Table of Contents Author Guidelines Submit a Manuscript
Journal of Diabetes Research
Volume 2015 (2015), Article ID 758564, 8 pages
http://dx.doi.org/10.1155/2015/758564
Research Article

Use of Drosophila as an Evaluation Method Reveals imp as a Candidate Gene for Type 2 Diabetes in Rat Locus Niddm22

1Division of Natural Sciences, Department of Life Science, International Christian University, Mitaka, Tokyo 181-8585, Japan
2Laboratory of Animal Genetics, Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
3Department of Animal Medical Sciences, Faculty of Life Sciences, Kyoto Sangyo University, Kyoto 603-8555, Japan

Received 7 October 2014; Revised 3 January 2015; Accepted 3 January 2015

Academic Editor: Mark A. Yorek

Copyright © 2015 Kurenai Kawasaki et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Type 2 diabetes (T2D) is one of the most common human diseases. QTL analysis of the diabetic Otsuka Long-Evans Tokushima Fatty (OLETF) rats has identified numerous hyperglycemic loci. However, molecular characterization and/or gene identification largely remains to be elucidated due mostly to the weak genetic variances contributed by each locus. Here we utilized Drosophila melanogaster as a secondary model organism for functional evaluation of the candidate gene. We demonstrate that the tissue specific knockdown of a homologue of igf2bp2 RNA binding protein leads to increased sugar levels similar to that found in the OLETF rat. In the mutant, the expression of two of the insulin-like peptides encoded in the fly genome, dilp2 and dilp3, were found to be downregulated. Consistent with previous reports of dilp mutants, the imp mutant flies exhibited an extension of life span; in contrast, starvation tolerance was reduced. These results further reinforce the possibility that imp is involved in sugar metabolism by modulating insulin expression.

1. Introduction

The world health organization (WHO) currently estimates that over 300 million individuals worldwide suffer from diabetes, 90% being type 2 diabetes (T2D) [1]. T2D, the primary feature of which is a state of chronic elevation of plasma glucose levels, is a polygenic disease that is caused by a metabolic and hormonal imbalance between insulin secretion from pancreatic β-cells and insulin resistance in peripheral tissues. Much effort has been devoted to the development and characterization of monogenic diabetes animal models, which have led to significant advancements in our understanding of the genetic basis of glucose/lipid metabolisms as well as the molecular pathogenesis of complications [2]. In spite of the progress, the importance of polygenic or spontaneous diabetes models is not diminished because the majority of genetic variations that are causative for a complex disease are not amorphic, but hypomorphic [35]. However, the importance of spontaneous diabetes models has been relatively underestimated owing to the difficulty of positional cloning [6].

The OLETF rat is one of the most studied strains by virtue of its similarity to a particular human population marked by propensity for disorders of glucose metabolism [7]. Traditional genetic analysis in the OLETF has been based on mapping QTL using microsatellite markers, followed by genetic isolation of QTL in congenic strains [8]. Recently there have been several studies reporting the successful positional cloning of QTLs by further extensive fine mapping of congenic strains [3]. However, in these cases the LOD scores of the QTL are relatively high (above 6.0) and consistently the identified mutations led to a more than twofold increase or reduction in expression levels [3, 4]. Thus, the search for genetic factors for polygenic traits remains to be a formidable challenge, especially for those whose LOD scores are not very high. Ideally rodent models should be used for functional probing of the candidate genes, yet the screening of a large number of genes is considered to be intractable with current techniques.

Drosophila melanogaster has progressively been recognized as the most feasible nonmammalian model for metabolic diseases [9, 10]. The Drosophila genome encodes eight insulin-like peptides and the backbone of the insulin/IGF-like signaling (IIS) pathway is highly conserved in comparison to that of vertebrates. Furthermore, physiological roles of the IIS pathway, including growth, lifespan, stress resistance, and metabolism, are also analogous across animal kingdom, making Drosophila a potential alternative agent for functional evaluation of the genes whose candidacy is suggested in other systems. The use of Drosophila as an evaluation method will be useful at least for those genes whose orthologs are encoded by the fly genome. One of the hyperglycemic QTLs identified in our previous studies is intriguing in terms of its association with obesity (see Section 4) and it is worth further investigation.

