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Human Molecular Genetics Advance Access originally published online on August 4, 2004
Human Molecular Genetics 2004 13(19):2221-2231; doi:10.1093/hmg/ddh245
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Human Molecular Genetics, Vol. 13, No. 19 © Oxford University Press 2004; all rights reserved

SNPs in the promoter of a B cell-specific antisense transcript, SAS-ZFAT, determine susceptibility to autoimmune thyroid disease

Senji Shirasawa1, Haruhito Harada1, Koichi Furugaki1, Takashi Akamizu2, Naofumi Ishikawa3, Kunihiko Ito3, Koichi Ito3, Hajime Tamai4, Kanji Kuma4, Sumihisa Kubota4, Hitomi Hiratani2, Tomoko Tsuchiya1, Iwai Baba1, Mayuko Ishikawa1, Masao Tanaka5, Kenji Sakai6, Masayuki Aoki6, Ken Yamamoto6 and Takehiko Sasazuki1,*

1Department of Pathology, Research Institute, International Medical Center of Japan, Toyama1-21-1, Shinjuku-ku, Tokyo 162-8655, Japan, 2Kyoto University, Kyoto 606-8507, Japan, 3Ito Hospital, Tokyo 150-8308, Japan, 4Kuma Hospital, Kobe 650-0011, Japan, 5Department of Surgery and Oncology and 6Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan

Received May 7, 2004; Revised July 6, 2004; Accepted July 20, 2004


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Autoimmune thyroid disease (AITD) is caused by an immune response to self-thyroid antigens and has a significant genetic component. Antisense RNA transcripts have been implicated in gene regulation. Here we have identified a novel zinc-finger gene, designated ZFAT (zinc-finger gene in AITD susceptibility region), as one of the susceptibility genes in 8q23–q24 through an initial association analysis using the probands in the previous linkage analysis and a subsequent association analysis of the samples from a total of 515 affected individuals and 526 controls. The T allele of the single-nucleotide polymorphism (SNP), Ex9b-SNP10 located in the intron 9 of ZFAT, is associated with increased risk for AITD (dominant model: odds ratio=1.7, P=0.000091). The Ex9b-SNP10 falls into the 3'-UTR of truncated-ZFAT (TR-ZFAT) and the promoter region of the small antisense transcript of ZFAT (SAS-ZFAT). In peripheral blood lymphocytes, SAS-ZFAT is exclusively expressed in CD19+ B cells and expression levels of SAS-ZFAT and TR-ZFAT seemed to correlate with the Ex9b-SNP10-T-associated ZFAT-allele, inversely and positively, respectively. The Ex9b-SNP10 is critically involved in the regulation of SAS-ZFAT expression in vitro and this expression results in a decreased expression of TR-ZFAT. These results suggested that the SNP-associated ZFAT-allele plays a critical role in B cell function by affecting the expression level of TR-ZFAT through regulating SAS-ZFAT expression and that this novel regulatory mechanism of SNPs might be involved in controlling susceptibility or resistance to human disease.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Autoimmune thyroid disease (AITD), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), is caused by an immune response to self-thyroid antigens (1). GD is characterized by the production of thyroid-stimulating hormone receptor-stimulating antibodies, leading to hyperthyroidism, whereas HT is characterized by the apoptosis of the thyrocytes, resulting in hypothyroidism (2). However, GD and HT share common features, such as T cell infiltration of the thyroid and production of anti-thyroid autoantibodies (1).

Twin studies and familial aggregation showed that AITD is a complex disease with genetic factors (3–6). Furthermore, GD and HT cluster in a family (7), in identical twins and triplets (8), and those in whom GD evolved into HT (9), indicating existence of common susceptibility loci shared by GD and HT. We have previously performed a whole-genome scan in a dataset of 123 Japanese sib-pairs affected with AITD and found that 8q24 was linked to AITD (10). A locus on chromosome 8q24 with evidence of linkage to AITD has also been reported in Caucasians (11,12). Recently, the thyroglobulin gene in 8q24 was reported to be associated with AITD in Caucasians (11,13). However, there is still a possibility that other susceptibility genes for AITD exist in 8q24.

Antisense RNA transcripts have been originally implicated in the initiation of genomic imprinting and X-inactivation (14–24). Endogenous antisense RNA was reported to affect the translation of the gene on the sense-strand (25) and antisense RNA-mediated gene silencing through methylation of the associated CpG island has been recently reported in {alpha}-thalassemia (26).

