G2Cdb::Gene report

Gene id
Gene symbol
Homo sapiens
proline-rich transmembrane protein 1
G00001134 (Mus musculus)

Databases (7)

Curated Gene
OTTHUMG00000031144 (Vega human gene)
ENSG00000204314 (Ensembl human gene)
80863 (Entrez Gene)
1027 (G2Cdb plasticity & disease)
PRRT1 (GeneCards)
Marker Symbol
HGNC:13943 (HGNC)
Protein Sequence
Q99946 (UniProt)

Synonyms (2)

  • NG5

Literature (6)

Pubmed - other

  • High-density SNP screening of the major histocompatibility complex in systemic lupus erythematosus demonstrates strong evidence for independent susceptibility regions.

    Barcellos LF, May SL, Ramsay PP, Quach HL, Lane JA, Nititham J, Noble JA, Taylor KE, Quach DL, Chung SA, Kelly JA, Moser KL, Behrens TW, Seldin MF, Thomson G, Harley JB, Gaffney PM and Criswell LA

    Division of Epidemiology, School of Public Health, University of California Berkeley, Berkeley, California, USA.

    A substantial genetic contribution to systemic lupus erythematosus (SLE) risk is conferred by major histocompatibility complex (MHC) gene(s) on chromosome 6p21. Previous studies in SLE have lacked statistical power and genetic resolution to fully define MHC influences. We characterized 1,610 Caucasian SLE cases and 1,470 parents for 1,974 MHC SNPs, the highly polymorphic HLA-DRB1 locus, and a panel of ancestry informative markers. Single-marker analyses revealed strong signals for SNPs within several MHC regions, as well as with HLA-DRB1 (global p = 9.99 x 10(-16)). The most strongly associated DRB1 alleles were: *0301 (odds ratio, OR = 2.21, p = 2.53 x 10(-12)), *1401 (OR = 0.50, p = 0.0002), and *1501 (OR = 1.39, p = 0.0032). The MHC region SNP demonstrating the strongest evidence of association with SLE was rs3117103, with OR = 2.44 and p = 2.80 x 10(-13). Conditional haplotype and stepwise logistic regression analyses identified strong evidence for association between SLE and the extended class I, class I, class III, class II, and the extended class II MHC regions. Sequential removal of SLE-associated DRB1 haplotypes revealed independent effects due to variation within OR2H2 (extended class I, rs362521, p = 0.006), CREBL1 (class III, rs8283, p = 0.01), and DQB2 (class II, rs7769979, p = 0.003, and rs10947345, p = 0.0004). Further, conditional haplotype analyses demonstrated that variation within MICB (class I, rs3828903, p = 0.006) also contributes to SLE risk independent of HLA-DRB1*0301. Our results for the first time delineate with high resolution several MHC regions with independent contributions to SLE risk. We provide a list of candidate variants based on biologic and functional considerations that may be causally related to SLE risk and warrant further investigation.

    Funded by: NCRR NIH HHS: M01 RR000079, P20 RR020143, RR20143; NIAID NIH HHS: AI063274, AI24717, AI31584, AI53747, AI62629, N01AI40076, R01 AI024717, R01 AI031584, R01 AI063274, R21 AI053747, R37 AI024717, R56 AI063274, U19 AI062629; NIAMS NIH HHS: AR02175, AR043274, AR052125, AR052300, AR19084, AR22804, AR42460, AR48940, K24 AR002175, N01AR62277, P30 AR053483, P50 AR048940, R01 AR042460, R01 AR043274, R01 AR052125, R01 AR052300; NIDCR NIH HHS: DE15223, R01 DE015223

    PLoS genetics 2009;5;10;e1000696

  • Association of MHC SNP genotype with susceptibility to type 1 diabetes: a modified survival approach.

    McKinnon E, Morahan G, Nolan D, James I and Diabetes Genetics Consortium

    Centre for Clinical Immunology and Biomedical Statistics, Murdoch University and Royal Perth Hospital, Perth, Western Australia, Australia. e.mckinnon@murdoch.edu.au

    Aim: The Major Histocompatibility Complex (MHC) is a highly polymorphic region on chromosome 6 encompassing the human leucocyte antigen (HLA)-DQ/DR loci most predictive of susceptibility to type 1 diabetes (T1D). To assess the contribution of other MHC genes, in this exploratory analysis of Type 1 Diabetes Genetics Consortium (T1DGC) family data we characterize association between susceptibility and MHC single nucleotide polymorphism (SNP) genotype, with an emphasis on effects of genetic variation additional to carriage of predisposing or protective MHC haplotypes.