In the current study, prior to full-scale screening, we chose to focus on another QTL, Niddm22 (Nidd4/of as our original nomenclature), because of the presence of a strong candidate gene. Niddm22 is a region of 35.4 cM, corresponding to a physical distance of 24 Mbp, on the rat chromosome 11 [8]. Several human linkage studies reported metabolic QTLs in its syntenic region [11, 12]. According to the Ensemble database (release 73), 161 genes are annotated in this rat chromosomal segment [13]. Among those, 80 genes have fly orthologues. Here we focused on imp, a homolog of vertebrate igf2bp2, because the association studies identified an SNP within the locus to be linked not only to the diabetic phenotype but also to other diabetes-related traits such as fasting glucose, glucose AUC (area under curve), and Cederholm index [1416].

2. Materials and Methods

2.1. Fly Stocks

All fly stocks were reared at 25°C on a standard yeast (4%, w/v), corn meal (8%, w/v), glucose (10%, w/v), and agar medium, under 12 h:12 h light:dark conditions unless otherwise stated. The following fly stocks were used: UAS-imp-RNAi (v20321) from the Vienna Drosophila RNAi Center, Imp protein trap strain (number 110921) from the Drosophila Genetic Resource Center at Kyoto Institute of Technology. Additional fly stocks were generously provided by the Drosophila community: elav-GAL4 and UAS-Dcr2 from Yasushi Hiromi [1719], dilp2-Gal4 from Takashi Nishimura [20, 21]. Using standard fly genetics, UAS-Dcr2 and UAS-imp-RNAi were intercrossed into one strain in order to enhance the effect of RNA interference. Here UAS-imp-RNAi; UAS-Dcr-2 is referred to as UAS-imp.

2.2. Metabolic Studies

Whole-fly or hemolymph trehalose was measured by a Trehalose Assay Kit (Megazyme, K-TREH). For whole-fly preparation, 10 larvae were collected and briefly rinsed in Ringer’s solution. The larvae were homogenized by vigorous shaking in the presence of Zirconia beads (NIKKATO, 0.8 YTZ Ball). The resultant homogenate was heated at 70°C for 5 min and centrifuged at 12000 rpm for 5 min and the resultant supernatant was used for subsequent measurements. Hemolymph was prepared as previously described [22]. Briefly, 10 third instar larvae were pricked with a tungsten needle and transferred to a microfuge tube which had been pierced in the bottom, which was then piggybacked and centrifuged for 5 min at 4°C, 7,000 rpm. The resultant supernatant or hemolymph was used for subsequent measurements. Protein quantity was determined by Quant-iT Protein Assay Kits (Invitrogen).

2.3. Lifespan Assay

Lifespan studies were performed as previously mentioned with modifications [23]. For both fed and starved samples, three to ten virgin males and virgin females with approximately 1 : 1 ratio were placed in a single plastic vial. For starvation, the vial contained a piece of filter paper moisturized with distilled water. Flies were transferred to fresh medium or moisture vials every four to five days, and deaths were scored three times per week. The number of live individuals was recorded until all flies died.

2.4. q-PCR

Total RNA was extracted from 25 whole larvae in TRIzol reagent (Invitrogen). One microgram of total RNA was used for reverse transcription with iScript Select cDNA Synthesis Kit (Bio-Rad) by using oligo(dT) primer. q-PCR was performed on a MiniOpticon real-time PCR System (Bio-Rad) using iQ SYBR Green Supermix (Bio-Rad). Primers used for Q-RT-PCR are summarized in Table S1 available online at http://dx.doi.org/10.1155/2015/758564 [24, 25].

2.5. Statistical Analyses

For all experiments, error bars represent SEM, and values are the results of ANOVA followed by post hoc analyses using Scheffe’s test.

2.6. Microscopy

Fluorescent and bright field images were taken using an Axio 200 microscope (Zeiss).