In this paper, we have carried out the association analysis using microsatellite markers and single nucleotide polymorphisms (SNPs) to identify the AITD susceptibility gene in 8q24 in Japanese population. First we have done the association analysis using the probands in the previous linkage analysis (10), then subsequent independent association analysis of the samples from a total of 515 affected individuals and526 controls was done to confirm the association detected in the first screening. Here, we identify a novel zinc-finger gene, designated ZFAT (a novel zinc-finger gene in AITD susceptibility region), as one of the susceptibility genes in 8q24.

The Ex9b-SNP10, one of the most statistically significant SNPs, is located in the intron of ZFAT, the 3'-UTR of truncated form of ZFAT (TR-ZFAT) and the promoter region of the small antisense transcript of ZFAT (SAS-ZFAT). The Ex9b-SNP10 is critically involved in the regulation of SAS-ZFAT expression and this expression results in a decreased expression of TR-ZFAT. This observation is intriguing that endogenous antisense transcript, which is regulated by a functional SNP statistically associated with AITD, affects the expression of the gene on the sense strand. This novel regulatory mechanism of SNPs might be involved in controlling susceptibility or resistance to human diseases.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Narrow down the susceptibility region by association analysis on the probands used in the previous linkage analysis
First, to identify the susceptibility region for AITD in 8q23–q24, association analysis of the samples from a total of 112 probands of the AITD families (10) and 526 control individuals using 169 microsatellite markers (Supplementary Material, Table S1) in 8q23–q24 (21 Mb long) was done. As the multipoint maximum LOD score at D8S272 for AITD was highest in the previous linkage study (10), the affected sibs were divided into 86 of the D8S272-linked families (the number of the sharing alleles of the D8S272 was one or two) and 26 of the D8S272-non-linked families (the number of the sharing alleles of the D8S272 was zero). The alleles of the two adjacent microsatellite markers in the contig NT_007994 were associated with the probands from the D8S272-linked families but not from the non-linked families (Table 1), suggesting that the contig NT_007994 was one of the narrowed susceptibility region in 8q24. Further association analysis of the samples from the 86 probands and 526 controls using 36 SNPs registered on the NT_007994 in the dbSNP database demonstrated that four SNPs located between 119.7 and 150.5 kb in the contig were associated with AITD (Tables 2 and 3). These results suggested that the susceptibility gene for these AITD families might exist around this associated region.


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  		Table 1. Association of the alleles of MS2 and MS3 in NT_007994 with the probands from the D8S272-linked families
 

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  		Table 2. Information of the SNP sequences in NT_007994
 

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  		Table 3. Association of the SNPs in NT_007994 with AITD and LD between Ex9b-SNP10 and other SNPs
 
Genomic structure of ZFAT, TR-ZFAT and SAS-ZFAT
In this associated region, northern blots, 5' and 3' rapid amplification of cDNA ends (RACE) and reverse transcriptase–polymerase chain reaction (RT–PCR) identified the completegene structures of (1) full length of ZFAT (DDBJ accession number AB167738, AB167739 and AB167740) composed of 19 exons, (2) TR-ZFAT (DDBJ accession number AB167741) using 3 kb exon 9b immediately following the exon 9a of ZFAT as 3'-UTR and (3) SAS-ZFAT (DDBJ accession number AB167742) transcribed from the antisense strand of ZFAT, which mRNA is 939 nt long, composed of two exons mostly located in exon 9b and exon 9a of ZFAT (Fig. 1). ZFAT has several kinds of alternative splicing forms, of which the longest predicted product is 1243 amino acids long, whereas TR-ZFAT uses both exon 9a and exon 9b of ZFAT, resulting in the 846 amino acids truncated form due to the presence of stop codon in the exon 9b (Fig. 1). ZFAT and TR-ZFAT has 18 and 11 repeats of the zinc-finger domain, respectively. On the other hand, the longest open reading frame for SAS-ZFAT is 39 amino acids long and similar protein for this predicted protein of SAS-ZFAT in mouse was not predicted in the mouse ZFAT region, suggesting that SAS-ZFAT might be a non-coding RNA (27–31).



