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Blackwell Publishing Ltd.Oxford, UKGTCGenes to Cells1356-9597© Blackwell Publishing LtdApril 200284Original ArticlePolymorphisms in the BAT1 promoterA M-L Wong et al.

Alleles of the proximal promoter of BAT1, a putative anti-inflammatory gene adjacent to the TNF cluster, reduce transcription on a disease-associated MHC haplotype

Agnes M.-L. Wong*, Richard J. N. Allcock, Karey Y. M. Cheong, Frank T. Christiansen and Patricia Price

Department of Pathology, University of Western Australia, Nedlands 6009, Western Australia; and Department of Clinical Immunology and Biochemical Genetics, Royal Perth Hospital, Perth 6001, Western Australia

Abstract

Background

:

BAT1 belongs to the DEAD-box familyof proteins, and is encoded in the central region ofthe MHC, a region containing genes affectingimmunopathological disorders including Type 1 dia-betes. We showed that BAT1 can reduce inflamma-tory cytokine production, supporting its candidacyas a disease gene. Here we examined the proximalpromoter region of

BAT1

.

Results

:

Ten single nucleotide polymorphisms wereidentified in

≈≈≈≈

1.4 kb of sequence, defining at leastseven alleles. Sections of the

BAT1

promoter regionwere amplified from cells homozygous for the MHChaplotypes associated with susceptibility (

HLA-A1

,

B8

,

DR3

; 8.1 haplotype) and resistance (

HLA-A3

,

B7

,

DR15

; 7.1 haplotype) to diabetes and cloned into

a promoter-less luciferase-encoding plasmid. Jurkatcells transiently transfected with fragments from the8.1 haplotype exhibited a lower luciferase activitythan those transfected with fragments from the7.1 haplotype, indicating reduced transcription.The effect was clearest with the 520 bp immediatelyupstream of the transcriptional start site. Electro-phoretic mobility shift assays using oligonucleotidesspanning polymorphic sites within the 520 bp (prox-imal) promoter fragment showed haplotype-specificbinding of nuclear proteins.

Conclusions

:

In view of the anti-inflammatory role of

BAT1

, reduced production on a disease-associatedhaplotype constitutes a novel and self-consistentmodel for the effect of central MHC genes on disease.

Introduction

BAT1 is a member of the DEAD-box family of RNA-dependent ATPases, encoded in the central (class III)region of the major histocompatibility complex (MHC)on the short arm of human chromosome 6 (Spies

et al

.1989). BAT1 has been identified as a cellular splicingfactor, RAF-2p48/NPI-5/BAT1/UAP56, which is requiredfor the replication and translation of influenza virusRNA (Momose

et al

. 2001). We have shown that

BAT1

may encode a negative regulator of the inflammatorycytokines TNF-

α

, IL-1 and IL-6 (Allcock

et al

. 2001)and may therefore influence immunological processesincluding the development of immunopathologicaldiseases. A role for

BAT1

in diseases affected by MHChaplotypes is consistent with epidemiological studies

showing that unidentified genes in the central MHCaffect numerous immunopathological conditions includ-ing Type 1 diabetes (Hanifi Moghaddam

et al

. 1998;Cheong

et al

. 2001), IgA deficiency (Price

et al

. 1999),myasthenia gravis (Price

et al

. 1999), multiple sclerosis(Allcock

et al

. 1999a), rheumatoid arthritis (Ota

et al

.2001) and ulcerative colitis (de la Concha

et al

. 2000).Analyses based on haplotypic single nucleotide polymor-phisms (SNPs) and polymorphic microsatellites, suggestthat a gene able to amplify the effect of

HLA-DR3

ondiabetes lies between

TNFA

and

HLA-B

(Cheong

et al

.2001). This region spans only five expressed genes,including

BAT1

, so it is timely to determine whether

BAT1

has haplotypic functional polymorphisms thatcould affect disease susceptibility. We have previouslyreported that no exonic

BAT1

polymorphisms differen-tiate the disease associated 8.1 ancestral haplotype (

AH

;

HLA-A1

,

B8

,

DR3

) from the resistant 57.1 AH (

HLA-A1

,

B57

,

DR7

) and subsequent analyses of exonic

Communicated by

: Thomas Graf*

Correspondence

: E-mail: ajessiew@cyllene.uwa.edu.au

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et al.