3. Results

3.1. CNS Specific imp Knockdown Resulted in Hypertrehalosemia

Previous studies showed that imp is expressed in the central nervous system and pole cells during embryonic development and germ cells in adults [2628]. In order to examine the expression pattern of imp in larvae, we analyzed a protein trap strain, ZCL0310 [28]. In the third instar wandering larvae, the expression was exclusively detected in the central nervous system (CNS) (Figure 1). In contrast, imp is not expressed in other metabolically crucial tissues, including body wall muscle, fat body, gut, and oenocytes (Figure 1). Next we produced an CNS specific imp knockdown strain. The mutant had normal hatching rate and developmental growth. No morphological defect was observed. We confirmed that, in the third instar larvae, imp expression was reduced to about 20% of that of control (Figure 2(a)). Hemolymph was extracted from the third instar larvae that were immersed in the food medium (fed state). We also tested hemolymph from larvae starved for 15 hours (starved state). In both cases, the trehalose levels were significantly higher for the imp mutant compared with either control strain (Figure 2(c)). In contrast, no difference was observed among these strains for protein levels in either fed or starved condition. In order to examine the effect of imp knockdown mutation on total trehalose levels, whole-fly trehalose that is normalized by total protein levels was compared. In the starved state, the total amount of trehalose was higher than the control (Figure 2(b)). Because in our QTL analysis Niddm22 locus was identified as fasting hyperglycemic QTL, the observation of a more prominent effect on the starved state implies gene candidacy.

Figure 1: Expression pattern of the GFP-tagged protein trap. imp expression in third instar larva was examined using a protein trap strain ZCL0310, which expresses GFP-Imp chimeric protein in endogenous imp-expressing tissues. Bright field (a, c) and intrinsic GFP (b, d) images are shown. The GFP signal was detected in the central nervous system (CNS) (a, b), but only in a subset of neurons within the CNS. In contrast, GFP-Imp was not confirmed in the fat body (c, d). Bar, 100 μm.
Figure 2: Abnormal sugar metabolism is observed in the imp knockdown larva. (a) imp transcript was analyzed by q-PCR in larvae of the indicated genotypes. It was confirmed that the CNS specific knockdown of imp led to reduction of imp to about one-fifth of that of the control strain. (b) Normalized trehalose in whole larvae homogenized preparation was compared in order to examine the overall carbohydrate metabolism with protein concentration as an internal reference. The imp mutant shows a delay in trehalose usage in the fasting condition (7-hour fast, ). (c) Hemolymph trehalose concentration is increased in the imp mutant for both fed and starved condition. The difference is more prominent after 15-hour fasting (). . (d) In contrast, hemolymph protein concentration was unchanged for both fed and starved condition.
3.2. dilp Expression Is Downregulated in imp Knockdown Mutant

We examined the expression of a subset of dilp genes that are crucial for carbohydrate metabolism [29, 30]. The expression levels of dilp2 and dilp3, but not dilp5, were significantly reduced in the imp mutant larva (Figure 3). Imp belongs to a family of mRNA-binding proteins that play an important role in RNA localization, stability, and translation. RNA binding is mediated by highly conserved KH domains [31]. One of the most characterized KH domains, KH3 of Nova, recognizes a single UCAY element in the context of a 20-base hairpin RNA [32]. We found 2, 6, and 2 consensus motifs in dilp2, dilp3, and dilp5 mRNA, respectively (Table S2), leading us to the hypothesis that Imp may posttranscriptionally control the translation of dilps by direct binding. To test this, we knocked down the function of imp only in insulin-producing cells (IPCs) in which the three dilp isoforms are most exclusively expressed. However, the levels of dilps (dilp2, dilp3, and dilp5) or imp were unchanged and no hypertrehalosemia was observed (Figure S1). Furthermore, immunostaining revealed no apparent imp expression in IPCs (Figure S2). All of these results suggest that imp influences subtypes of dilp expression in a cell-non-autonomous manner.

Figure 3: dilp2 and dilp3 expression are significantly reduced in the imp mutant larvae. q-PCR analysis was conducted to examine the dilp expression on the third instar larva in the fed state. dilp2 and dilp3, but not dilp5, were reduced to less than the half of the control strain. .
3.3. imp Knockdown Resulted in Longer Lifespan and Reduced Starvation Tolerance

There are numerous reports that link the IIS pathway to lifespan or aging [24]. Our results so far suggest that the IIS signaling activity may be chronically lowered in the imp mutant. Consistently the imp knockdown mutant exhibited a significant increase in average and maximum lifespan over that of control flies (Figure 4(a)). Previous studies reported that the IPC-ablated flies were slightly starvation resistant [24, 33]. The extended lifespan is usually considered to be the result of enhanced stress resistance. However, the longevity on starvation of imp mutants is significantly lower than that of the control strains (Figure 4(b)), suggesting that imp may be involved in stress response regulation independent of dilp activity.