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  		Figure 1. Genomic structure of ZFAT, TR-ZFAT and SAS-ZFAT. (A) Splicing variants of the ZFAT gene. ZFAT-1, encoding 1243 amino acids, is composed of 16 exons. ZFAT-2 and ZFAT-3, encoding 1231 amino acids, use the first methionine in the exon 4. TR-ZFAT uses exon 9a+b, resulting in the termination codon at 100 bp downstream from the entry of the exon 9b and encodes 846 amino acids. SAS-ZFAT is composed of two exons and is a 939 bp transcript on an antisense strand of the ZFAT. The exon 14 was reported in an EST sequence covering 3'-half of the exon 12 to 5'-half of the exon 17 (GenBank accession number BE747464). Arrows indicate the direction of transcription. An open triangle indicates the first methionine for translation and a solid triangle indicates a termination codon. (B) Positional relationship between SAS-ZFAT and exons 9a and 9b of ZFAT.

 
Discovery of SNPs and linkage–disequilibrium analysis around ZFAT region
Discovery of SNPs in their exons with flanking regions was done by direct sequencing on the 112 probands from the AITD families (Table 2). Linkage disequilibrium (LD) analysis indicated that a LD block ranging from the intron 5 of ZFAT (Int5-SNP2 at 150.5 kb in NT_007994) to the intron 14 of ZFAT (Int14-SNP1 at 86.0 kb in NT_007994) exists (Table 3). Association analysis of the samples from 86 probands and 526 controls using the 50 SNPs was performed, and the association of the SNPs, located from the intron 5 (Int5-SNP2) to the intron 9 (Int9-SNP3), was observed (Table 3). The G allele of Ex9b-SNP2, the most statistically significant SNP, which is located in intron 9 of ZFAT/3'-UTR of TR-ZFAT/intron 1 of SAS-ZFAT, was associated with the 86 probands from the D8S272-linked AITD families but not from the non-linked families (Tables 3 and 4). The T allele of Ex9b-SNP10, which is located in intron 9 of ZFAT/3'-UTR of TR-ZFAT/possible promoter region of SAS-ZFAT, a functional SNP (described later) located 1.7 kb downstream of the Ex9b-SNP2 and one of the most statistically significant SNPs representing the LD block, was also associated with the probands from the D8S272-linked AITD families (Tables 3 and 4).


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  		Table 4. Association of Ex9b-SNP2 and Ex9b-SNP10 with AITD
 
Association analysis of Ex9b-SNP2 and Ex9b-SNP10 on independent 515 AITD cases
To elucidate whether the Ex9b-SNP2 and Ex9b-SNP10 representing the LD block are associated with AITD in other population (32), a subsequent association analysis of the independent 515 AITD cases and 526 controls used in the first association study was performed. Ex9b-SNP2 and Ex9b-SNP10 were genotyped by TaqMan PCR assay. Although the G allele of the Ex9b-SNP2 was associated with AITD (allele frequency: P=0.0043), the T allele of the Ex9b-SNP10 was more strongly associated with increased risk for AITD [dominant association model: odds ratio (OR)=1.7, 95% confidential interval (CI)=1.3–2.3, P=0.000091] (Table 4). These results, together, suggested that the Ex9b-SNP10-T-associated ZFAT-allele (SNPs in LD with Ex9b-SNP10, including Ex9b-SNP2) is involved in susceptibility to AITD. AITD cases were stratified into 354 GD cases and 161 HT cases and the association of Ex9b-SNP10 with GD or HT was analyzed. Allele frequency of the T allele of the Ex9b-SNP10 in HT (54.7%) was higher than that observed in GD (51.0%) and the T allele of the Ex9b-SNP10 seemed to be more strongly associated with increased risk for HT than GD (OR=1.9 versus 1.7) (Table 5), suggesting that Ex9b-SNP10-T-associated ZFAT-allele might be more involved in susceptibility to HT than GD. A marker (Tgms2) in thyroglobulin gene in 8q24 was reported to be both linked and associated with AITD (11), however, association of Tgms2 was observed neither in the AITD cases nor in the probands from the D8S272-linked families (10) (Supplementary Material, Table S2).


