Domestic Animal Endocrinology 50 (2015) 65–71

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Expression of variant transcripts of the potassium channel tetramerization domain-containing 15 (KCTD15) gene and their association with fatness traits in chickens S.S. Liang a, b, H.J. Ouyang a, b, J. Liu a, b, B. Chen a, b, Q.H. Nie a, b, *, X.Q. Zhang a, b a

Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 9 April 2014 Received in revised form 19 September 2014 Accepted 22 September 2014

The aim of this study was to characterize the structure, expression, and biological functions of potassium channel tetramerization domain containing 15 (KCTD15) in chickens. We compared the KCTD15 expression level in samples of hypothalamic, adipose, and liver tissue of Xinghua chickens that were maintained on different dietary status. An association analysis of KCTD15 gene variant transcripts with fatness traits in a F2 resource population of chickens was performed. Three KCTD15 transcripts were identified in which the complete transcript was predominantly expressed in adipose tissue and the hypothalamus. The chicken KCTD15 gene was regulated by both feeding and fasting and consumption of a high-fat diet. The expression level of KCTD15 gene was markedly decreased in hypothalamus and liver of fasted and refed chickens (P < 0.05) and significantly downregulated in adipose tissue by the high-fat diet (P < 0.05). Three single-nucleotide polymorphisms of the KCTD15 gene were significantly associated with a number of fatness traits in chicken (P < 0.05). These results suggest that KCTD15 have a potential role regulation of obesity and fat metabolism in chickens. Ó 2014 Elsevier Inc. All rights reserved.

Keywords: KCTD15 Chicken Gene expression Fatness Association analysis

1. Introduction Obesity is a major public health problem because of an increased risk for development of several diseases and imposition of severe economic burdens on health care systems [1,2]. The prevalence of obesity has dramatically increased worldwide during the past years. Recently, many genome-wide association studies showed that potassium channel tetramerization domain containing 15 (KCTD15) gene was significantly associated with both body mass index and weight in adult of various populations, including European [3,4,5,6], Chinese [7,8], Americans [9], and Japanese [10]. This result was also confirmed in children and adolescents [11,12,13,14].

* Corresponding author. Tel.: þ86 20 85285759; fax: þ86 20 85280740. E-mail address: [email protected] (Q.H. Nie). 0739-7240/$ – see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.domaniend.2014.09.006

A family of T1 domain containing proteins (the KCTD family) was described in recent years [15,16]. The KCTD family shares a common N-terminal domain. It is a close relative of the BTB (Broad-Complex, Tramtrack and Bric-a-brac)/POZ (poxvirus and zinc finger) domain, which is a major proteinprotein interaction motif found in viruses and throughout eukaryotes [17]. The KCTD proteins play an important role in cell differentiation and vertebrate development [18]. As a member of the KCTD family, KCTD15 encodes a protein with BTB domain and inhibits neural crest induction [19,20], and it could have transcription factor activity because of its sequence homology to KCTD1 [21]. Another voltage-gated K channel, Kv1.3, has been reported to regulate body weight, glucose uptake, insulin sensitivity, and energy homeostasis [22,23]. It is possible that KCTD15 could have similar functions. Obesity is a result of an imbalance between food intake and energy expenditure. The KCTD15 gene was highly

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expressed in the hypothalamus, which is a crucial center for energy balance and regulation of food intake [4,24,25]. The highest expression of KCTD15 was also found for rats and mice in the hypothalamus [26,27]. The single-nucleotide polymorphisms (SNPs) of KCTD15 were associated with dietary intake, including carbohydrate and fat intake. A recent study in mice showed that the messenger RNA (mRNA) level of KCTD15 was dependent on the nutritional status [27], its expression was upregulated in hypothalamus and adipose tissue of fed mice and downregulated by high-fat feeding in adipose tissue and the hypothalamus. Decreased KCTD15 expression was also found in hypothalamus and adipose tissues of rats that fed on a high-fat diet [28]. This suggests a central regulation role of KCTD15 gene on energy balance. Fatness traits are important economic traits in chickens, the fat mass play an important role in the meat quality and flavor of chicken. The KCTD15 gene was found to be associated with multiple meat quality traits in swine [29]. There were very less information about KCTD15 gene in chicken and whether it might be linked to fatness traits remains unknown. In this study, we identified the chicken KCTD15 gene and monitored its mRNA level in various tissues under different conditions of nutrition and performed association analysis of KCTD15 SNPs with fatness traits in chicken, so as to first characterize the KCTD15 gene in poultry. 2. Materials and methods 2.1. Ethics statement All animal experiments were handled in compliance with and approved by the Animal Care Committee of South China Agricultural University (Guangzhou, People’s Republic of China) (approval number: SCAU#0011). All efforts were made to minimize suffering to animal.