Figure 4: imp knockdown mutant exhibited longer lifespan and reduced starvation resistance. (a) Survival of elav-Gal4 virgin flies (blue, ), UAS-imp (green, ), and imp mutant [elav-Gal4; UAS-imp] (orange, ). Median lifespans are as follows: elav-Gal4, 51 days; UAS-imp; UAS-Dicer2, 40 days; elav-Gal4; UAS-imp 62 days, versus elav-Gal4, versus UAS-imp (log-rank test). (b) Survival of virgin flies during starvation: elav-Gal4 virgin flies (blue, ), UAS-imp (green, ), and imp mutant [elav-Gal4; UAS-imp] (orange, ). Average lifespans are as follows: elav-Gal4, days; UAS-imp days; imp mutant [elav-Gal4; UAS-imp] days, versus elav-Gal4, versus UAS-imp (log-rank test).

It is also widely known that IIS signaling pathway plays an essential role in the control of cell size and growth [30, 34]. The loss of dilp2, but not dilp3 or dilp5, reduces body weight [30]. Body size and weight of the imp knockdown strain are unchanged (Figure S3). This may be because the remaining dilp2 expression is sufficient to maintain normal growth, or other members of dilps that control growth compensate for the effect of dilp2 downregulation.

3.4. Polymorphisms of igf2bp2 Locus and Expression Analysis

Next we sequenced the coding region of igf2bp2, a rat orthologue of imp for the OLETF and F344 rat. There is one SNP in the fourth exon; however this SNP is a synonymous substitution (Table S3). Furthermore, in the tissue examined, our q-PCR analysis failed to detect any difference in the expression levels between the two strains. Further studies will be necessary for establishing the causality of the igf2bp2 in the OLETF rat.

4. Discussion

In the present study we demonstrated that the examination of the homologous gene provides us with a unique opportunity to search for novel metabolic genes. We tested Niddm22 here partly because our aim was to establish the methodology; we now wish to tackle other novel QTLs.

Previously we demonstrated that one of the hyperglycemic QTLs, Niddm20 (Nidd2/of as our original nomenclature), located on chromosome 14 of the OLETF rat, is quite unique for the following reasons: (1) its LOD score (4.07 for 30 min postprandial plasma glucose) is one of the highest among the other QTLs [35, 36]; (2) there is a strong epistasis with other QTLs [37]; (3) most importantly it interacts with the obese condition: the congenic strain exhibits more severe diabetic symptoms when combined with either genetically or nutritionally induced obesity [38, 39]. From the clinical point of view, identification of causative genes in such QTL has to be given higher priority. We further fine-mapped the region to discover that Niddm20 is composed of at least two narrower loci, each of which is localized at proximal and distal ends of the QTL region [40]. The analysis of subcongenic strains of Niddm20 showed that the exclusion of either locus from the original Niddm20 region resulted in the loss of the hyperglycemic phenotype, suggesting an epistatic relationship between the subloci. Within the syntenic region of the human genome, neither diabetic QTL has been reported nor have any of the T2D susceptibility genes been mapped [41]. Therefore, elucidation of the molecular nature of Niddm20 may provide novel opportunity for understanding human T2D. According to the Ensemble database, there are 62 genes annotated within the proximal 10Mb of Niddm20, none of which has been implicated with T2D. Our aim is to utilize Drosophila for functional evaluation of those candidate genes. A similar attempt was recently reported elsewhere [42] and it is hoped that Drosophila as a secondary model will help to find novel diabetic genes.

igf2bp2 has been implicated by genome-wide association studies as a candidate susceptibility gene for T2D [14, 15]. Several association studies correlated igf2bp2-SNPs more with reduced pancreatic β-cell activity than insulin resistance [43, 44]. However, the SNP is found in the second intron and the mechanism by which this susceptibility is engendered is unknown. Dai et al. reported that igf2bp2 mRNA is promoted by phosphorylation of Igf2bp2 by mTOR [45]. Another study indicated that Igf2bp2 directly binds to laminin-β2 mRNA and regulates its translation in a glucose concentration-dependent manner in the podocyte [46]. Several Drosophila studies also investigated the role of imp in the context of mRNA translocalization as well as translational regulation [26, 27, 47]. In the tests imp plays a crucial role in the aging of germ line stem cells (GSC), implicating a possible connection with the extended lifespan observed in the imp knockdown flies [48].

