.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Gingeras TR: 'Implications of chimaeric non-co-linear transcripts'. Nature. 2009, 461: 206-211. 10.1038/nature08452.PubMed CentralView ArticlePubMedGoogle Scholar
  7. Solis AS, Shariat N, Patton JG: 'Splicing fidelity, enhancers, and disease'. Front Biosci. 2008, 13: 1926-1942. 10.2741/2812.View ArticlePubMedGoogle Scholar
  8. Wilkins JM, Southam L, Mustafa Z, Chapman K, et al: 'Association of a functional microsatellite within intron 1 of the BMP5 gene with susceptibility to osteoarthritis'. BMC Med Genet. 2009, 10: 141-10.1186/1471-2350-10-141.PubMed CentralView ArticlePubMedGoogle Scholar
  9. Manolio TA, Collins FS, Cox NJ, Goldstein DB, et al: 'Finding the missing heritability of complex diseases'. Nature. 2009, 461: 747-753. 10.1038/nature08494.PubMed CentralView ArticlePubMedGoogle Scholar
  10. McCauley JL, Kenealy SJ, Margulies EH, Schnetz-Boutaud N, et al: 'SNPs in multi-species conserved Sequences (MCS) as useful markers in association studies: A practical approach'. BMC Genomics. 2007, 8: 266-10.1186/1471-2164-8-266.PubMed CentralView ArticlePubMedGoogle Scholar
  11. Kwan T, Benovoy D, Dias C, Gurd S, et al: 'Genome-wide analysis of transcript isoform variation in humans'. Nat Genet. 2008, 40: 225-231. 10.1038/ng.2007.57.View ArticlePubMedGoogle Scholar
  12. Coulombe-Huntington J, Lam KC, Dias C, Majewski J: 'Fine-scale variation and genetic determinants of alternative splicing across individuals'. PLoS Genet. 2009, 5: e1000766-10.1371/journal.pgen.1000766.PubMed CentralView ArticlePubMedGoogle Scholar
  13. Millar DS, Horan M, Chuzhanova NA, Cooper DN: 'Characterisation of a functional intronic polymorphism in the human growth hormone (GH1) gene'. Hum Genomics. 2010, 4: 289-301.PubMed CentralView ArticlePubMedGoogle Scholar
  14. Hull J, Campino S, Rowlands K, Chan M-S, et al: 'Identification of common genetic variation that modulates alternative splicing'. PLoS Genet. 2007, 3: e99-10.1371/journal.pgen.0030099.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Nembarware V, Lupindo B, Schouest K, Spillane C, et al: 'Genome-wide survey of allele-specific splicing in humans'. BMC Genomics. 2008, 9: 265-10.1186/1471-2164-9-265.View ArticleGoogle Scholar
  16. Lomelin D, Jorgenson E, Risch N: 'Human genetic variation recognizes functional elements in noncoding sequence'. Genome Res. 2010, 20: 311-319. 10.1101/gr.094151.109.PubMed CentralView ArticlePubMedGoogle Scholar
  17. Enattah NS, Sahi T, Savilahti E, Terwilliger JD, et al: 'Identification of a variant associated with adult-type hypolactasia'. Nat Genet. 2002, 30: 233-237. 10.1038/ng826.View ArticlePubMedGoogle Scholar
  18. Olds LC, Sibley E: 'Lactase persistence DNA variant enhances lactase promoter activity in vitro: Functional role as a cis regulatory element'. Hum Mol Genet. 2003, 12: 2333-2340. 10.1093/hmg/ddg244.View ArticlePubMedGoogle Scholar
  19. Lewinsky RH, Jensen TG, Møller J, Stensballe A, et al: 'T-13910 DNA variant associated with lactase persistence interacts with Oct-1 and stimulates lactase promoter activity in vitro'. Hum Mol Genet. 2005, 14: 3945-3953. 10.1093/hmg/ddi418.View ArticlePubMedGoogle Scholar
  20. Ragvin A, Moro E, Fredman D, Navratilova P, et al: 'Long-range gene regulation links genomic type 2 diabetes and obesity risk regions to HHEX, SOX4, and IRX3'. Proc Natl Acad Sci USA. 2010, 107: 775-780. 10.1073/pnas.0911591107.PubMed CentralView ArticlePubMedGoogle Scholar
  21. Jowett JB, Curran JE, Johnson MP, Carless MA, et al: 'Genetic variation at the FTO locus influences RBL2 gene expression'. Diabetes. 2010, 59: 726-732. 10.2337/db09-1277.PubMed CentralView ArticlePubMedGoogle Scholar
  22. Dostie J, Dekker J: 'Mapping networks of physical interactions between genomic elements using 5C technology'. Nat Protoc. 2007, 2: 988-1002. 10.1038/nprot.2007.116.View ArticlePubMedGoogle Scholar
  23. Visel A, Blow MJ, Li Z, Zhang T, et al: 'ChIP-seq accurately predicts tissue-specific activity of enhancers'. Nature. 2009, 457: 854-858. 10.1038/nature07730.PubMed CentralView ArticlePubMedGoogle Scholar

Copyright

© Henry Stewart Publications 2010

Advertisement