G2Cdb::Gene report

Gene id
Gene symbol
Homo sapiens
mitochondrial carrier homolog 2 (C. elegans)
G00000733 (Mus musculus)

Databases (6)

ENSG00000109919 (Ensembl human gene)
23788 (Entrez Gene)
1158 (G2Cdb plasticity & disease)
MTCH2 (GeneCards)
Marker Symbol
HGNC:17587 (HGNC)
Protein Sequence
Q9Y6C9 (UniProt)

Literature (16)

Pubmed - other

  • Novel obesity risk loci do not determine distribution of body fat depots: a whole-body MRI/MRS study.

    Haupt A, Thamer C, Heni M, Machicao F, Machann J, Schick F, Stefan N, Fritsche A, Häring HU and Staiger H

    Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard-Karls-University Tübingen, Tübingen, Germany.

    A recent meta-analysis of genome-wide association studies has identified six new risk-loci for common obesity. We studied whether these risk loci influence the distribution of body fat depots. We genotyped 1,469 nondiabetic subjects for the single-nucleotide polymorphisms (SNPs) TMEM18 rs6548238, KCTD15 rs11084753, GNPDA2 rs10938397, SH2B1 rs7498665, MTCH2 rs10838738, and NEGR1 rs2815752. We assessed BMI, waist circumference, total body fat, and lean body mass (bioimpedance). All subjects underwent an oral glucose tolerance test (OGTT) for estimation of insulin sensitivity. In 332 subjects, we measured total adipose tissue (TAT), visceral adipose tissue (VAT), nonvisceral adipose tissue (NVAT), liver fat content, and intramyocellular lipids (IMCLs) using whole-body magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS). In the dominant inheritance model, the risk alleles of TMEM18 rs6548238 and MTCH2 rs10838738 were nominally associated with higher BMI (P = 0.04, both). The risk allele of TMEM18 rs6548238 was additionally associated with higher waist circumference and total body fat (P <or= 0.03), the risk allele of NEGR1 rs2815752 with higher waist circumference (P = 0.05) and unexpectedly with lower BMI (P = 0.01). In the MR cohort, we found an association of the risk allele of SH2B1 rs7498665 with higher VAT (P = 0.009) and of GNPDA2 rs10938397 with increased IMCLs (P = 0.03). After Bonferroni correction for multiple comparisons (corrected alpha-level: P = 0.0085), none of the SNPs was significantly associated with measures of adiposity or body fat distribution (all P > 0.009, dominant inheritance model). Therefore, our results suggest that these new obesity SNPs, despite their influence on BMI, are neither associated with a metabolically unfavorable nor with a favorable body composition.

    Obesity (Silver Spring, Md.) 2010;18;6;1212-7

  • Are recently identified genetic variants regulating BMI in the general population associated with anorexia nervosa?

    Brandys MK, van Elburg AA, Loos RJF, Bauer F, Hendriks J, van der Schouw YT and Adan RAH

    Department of Neuroscience & Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.

    The influence of body mass index (BMI) on susceptibility to anorexia nervosa (AN) is not clear. Recently published genome-wide association (GWA) studies of the general population identified several variants influencing BMI. We genotyped these variants in an AN sample to test for association and to investigate a combined effect of BMI-increasing alleles (as determined in the original GWA studies) on the risk of developing the disease. Individual single nucleotide polymorphisms (SNPs) were tested for association with AN in a sample of 267 AN patients and 1,636 population controls. A logistic regression for the combined effect of BMI-increasing alleles included 225 cases and 1,351 controls. We found no significant association between individual SNPs and AN. The analysis of a combined effect of BMI-increasing alleles showed absence of association with the investigated condition. The percentages of BMI-increasing alleles were equal between cases and controls. This study found no evidence that genetic variants regulating BMI in the general population are significantly associated with susceptibility to AN.

    Funded by: Medical Research Council: MC_U106188470

    American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 2010;153B;2;695-699

  • Obesity genotype score and cardiovascular risk in women with type 2 diabetes mellitus.

    He M, Cornelis MC, Franks PW, Zhang C, Hu FB and Qi L

    Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA.