2.3. RNA isolation and complementary DNA synthesis Chickens were euthanized, and 16 tissues (cerebrum, cerebellum, hypothalamus, pituitary, abdominal fat, subcutaneous fat, breast muscle, heart, liver, spleen, lungs, kidney, muscular stomach, glandular stomach, duodenum, and ovary and/or testis) were rapidly dissected and immediately placed in liquid nitrogen then stored at 80 C. Total RNA was extracted from each tissue using Trizol reagent (Invitrogen, Foster City, CA), following the manufacturer’s protocol. The quality and quantity of all obtained RNA samples were determined by 1.5% agarose gel electrophoresis and evaluated for optical density 260/280 ratio. A RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific, Femantas, CA) was used to synthesize complementary DNA (cDNA) from 2 mg total RNA. 2.4. Primers Primers were designed by Premier Primer 5.0 software (Premier Biosoft International, Palo Alto, CA) and synthesized by Biosune Co Ltd (Shanghai, China). Primers of KF1KR1 and KF2-KR2 were used to clone partial cDNA of cKCTD15. Other 3 primers (K50 -R1, K50 -R2, and K50 -R3) were used to clone the full-length KCTD15 cDNA of chicken. QKF1-QKR1 was used for real-time polymerase chain reaction (PCR) analysis of cKCTD15. SKF1-SKR1, SKF2-SKR2, and SKF3-SKR3 were used to identify and genotype SNPs of cKCTD15 (Supplementary Table 1). 2.5. 50 RACE and 30 RACE PCR The hypothalamus and adipose tissue total RNA were used as template for RACE PCR, which was performed with the SMARTer RACE cDNA Amplification Kit (Clontech, Osaka, Japan) following the manufacturer’s instructions. Products of RACE PCR were cloned into pMD-18T vector (Takara, Osaka, Japan) and sequenced by Invitrogen Co Ltd (Guangzhou, China).

2.2. Animals and DNA samples

2.6. KCTD15 database and phylogenetic analysis

A total of 35 Xinghua (XH) chickens (10 males and 10 females at 14 wk of age; 15 females at 20 wk of age, respectively) were raised in individual cages and kept in identical light/dark cycles. The 14-wk-old chickens were divided into 2 groups (n ¼ 10, 5 males and 5 females each) and fed a high-fat diet (lard oil 20%, cholesterol 2%, cholate 0.5%, yolk power 5%, and basal diet 72.5%) or a basal diet, respectively. The high-fat diet was bought from Botai biology Co Ltd (Beijing, China), and nutrient information was listed in Supplementary Table 1. Chickens had ad libitum access to water and their respective diets for 2 wk. The Xinghua chickens at 20 wk were divided into chow fed, fasted, and refed groups, each group comprising 5 female chickens. The fasted group was fasted for 3 d during which they had ad libitum access to water. The refed group was fed the basal diet 1 d after the chickens were fasted for 3 d. The DNA samples from an F2 resource population crossed from XH and white recessive rock (XH and WRR), previously described by Lei et al [30], were used for association analysis of KCTD15 variations with fatness traits.

The full-length KCTD15 cDNA sequences of the other 16 species were obtained from Genebank (human NM_ 001129994.1, mouse NM_146188.1, rat NM_001109141.1, cat XM_003997946.2, dog XM_541709.3, cattle NM_001075568.1, goat XM_005692247.1, horse XM_001489117.2, frog NM_ 203908.1, mallard XM_005019976.1, zebra finch XM_ 002188719.2, ground finch XM_005428465.1, ground tit XM_005530122.1, budgerigar XM_005152184.1, pigeon XM_005514436.1, and saker XM_005444627.1). The obtained cDNA sequences were analyzed by Basic Local Alignment Search Tool (BLAST) (http://blast.ncbi.nlm.nih. gov/Blast.cgi). On the basis of the 17 KCTD15 sequences, a phylogenetic tree was constructed by using neighborjoining method of the MEGA 4.1 (http://www.megasoft ware.net/mega41.html) program. 2.7. Real-time PCR analysis The relative quantity of mRNA was detected using SsoFast EvaGreen Supermix and CFX9600 (BIO-RAD, Hercules), for which the chicken b-actin was used as an internal

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control. Each sample was assayed in triplicate, following the manufacturer’s instructions. The specificity of the product was decided by the solubility curve, and the quantitative values were obtained from the threshold PCR cycle number (Ct) at which the increase in signal associated with an exponential growth for PCR product starts to be detected. The relative mRNA level in each sample was indicated by 2DCt (DCt ¼ Ct target gene  Ct ß-actin). 2.8. Identification of SNP and genotyping Chicken KCTD15 SNPs was obtained from NCBI database and confirmed in our F2 resource population (XH and WRR). The confirmed SNPs were genotyped by PCR-restriction fragment length polymorphism in F2 resource population (XH and WRR). PCR was performed in 10 mL of a mixture containing 50 ng of chicken genomic DNA, 5 pmol of primers, and 5 mL PCR Master Mix (Transgen, Beijing, China) and using the following protocol: 94 C for 3 min, followed by 32 cycles of 30 s at 94 C, 30 s at annealing temperature (58 C–62 C), 30 s at 72 C and 72 C for 5 min at last. PCR products were digested by fasted restriction enzymes (Femantas, CA) following the manufacturer’s instructions and then detected through 2% agarose gel electrophoresis.