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  		Table 5. Association of Ex9b-SNP10 with GD and HT
 
Expression analysis of ZFAT, TR-ZFAT and SAS-ZFAT
RT–PCR expression analysis in the human tissues revealed that ZFAT is strongly expressed in placenta, kidney, spleen, testis and peripheral blood lymphocytes (PBL), whereas TR-ZFAT is strongly expressed in placenta, ovary and tonsil (Fig. 2A). On the other hand, SAS-ZFAT expression was only detected in placenta with weak signal in the human tissues examined (Fig. 2A). Both ZFAT and TR-ZFAT are expressed in immune-related tissues, thus we next investigated these expressions in each fraction of pooled-PBL samples. ZFAT expression was equally detected in CD4+ T cells, CD8+ T cells, CD19+ B cells and CD14+ monocytes, whereas TR-ZFAT was strongly detected in CD19+ B cells and CD14+ monocytes. Interestingly, SAS-ZFAT expression level in CD19+ B cells was higher than that observed in placenta and SAS-ZFAT was specifically expressed in CD19+ B cells in PBL (Fig. 2B).



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  		Figure 2. Expression of ZFAT, TR-ZFAT and SAS-ZFAT mRNA. (A, B) Each expression in various human tissues (Clontech) (A) and in the subsets of PBL (B) was detected by RT–PCR using pooled normalized first-strand cDNA (Clontech). (C) Representative each expression in CD19+ B cells from an individual with a distinct genotype of Ex9b-SNP10. (D) Real-time quantitative PCR assay for ZFAT, TR-ZFAT and SAS-ZFAT expressions. Expression levels of ZFAT, TR-ZFAT and SAS-ZFAT were normalized with GAPDH expression and the ratio of each expression was determined as 1.0 for the genotype A/A of Ex9b-SNP10. Data shown are the mean±SD from individuals with the distinct genotypes of Ex-9b-SNP10 (n=4 for A/A, n=9 for T/A and n=6 for T/T). Experiments were repeated three times with similar results. *P<0.01 in a comparison between A/A and T/T (Student's t-test). NC, negative control and Mono, mononuclear cells.

 
Correlation between Ex9b-SNP10 and expressions of TR-ZFAT and SAS-ZFAT
Three SNPs, including the Ex9b-SNP10 (A/T), -SNP11 (A/G) and -SNP12 (T/C) (Fig. 3A), in being almost complete LD (Table 3), are located in a possible promoter region of SAS-ZFAT. To determine whether a correlation between the Ex9b-SNP10-associated allele and the expression levels of ZFAT, TR-ZFAT and SAS-ZFAT exists, their expressions were analyzed in CD19+ B cells separated from PBL in each individual by real-time quantitative PCR. It is interesting to note that expression of ZFAT in CD19+ B cells was not affected by the Ex9b-SNP10-associated allele, whereas SAS-ZFAT expression was inversely correlated with the Ex9b-SNP10-T-associated ZFAT-allele with statistical significance (Fig. 2C and D). Although the correlation between the TR-ZFAT expression and the Ex9b-SNP10-T-associated ZFAT-allele was not statistically significant, TR-ZFAT expression seemed to be correlated with the Ex9b-SNP10-T-associated ZFAT-allele (Fig. 2D). These results suggested that the Ex9b-SNP10-associated ZFAT-allele may be involved in regulation of the TR-ZFAT and SAS-ZFAT expressions in B cells, but not ZFAT.



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  		Figure 3. Transcriptional regulatory activity affected by SNPs. (A) Genomic structure of TR-ZFAT and SAS-ZFAT around the Ex9b-SNP10. A double-head arrow shows a promoter region used for luciferase assay. (B) Haplotypes constructed by the three SNPs, including Ex9b-SNP10 (A/T), -SNP11 (A/G) and -SNP12 (T/C), in 611 bp 5'-flanking region of SAS-ZFAT affected relative luciferase activity in HEK293 cells. P*<1x10–5, P**<1x 10–5 and P***<1x10–3 for comparison between one common haplotype (A-A-T) and the other common haplotype (T-G-C), between A-A-T and T-A-T and between T-G-C and A-G-C, respectively (Student's t-test). Similar results were also obtained in four independent experiments done in triplicates. (C) Binding of unknown nuclear factor(s) to the 5'-flanking region of SAS-ZFAT. The 33 bp oligonucleotide including –107A or –107T SNP was labeled with digoxigenin-11-ddUTP. An arrow indicates a band which shows tighter binding of nuclear factor(s) to T allele. The experiments were repeated three times with similar results.