    Methods: We use Cox regression analyses of age of onset, stratified by family, to jointly test both linkage and association. Analysis is restricted to children from families having both affected and unaffected siblings and is conducted with and without adjustment for known HLA class I and II effects. Model fits provide scores for each individual that are based on estimates of the probability of being affected by the age of 35, given the individual's SNP genotype. The mean within-family variation in these scores provides a measure that closely reflects the relative size of the likelihood ratio test statistics, and their covariation provides a means of mapping patterns of association that incorporate both effect size and commonality of effect that is attributable to the strong linkage disequilibrium (LD) extending across the region.

    Results: Univariate analyses yielded strong associations with T1D susceptibility that are dominated by SNPs in the class II HLA-DR/DQ region but extend across the MHC. Similar effects are frequently observed across SNPs within multiple genes, sometimes spanning hundreds of kilobases. SNPs within a region at the telomeric end of the class II gene HLA-DRA yielded significant associations with and without adjustment for carriage of the predictive DR3, DR4, DR2 and DR7 HLA haplotypes, and remained highly prominent in a secondary analysis that was restricted to 66 families in whom at least one of the affected siblings carried neither the DR3 nor DR4 haplotype.

    Conclusions: While many of the associations can be attributed to LD between the SNPs and the dominant HLA-DRB/DQA/DQB loci, there is also evidence of additional modifying effects.

    Funded by: NIDDK NIH HHS: U01 DK062418, U01 DK062418-06

    Diabetes, obesity & metabolism 2009;11 Suppl 1;92-100

  • Genetic association of the major histocompatibility complex with rheumatoid arthritis implicates two non-DRB1 loci.

    Vignal C, Bansal AT, Balding DJ, Binks MH, Dickson MC, Montgomery DS and Wilson AG

    GlaxoSmithKline, Harlow, UK.

    Objective: The HLA-DRB1 locus within the major histocompatibility complex (MHC) at 6p21.3 has been identified as a susceptibility gene for rheumatoid arthritis (RA); however, there is increasing evidence of additional susceptibility genes in the MHC region. The aim of this study was to estimate their number and location.

    Methods: A case-control study was performed involving 977 control subjects and 855 RA patients. The HLA-DRB1 locus was genotyped together with 2,360 single-nucleotide polymorphisms in the MHC region. Logistic regression was used to detect DRB1-independent effects.

    Results: After adjusting for the effect of HLA-DRB1, 18 markers in 14 genes were strongly associated with RA (P<10(-4)). Multivariate logistic regression analysis of these markers and DRB1 led to a model containing DRB1 plus the following 3 markers: rs4678, a nonsynonymous change in the VARS2L locus, approximately 1.7 Mb telomeric of DRB1; rs2442728, upstream of HLA-B, approximately 1.2 Mb telomeric of DRB1; and rs17499655, located in the 5'-untranslated region of DQA2, only 0.1 Mb centromeric of DRB1. In-depth investigation of the DQA2 association, however, suggested that it arose through cryptic linkage disequilibrium with an allele of DRB1. Two non-shared epitope alleles were also strongly associated with RA (P<10(-4)): *0301 with anti- cyclic citrullinated peptide-negative RA and *0701 independently of autoantibody status.

    Conclusion: These results confirm the polygenic contribution of the MHC to RA and implicate 2 additional non-DRB1 susceptibility loci. The role of the HLA-DQ locus in RA has been a subject of controversy, but in our data, it appears to be spurious.

    Arthritis and rheumatism 2009;60;1;53-62

  • The status, quality, and expansion of the NIH full-length cDNA project: the Mammalian Gene Collection (MGC).