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404

sequence revealed no non-synonomous polymorphisms(unpublished results). A polymorphism was found by res-triction fragment length polymorphism (RFLP) analysis,but was localized to intron 10 (Allcock

et al

. 1999b).Here we asked whether polymorphisms in the

BAT1

promoter region may affect expression of this gene andhence disease susceptibility. We sequenced overlappingpolymerase chain reaction (PCR) products from Epstein–Barr virus (EBV) transformed human B-cell lines repre-senting haplotypes that are highly conserved and/or havewell described disease association (Price

et al

. 1999). Wehave previously used this strategy to identify SNP in the

IKBL

(

NFKBL

) promoter (Allcock

et al

. 2000). Ten sin-gle nucleotide polymorphisms were identified in a

≈

1.4kilobase (kb) sequence upstream of the

BAT1

transcrip-tional start site. The combinations of polymorphismsdefine at least seven promoter alleles of

BAT1

.Functional analyses of

BAT1

promoter fragmentsfrom MHC haplotypes associated with susceptibility(8.1AH) and resistance (7.1AH;

HLA-A3

,

B7

,

DR15

) toType 1 diabetes were undertaken to determine whetherthe polymorphisms affect transcription. Fragments ofthe

BAT1

promoter amplified from cell lineshomozygous for the 8.1AH or 7.1AH were cloned intoa promoter-less luciferase expression vector and trans-fected into Jurkat T-cells. The relative transcriptionalactivity was in all cases lower with the

BAT1

promoterfragments from the 8.1AH compared to the correspond-ing 7.1AH fragments. The largest differences in luciferaseactivity between the two alleles were seen with con-structs containing the first

≈

500 bp upstream of thetranscriptional start site. Furthermore, we demonstratehaplotypic differences in the nuclear proteins bindingaround two polymorphic sites within this fragment.

Together with our previous studies, these data suggestthat the cells of the diabetogenic 8.1 haplotype maygenerate less BAT1 protein than cells from the 7.1 haplo-type, resulting in an increased pro-inflammatory cyto-kine production (Allcock

et al

. 2001). Thus, BAT1promoter polymorphisms may accentuate an individual’srisk of diabetes or other immunopathological diseases.Clearly, BAT1 provides a self-consistent explanation forwhy the 8.1AH potentiates diabetes more effectivelythan HLA-DR3 alone (Cheong

et al

. 2001).

Results

The sequence upstream of the BAT1 gene is polymorphic

To identify polymorphisms in the

BAT1

promoterregion, 1374 bp of the DNA upstream of the

BAT1

transcription start site was sequenced from 13 cell lines.The cell lines covered 10 ancestral haplotypes (AH) rep-resenting commonly conserved haplotypes, predomi-nantly of Caucasian origin (Table 1). The sequencingstrategy utilized three overlapping PCR products per cellline, including both forward and reverse passes, giving 4–6-fold redundancy. Alignment of these sequences revealednine SNPs (Table 2). Five SNPs occurred in the first

≈

500 bpupstream of the transcription start site, whilst the remainingfour were clustered between position

−

1101 bp and

−

1178 bp. On this basis, a further 34 cell lines containingadditional ancestral haplotypes were then sequencedusing a single pass sequencing strategy (Table 1). A fur-ther polymorphism was identified at position

−

244 bpinvolving the insertion of a guanine (G) residue. As mostchosen cell lines were homozygous, seven distinct

BAT1

promoter alleles could then be defined (Table 2).

The BAT1 promoter regions of the 7.1 and 8.1 AH have different transcriptional activity

Three promoter fragments of 520 bp, 1034 bp and1400 bp upstream of

BAT1

(spanning

−

1374 bp to+26 bp) were amplified from cell lines homozygous forthe 7.1 AH and the 8.1 AH (

BAT1

alleles 1 and 2,respectively; Table 2). The resulting PCR products wereligated into the multiple cloning site of a promoter-lessluciferase-encoding plasmid (pGL3-Enhancer, Promega).

Reporter activity with the allele 1 (7.1 AH)

BAT1

promoter fragments was approximately twofold higherthan with the SV40 promoter (Fig. 1) demonstrating thestrong transcriptional activity in Jurkat cells. Moreover,reporter gene expression was observed using all threefragments of the

BAT1

promoter from allele 1 and allele2, suggesting that the first

≈

500 bp upstream of the

BAT1

transcriptional start site is sufficient for transcrip-tion in Jurkat cells. Reporter activity induced by allele 2was lower than that of allele 1 in all cases (1400 bp,

P

=0.03; 1034 bp,

P

= 0.13; and 520 bp,

P

= 0.0002). As thelargest and most significant difference in luciferase activ-ity between the two alleles (approximately twofold) wasseen with the 520 bp fragment, further studies addressedthe SNPs within this region.