 
Ex9b-SNP10-associated ZFAT-allele regulates SAS-ZFAT expression
The Ex9b-SNP10, -SNP11 and -SNP12 are located upstream (–107, –172 and –194, respectively) of the exon 1 of SAS-ZFAT, therefore luciferase reporter assay was done using HEK293 cells to confirm if the 611 bp DNA fragment, containing EX9b-SNP10(A/T) (–107), Ex9b-SNP11(A/G) (–172) and Ex9b-SNP12(T/C) (–194) (Fig. 3A), is involved in transcriptional regulatory activity. One common haplotype A-A-T of Ex9b-SNP10-11-12 showed 2.3-fold greater transcriptional activity than the other common haplotype T-G-C (Fig. 3B). Furthermore, reporter assay using six other haplotypes constructed by these three SNPs in addition to the two common haplotypes indicated that the Ex9b-SNP10 is most critically involved in transcriptional regulation, although both Ex9b-SNP11 and Ex9b-SNP12 may affect the transcriptional activity (Fig. 3B). Gel-shift analysis was done using nuclear extracts from HEK293 cells and BJAB cells and oligonucleotides corresponding to the genomic sequences, including –107A or –107T alleles. It was demonstrated that a band corresponding to the –107T allele is more intense than that of the –107A allele (Fig. 3C). All these results suggested that some unknown nuclear factor(s) binds more tightly to the Ex9b-SNP10-T-associated ZFAT-allele, culminating in repression of SAS-ZFAT expression.

SAS-ZFAT expression affects the amount of TR-ZFAT expression
We further examined whether SAS-ZFAT transcript itself affects the expression level of TR-ZFAT or not. Expression of TR-ZFAT detected by northern blot was reduced by expression of SAS-ZFAT in a co-transfection experiments with expression vectors of TR-ZFAT and SAS-ZFAT in HEK293 cells, while it was unchanged by empty or unrelated (Mig6-3'-UTR) vectors (Fig. 4A). Expression of ZFAT was not changed by SAS-ZFAT expression (Fig. 4B). Furthermore, stability of the TR-ZFAT mRNA was not different between the Ex9b-SNP10-T- and -A-associated alleles (Fig. 5). Thus, TR-ZFAT expression seems to be regulated by the SAS-ZFAT transcript.



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  		Figure 4. SAS-ZFAT expression-induced reduction in TR-ZFAT expression. (A, B) HEK293 cells were transfected with pCI-TR-ZFAT-3'-UTR and pCI, pCI-SAS-ZFAT or pCI-Mig6-3'-UTR (A), and pCI-ZFAT and pCI, pCI-SAS-ZFAT or pCI-Mig6-3'UTR (B). Expressions of ZFAT, TR-ZFAT-3'-UTR, SAS-ZFAT, Mig6-3'-UTR and GAPDH were analyzed using northern blot.

 


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  		Figure 5. Stability of TR-ZFAT mRNA in vitro. (A) Peripheral blood lymphocyte extracts. (B) HL-60 cell extracts. Diluted whole cell extracts were mixed with in vitro transcripts of TR-ZFAT mRNA and then RNAs were detected by northern blot hybridization. Signal intensity was measured by Image Gauge version 4.0 (FUJIFILM). Square, Ex9b-SNP10-T-associated allele and triangle, Ex9b-SNP10-A-associated allele.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Here we have identified ZFAT/TR-ZFAT/SAS-ZFAT as one of the susceptibility genes for AITD in 8q23–q24 and found that a functional SNP (Ex9b-SNP10), located in the intron of ZFAT, in the 3'-UTR of TR-ZFAT and in the promoter region of SAS-ZFAT, is statistically associated with AITD. ZFAT and TR-ZFAT encodes a protein with 18 and 11 repeats of zinc-finger domains, respectively, and both are expressed in immune-related tissues. On the other hand, SAS-ZFAT will be a non-coding RNA and it is exclusively expressed in B cells in peripheral blood, except placenta.

The association of the Ex9b-SNP10-associated ZFAT-allele with AITD was initially detected in the probands from the D8S272-linked families in the linkage analysis (10), and was confirmed by subsequent association study of the samples from a total of 515 affected individuals and 526 controls. The most statistically significant SNP associated with the 86 probands from the D8S272-linked AITD families was the Ex9b-SNP2, which is in LD with Ex9b-SNP10 (Table 3). The Ex9b-SNP2, which is located in the 3'-UTR of TR-ZFAT, did not affect the stability of TR-ZFAT mRNA (Fig. 5), indicating that Ex9b-SNP2 will not be a causal SNP for AITD. However, a possibility that Ex-9bSNP2 might have some function for the etiology of AITD cannot be excluded. The allele frequency of G allele of Ex9b-SNP2 and T allele of Ex9b-SNP10 in the probands from the D8S272-linked AITD families used in the linkage analysis are both higher than those observed in the sporadic AITD cases (Table 4), supporting the association of Ex9b-SNP10-associated ZFAT-allele with AITD in the presence of linkage.