    Objective: To investigate the associations between obesity-predisposing genetic variants, cardiovascular biomarkers, and cardiovascular disease (CVD) risk in women with preexisting type 2 diabetes mellitus.

    We genotyped polymorphisms at nine established obesity loci in 1,395 women with diabetes from the Nurses' Health Study: 449 women developed CVD, and 946 women did not develop CVD. A genetic risk score (GRS) was derived by summing risk alleles for each individual. Four polymorphisms (rs9939609 [FTO], rs11084753 [KCTD15], rs10838738 [MTCH2], and rs10938397 [GNPDA2]) showed nominally significant associations with CVD. The GRS combining all obesity loci was linearly related to CVD risk (P = 0.013 for trend). The odds ratio was 1.08 per risk allele (95% confidence interval, 1.02-1.15; P = 0.01) after adjustment for body mass index and other conventional risk factors. Women with the highest quartile of GRS had 53% (95% confidence interval, 6%-122%) increased CVD risk, compared with those in the lowest quartile of GRS (P = 0.024). In addition, a higher GRS was associated with lower adiponectin levels (P = 0.02). Further adjustment for body mass index and other covariates did not change the association (P = 0.006). A higher GRS was also correlated with lower levels of high-density lipoprotein (P = 0.01).

    Conclusions: Obesity-predisposing variants may jointly affect CVD risk among women with diabetes.

    Funded by: NHLBI NIH HHS: HL34594, HL71981, R01 HL034594, R01 HL071981, R01 HL071981-05A1; NIDDK NIH HHS: DK46200, DK58845, P30 DK046200, R01 DK058845

    Arteriosclerosis, thrombosis, and vascular biology 2010;30;2;327-32

  • Cumulative effects and predictive value of common obesity-susceptibility variants identified by genome-wide association studies.

    Li S, Zhao JH, Luan J, Luben RN, Rodwell SA, Khaw KT, Ong KK, Wareham NJ and Loos RJ

    MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, UK.

    Background: Large-scale genome-wide association studies have identified 12 genetic loci that are robustly associated with body mass index (BMI).

    Objectives: We examined associations and compared effect sizes of these newly identified obesity susceptibility loci with various anthropometric traits and assessed their cumulative effects and predictive value for obesity risk.

    Design: We genotyped 12 single nucleotide polymorphisms (SNPs) from each locus in 20,431 individuals (age: 39-79 y) from the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort. General linear model and logistic regression were used to examine associations, and the area under the receiver operating characteristic curve (AUC) was used to assess the predictive value of these variants for obesity risk.

    Results: Effect sizes of the risk alleles ranged between 0.058 and 0.329 for BMI (in kg/m(2)), between 0.094 and 0.866 kg for weight, and between 0.085 and 0.819 cm for waist circumference, with rs1121980 (FTO locus) showing the largest effect. Risk alleles of rs7132908 (FAIM2 locus) and rs17782313 (MC4R locus) were also associated with taller height. On average, each additional risk allele was associated with increases of 0.149 in BMI (P = 1.54 x 10(-22)), 0.444 kg in body weight (P = 9.88 x 10(-22)), and 0.357 cm in waist circumference (P = 1.10 x 10(-18)) and 10.8% (P = 9.83 x 10(-16)) and 5.5% (P = 3.38 x 10(-10)) increased risks of obesity and overweight, respectively. All SNPs combined explained 0.9% of BMI variation, with an AUC of 0.574 (95% CI: 0.559, 0.590) for prediction of obesity.

    Conclusions: Common variants for BMI have small effects on obesity measures and show different association patterns with anthropometric traits, with the largest effect shown for the FTO locus. These variants have cumulative effects, yet their predictive value for obesity risk is limited.

    Funded by: Cancer Research UK; Medical Research Council: G0401527, G0701863, MC_U105630924, MC_U106179471, MC_U106179472, MC_U106188470

    The American journal of clinical nutrition 2010;91;1;184-90

  • Association between obesity and polymorphisms in SEC16B, TMEM18, GNPDA2, BDNF, FAIM2 and MC4R in a Japanese population.