The haplotypic differences in promoter activity areunlikely to be due to artefacts generated by the plasmidDNA for several reasons. Firstly, all the DNA concentra-tions were measured spectrophotometrically and con-firmed by gel electrophoresis and ethidium bromidestaining. Secondly, all the promoter constructs were re-sequenced in both forward and reverse directions to con-firm that the construct contained the identified SNPsand no spurious mutations. Thirdly, luciferase activity for

Polymorphisms in the BAT1 promoter

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Table 1

BAT1

and

TNF

typing of conserved ancestral haplotypes

Table 2

Distribution of

BAT1

alleles in conserved ancestral haplotypes

AH nHLA-A

HLA-B

BAT1 allele

TNF a,b

TNFA-308

HLA-DRB1

Workshop numbers

7.1 6 3 7 1 11,4 1 1501 9013*, 9017, 9081, 9082*, 9083, 1000407.2 3 24 7 1 11,4 1 0101 9001, 100042Z, 100043X8.1 5 1 8 2 2,3 2 0301 9022*, 9023, 9086, 9087,100044D*13.1 1 30 13 6 7,4 1 07011 904818.1 1 25 18 4 10,4 1 1501 9008*18.2 3 30 18 4 1,5 1/2 0301 9018*, 9019, 908535.1 2 1 35 2 6,5 1 1104 9041*35.2 1 11 35 5 2,1 1 0101 9006*35.x 1 24 35 4 5,5 1 1103 904238.1 1 26 38 4 10,4 1 0402 902642.1 1 30/68 42 2 6,5 1 0302 902144.1 1 2 44 2 6,5 1 0401 9090*44.2 1 29 44 6 7,4 1 0701 905144.2/44.x 1 29 44 2/6 6,5/7,4 1 0401/1401 9027*44.2/58.x 1 28 44/58 2/6 – 1/2 1301/07 100108 V*44.4 1 33 44 2 6,5 1 1302 905344.x 1 29 44 6 8,4 1 07011 905044.x 1 2 44 5 2,1 1 1101 903644.x 1 2 44 2 7,5 1 1401 905444.x 1 32 44 7 4,5 2 1302 906346.1 2 2 46 2 6,5 1 08032 9066,100152Z47.1 1 3 47 4 10,4 1 0701 904754.1 1 24 54 4 11,4 1 0405 100062T57.1 2 1 57 3 2,5 1 07 9052*, 100083 J*58.1 2 33 58 2 2,3 2 0301 100086C, 100087 A60.1 1 31 60 1 11,4 1 0404 909862.1 2 2 62 5 2,1 1 04011 9031, 90327.1/44.1 1 3 7/44 1/2 6,5/11,4 1 0401/1501 100055Q7.1/8.1 1 1/3 7/8 1/2 2,3/11,4 1/2 0301/1501 Bone marrow donor44.2 — 29 44 6 7,4 1 0701

GenBank

accession no. AC004181

*Workshop cell lines sequenced using three overlapping PCR products. Other cell lines were typed by single pass sequencing spanning the SNPs defined in Table 2.

BAT1*Allele

Ancestral Haplotype

Nucleotide Position†

−

22

−210 −223 −244 −245 −348 −1101 −1167 −1176 −1178

1 7.1, 7.2, 60.1 G C C — G T A T T G2 8.1, 35.1, 44.1, 42.1, 44.4, 46.1, 58.1 C C C — G C G T G C3 57.1 G C A — G C G C T G4 18.1, 18.2, 38.1, 47.1, 54.1 G C C — G C G C T G5 35.2, 62.1 G A C — G C G T T G6 44.2, 13.1 G C C — C C G C T G7 44.x C C C G G C G T G C

*Sequences from HLA homozygous cell lines were aligned and compared identifying 10 SNPs, defining seven BAT1 alleles.†Positions are defined relative to the BAT1 transcriptional start site (GenBank accession no. AC004181). Nucleotides in bold indicate the less common allele.

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each preparation was measured using increasing amountsof DNA (0.5–1.5 µg DNA per transfection) to confirmthe linearity of expression. Titrations were done for allplasmid preparations prior to the selection of 1 µg DNAfor comparative studies. Finally, each construct was testedusing three separate DNA preparations and assessedin at least two separate experiments with duplicateor triplicate samples at multiple time points for eachtransfection. A similar trend was seen in each individualexperiment and in the combined data (Fig. 1).

Differential binding of nuclear proteins at the −−−−22 or −−−−348 position

As the largest difference in reporter activity betweenallele 1 (7.1 AH) and allele 2 (8.1 AH) was seen with the520 bp promoter fragment (Fig. 1), the SNPs likely toaffect BAT1 activity must include positions −22 bp and/or −348 bp. Alleles 1 and 2 do not differ at positions−210 bp, −223 bp, −244 bp or −245 bp (Table 2).

Electrophoretic mobility shift assays (EMSAs) wereperformed using 20 bp oligonucleotides spanning thepolymorphic site at position −22 bp or −348 bp, todetermine if they bind transcription factors and if thepolymorphisms affect binding (Fig. 2).