Association of thyroglobulin gene with AITD was not detected in this study (Supplementary Material, Table S2), which might be due to ethnic difference between Caucasians and Japanese. AITD susceptibility in the Caucasians was mapped to the 6.1 kb 3'-UTR of the cytotoxic T-lymphocyte antigen-4 (CTLA4) gene (33), encoding a negative regulator of the T-lymphocyte immune response. We had reported that the disease susceptible G allele of the SNP-JO31 in the CTLA4 (33) was also associated with AITD in the Japanese (67.1% versus 74.2%) (34), however, its allele frequency in Japanese controls (67.1%) was much higher than those of the controls (50.2%) and AITD (61.0%) in the Caucasians (33). Furthermore, SNP-JO30 in the 3'-UTR of CTLA4, which was in LD with JO31 and was strongly associated with AITD in Caucasians (33), was not associated with AITD in the Japanese (34). These results, together, suggested that the ethnic difference between Caucasians and Japanese may exist in the etiology of AITD.

ZFAT is strongly expressed in placenta, kidney, spleen, testis and PBL, whereas TR-ZFAT is strongly expressed in placenta, ovary and tonsil (Fig. 2A). In peripheral blood, ZFAT expression was equally detected in CD4+ T cells, CD8+ T cells, CD19+ B cells and CD14+ monocytes, whereas TR-ZFAT was strongly detected in CD19+ B cells and CD14+ monocytes. Furthermore SAS-ZFAT was evidently and specifically expressed in CD19+ B cells (Fig. 2B). On the other hand, these genes expression in the thyroid was little (data not shown). When considering the etiology of AITD, the expressions of ZFAT in PBL, TR-ZFAT expression in B cells and monocytes of peripheral blood and SAS-ZFAT expression in B cells of peripheral blood may affect with each other and thus, in turn, might be involved in the development of AITD. ZFAT and TR-ZFAT encode zinc-finger proteins and both expressions were detected in the nucleus (data not shown), suggesting that ZFAT and TR-ZFAT might work as transcriptional regulators. Further functional analysis of ZFAT and TR-ZFAT should be needed to understand how these molecules are involved in the development of AITD.

The Ex9b-SNP10-associated ZFAT-allele affects the expression levels of SAS-ZFAT and TR-ZFAT in B cells, suggesting that the SNP-associated ZFAT-allele plays critical roles in B cell function, and thus might be involved, in part, in etiology of AITD. There might be a possibility that the Ex9b-SNP10-T-associated ZFAT-allele may affect the function of ZFAT protein if higher expression of TR-ZFAT interferes with the function of ZFAT in dominant negative fashion.

Antisense RNA transcripts have been implicated in gene regulation (14–26). This current observation that endogenous antisense transcript, which is regulated by functional SNPs, affects expression of the gene on the sense strand is intriguing. This novel regulatory mechanism might be common and SNPs function might be involved in controlling susceptibility or resistance to human diseases. Identification of the regulatory proteins bound to the EX9b-SNP10-T-associated ZFAT-allele and elucidation of a regulatory mechanism of SAS-ZFAT-induced decreased expression of TR-ZFAT should shed light on gene regulation by antisense RNA.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Genetic analysis
These Japanese participants were interviewed and examined and gave written informed consent. This project was approved by the Ethical Committee of the related institutes. This study included 112 affected sib-pairs with AITD (10), 515 unrelated individuals with AITD, including 354 cases with GD and 161 cases with HT, and 526 control individuals. The genomic DNA sequence of 8q23–q24 between D8S514 and 8q-ter was obtained from the GenBank database (http://www.ncbi.nlm.nih.gov/). We searched dinucleotide repeats [CA]n and/or [TG]n (n>4) in the sequence of each contig and designed polymerase chain reaction (PCR) primers, and 768 pairs of PCR primers were totally designed. PCR was done using GeneAmp PCR System 9700 (Applied Biosystems). Genotyping was done using the ABI 3100 Genetic Analyzer (Applied Biosystems), and analyses and assignment of the marker alleles were done with GENESCAN and GENOTYPER programs (Applied Biosystems). CA repeat markers examined in unrelated eight Japanese healthy subjects with more than two alleles were used in the association study. Information on SNPs was obtained from the dbSNP database (http://www.ncbi.nlm.nih.gov/SNP/index.html). Discovery of SNPs in ZFAT, TR-ZFAT and SAS-ZFAT were done by direct sequencing. All PCR products for direct sequencing were purified using the ExoSAP-IT (USB). Sequencing reaction was performed using BigDye Terminator Cycle Sequencing v2.0 (Applied Biosystems). The SNPs were genotyped through the TaqMan PCR assay (Applied Biosystems) using ABI PRISM 7900HT (Applied Biosystems) as described (34). The products were purified using Wizard MagneSil Sequencing Reaction Clean-Up System (Promega). Nucleotide sequences were determined by ABI 3100 and ABI 3730XL Genetic Analyzer (Applied Biosystems). Association analyses between controls and cases were carried out using a contingency 2x2 table to calculate an OR and {chi}2as described (10). The P values shown were not corrected for multiple comparisons. LD mapping (r2) was done using the EH program through analysis of 260 controls. The power to detect an OR of 2.3 at 0.05 significance level using 86 linked probands and 526 controls was 0.75 (35).