    Hotta K, Nakamura M, Nakamura T, Matsuo T, Nakata Y, Kamohara S, Miyatake N, Kotani K, Komatsu R, Itoh N, Mineo I, Wada J, Masuzaki H, Yoneda M, Nakajima A, Funahashi T, Miyazaki S, Tokunaga K, Kawamoto M, Ueno T, Hamaguchi K, Tanaka K, Yamada K, Hanafusa T, Oikawa S, Yoshimatsu H, Nakao K, Sakata T, Matsuzawa Y, Kamatani N and Nakamura Y

    Laboratory for Endocrinology and Metabolism, Center for Genomic Medicine, RIKEN, Yokohama, Japan. kikuko@src.riken.jp

    There is evidence that the obesity phenotype in the Caucasian populations is associated with variations in several genes, including neuronal growth regulator 1 (NEGR1), SEC16 homolog B (SCE16B), transmembrane protein 18 (TMEM18), ets variant 5 (ETV5), glucosamine-6-phosphate deaminase 2 (GNPDA2), prolactin (PRL), brain-derived neurotrophic factor (BDNF), mitochondrial carrier homolog 2 (MTCH2), Fas apoptotic inhibitory molecule 2 (FAIM2), SH2B adaptor protein 1 (SH2B1), v-maf musculoaponeurotic fibrosarcoma oncogene homolog (MAF), Niemann-Pick disease, type C1 (NPC1), melanocortin 4 receptor (MC4R) and potassium channel tetramerisation domain containing 15 (KCTD15). To investigate the relationship between obesity and these genes in the Japanese population, we genotyped 27 single-nucleotide polymorphisms (SNPs) in 14 genes from obese subjects (n=1129, body mass index (BMI) > or =30 kg m(-2)) and normal-weight control subjects (n=1736, BMI <25 kg m(-2)). The SNP rs10913469 in SEC16B (P=0.000012) and four SNPs (rs2867125, rs6548238, rs4854344 and rs7561317) in the TMEM18 gene (P=0.00015), all of which were in almost absolute linkage disequilibrium, were significantly associated with obesity in the Japanese population. SNPs in GNPDA2, BDNF, FAIM2 and MC4R genes were marginally associated with obesity (P<0.05). Our data suggest that some SNPs identified by genome-wide association studies in the Caucasians also confer susceptibility to obesity in Japanese subjects.

    Journal of human genetics 2009;54;12;727-31

  • Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference.

    Bauer F, Elbers CC, Adan RA, Loos RJ, Onland-Moret NC, Grobbee DE, van Vliet-Ostaptchouk JV, Wijmenga C and van der Schouw YT

    Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, Utrecht, Netherlands.

    Background: New genetic loci, most of which are expressed in the brain, have recently been reported to contribute to the development of obesity. The brain, especially the hypothalamus, is strongly involved in regulating weight and food intake.

    Objectives: We investigated whether the recently reported obesity loci are associated with measures of abdominal adiposity and whether these variants affect dietary energy or macronutrient intake.

    Design: We studied 1700 female Dutch participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Their anthropometric measurements and intake of macronutrients were available. Genotyping was performed by using KASPar chemistry. A linear regression model, with an assumption of an additive effect, was used to analyze the association between genotypes of 12 single nucleotide polymorphisms (SNPs) and adiposity measures and dietary intake.

    Results: Seven SNPs were associated (P < 0.05) with weight, body mass index (BMI), and waist circumference (unadjusted for BMI). They were in or near to 6 loci: FTO, MC4R, KCTD15, MTCH2, NEGR1, and BDNF. Five SNPs were associated with dietary intake (P < 0.05) and were in or near 5 loci: SH2B1 (particularly with increased fat), KCTD15 (particularly with carbohydrate intake), MTCH2, NEGR1, and BDNF.

    Conclusions: We confirmed some of the findings for the newly identified obesity loci that are associated with general adiposity in a healthy Dutch female population. Our results suggest that these loci are not specifically associated with abdominal adiposity but more generally with obesity. We also found that some of the SNPs were associated with macronutrient-specific food intake.