Double-stranded 32P-labelled oligonucleotides repre-senting the −31 to −12 bp and −358 to −339 bp regionsof the BAT1 promoter alleles 1 and 2, were incubatedwith or without 3 µg Jurkat cell nuclear extracts andanalysed on a 6% polyacrylamide/TBE gel (Fig. 2). Nobands were visible in lanes containing the probes withoutnuclear extracts (Fig. 2, lanes 1, 3, 5 and 7). The BAT1–22*G and BAT1–22*C oligonucleotides each formedfour major protein complexes with distinct migrationpatterns (lanes 2 and 4). Significantly, Band A was moreintense with BAT1–22*G (allele 1, 7.1 AH) than with

Figure 1 Transient reporter expression from the BAT1 promoterfragments in Jurkat cells. The BAT1 promoter constructs derivedfrom allele 1 (7.1 haplotype) or allele 2 (8.1 haplotype) weretransfected together with the pRL-SV40 renilla luciferase controlplasmid into Jurkat T-cells. A negative control vector (pGL3-enhancer; Promega, USA) and a positive control vector with anSV40 promoter (pGL3-control; Promega, USA) were included.Transfected Jurkat cells were harvested 24 h after transfection andassayed for firefly and renilla luciferase activities, using Promega’sDual Luciferase Assay. The firefly luciferase activity was divided bythe renilla activity to correct for different transfection efficiencies.Each bar represents the mean (± SEM) of the ratios fromindependent experiments. Numbers in parentheses indicates thenumber of independent experiments, each with duplicate ortriplicate samples. Significant differences between each BAT1allele 2 construct and the respective (same size) BAT1 allele 1construct are indicated: *P < 0.05, **P < 0.05 or ***P < 0.005.

Figure 2 EMSA of double-stranded γ32P-labelled oligonucle-otides representing the −31 to −12 bp and −358 to −339 bpregions of the BAT1 promoter alleles 1 and 2. Probes wereincubated with (+) or without (–) 3 µg Jurkat T-cell nuclearextracts and analysed on a 6% polyacrylamide/TBE gel. Lanes 1,3, 5 and 7 contain the probes without nuclear extracts. Lanes 2 and4 demonstrate the binding of nuclear extract complexes tooligonucleotides spanning the BAT1–22 region. Lanes 6 and 8demonstrates binding of nuclear extract complexes tooligonucleotides spanning the BAT1–348 region. Major bands areindicated with arrows and labelled (A–G). Specific bands(competed with self; see Fig. 3) are capitalized.

Polymorphisms in the BAT1 promoter

© Blackwell Publishing Limited Genes to Cells (2003) 8, 403–412 407

BAT1-22*C (allele 2, 8.1 AH), whilst Band D was ofsimilar intensity with both probes. Bands b and c werelater shown to be nonspecific (see Fig. 3a).

The BAT1–348*T (allele 1, 7.1 haplotype) probeyielded three bands, designated Bands e, f and G (Fig. 2;lane 6). Interestingly, Band G was not detected with theBAT1–348*C (allele 2, 8.1 AH) probe, suggesting aspecificity for the T allelic form (allele 1, 7.1 haplotype).Bands e and f were nonspecific (see Fig. 3b).

The specificity of binding to the BAT1–22 probes wasassessed in competition assays using 50-, 100- or 200-fold molar excess of unlabelled BAT1–22*G or BAT1–22*C oligonucleotides (Fig. 3a). Unlabelled BAT1–22*Greduced binding of the Band A proteins to labelled BAT1–22*G (Fig. 3a, lanes 2–4), whilst unlabelled BAT1–22*C(Fig. 3a, lanes 5–7) was far less effective, demonstratingthe specificity of complex A for the G allelic form (allele1, 7.1 haplotype). Both cold probes competed for BandD, suggesting that the binding is not haplotypic. Bands band c were either not present or not eliminated by eithercold probe, suggesting non-specific interactions.

Similar competition studies were performed usingBAT1–348*T and BAT1–348*C. Competition oflabelled BAT1–348*T with unlabelled BAT1–348*Toligonucleotide (Fig. 3b, lanes 2–4) but not unlabelledBAT1–348*C (lanes 5–7) decreased the intensity of BandG, suggesting that the DNA–protein interaction of thiscomplex is specific for BAT1–348*T (allele 1, 7.1 AH).Bands e and f were either not present or not eliminatedby either cold probe, suggesting non-specific interactions.

Predicted effects of SNPs on transcription factor binding to BAT1 allele 1 and allele 2

Transcription factors likely to bind differentially at ornear the SNPs in the BAT1 promoter were identifiedusing MatInspector software (Quandt et al. 1995) witha core and matrix similarity cut-off value of 0.8. Threetranscription factors predicted to bind differentiallyaround position −22 bp are shown in Table 3. No tran-scription factors likely to bind differentially at −348 bpwere predicted using this software.