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BLAT showed that the chicken KCTD15 was located at chromosome 11 and spanned about 40 Kb. The cKCTD15-a comprised 6 exons and 5 introns, and the cKCTD15-b had the same exons and introns with cKCTD15-a except for a 129 bp deletion at exon 1, whereas the cKCTD15-c only had 3 exons and 2 introns (Fig. 1). The cKCTD15-a and cKCTD15b shared the same 795 bp open reading frame encoding 264 amino acids (AA). The open reading frame of cKCTD15c was 414 bp long, which produced a short KCTD15 precursor of 137 AA (Fig. 2). 3.2. Sequence alignment and phylogeny analysis Blast analysis of KCTD15 among 17 species showed that within 2 conserved domains (40th–127th AA and 149th– 211st AA), the 40–127th AA was a typical BTB/POZ domains of BTB superfamily. The amino acid sequences of KCTD15 were conservative; it had a percent identity of above 98% to other birds, among 89% to92% to mammalians and 94.9% to frog, respectively. The generated phylogenetic tree showed that the 17 species were divided into 2 distinct groups. The first group included 8 mammalian species, whereas the other group contained the chicken along with 7 other bird species and a frog species (Supplementary Fig. 1).

2.9. Statistical analysis 3.3. Tissue specific expression of KCTD15 in XH chicken The SNPs that do not follow Hardy-Weinberg equilibrium were excluded from association analysis. Association analysis of SNPs and fatness traits were performed using the General Linear Models Procedures of SAS 9.0 (SAS Institute Inc, Cary, NC) using the following model:

Yijkl ¼ m þ Si þ Gj þ Hk þ Fl þ eijkl where Y represents the traits’ phenotypic values; m, the overall population mean; S, the effect of gender; G, the effect of genotype; H, the effect of incubation batch; F, the effect of family; e, the random residuals. 3. Results 3.1. The chicken KCTD15 cDNA and variant transcripts Three KCTD15 transcripts were identified in chickens, cKCTD15-a (NCBI accession number: JX500454) was 1377 bp long, cKCTD15-b (JX500455) was 1248 bp long, and cKCTD15-c (JX500456) was 1153 bp long. UCSC genome

Chicken KCTD15 gene was expressed in all 17 tested tissues, and the expression level was not significantly different between female and male chickens (P > 0.05) (Fig. 3). The expression level of chicken KCTD15 gene was the highest in abdominal fat and fairly high in subcutaneous fat, hypothalamus, and duodenum. The expression level was low in other tissues, especially in kidney. 3.4. The effects of dietary status on cKCTD15 mRNA level Chicken KCTD15 gene was regulated by both feeding and fasting and by consumption of a high-fat diet. Chicken KCTD15 expression was downregulated in all detected tissue in both fasted and refed chickens (Fig. 4). In the fasted chickens, the mRNA level of cKCTD15 both decreased by 64.3% (P < 0.05) in liver and hypothalamus, but no significant difference was found in adipose tissue compared with chowfed control (P > 0.05). In the refed chickens, the mRNA level of cKCTD15 decreased by 73.0% (P < 0.05) in liver, 83.6% (P < 0.05) in hypothalamus, and 87.5% (P < 0.05) in abdominal fat,

Fig. 1. Structure of 3 variant transcripts of chicken KCTD15.

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Fig. 2. The open reading frame of cKCTD15-a, b, and c. The bold letter at 237 is initiation codon of the cKCTD15-a and cKCTD15-b, and the bold letter at 612 is initiation codon of the cKCTD15-c.

but no significant difference was found in the subcutaneous fat compared with chow-fed control (P > 0.05). Compared with chow-fed chicken, cKCTD15 expression of high-fat diet chickens was downregulated in the hypothalamus, abdominal fat, and subcutaneous fat but upregulated in liver. In male chickens, the mRNA level of cKCTD15 decreased by 73.0% (P < 0.05) in abdominal fat (Fig. 5A). In female chickens, the mRNA level of cKCTD15 decreased by 44.4% (P > 0.05) in the hypothalamus, 60.0% (P < 0.05) in abdominal fat, and 63.0% (P < 0.01) in subcutaneous fat (Fig. 5B), whereas increased by 1.4-folds (P > 0.05) in liver.