5' and 3' rapid amplification of cDNA ends
To isolate full-length cDNAs, a partially reported cDNA (KIAA1485, AB040918) or predicted exons [Digit program (http://digit.gsc.riken.go.jp/cgi-bin/index.cgi)] were extended toward the 5' and 3' directions using the (RACE) method. RACE reactions were performed using poly A RNA from liver and placenta purchased from Clontech and the SMART RACE cDNA amplification kit (Clontech) according to the manufacturer's instruction. The amplified products were cloned into TA cloning plasmid (Clontech) and sequenced.

Expression analysis in human tissues and CD19+ B cells from PBL
Each expression in human tissues/cells was determined by RT–PCR using pooled normalized first-strand cDNA (Human MTC Panel I and II, Human Blood Fractions MTC Panel, Clontech) (Fig. 2A and B). CD19+ B cells from each healthy individual were prepared from PBL by an immunomagnetic method using magnetic beads (MACS system, Miltenyi Biotec), and then total RNA was extracted by TRIZOL (Invitrogen) (Fig. 2C and D). RT–PCR (Fig. 2A–C) was done with Superscript II (Invitrogen) and LA Taq polymerase (TAKARA), using primers for ZFAT (5'-TGGCTCAGACCTTCAGCGTCA-3' and 5'-TGATCTGCTGCAGGATGTTCA-3'), TR-ZFAT (5'-AGAGGCTCATGCTGCTCCTGAGAA-3' and 5'-ACGTGCACAGCTGTGTAAGGAGAAGGATCT-3'), and SAS-ZFAT (5'-GGCAGAGGCTTCCCAGGTTCCTTTCACAGC-3' and 5'-CATGGTTCTTGGTAGGTCTC-3'). Primers for GAPDH were purchased from Clontech.

Real-time quantitative PCR assay
First strand cDNA was synthesized using SuperScript First-Strand Synthesis System (Invitrogen). PCR primers for quantitative PCR were designed by DNASIS PRO software (HITACHI Software engineering): ZFAT (5'-AGCAAGGTGGTTTGAAGTG-3' and 5'-TGATGTGGAGATACTGGGTG-3'), TR-ZFAT (5'-GTGTCATTATTCTTCCATCACC-3' and 5'-GCTTGGGCTTGCTACTTAC-3'), SAS-ZFAT (5'-GCACATTCCTGACACTCC-3' and 5'-TGCTCATTGCTTTCTCAAG-3') and GAPDH (5'-AACATCATCCCTGCCTCTAC-3' and 5'-CTGCTTCACCACCTTCTTG -3'). Real-time quantitative PCR was performed using LightCycler and SYBR Green I enzyme master mix (Roche Diagnostics) according to the manufacture's instructions. Expression levels of ZFAT, TR-ZFAT and SAS-ZFAT were normalized with GAPDH expression and the ratio of each expression was determined as 1.0 for the genotype A/A of Ex9b-SNP10.