Figure 3 The specificity of Jurkat T-cellnuclear proteins binding to the regionencompassing the BAT1 promoter SNPswere assessed in gel-shift competitionassays. Total nuclear extracts were incubatedwith the probe alone (lanes 1 and 8) or witha 50-, 100- or 200-fold molar excess ofunlabelled self (lanes 2–4; lanes 9–11) orthe alternative allelic competitor (lanes5–7; lanes 12–14). Nuclear proteinswere then incubated with the labelledoligonucleotides encompassing thefollowing SNP: (A) BAT1–22*G orBAT1–22*C; (B) BAT1–348*T or BAT1–348*C, before loading on to a 6% non-denaturing polyacrylamide gel. Majorbands identified are indicated with arrows(A–H).

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DiscussionThe identification of genes responsible for the associa-tion between the 8.1 AH and a range of autoimmune/immunopathological diseases has been complicated bythe conservation of this haplotype. Therefore, it is helpfulto characterize candidate genes within the region impli-cated. Recent mapping by SNP and microsatellite typ-ing suggests that the region between the TNF cluster andHLA-B contains a disease susceptibility allele on the 8.1AH (Cheong et al. 2001). In addition to BAT1, thisregion includes only four other known genes; the MICAand MICB genes, which encode stress-induced antigensthat interact with NKG2D on the surface of some NKand T cells (Li et al. 2001), AT6PG, which has no knownfunction and IKBL, which encodes a protein withankyrin repeat elements consistent with a role inprotein : protein interactions (Allcock et al. 2000). Nodirect role for these genes in immunopathology has beenestablished.

Previous studies revealed no exonic polymorphismswithin the BAT1 gene, suggesting that the amino acidsequence of BAT1 is identical across the haplotypesstudied (unpublished data). However, anti-sense studiesrevealed an effect of BAT1 on pro-inflammatory cytokineproduction. Therefore, polymorphisms that affect BAT1expression could affect the production of these cytokinesand contribute to disease susceptibility. Here we exam-ined 1374 bp upstream of the BAT1 transcription startsite and identified 10 SNPs by sequencing overlappingPCR products derived from a number of homozygouscell lines representing the most commonly conservedCaucasian MHC haplotypes. The use of cell lines that arehomozygous for defined haplotypes enabled us to iden-tify seven stable inherited BAT1 promoter alleles repre-sented in the Caucasian population. African and Asianpopulations may carry additional polymorphisms.

We utilized a dual-luciferase reporter system to eval-uate the transcriptional activity of the BAT1 promoter.

Transfected cells containing BAT1 promoter fragmentsfrom the 8.1 AH (allele 2) consistently exhibited a lowerreporter activity compared to the 7.1 AH (allele 1). Sincethe 7.1 AH and 8.1 AH are associated with resistanceand susceptibility to Type 1 diabetes, respectively, theobserved effects may have significant implications forthe pathogenesis of this disease. Preliminary results haveconfirmed these results in HeLa cells, and studies ofother lineages are underway. Previous studies of THP1,Jurkat and U937 cells stably transfected with an anti-sense DNA for BAT1 have shown that BAT1 mayencode a negative regulator of inflammatory cytokinessuch as TNF, IL-1 and IL-6 (Allcock et al. 2001). Thepresent study suggests that the high levels of TNFobserved in the immunopathological conditions associ-ated with the 8.1 AH (Jacob et al. 1990; Price et al. 1999)could be mediated by haplotypic polymorphisms in theBAT1 promoter.

Clearly, allele 1 and allele 2 of the BAT1 gene arecommon to several AHs with different phenotypes.Specifically, allele 2 is present in seven AHs, of which onlythree have been associated with disease susceptibility.This includes the 8.1 AH (HLA-A1, B8, DR3), 44.1 AH(HLA-A2, B44, DR4) and 58.1 AH (HLA-A33, B58,DR3) that are associated with increased susceptibilityto immunopathological conditions (Monos et al. 1995;Price et al. 1999; Candore et al. 2002). These data suggestthat the SNP within the BAT1 promoter are not suffi-cient to explain differences in disease susceptibility, inde-pendent of other genes. However, it is likely that morethan one gene is involved (Price et al. 1999). Thus, BAT1may act in combination with, or in synergy with, otherdisease susceptibility genes. For example, specific allelesof the BAT1 promoter may amplify the effect of HLAclass II alleles, such as HLA-DR3 on the 8.1 and 58.1AHand HLA-DR4 on the 44.1AH.