3.5. SNPs association analysis with fatness traits The cKCTD15 SNPs were genotyped in F2 resource population (XH and WRR) for association analysis with fatness traits. Three SNPs in cKCTD15 gene were found to be significantly associated with a number of fatness traits in chickens (Table 1). Among them, g.7300C > T (rs15616322) was associated with subcutaneous fat thickness and abdominal fat pad weight (AFW) (P < 0.01); g.32333C > T (rs14964286) was also associated with AFW (P < 0.05); g.7414 A > G was highly significantly associated with

Fig. 3. Expression of KCTD15 gene in adult XH chicken tissues. The horizontal axis and vertical axis indicate different tissues and relative expression value (mean  SD) each. Abd, abdominal fat; Ceb, cerebellum; Cer, cerebrum; Chm, breast muscle; Dub, duodenum; Gst, glandular stomach; Hea, heart; Hyp, hypothalamus; Kid, kidney; Liv, liver; Lun, lung; mRNA, messenger RNA; Mst, muscular stomach; Ova, ovary; Pit, pituitary; SD, standard deviation; Spl, spleen; Suf, subcutaneous fat; Tes, testis; XH, Xinghua.

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Fig. 4. Level of cKCTD15 mRNA in chow fed, fasted, and refed XH chicken. Data are presented as the mean  SEM, *P < 0.05, **P < 0.01. Abd, abdominal fat; Hyp, hypothalamus; Liv, liver; mRNA, messenger RNA; SEM, standard error of the mean; Suf, subcutaneous fat; XH, Xinghua.

muscle flesh color and breast muscle shear stress extremely significantly (P < 0.01). 4. Discussion Three novel chicken KCTD15 transcripts were identified by this study, 2 of which encoded the same 264 AA peptide, whereas the third one encoded a short KCTD15 precursor of 137 AA. This finding is similar with human KCTD15, which also have 3 transcripts encoding 2 different peptides [31,32]. KCTD protein family belongs to a large superfamily with a common BTB domain [33]. BLAST analysis of KCTD15 found that chicken KCTD15 has a typical BTB/POZ domain. Phylogenetic analysis showed that amino acid sequence of KCTD15 was conservative, because the homology of chicken and frog was up to 94.1% as reported previously [34]. It is known that several KCTD family members are expressed in the nervous system [35,36]. KCTD15 gene was found highly expressed in the brain in Xenopus [34], zebrafish [37], and human [3]. In mice and rats, it was reported highly expressed both in hypothalamus and adipose tissue [27,28]. Similar to previous studies, our result showed that chicken KCTD15 also predominantly expressed in the hypothalamus and adipose tissues (subcutaneous fat and abdominal fat). We found that chicken KCTD15 was widely expressed in various tissues and was not affected by gender.

Fig. 5. Level of cKCTD15 mRNA with chow fed and high-fat diets in (A) male and (B) female XH chicken. Data are presented as the mean  SEM, *P < 0.05, **P < 0.01. mRNA, messenger RNA; SEM, standard error of the mean; XH, Xinghua.

Many genes involved in metabolism and maintaining energy balance are regulated in response to nutrition status or by dietary components. Identification of such regulatory patterns would provide potential information for the formation of obesity. In this study, we detected the dynamic KCTD15 expression in different dietary status conditions in the hypothalamus, a central area in regulating energy homeostasis and food intake, as well as in metabolically important peripheral organs, including adipose tissue and liver. We found that chicken KCTD15 gene was regulated by both feeding and fasting and by consumption of a high-fat diet. KCTD15 expression was downregulated in the hypothalamus and adipose tissue of fasted, refed, and high-fat diet chickens. These results were similar with other studies in mice and rats. Recent studies showed that KCTD15

Table 1 Association of fatness traits and KCTD15 SNPs. Markers

Traits

P-value

Least-squares mean  SEM

g.7300C > T

SFT (mm) AFW (g) AFW (g) BMF LMF BMSS

0.0095 0.0474 0.0274 0.0021 0.0065 T g.7414A > G

     

0.23 1.59 1.38 0.61 0.54 0.64

(TT, 258) (TT, 258) (TT, 61) (GG, 78) (GG, 78) (GG, 78)

4.04 28.7 26.5 54.7 65.0 30.8

     

0.15 1.45 1.40 0.69 0.62 0.73

(TC, 187) (TC, 187) (TC, 194) (GA, 168) (GA, 168) (GA, 168)

4.63 27.6 25.5 56.7 64.9 33.0

     

0.19 1.62 1.82 1.04 0.92 1.09

(CC, 19) (CC, 19) (CC, 205) (AA, 220) (AA, 220) (AA, 220)

Abbreviations: AFW, abdominal fat pad weight; BMF, breast muscle flesh color; BMSS, breast muscle shear stress; LMF, leg muscle flesh color; SEM, standard error of the mean; SFT, subcutaneous fat thickness; SNPs, single-nucleotide polymorphisms.