    Funded by: Medical Research Council: MC_U106188470

    The American journal of clinical nutrition 2009;90;4;951-9

  • Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden.

    Renström F, Payne F, Nordström A, Brito EC, Rolandsson O, Hallmans G, Barroso I, Nordström P, Franks PW and GIANT Consortium

    Department of Public Health and Clinical Medicine, Umeå University Hospital, Umeå, Sweden.

    Recent genome-wide association studies (GWAS) have identified multiple risk loci for common obesity (FTO, MC4R, TMEM18, GNPDA2, SH2B1, KCTD15, MTCH2, NEGR1 and PCSK1). Here we extend those studies by examining associations with adiposity and type 2 diabetes in Swedish adults. The nine single nucleotide polymorphisms (SNPs) were genotyped in 3885 non-diabetic and 1038 diabetic individuals with available measures of height, weight and body mass index (BMI). Adipose mass and distribution were objectively assessed using dual-energy X-ray absorptiometry in a sub-group of non-diabetics (n = 2206). In models with adipose mass traits, BMI or obesity as outcomes, the most strongly associated SNP was FTO rs1121980 (P < 0.001). Five other SNPs (SH2B1 rs7498665, MTCH2 rs4752856, MC4R rs17782313, NEGR1 rs2815752 and GNPDA2 rs10938397) were significantly associated with obesity. To summarize the overall genetic burden, a weighted risk score comprising a subset of SNPs was constructed; those in the top quintile of the score were heavier (+2.6 kg) and had more total (+2.4 kg), gynoid (+191 g) and abdominal (+136 g) adipose tissue than those in the lowest quintile (all P < 0.001). The genetic burden score significantly increased diabetes risk, with those in the highest quintile (n = 193/594 cases/controls) being at 1.55-fold (95% CI 1.21-1.99; P < 0.0001) greater risk of type 2 diabetes than those in the lowest quintile (n = 130/655 cases/controls). In summary, we have statistically replicated six of the previously associated obese-risk loci and our results suggest that the weight-inducing effects of these variants are explained largely by increased adipose accumulation.

    Funded by: Wellcome Trust: 090532

    Human molecular genetics 2009;18;8;1489-96

  • Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

    Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, Berndt SI, Elliott AL, Jackson AU, Lamina C, Lettre G, Lim N, Lyon HN, McCarroll SA, Papadakis K, Qi L, Randall JC, Roccasecca RM, Sanna S, Scheet P, Weedon MN, Wheeler E, Zhao JH, Jacobs LC, Prokopenko I, Soranzo N, Tanaka T, Timpson NJ, Almgren P, Bennett A, Bergman RN, Bingham SA, Bonnycastle LL, Brown M, Burtt NP, Chines P, Coin L, Collins FS, Connell JM, Cooper C, Smith GD, Dennison EM, Deodhar P, Elliott P, Erdos MR, Estrada K, Evans DM, Gianniny L, Gieger C, Gillson CJ, Guiducci C, Hackett R, Hadley D, Hall AS, Havulinna AS, Hebebrand J, Hofman A, Isomaa B, Jacobs KB, Johnson T, Jousilahti P, Jovanovic Z, Kraft P, Kuokkanen M, Kuusisto J, Laitinen J, Lakatta EG, Luan J, Luben RN, Mangino M, McArdle WL, Meitinger T, Mulas A, Munroe PB, Narisu N, Ness AR, Northstone K, O'Rahilly S, Purmann C, Rees MG, Ridderstråle M, Ring SM, Rivadeneira F, Ruokonen A, Sandhu MS, Saramies J, Scott LJ, Scuteri, Silander K, Sims MA, Song K, Stephens J, Stevens S, Stringham HM, Tung YC, Valle TT, Van Duijn CM, Vimaleswaran KS, Vollenweider P, Waeber G, Wallace C, Watanabe RM, Waterworth DM, Watkins N, Wellcome Trust Case Control Consortium, Witteman JC, Zeggini E, Zhai G, Zillikens MC, Altshuler D, Caulfield MJ, Chanock SJ, Farooqi IS, Ferrucci L, Guralnik JM, Hattersley AT, Hu FB, Jarvelin MR, Laakso M, Mooser V, Ong KK, Ouwehand WH, Salomaa V, Samani NJ, Spector TD, Tuomi T, Tuomilehto J, Uda M, Uitterlinden AG, Wareham NJ, Deloukas P, Frayling TM, Groop LC, Hayes RB, Hunter DJ, Mohlke KL, Peltonen L, Schlessinger D, Strachan DP, Wichmann HE, McCarthy MI, Boehnke M, Barroso I, Abecasis GR, Hirschhorn JN and Genetic Investigation of ANthropometric Traits Consortium