The present study suggests that SNP located at posi-tions −22 bp and/or −348 bp of BAT1 can affect tran-scription and are therefore likely to affect BAT1 protein

Table 3 Putative transcription factor binding motifs in the 520 bp fragment proximal to the BAT1 gene identified from the MatInspectordatabase

SNP AllelesTranscription factorsa

BAT1 alleles Comments

−22 G GFI1 Growth Factor Independence 1TH1E47 1 Member of the E47 family of transcription factors

C USF 2 Upstream stimulating factor−348 T — 1 —

C — 2 —

aSearches were performed on sequences from BAT1 promoter allele 1 (7.1 AH) and allele 2 (8.1 AH) that encompass the relevant SNPs.

Polymorphisms in the BAT1 promoter

© Blackwell Publishing Limited Genes to Cells (2003) 8, 403–412 409

levels and hence indirectly affect TNF expression. Thismust be interpreted in relation to linked alleles in theTNF cluster. This includes TNFA-308*2, which is alsofound on the 8.1AH, and yields 2–3-fold greater tran-scriptional activity than the TNFA-308*1 promoter inmitogen-stimulated Jurkat T-cells or U937 premono-cytic cells (Kroeger et al. 2000). The present data sup-ports BAT1 as an alternative or additional explanationfor the pro-inflammatory effects of the 8.1AH.

In addition to our luciferase studies, the EMSA studiespresented here provide supporting evidence that SNPwithin the BAT1 promoter can affect transcriptionalactivity by demonstrating the formation of haplotype-specific DNA–protein complexes. Thus, the haplotypicdifference in BAT1 transcriptional activity may beexplained by the differential binding of nuclear proteincomplexes at position −22 and/or −348 bp. Similarresults have been obtained with other cell lineages, includingmonocytes, and bands are affected by the mitogenicstimulation of Jurkat cells (A.M.-L. Wong, D. Williamson,M. Glasson, F.T. Christiansen and P. Price, in prepara-tion). The results suggest a complex sequence of eventsdetermined by haplotypic SNP in the BAT1 promoter.

Using the MatInspector software (Quandt et al.1995), three transcription factors were predicted to bespecific for alleles 1 or 2 at position −22 bp. The GFI1gene encodes a zinc finger protein specifically expressedin T-cells, which would fit with a role for BAT1 poly-morphisms in immunological diseases. Transgenic studiesindicate that the mouse orthologue, gfi1, is involvedin T-cell lymphomagenesis and T-cell development(Bayley et al. 2001). However, the cytokines affected byBAT1 in our anti-sense studies (TNF-α, IL-1 and IL-6)are predominantly produced by monocytes. The G-to-Ctransition at BAT1–22bp may also affect binding of theTh1/E47 transcription factor. The transcription factorE47 belongs to the E-protein class of basic helix-loop-helix proteins that are essential for lymphocyte develop-ment and function (Schmidt et al. 1998). E-proteinsregulate many aspects of lymphocyte maturation, survival,proliferation and differentiation. Moreover, a polymor-phism in the binding site of Th1/E47 on the regulatoryregion of the APOE gene correlates with an effect ofAPOE ε allele 4 in Alzheimer’s disease (Saunders 2000).

The third transcription factor predicted to bind differ-entially to allele1 and 2 at −22 bp is USF-1, a memberof the c-myc-related family of transcription factors thatrecognize and bind a CACGTG motif (termed E-box)of target genes resulting in the activation or repression ofgene transcription. USF-1 is a ubiquitously expressedtranscription factor that can modulate interferon-γ-inducible MHC class I and class II gene expression by

binding to E-box motifs of regulatory elements such asinterferon-stimulated response element (ISRE; Gobinet al. 1999) or class II transactivator (CIITA) promoter IV(Muhlethaler-Mottet et al. 1998).

In summary, our results provide further evidence fora role of BAT1 in susceptibility to immunological disor-ders. We have shown that the BAT1 promoter region ishighly polymorphic and that the polymorphisms affecttranscription in vitro. The luciferase expression driven bythe 520 bp proximal BAT1 promoter region of the 8.1AH was lower than with the 7.1 AH, suggesting the pres-ence of key regulatory elements at the −22 bp and/or −348 bp position of BAT1. In addition, differentialbinding of nuclear proteins for the two haplotypes wasdemonstrated at these sites and may contribute to theobserved differences in transcriptional activity. Togetherwith evidence that BAT1 down-regulates inflammatorycytokine production (Allcock et al. 2001), this may atleast partially explain the generalized immune dysfunc-tion ascribed to the 8.1 AH (A1, B8, DR3) (Price et al.1999; Candore et al. 2002). Hence this study has importantimplications in the regulation of acute phase cytokinesand for disease pathogenesis.