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expression was downregulated in the hypothalamus, brain, and adipose tissue of fasted mice and also significantly decreased in adipose tissue of mice and rats with high-fat diet [27,28]. The mRNA level of KCTD15 responds to highfat diet similar in the male and female chickens. A high-fat diet could promote metabolism of fat synthesis in liver; KCTD15 may be involved in this process, so it increased in liver and decreased in adipose tissue by feedback inhibition; the fasted experiment also showed that KCTD15 decreased in liver and adipose tissue of fasted chickens. Interestingly, compared with the fasted group, KCTD15 expression did not return but it decreased in the refed group. This phenomenon is very unusual; it need furthermore study to elucidate the function of chicken KCTD15. The genomic structure of chicken KCTD15 gene was different from that of human and mouse. The chicken KCTD15 gene spanned over 40 Kb in length which was longer than that of human and mouse (about 20 Kb and 13 Kb, respectively). UCSC genome BLAT showed that cKCTD15-a comprised 6 exons and 5 introns, the second exon was located in 1 genome gap. A total of 96 SNPs were provided by NCBI SNP database across the whole chicken KCTD15 gene, most of which were in introns. Three cKCTD15 SNPs were found to be significantly associated with fatness traits, such as subcutaneous fat thickness and AFW. The associations of cKCTD15 SNPs with fatness traits support the functional importance of this gene in chickens, which was similar to that in mammals. 5. Conclusion This is the first study to report 3 chicken KCTD15 transcripts. The chicken KCTD15 gene was predominantly expressed in subcutaneous fat, abdominal fat, and hypothalamus. We found that the mRNA level of KCTD15 was markedly decreased in the hypothalamus and liver of fasted and refed chicken and was significantly downregulated in adipose tissue when fed with high-fat diet. Three SNPs of KCTD15 gene were significantly associated with fatness traits in chickens. Our findings suggest that the KCTD15 gene is related to adiposity and fat metabolism in chicken. Acknowledgments This research was supported by grants from the National High Technology Research and Development Program (863) of China (2011AA100301 and 2013AA102501), Key Technology Research and Development Program of Guangdong Emerging Strategic Industries (2012A020800005), and the National Natural Science Foundation of China (31172200). The authors acknowledge Endashaw Jebessa Bekele (South China Agricultural University) for editing English language of this manuscript. The authors declare no conflict of interest. The first two authors contributed equally to this work. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. domaniend.2014.09.006.