    Genetic Investigation of ANthropometric Traits Consortium.

    Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

    Funded by: British Heart Foundation: FS/05/061/19501; Intramural NIH HHS; Medical Research Council: G0000649, G0000934, G0400874, G0401527, G0600705, G0601261, G0701863, G0800582, G9521010, G9815508, G9824984, MC_U105630924, MC_U106179471, MC_U106179472, MC_U106188470, MC_U147585819, MC_UP_A620_1014, U.1475.00.003.00010.02 (85819); NCI NIH HHS: 5UO1CA098233, CA49449, CA50385, CA65725, CA67262, CA87969, P01 CA087969, R01 CA049449, R01 CA050385, R01 CA065725, R01 CA067262, U01 CA049449, U01 CA067262, U01 CA098233; NHGRI NIH HHS: 01-HG-65403, 1Z01 HG000024, HG02651, N01HG65403, R01 HG002651, Z01 HG000024; NHLBI NIH HHS: HL084729, HL087679, R01 HL087679, U01 HL084729; NIA NIH HHS: N01-AG-1-2109; NIDDK NIH HHS: DK062370, DK072193, DK075787, F32 DK079466, F32 DK079466-01, K23 DK067288, K23 DK080145, K23 DK080145-01, R01 DK029867, R01 DK062370, R01 DK072193, R01 DK075787, R56 DK062370, T32 DK007191, T32DK07191, U01 DK062370; NIMH NIH HHS: 1RL1MH083268, RL1 MH083268; Wellcome Trust: 068545/Z/02, 076113, 076467/Z/05/Z, 077011, 077016, 079557, 082390, 089061, 090532

    Nature genetics 2009;41;1;25-34

  • Mitochondrial carrier homolog 2 is a target of tBID in cells signaled to die by tumor necrosis factor alpha.

    Grinberg M, Schwarz M, Zaltsman Y, Eini T, Niv H, Pietrokovski S and Gross A

    Department of Biological Regulation, Weizmann Institute of Science, Rehovot 76100, Israel.

    BID, a proapoptotic BCL-2 family member, plays an essential role in the tumor necrosis factor alpha (TNF-alpha)/Fas death receptor pathway in vivo. Activation of the TNF-R1 receptor results in the cleavage of BID into truncated BID (tBID), which translocates to the mitochondria and induces the activation of BAX or BAK. In TNF-alpha-activated FL5.12 cells, tBID becomes part of a 45-kDa cross-linkable mitochondrial complex. Here we describe the biochemical purification of this complex and the identification of mitochondrial carrier homolog 2 (Mtch2) as part of this complex. Mtch2 is a conserved protein that is similar to members of the mitochondrial carrier protein family. Our studies with mouse liver mitochondria indicate that Mtch2 is an integral membrane protein exposed on the surface of mitochondria. Using blue-native gel electrophoresis we revealed that in viable FL5.12 cells Mtch2 resides in a protein complex of ca. 185 kDa and that the addition of TNF-alpha to these cells leads to the recruitment of tBID and BAX to this complex. Importantly, this recruitment was partially inhibited in FL5.12 cells stably expressing BCL-X(L). These results implicate Mtch2 as a mitochondrial target of tBID and raise the possibility that the Mtch2-resident complex participates in the mitochondrial apoptotic program.

    Molecular and cellular biology 2005;25;11;4579-90

  • Automated yeast two-hybrid screening for nuclear receptor-interacting proteins.

    Albers M, Kranz H, Kober I, Kaiser C, Klink M, Suckow J, Kern R and Koegl M

    PheneX Pharmaceuticals AG, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany.