Experimental proceduresCell lines and preparation of genomic DNA

Thirteen EBV-transformed human B-cell lines from the 4th Asia-Oceania Histocompatibility Workshop (4AOH; Degli-Espostiet al. 1995; Prasad & Yang 1996) and the 10th International His-tocompatibility Workshop (10IHW) were selected for sequencing.The panel covered nine AH that are highly conserved and/or havewell described disease associations. Cells were cultured in RPMI-1640 medium containing 100 U/mL penicillin, and 100 µg/mLstreptomycin supplemented with 10% foetal calf serum, and main-tained at 37 °C with 5% CO2. Genomic DNA was extracted bysalting-out as previously described (Miller et al. 1988). Concen-trations and purity were measured spectrophotometrically. Threeoverlapping PCR products of ≈500 bp were sequenced for eachcell line using both forward (Fwd) and reverse (Rev) passes. A fur-ther 34 cell lines were then selected from the workshop panels forsingle pass sequencing.

PCR and sequencing

Primers were designed to specifically amplify three overlappingPCR products spanning over 1374 bp upstream of BAT1(Table 4). These primers carried the M13 tags for sequencing. Thenumbers are given according to the bp position in GenBank acces-sion no. AC004181. The sequence found in GenBank accessionno. AC004181 was used as a reference.

PCR amplifications were performed as follows: 100 nggenomic DNA was amplified in a 50 µL reaction mix containing

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4 mm dNTP, 50 mm KCl, 10 mm Tris-HCl, 10 pmol of eachprimer and 0.2 units Amplitaq polymerase (Perkin Elmer Cetus,NJ, USA). The optimal pH and MgCl2 concentration for eachprimer pair were determined prior to use (PCR OptimizationKit, Boehringer Mannheim, Germany). The PCR was carried outin a PTC200 thermal cycler (MJ Research Inc., MA, USA) underthe following conditions: 5 min at 95 °C followed by 35 cycles of95 °C for 20 s, 60 °C or 65 °C for 20 s (see below) and 72 °C for20 s. Touchdown-PCR was used to increase the specificity ofprimer annealing during the first eight cycles (Don et al. 1991). Anannealing temperature of 65 °C was used for BAT1 combinationprCFwd and prFRev whilst an annealing temperature of 60 °Cwas used for combinations prAFwd and prDRev, prBFwd andprERev. 10 µL of each PCR product was added to 2 µL loadingbuffer and separated on a 2% agarose gel to confirm amplification.The products were then purified (PCR Purification Kit, BoehringerMannheim, Germany), sequenced in forward and reverse direc-tions using dye-terminator chemistry and analysed using MTNavigator (ABI, CA, USA).

Promoter reporter constructs

Dual luciferase reporter constructs containing 5′ end truncationsof the BAT1 promoter region were generated by amplifyinggenomic DNA from workshop cell lines homozygous for the 7.1or 8.1 haplotypes. Primers BAT1prAFwd, prBFwd, or prCFwdwere used in conjunction with the prFRev primer to generatefragments of 1400, 1034 or 520 bp, respectively, containing anartificially added 5′ SacI site and a 3′ BglII site. Amplifications wereperformed using the conditions previously described for sequenc-ing of the upstream region of BAT1. The amplified PCR productswere digested with SacI and BglII and directionally cloned into thepoly linker of a promoter-less luciferase-encoding plasmid, pGL3-Enhancer (Promega, USA).

All the DNA used for transfection was prepared using theendotoxin-free Qiagen plasmid maxi kit (Qiagen GmbH, Germany).Concentrations and purity were measured spectrophotometricallyand confirmed by gel electrophoresis. The BAT1 promoterreporter constructs were sequenced in the forward and reversedirections using dye-terminator chemistry and analysed using MTNavigator (ABI, USA) to confirm their identity.

Culture and transfection of mammalian cell lines

The human derived Jurkat T-cell line was obtained from theAmerican Type Culture Collection (ATCC, MD, USA). Cells

were cultured using the conditions described for the workshopcell lines. One day prior to transfection, the cells were plated atapproximately 0.5 × 106 cells/mL and subsequently adjusted to1 × 106 cells in 1.5 mL medium at the time of transfection. Thetransfection of Jurkat cells was performed using Fugene reagent(Boehringer Mannheim, Germany) according to the manufac-turer’s instructions. Briefly, 1 µg of the firefly luciferase-expressingreporter plasmid containing the test promoter (pGL3-BAT1)was co-transfected with 10 ng control Renilla luciferase-expressingplasmid (pRL, Promega, USA) using 3 µL Fugene. The cells wereallowed to recover at 37 °C in 5% CO2 for 24, 48 and 72 h aftertransfection before being washed in phosphate-buffered saline andlysed with 100 µL passive lysis buffer (Promega, USA). The celllysates were then cleared by centrifugation and 40 µL aliquotsassayed using the Dual Luciferase Assay Kit (Promega, USA). Lightemission (wavelength 300–650 nm) for each sample was measuredfor 1 s using a 96-well plate reading luminometer (Wallac/Perkin-Elmer, Boston, MA, USA).