Among the genes annotated in Niddm22, there are other candidate genes that are inferred to be involved in metabolic functions, including somatostatin [49], Ahsg [50], and Adipoq [51]. Adipoq is the only other gene that has been identified as a diabetes candidate gene by GWAS. Recently it was reported that an adiponectin receptor homologue is involved in carbohydrate metabolism in the fly; however its orthologous ligand is not encoded in the fly genome and the authentic ligand remains to be discovered [52].

In general Drosophila offers a convenient resource for providing a rapid, inexpensive in vivo test of gene function. In addition fly genetics could also be useful for understanding molecular mechanisms. Indeed some insulin pathway components have been identified or validated by Drosophila research [53]. Reduced dilp level in the imp mutant is consistent at least partially with mammalian studies. It is, however, important to notice that in this system the following: (1) genes can only be characterized for which there are functional homologues in fly and (2) findings of diabetes-like phenotypes may not be valid for vertebrates or humans. For example, even though many insulin signaling components are conserved between flies and mammals, there are as many as eight insulin-like genes in Drosophila and they are expressed in tissues of various developmental origins, such as dilp2, dilp3, and dilp5 in neurons or dilp6 in the fat body [54]. With that in mind, it is hoped that genetic screening using this strain as a platform might elucidate details of the molecular pathway.

5. Conclusions

In summary, we performed a functional analysis on one of the diabetic candidate genes derived from the OLETF rat. We showed that downregulation of imp led to a hypertrehalosemic condition in Drosophila. Although further studies will be necessary to confirm the causative relationship between imp and diabetes in the OLETF rat, our results indicate that Drosophila is a useful secondary model for examination of the mammalian diabetes model.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This study was supported in part by a grant from the National Bio Resource Project (NBRP) for Rat in Japan (Kozo Matsumoto) and JSPS KAKENHI Grant number 20300145 (Kozo Matsumoto, Hiroyuki Kose). The authors thank Y. Hiromi, T. Nishimura, the Bloomington Stock Center, Drosophila Genetic Resource Center in Kyoto, and the Vienna Drosophila RNAi Center for fly stocks.