    Gerhard DS, Wagner L, Feingold EA, Shenmen CM, Grouse LH, Schuler G, Klein SL, Old S, Rasooly R, Good P, Guyer M, Peck AM, Derge JG, Lipman D, Collins FS, Jang W, Sherry S, Feolo M, Misquitta L, Lee E, Rotmistrovsky K, Greenhut SF, Schaefer CF, Buetow K, Bonner TI, Haussler D, Kent J, Kiekhaus M, Furey T, Brent M, Prange C, Schreiber K, Shapiro N, Bhat NK, Hopkins RF, Hsie F, Driscoll T, Soares MB, Casavant TL, Scheetz TE, Brown-stein MJ, Usdin TB, Toshiyuki S, Carninci P, Piao Y, Dudekula DB, Ko MS, Kawakami K, Suzuki Y, Sugano S, Gruber CE, Smith MR, Simmons B, Moore T, Waterman R, Johnson SL, Ruan Y, Wei CL, Mathavan S, Gunaratne PH, Wu J, Garcia AM, Hulyk SW, Fuh E, Yuan Y, Sneed A, Kowis C, Hodgson A, Muzny DM, McPherson J, Gibbs RA, Fahey J, Helton E, Ketteman M, Madan A, Rodrigues S, Sanchez A, Whiting M, Madari A, Young AC, Wetherby KD, Granite SJ, Kwong PN, Brinkley CP, Pearson RL, Bouffard GG, Blakesly RW, Green ED, Dickson MC, Rodriguez AC, Grimwood J, Schmutz J, Myers RM, Butterfield YS, Griffith M, Griffith OL, Krzywinski MI, Liao N, Morin R, Morrin R, Palmquist D, Petrescu AS, Skalska U, Smailus DE, Stott JM, Schnerch A, Schein JE, Jones SJ, Holt RA, Baross A, Marra MA, Clifton S, Makowski KA, Bosak S, Malek J and MGC Project Team

    The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5'-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline.

    Funded by: PHS HHS: N01-C0-12400

    Genome research 2004;14;10B;2121-7

  • Complete sequencing and characterization of 21,243 full-length human cDNAs.

    Ota T, Suzuki Y, Nishikawa T, Otsuki T, Sugiyama T, Irie R, Wakamatsu A, Hayashi K, Sato H, Nagai K, Kimura K, Makita H, Sekine M, Obayashi M, Nishi T, Shibahara T, Tanaka T, Ishii S, Yamamoto J, Saito K, Kawai Y, Isono Y, Nakamura Y, Nagahari K, Murakami K, Yasuda T, Iwayanagi T, Wagatsuma M, Shiratori A, Sudo H, Hosoiri T, Kaku Y, Kodaira H, Kondo H, Sugawara M, Takahashi M, Kanda K, Yokoi T, Furuya T, Kikkawa E, Omura Y, Abe K, Kamihara K, Katsuta N, Sato K, Tanikawa M, Yamazaki M, Ninomiya K, Ishibashi T, Yamashita H, Murakawa K, Fujimori K, Tanai H, Kimata M, Watanabe M, Hiraoka S, Chiba Y, Ishida S, Ono Y, Takiguchi S, Watanabe S, Yosida M, Hotuta T, Kusano J, Kanehori K, Takahashi-Fujii A, Hara H, Tanase TO, Nomura Y, Togiya S, Komai F, Hara R, Takeuchi K, Arita M, Imose N, Musashino K, Yuuki H, Oshima A, Sasaki N, Aotsuka S, Yoshikawa Y, Matsunawa H, Ichihara T, Shiohata N, Sano S, Moriya S, Momiyama H, Satoh N, Takami S, Terashima Y, Suzuki O, Nakagawa S, Senoh A, Mizoguchi H, Goto Y, Shimizu F, Wakebe H, Hishigaki H, Watanabe T, Sugiyama A, Takemoto M, Kawakami B, Yamazaki M, Watanabe K, Kumagai A, Itakura S, Fukuzumi Y, Fujimori Y, Komiyama M, Tashiro H, Tanigami A, Fujiwara T, Ono T, Yamada K, Fujii Y, Ozaki K, Hirao M, Ohmori Y, Kawabata A, Hikiji T, Kobatake N, Inagaki H, Ikema Y, Okamoto S, Okitani R, Kawakami T, Noguchi S, Itoh T, Shigeta K, Senba T, Matsumura K, Nakajima Y, Mizuno T, Morinaga M, Sasaki M, Togashi T, Oyama M, Hata H, Watanabe M, Komatsu T, Mizushima-Sugano J, Satoh T, Shirai Y, Takahashi Y, Nakagawa K, Okumura K, Nagase T, Nomura N, Kikuchi H, Masuho Y, Yamashita R, Nakai K, Yada T, Nakamura Y, Ohara O, Isogai T and Sugano S

    Helix Research Institute, 1532-3 Yana, Kisarazu, Chiba 292-0812, Japan.