For all the co-transfection studies, values were normalized fortransfection efficiency by dividing values for firefly luciferaseactivity by values obtained for Renilla luciferase activity. An emptyvector (pGL3-enhancer; Promega, USA) and a vector containingan SV40 promoter (pGL3-control; Promega, USA) were used ascontrols. Experiments in which the Renilla activity varied by morethan 25% between samples were discarded.

Oligonucleotides, nuclear extracts and electrophoretic mobility shift assay

Oligonucleotides (20 bp) representing the −31 bp to −12 bpregion and −358 bp to −339 bp region of the BAT1 promoterrepresenting allele 1 (7.1 AH) and allele 2 (8.1 AH) were synthe-sized in the forward and reverse directions for gel shift assays. Double-stranded oligonucleotides encompassing the BAT1–22 SNPand the BAT1–348 SNP were labelled with [γ-32P]-ATP using T4polynucleotide kinase according to the manufacturer’s instructions(Promega, USA).

Approximately 1 × 107 Jurkat cells were used to make thenuclear extracts according to a standard method (Schreiber et al.1989). Extracts were frozen in liquid nitrogen and stored at−80 °C. Protein concentrations were determined using a Bio-Radprotein assay kit (Bradford 1976). For EMSA, 3 µg of total nuclearprotein extracts were pre-incubated on ice for 30 min togetherwith 1 µg of poly(dI-dC) in a binding buffer consisting of 20 mmHEPES (pH 7.9), 0.1 m KCl, 0.2 mm EDTA, 20% glycerol,0.5 mm DTT, 1 mm sodium orthovanadate and a cocktail of

Primer Position

BAT1prAFwd 5′-CCTTCTATGACACCATTC-3′ 25819–25836BAT1prBFwd 5′-CCAAGAACATTCTGCTCG-3′ 26242–26259BAT1prCFwd 5′-AATCCAGTTCCCTGAGAC-3′ 26757–21527BAT1prDRev 5′-CATGTATGACCTCAGGTG-3′ 26338–26355BAT1prERev 5′-GTAGTGAAGGTGACCTGA-3′ 26834–26851BAT1prFRev 5′-ACAGGGAGAGCGCGTATG-3′ 27268–27285

Table 4 Primers designed to specificallyamplify three overlapping PCR productsspanning over 1374 bp upstream of BAT1

Polymorphisms in the BAT1 promoter

© Blackwell Publishing Limited Genes to Cells (2003) 8, 403–412 411

protease inhibitors (Boehringer Mannheim, GmH). For competitionassays, a 25-, 50- or 100-fold molar excess of specific or alternativeallelic competitor was incubated with the nuclear extract for 30 minon ice. Nuclear proteins were subsequently incubated with32P-labelled oligonucleotide (25 fmol) for 30 min on ice beforeloading on to a 6% non-denaturing polyacrylamide gel/TBE forelectrophoresis at 180 V using 0.5×TBE running buffer for 3–4 h.The gels were then dried for 1–2 h under vacuum and exposed toan X-ray film, which was developed after a 1–4 day exposure.

In silico analysis of the BAT1 promoter around polymorphic sites

The MatInspector program (http://genomatix.de; Quandt et al.1995) was used to examine the effects of polymorphisms on thepredicted binding of transcription factors. Program searcheswere based on sequence matches with known transcription factorbinding motifs stored in the database. This program searches thesequence against weight matrices complied from known bindingsites, generating a quantitative rating for the likelihood of bindingof each transcription factor. A reduction of more than 0.2 in thematrix similarity score was taken as an indication that bindingmight be affected. Core similarity and matrix similarity scoreswere set at a cut-off value of 0.8.

Statistical analysis

Results were expressed as the mean ± standard error of the mean(SEM) of three DNA preparations each assessed in at least twoseparate experiments, where each data point represented the meanof duplicate or triplicate samples. Differences between the groupswere examined using Student’s t-test and statistical significancewas assigned at P < 0.05.

AcknowledgementsWe thank Dr Campbell Witt and Dr John Daly for their input intothis study and acknowledge the assistance of the Department ofClinical Immunology (RPH) sequencing team. This work wasundertaken with support from the National Health and MedicalResearch Council of Australia. Nucleotide sequences presentedhere have been submitted to GenBank and allocated the accessionnumbers AY055582 to AY055588.

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Received: 3 December 2002 Accepted: 8 January 2003