Luciferase assay
The DNA fragment corresponding to nucleotide –1 to –611 of SAS-ZFAT was amplified by PCR using genomic DNA as a template, and then cloned into pGL3-enhancer vector (Promega) in 5'–3' orientation. In addition to the two common haplotypes, six other haplotypes constructed by Ex9b-SNP10, SNP11 and SNP12 were made by using a mutagenesis kit (Stratagene). HEK293 cells (4x105) were grown in DMEM medium supplemented with 10% fetal calf serum, then transfected with 1 µg of luciferase construct and 50 ng of pRL-TK as an internal control, using Lipofectamine and Plus transfection reagents (Invitrogen). After 24 h, the cells were collected and luciferase activity was measured using the Dual-Luciferase Reporter Assay System (Promega), as described (36)

Gel-shift assay
Nuclear extracts from HEK293 and BJAB cells were prepared using Nuclear Extract Kits (Active Motif). An aliquot 3 µg of nuclear extract were incubated with 0.15 pmol of 33 bp oligonucleotides labeled with digoxigenin-11-ddUTP, using the Digoxigenin Gel-shift Kit (Roche). For competition studies, nuclear extracts were preincubated with 20 pmol of unlabeled oligonucleotide before adding the digoxigenin-labeled oligonucleotide. The protein–DNA complexes were run on a non-denaturing 7.5% polyacrylamide gel in 0.5x Tris–Borate–EDTA buffer followed by transferring the gel to nylon membrane by electro-blotting and the signal was detected using a chemiluminescent detection system (Roche) according to the manufacturer's instructions.

Northern blot analysis
The cDNAs of ZFAT, TR-ZFAT-3'-UTR, SAS-ZFAT and 3'-UTR of Mig6 gene (36) were amplified by RT–PCR, then cloned into a pCI expression vector (Promega). HEK293 cells (2.5x106) were transfected with 0.5 µg of pCI-TR-ZFAT-3'-UTR (Fig. 4A) or pCI-ZFAT (Fig. 4B), and 7.5 µg of pCI, pCI-SAS-ZFAT or pCI-Mig6-3'-UTR, as described earlier. After 18 h, total RNA was isolated using TRIZOL (Invitrogen). By electrophoresis 15 µg of total RNA was separated, followed by transfer to nylon-membrane, and then filters were hybridized with the indicated probes, as described (36).


   IN VITRO RNA STABILITY ASSAY
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 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
SUPPLEMENTARY MATERIAL
 REFERENCES
 
Two major haplotypes of 3'-UTR of TR-ZFAT were amplified by PCR and cloned into the 3' end of the coding region of the TR-ZFAT expression plasmid with T7 promoter (Promega). In vitro transcripts were synthesized by RiboMAX Large Scale RNA Production Systems-T7 (Promega) and purified by TRIzol (Invitrogen). Whole-cell extracts from were prepared PBL or HL-60 cells as described (37). We mixed and incubated each 5 µg of synthesized RNA and diluted whole-cell extracts (1 : 15) at room temperature. The reaction was stopped with the addition of formamide dye, and the samples were then heated at 65°C for 15 min. After the reaction, we detected RNA using northern blot hybridization. We scanned results on a BAS-2500 (FUJIFILM) and measured signal intensity of TR-ZFAT RNAs using Image Gauge version 4.0 (FUJIFILM).


   SUPPLEMENTARY MATERIAL
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
REFERENCES
 
Supplementary Material is available at HMG Online.


   ACKNOWLEDGEMENTS
 
We thank all patients for participating in this study, Dr Sumio Sugano for helpful discussion, S. Ohkubo for preparation of the manuscript and T. Tokuyasu, Y. Hagishima, A. Murakami, E. Yachi, J. Nakai, S. Oishi, T. Akinaga, H. Yamaguchi and K. Fukuyama for technical assistance. This work was supported by a Grant-in Aid for Scientific Research on Priority Areas ‘Medical Genome Science’ from the Ministry of Education, Science, Technology, Sports and Culture, Japan, and a Grant-in Aid for Scientific Research (A) from the Japan Society for the Promotion of the Science, a Research Grant on Human Genome and Gene Therapy from the Ministry of Health, Labour and Welfare, Japan and the Japan Science and Technology Corporation (CREST).


   FOOTNOTES
 
* To whom correspondence should be addressed. Tel: +813 32027181; Fax: +813 32027364; Email: sasazuki{at}nciryo.hosp.go.jp


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 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 IN VITRO RNA STABILITY...
 SUPPLEMENTARY MATERIAL
 REFERENCES
 

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