    High throughput analysis of protein-protein interactions is an important sector of hypothesis-generating research. Using an improved and automated version of the yeast two-hybrid system, we completed a large interaction screening project with a focus on nuclear receptors and their cofactors. A total of 425 independent yeast two-hybrid cDNA library screens resulted in 6425 potential interacting protein fragments involved in 1613 different interaction pairs. We show that simple statistical parameters can be used to narrow down the data set to a high confidence set of 377 interaction pairs where validated interactions are enriched to 61% of all pairs. Within the high confidence set, there are 64 novel proteins potentially binding to nuclear receptors or their cofactors. We discuss several examples of high interest, and we expect that communication of this huge data set will help to complement our knowledge of the protein interaction repertoire of this family of transcription factors and instigate the characterization of the various novel candidate interactors.

    Molecular & cellular proteomics : MCP 2005;4;2;205-13

  • 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

  • Met-HGF/SF signal transduction induces mimp, a novel mitochondrial carrier homologue, which leads to mitochondrial depolarization.

    Yerushalmi GM, Leibowitz-Amit R, Shaharabany M and Tsarfaty I

    Department of Human Microbiology, Sackler Faculty of Medicine, Tel-Aviv University, Israel.

    Met-hepatocyte growth factor/scatter factor (HGF/SF) signaling plays an important role in epithelial tissue morphogenesis, lumen formation, and tumorigenicity. We have recently demonstrated that HGF/SF also alters the metabolic activity of cells by enhancing both the glycolytic and oxidative phosphorylation pathways of energy production. Using differential display polymerase chain reaction, we cloned a novel gene, designated mimp (Met-Induced Mitochondrial Protein), which is upregulated in NIH-3T3 cells cotransfected with both HGF/SF and Met (HMH cells). Northern and Western blot analyses showed that mimp is induced in several Met-expressing cell lines following treatment with HGF/SF. Mimp encodes a 33-kDa protein that shows sequence homology to the family of mitochondrial carrier proteins (MCPs). Murine Mimp (mMimp) is expressed in a wide variety of tissues, exhibiting an expression pattern similar to Met. Predominant expression is seen in liver, kidney, heart, skeletal muscle, and testis. Using immunostaining for HA-tagged mMimp and a GFP-mMimp chimeric protein as well as subcellular fractionation, we determined that Mimp is primarily localized to the mitochondria. Ectopic expression of mMimp in the Met-responsive adenocarcinoma cell line, DA3, reduced the mitochondrial membrane potential (uncoupling activity). The extent of the mitochondrial depolarization positively correlated with the level of Mimp expression. Our results demonstrate that Mimp is a novel mitochondrial carrier homologue upregulated by Met-HGF/SF signal transduction, which leads to mitochondrial depolarization, and suggest novel links among tyrosine kinase signaling, mitochondrial function, and cellular bioenergetics.

    Neoplasia (New York, N.Y.) 2002;4;6;510-22

  • Cloning and functional analysis of cDNAs with open reading frames for 300 previously undefined genes expressed in CD34+ hematopoietic stem/progenitor cells.

    Zhang QH, Ye M, Wu XY, Ren SX, Zhao M, Zhao CJ, Fu G, Shen Y, Fan HY, Lu G, Zhong M, Xu XR, Han ZG, Zhang JW, Tao J, Huang QH, Zhou J, Hu GX, Gu J, Chen SJ and Chen Z

    Shanghai Institute of Hematology (SIH), Rui Jin Hospital affiliated with Shanghai Second Medical University, Shanghai 200025, China.