References [1] Flegal KM, Graubard BI, Williamson DF, Gail MH. Cause-specific excess deaths associated with underweight, overweight, and obesity. J Am Med Assoc 2007;298:2028–37. [2] Finkelstein EA, Trogdon JG, Brown DS, Allaire BT, Dellea PS, KamalBahl SJ. The lifetime medical cost burden of overweight and obesity: implications for obesity prevention. Obesity 2008;16:1843–8. [3] 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, Khaw KT, 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 A, 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 JNGenetic Investigation of ANthropometric Traits Consortium. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 2009;41:25–34. [4] Bauer F, Elbers CC, Adan RA, Loos RJ, Onland-Moret NC, Grobbee DE, van Vliet-Ostaptchouk JV, Wijmenga C, van der Schoue YT. Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference. Am J Clin Nutr 2009;90:951–9. [5] Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, Lango Allen H, Lindgren CM, Luan J, Mägi R, Randall JC, Vedantam S, Winkler TW, Qi L, Workalemahu T, Heid IM, Steinthorsdottir V, Stringham HM, Weedon MN, Wheeler E, Wood AR, Ferreira T, Weyant RJ, Segrè AV, Estrada K, Liang L, Nemesh J, Park JH, Gustafsson S, Kilpeläinen TO, Yang J, BouatiaNaji N, Esko T, Feitosa MF, Kutalik Z, Mangino M, Raychaudhuri S, Scherag A, Smith AV, Welch R, Zhao JH, Aben KK, Absher DM, Amin N, Dixon AL, Fisher E, Glazer NL, Goddard ME, Heard-Costa NL, Hoesel V, Hottenga JJ, Johansson A, Johnson T, Ketkar S, Lamina C, Li S, Moffatt MF, Myers RH, Narisu N, Perry JR, Peters MJ, Preuss M, Ripatti S, Rivadeneira F, Sandholt C, Scott LJ, Timpson NJ, Tyrer JP, van Wingerden S, Watanabe RM, White CC, Wiklund F, Barlassina C, Chasman DI, Cooper MN, Jansson JO, Lawrence RW, Pellikka N, Prokopenko I, Shi J, Thiering E, Alavere H, Alibrandi MT, Almgren P, Arnold AM, Aspelund T, Atwood LD, Balkau B, Balmforth AJ, Bennett AJ, Ben-Shlomo Y, Bergman RN, Bergmann S, Biebermann H, Blakemore AI, Boes T, Bonnycastle LL, Bornstein SR, Brown MJ, Buchanan TA, Busonero F, Campbell H, Cappuccio FP, CavalcantiProença C, Chen YD, Chen CM, Chines PS, Clarke R, Coin L, Connell J, Day IN, den Heijer M, Duan J, Ebrahim S, Elliott P, Elosua R, Eiriksdottir G, Erdos MR, Eriksson JG, Facheris MF, Felix SB, FischerPosovszky P, Folsom AR, Friedrich N, Freimer NB, Fu M, Gaget S, Gejman PV, Geus EJ, Gieger C, Gjesing AP, Goel A, Goyette P, Grallert H, Grässler J, Greenawalt DM, Groves CJ, Gudnason V, Guiducci C, Hartikainen AL, Hassanali N, Hall AS, Havulinna AS, Hayward C, Heath AC, Hengstenberg C, Hicks AA, Hinney A, Hofman A, Homuth G, Hui J, Igl W, Iribarren C, Isomaa B, Jacobs KB, Jarick I, Jewell E, John U, Jørgensen T, Jousilahti P, Jula A, Kaakinen M, Kajantie E, Kaplan LM, Kathiresan S, Kettunen J, Kinnunen L, Knowles JW, Kolcic I, König IR, Koskinen S, Kovacs P, Kuusisto J, Kraft P, Kvaløy K, Laitinen J, Lantieri O, Lanzani C, Launer LJ, Lecoeur C, Lehtimäki T, Lettre G, Liu J, Lokki ML, Lorentzon M, Luben RN, Ludwig B, MAGIC, Manunta P, Marek D, Marre M, Martin NG, McArdle WL, McCarthy A, McKnight B,

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[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