    As a base for human transcriptome and functional genomics, we created the "full-length long Japan" (FLJ) collection of sequenced human cDNAs. We determined the entire sequence of 21,243 selected clones and found that 14,490 cDNAs (10,897 clusters) were unique to the FLJ collection. About half of them (5,416) seemed to be protein-coding. Of those, 1,999 clusters had not been predicted by computational methods. The distribution of GC content of nonpredicted cDNAs had a peak at approximately 58% compared with a peak at approximately 42%for predicted cDNAs. Thus, there seems to be a slight bias against GC-rich transcripts in current gene prediction procedures. The rest of the cDNAs unique to the FLJ collection (5,481) contained no obvious open reading frames (ORFs) and thus are candidate noncoding RNAs. About one-fourth of them (1,378) showed a clear pattern of splicing. The distribution of GC content of noncoding cDNAs was narrow and had a peak at approximately 42%, relatively low compared with that of protein-coding cDNAs.

    Nature genetics 2004;36;1;40-5

  • Analysis of the gene-dense major histocompatibility complex class III region and its comparison to mouse.

    Xie T, Rowen L, Aguado B, Ahearn ME, Madan A, Qin S, Campbell RD and Hood L

    Institute for Systems Biology, Seattle, Washington 98103, USA.

    In mammals, the Major Histocompatibility Complex class I and II gene clusters are separated by an approximately 700-kb stretch of sequence called the MHC class III region, which has been associated with susceptibility to numerous diseases. To facilitate understanding of this medically important and architecturally interesting portion of the genome, we have sequenced and analyzed both the human and mouse class III regions. The cross-species comparison has facilitated the identification of 60 genes in human and 61 in mouse, including a potential RNA gene for which the introns are more conserved across species than the exons. Delineation of global organization, gene structure, alternative splice forms, protein similarities, and potential cis-regulatory elements leads to several conclusions: (1) The human MHC class III region is the most gene-dense region of the human genome: >14% of the sequence is coding, approximately 72% of the region is transcribed, and there is an average of 8.5 genes per 100 kb. (2) Gene sizes, number of exons, and intergenic distances are for the most part similar in both species, implying that interspersed repeats have had little impact in disrupting the tight organization of this densely packed set of genes. (3) The region contains a heterogeneous mixture of genes, only a few of which have a clearly defined and proven function. Although many of the genes are of ancient origin, some appear to exist only in mammals and fish, implying they might be specific to vertebrates. (4) Conserved noncoding sequences are found primarily in or near the 5'-UTR or the first intron of genes, and seldom in the intergenic regions. Many of these conserved blocks are likely to be cis-regulatory elements.

    Genome research 2003;13;12;2621-36

Gene lists (6)

Gene List Source Species Name Description Gene count
L00000009 G2C Homo sapiens Human PSD Human orthologues of mouse PSD adapted from Collins et al (2006) 1080
L00000016 G2C Homo sapiens Human PSP Human orthologues of mouse PSP adapted from Collins et al (2006) 1121
L00000049 G2C Homo sapiens TAP-PSD-95-CORE TAP-PSD-95 pull-down core list (ortho) 120
L00000061 G2C Homo sapiens BAYES-COLLINS-MOUSE-PSD-CONSENSUS Mouse cortex PSD consensus (ortho) 984
L00000069 G2C Homo sapiens BAYES-COLLINS-HUMAN-PSD-FULL Human cortex biopsy PSD full list 1461
L00000071 G2C Homo sapiens BAYES-COLLINS-MOUSE-PSD-FULL Mouse cortex PSD full list (ortho) 1556
© G2C 2014. The Genes to Cognition Programme received funding from The Wellcome Trust and the EU FP7 Framework Programmes:
EUROSPIN (FP7-HEALTH-241498), SynSys (FP7-HEALTH-242167) and GENCODYS (FP7-HEALTH-241995).

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