    Three hundred cDNAs containing putatively entire open reading frames (ORFs) for previously undefined genes were obtained from CD34+ hematopoietic stem/progenitor cells (HSPCs), based on EST cataloging, clone sequencing, in silico cloning, and rapid amplification of cDNA ends (RACE). The cDNA sizes ranged from 360 to 3496 bp and their ORFs coded for peptides of 58-752 amino acids. Public database search indicated that 225 cDNAs exhibited sequence similarities to genes identified across a variety of species. Homology analysis led to the recognition of 50 basic structural motifs/domains among these cDNAs. Genomic exon-intron organization could be established in 243 genes by integration of cDNA data with genome sequence information. Interestingly, a new gene named as HSPC070 on 3p was found to share a sequence of 105bp in 3' UTR with RAF gene in reversed transcription orientation. Chromosomal localizations were obtained using electronic mapping for 192 genes and with radiation hybrid (RH) for 38 genes. Macroarray technique was applied to screen the gene expression patterns in five hematopoietic cell lines (NB4, HL60, U937, K562, and Jurkat) and a number of genes with differential expression were found. The resource work has provided a wide range of information useful not only for expression genomics and annotation of genomic DNA sequence, but also for further research on the function of genes involved in hematopoietic development and differentiation.

    Genome research 2000;10;10;1546-60

  • Construction and characterization of a full length-enriched and a 5'-end-enriched cDNA library.

    Suzuki Y, Yoshitomo-Nakagawa K, Maruyama K, Suyama A and Sugano S

    International and Interdisciplinary Studies, The University of Tokyo, Japan.

    Using 'oligo-capped' mRNA [Maruyama, K., Sugano, S., 1994. Oligo-capping: a simple method to replace the cap structure of eukaryotic mRNAs with oligoribonucleotides. Gene 138, 171-174], whose cap structure was replaced by a synthetic oligonucleotide, we constructed two types of cDNA library. One is a 'full length-enriched cDNA library' which has a high content of full-length cDNA clones and the other is a '5'-end-enriched cDNA library', which has a high content of cDNA clones with their mRNA start sites. The 5'-end-enriched library was constructed especially for isolating the mRNA start sites of long mRNAs. In order to characterize these libraries, we performed one-pass sequencing of randomly selected cDNA clones from both libraries (84 clones for the full length-enriched cDNA library and 159 clones for the 5'-end-enriched cDNA library). The cDNA clones of the polypeptide chain elongation factor 1 alpha were most frequently (nine clones) isolated, and more than 80% of them (eight clones) contained the mRNA start site of the gene. Furthermore, about 80% of the cDNA clones of both libraries whose sequence matched with known genes had the known 5' ends or sequences upstream of the known 5' ends (28 out of 35 for the full length-enriched library and 51 out of 62 for the 5'-end-enriched library). The longest full-length clone of the full length-enriched cDNA library was about 3300 bp (among 28 clones). In contrast, seven clones (out of the 51 clones with the mRNA start sites) from the 5'-end-enriched cDNA library came from mRNAs whose length is more than 3500 bp. These cDNA libraries may be useful for generating 5' ESTs with the information of the mRNA start sites that are now scarce in the EST database.

    Gene 1997;200;1-2;149-56

  • Oligo-capping: a simple method to replace the cap structure of eukaryotic mRNAs with oligoribonucleotides.

    Maruyama K and Sugano S

    Institute of Medical Science, University of Tokyo, Japan.

    We have devised a method to replace the cap structure of a mRNA with an oligoribonucleotide (r-oligo) to label the 5' end of eukaryotic mRNAs. The method consists of removing the cap with tobacco acid pyrophosphatase (TAP) and ligating r-oligos to decapped mRNAs with T4 RNA ligase. This reaction was made cap-specific by removing 5'-phosphates of non-capped RNAs with alkaline phosphatase prior to TAP treatment. Unlike the conventional methods that label the 5' end of cDNAs, this method specifically labels the capped end of the mRNAs with a synthetic r-oligo prior to first-strand cDNA synthesis. The 5' end of the mRNA was identified quite simply by reverse transcription-polymerase chain reaction (RT-PCR).

    Gene 1994;138;1-2;171-4

Gene lists (7)

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
L00000010 G2C Homo sapiens Human mitochondria Human orthologues of mouse mitochondria adapted from Collins et al (2006) 91
L00000016 G2C Homo sapiens Human PSP Human orthologues of mouse PSP adapted from Collins et al (2006) 1121
L00000059 G2C Homo sapiens BAYES-COLLINS-HUMAN-PSD-CONSENSUS Human cortex PSD consensus 748
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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