Meitinger T, Melander O, Meyre D, Midthjell K, Montgomery GW, Morken MA, Morris AP, Mulic R, Ngwa JS, Nelis M, Neville MJ, Nyholt DR, O’Donnell CJ, O’Rahilly S, Ong KK, Oostra B, Paré G, Parker AN, Perola M, Pichler I, Pietiläinen KH, Platou CG, Polasek O, Pouta A, Rafelt S, Raitakari O, Rayner NW, Ridderstråle M, Rief W, Ruokonen A, Robertson NR, Rzehak P, Salomaa V, Sanders AR, Sandhu MS, Sanna S, Saramies J, Savolainen MJ, Scherag S, Schipf S, Schreiber S, Schunkert H, Silander K, Sinisalo J, Siscovick DS, Smit JH, Soranzo N, Sovio U, Stephens J, Surakka I, Swift AJ, Tammesoo ML, Tardif JC, Teder-Laving M, Teslovich TM, Thompson JR, Thomson B, Tönjes A, Tuomi T, van Meurs JB, van Ommen GJ, Vatin V, Viikari J, Visvikis-Siest S, Vitart V, Vogel CI, Voight BF, Waite LL, Wallaschofski H, Walters GB, Widen E, Wiegand S, Wild SH, Willemsen G, Witte DR, Witteman JC, Xu J, Zhang Q, Zgaga L, Ziegler A, Zitting P, Beilby JP, Farooqi IS, Hebebrand J, Huikuri HV, James AL, Kähönen M, Levinson DF, Macciardi F, Nieminen MS, Ohlsson C, Palmer LJ, Ridker PM, Stumvoll M, Beckmann JS, Boeing H, Boerwinkle E, Boomsma DI, Caulfield MJ, Chanock SJ, Collins FS, Cupples LA, Smith GD, Erdmann J, Froguel P, Grönberg H, Gyllensten U, Hall P, Hansen T, Harris TB, Hattersley AT, Hayes RB, Heinrich J, Hu FB, Hveem K, Illig T, Jarvelin MR, Kaprio J, Karpe F, Khaw KT, Kiemeney LA, Krude H, Laakso M, Lawlor DA, Metspalu A, Munroe PB, Ouwehand WH, Pedersen O, Penninx BW, Peters A, Pramstaller PP, Quertermous T, Reinehr T, Rissanen A, Rudan I, Samani NJ, Schwarz PE, Shuldiner AR, Spector TD, Tuomilehto J, Uda M, Uitterlinden A, Valle TT, Wabitsch M, Waeber G, Wareham NJ, Watkins H, Procardis Consortium, Wilson JF, Wright AF, Zillikens MC, Chatterjee N, McCarroll SA, Purcell S, Schadt EE, Visscher PM, Assimes TL, Borecki IB, Deloukas P, Fox CS, Groop LC, Haritunians T, Hunter DJ, Kaplan RC, Mohlke KL, O’Connell JR, Peltonen L, Schlessinger D, Strachan DP, van Duijn CM, Wichmann HE, Frayling TM, Thorsteinsdottir U, Abecasis GR, Barroso I, Boehnke M, Stefansson K, North KE, McCarthy MI, Hirschhorn JN, Ingelsson E, Loos RJ. Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index. Nat Genet 2010;42:937–48. Frida R, Felicity P, Anna N, Brito EC, Rolandsson O, Hallmans G, Barroso I, Nordstrom P, Franks PW. Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden. Hum Mol Genet 2009;18:1489–96. Ng MC, Tam CH, So WY, Ho JS, Chan AW, Lee HM, Wang Y, Lam VK, Chan JC, Ma RC. Implication of genetic variants near NEGR1, SEC16B,TMEM18, ETV5/DGKG, GNPDA2, LIN7C/BDNF, MTCH2, BCDIN3D/FAIM2, SH2B1, FTO, MC4R, and KCTD15 with obesity and type 2 diabetes in 7705 Chinese. J Clin Endocrinol Metab 2010;95:2418–25. Cheung CY, Tso AW, Cheung BM, Xu A, Ong KL, Fong CH, Wat NM, Janus ED, Sham PC, Lam KS. Obesity susceptibility genetic variants identified from recent genome-wide association studies: implications in a Chinese population. J Clin Endocrinol Metab 2010;95:1395–403. Thorleifsson G, Walters GB, Gudbjartsson DF, Steinthorsdottir V, Sulem P, Helgadottir A, Styrkarsdottir U, Gretarsdottir S, Thorlacius S, Jonsdottir I, Jonsdottir T, Olafsdottir EJ, Olafsdottir GH, Jonsson T, Jonsson F, Borch-Johnsen K, Hansen T, Andersen G, Jorgensen T, Lauritzen T, Aben KK, Verbeek ALM, Roeleveld N, Kampman E, Yanek LR, Becker LC, Tryggvadottir L, Rafnar T, Becker DM, Gulcher J, Kiemeney LA, Pedersen O, Kong A, Thorsteinsdottir U, Stefansson K. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet 2009;41:18–24. Takeuchi F, Yamamoto K, Katsuya T, Nabika T, Sugiyama T, Fujioka A, Isono M, Ohnaka K, Fujisawa T, Nakashima E, Ikegami H, Nakamura J, Yamori Y, Yamaguchi S, Kobayashi S, Ogihara T, Takayanagi R, Kato N. Association of genetic variants for susceptibility to obesity with type 2 diabetes in Japanese individuals. Diabetologia 2011;54:1350–9. den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, Ong KK, Wareham NJ, Loos RJF. Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies. Diabetes 2010;59:2980–8. Elks CE, Loos RJ, Hardy R, Wills AK, Wong A, Wareham NJ, Kuh D, Ong KK. Adult obesity susceptibility variants are associated with greater childhood weight gain and a faster tempo of growth: the 1946 British Birth Cohort Study. Am J Clin Nutr 2012;95:1150–6. Xi B, Zhao X, Shen Y, Wu L, Hou D, Mi J. An obesity genetic risk score predicts risk of insulin resistance among Chinese children. Endocrine 2014 [Epub ahead of print]. Warrington NM, Wu YY, Pennell CE, Marsh JA, Beilin LJ, Palmer LJ, Lye SJ, Briollais L. Modeling BMI trajectories in children for genetic association studies. PLoS One 2013;8:e53897.

71

[15] Stogios PJ, Downs GS, Jauhal JJ, Nandra SK, Prive GG. Sequence and structural analysis of BTB domain proteins. Genome Biol 2005;6:R82. [16] Birerdinc A, Nohelty E, Marakhonov A, Ganiraju M, Ivan P, Stephanie C, Nikitin E, Skoblov M, Chandhoke V, Baranova A. Proapoptotic and anti-proliferative activity of human KCNRG, a putative tumor suppressor in 13q14 region. Tumour Biol 2010;31: 33–45. [17] Perez-Torrado R, Yamada D, Defossez PA. Born to bind: the BTB protein- protein interaction domain. Bioessays 2006;28: 1194–202. [18] Skoblov M, Marakhonov A, Marakasova E, Guskova A, Chandhoke V, Birerdinc A, Baranova A. Protein partners of KCTD proteins provide insights about their functional roles in cell differentiation and vertebrate development. Bioessays 2013;35:586–96. [19] Dutta S, Dawid IB. Kctd15 inhibits neural crest formation by attenuating Wnt/betacatenin signaling output. Development 2010; 137:3013–8. [20] Zarelli VE, Dawid IB. Inhibition of neural crest formation by Kctd15 involves regulation of transcription factor AP-2. Proc Natl Acad Sci 2013;110:2870–5. [21] Ding XF, Luo C, Ren KQ, Zhang J, Zhou JL, Hu X, Liu RS, Wang Y, Gao X, Zhang J. Characterization and expression of a human KCTD1 gene containing the BTB domain, which mediates transcriptional repression and homomeric interactions. DNA Cell Biol 2008;27: 257–65. [22] Xu J, Koni PA, Wang P, Li G, Kaczmarek L, Wu Y, et al. The voltagegated potassium channel Kv1.3 regulates energy homeostasis and body weight. Hum Mol Genet 2003;12:551–9. [23] Xu J, Wang P, Li Y, Li G, Kaczmarek LK, Wu Y, Li Y, Flavell RA, Desir GV. The voltage-gated potassium channel Kv1.3 regulates peripheral insulin sensitivity. Proc Natl Acad Sci 2004;101:3112–7. [24] Adan RA, Vanderschuren LJ, la Fleur SE. Anti-obesity drugs and neural circuits of feeding. Trends Pharmacol Sci 2008;29:208–17. [25] Bell CG, Walley AJ, Froguel P. The genetics of human obesity. Nat Rev Genet 2005;6:221–34. [26] Schmid PM, Heid I, Buechler C, Steege A, Resch M, Birner C, Endemann DH, Riegger GA, Luchner A. Expression of fourteen novel obesity-related genes in Zucker diabetic fatty rats. Cardiovasc Diabetology 2012;11:48. [27] Yoganathan P, Karunakaran S, Ho MM, Clee SM. Nutritional regulation of genome-wide association obesity genes in a tissuedependent manner. Nutr Metab 2012;9:65. [28] Gutierrez-Aguilar R, Kim DH, Woods SC, Seeley RJ. Expression of new loci associated with obesity in diet-induced obese rats: from genetics to physiology. Obesity 2012;20:306–12. [29] Nonneman DJ1, Shackelford SD, King DA, Wheeler TL, Wiedmann RT, Rohrer GA, et al. Genome-wide association of meat quality traits and tenderness in swine. J Anim Sci 2013;91: 4043–50. [30] Lei M, Nie Q, Peng X, Zhang D, Zhang X. Single nucleotide polymorphisms of the chicken insulin-like factor binding protein 2 gene associated with chicken growth and carcass traits. Poult Sci 2005; 84:1191–8. [31] Stuebe AM, Lyon H, Herring AH, Ghosh J, Wise A, North KE, SiegaRiz AM. Obesity and diabetes genetic variants associated with gestational weight gain. Am J Obstet Gynecol 2010;203:283. [32] Orkunoglu-Suer FE, Harmon BT, Gordish-Dressman H, Clarkson PM, Thompson PD, Angelopoulos TJ, Gordon PM, Hubal MJ, Moyna NM, Pescatello LS, Visich PS, Zoeller RF, Hoffman EP, Devaney JM. MC4R variant is associated with BMI but not response to resistance training in young females. Obesity 2011;19:662–6. [33] Dementieva IS, Tereshko V, McCrossan ZA, Solomaha E, Araki D, Xu C, Grigorieff N, Goldstein SA. Pentameric assembly of potassium channel tetramerization domain-containing protein 15. Mol Biol 2009;387:175–91. [34] Takahashi C, Suzuki T, Nisida E, Kusakabe M. Identification and characterization of Xenopus kctd15, an ectodermal gene repressed by the FGF pathway. Int J Dev Biol 2012;56:393–402. [35] Resendes BL, Kuo SF, Robertson NG, Giersch AB, Honrubia D, Ohara O, Adams JC, Morton CC. Isolation from cochlea of a novel human intronless gene with predominant fetal expression. Assoc Res Otolaryngol 2004;5:185–202. [36] Gamse JT, Kuan YS, Macurak M, Brösamle C, Thisse B, Thisse C, Halpern ME. Directional asymmetry of the zebrafish epithalamus guides dorsoventral innervations of the midbrain target. Development 2005;132:4869–81. [37] Gharbi N, Zhao XF, Ellingsen S, Fjose A. Zebrafish enhancer trap line showing maternal and neural expression of kctd15a. Dev Growth Differ 2012;54:241–52.

Expression of variant transcripts of the potassium channel tetramerization domain-containing 15 (KCTD15) gene and their association with fatness traits in chickens.

The aim of this study was to characterize the structure, expression, and biological functions of potassium channel tetramerization domain containing 1...
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