References

  1. G. Danaei, M. M. Finucane, Y. Lu et al., “National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2·7 million participants,” The Lancet, vol. 378, no. 9785, pp. 31–40, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. A. E. Bunner, P. C. Chandrasekera, and N. D. Barnard, “Knockout mouse models of insulin signaling: relevance past and future,” World Journal of Diabetes, vol. 5, pp. 146–159, 2014. View at Google Scholar
  3. M. Dokmanovic-Chouinard, W. K. Chung, J.-C. Chevre et al., “Positional cloning of ‘Lisch-like’, a candidate modifier of susceptibility to type 2 diabetes in mice,” PLoS Genetics, vol. 4, no. 7, Article ID e1000137, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Bhatnagar, A. T. Oler, M. E. Rabaglia et al., “Positional cloning of a type 2 diabetes quantitative trait locus; Tomosyn-2, a negative regulator of insulin secretion,” PLoS Genetics, vol. 7, no. 10, Article ID e1002323, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. P. Gao, Y. Jiao, Q. Xiong, C.-Y. Wang, I. Gerling, and W. Gu, “Genetic and molecular basis of QTL of diabetes in mouse: genes and polymorphisms,” Current Genomics, vol. 9, no. 5, pp. 324–337, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. T. J. Aitman, J. K. Critser, E. Cuppen et al., “Progress and prospects in rat genetics: a community view,” Nature Genetics, vol. 40, no. 5, pp. 516–522, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. K. Kawano, T. Hirashima, S. Mori, M. Kurosumi, and Y. Saitoh, “A new rat strain with non-insulin-dependent diabetes mellitus, 'OLETF',” Rat News Letter, vol. 25, pp. 24–26, 1991. View at Google Scholar
  8. H. Kose, D. H. Moralejo, T. Ogino, A. Mizuno, T. Yamada, and K. Matsumoto, “Examination of OLETF-derived non-insulin-dependent diabetes mellitus QTL by construction of a series of congenic rats,” Mammalian Genome, vol. 13, no. 10, pp. 558–562, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. K. D. Baker and C. S. Thummel, “Diabetic larvae and obese flies-emerging studies of metabolism in Drosophila,” Cell Metabolism, vol. 6, no. 4, pp. 257–266, 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. P. Leopold and N. Perrimon, “Drosophila and the genetics of the internal milieu,” Nature, vol. 450, no. 7167, pp. 186–188, 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Mori, S. Otabe, C. Dina et al., “Genome-wide search for type 2 diabetes in Japanese affected sib-pairs confirms susceptibility genes on 3q, 15q, and 20q and identifies two new candidate Loci on 7p and 11p,” Diabetes, vol. 51, no. 4, pp. 1247–1255, 2002. View at Publisher · View at Google Scholar · View at Scopus
  12. N. Vionnet, E. H. Hani, S. Dupont et al., “Genomewide search for type 2 diabetes-susceptibility genes in French whites: evidence for a novel susceptibility locus for early-onset diabetes on chromosiome 3q27-qter and independent replication of a type 2-diabetes locus on chromosome 1q21-q24,” American Journal of Human Genetics, vol. 67, no. 6, pp. 1470–1480, 2000. View at Publisher · View at Google Scholar · View at Scopus
  13. P. Flicek, B. L. Aken, K. Beal et al., “Ensembl 2008,” Nucleic Acids Research, vol. 36, no. 1, pp. D707–D714, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. L. J. Scott, K. L. Mohlke, L. L. Bonnycastle et al., “A genome-wide association study of type 2 diabetes in finns detects multiple susceptibility variants,” Science, vol. 316, no. 5829, pp. 1341–1345, 2007. View at Publisher · View at Google Scholar · View at Scopus
  15. R. Saxena, B. F. Voight, V. Lyssenko et al., “Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels,” Science, vol. 316, no. 5829, pp. 1331–1336, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. S.-M. Ruchat, C. E. Elks, R. J. F. Loos et al., “Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies,” Acta Diabetologica, vol. 46, no. 3, pp. 217–226, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. M. I. Kanai, M. Okabe, and Y. Hiromi, “Seven-up controls switching of transcription factors that specify temporal identities of Drosophila neuroblasts,” Developmental Cell, vol. 8, no. 2, pp. 203–213, 2005. View at Publisher · View at Google Scholar · View at Scopus
  18. D. M. Lin and C. S. Goodman, “Ectopic and increased expression of Fasciclin II alters motoneuron growth cone guidance,” Neuron, vol. 13, no. 3, pp. 507–523, 1994. View at Publisher · View at Google Scholar · View at Scopus
  19. G. Dietzl, D. Chen, F. Schnorrer et al., “A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila,” Nature, vol. 448, no. 7150, pp. 151–156, 2007. View at Publisher · View at Google Scholar · View at Scopus
  20. N. Okamoto, Y. Nishimori, and T. Nishimura, “Conserved role for the Dachshund protein with Drosophila Pax6 homolog eyeless in insulin expression,” Proceedings of the National Academy of Sciences of the United States of America, vol. 109, no. 7, pp. 2406–2411, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. E. J. Rulifson, S. K. Kim, and R. Nusse, “Ablation of insulin-producing neurons in flies: growth and diabetic phenotypes,” Science, vol. 296, no. 5570, pp. 1118–1120, 2002. View at Publisher · View at Google Scholar · View at Scopus
  22. L. P. Musselman, J. L. Fink, K. Narzinski et al., “A high-sugar diet produces obesity and insulin resistance in wild-type Drosophila,” DMM Disease Models and Mechanisms, vol. 4, no. 6, pp. 842–849, 2011. View at Publisher · View at Google Scholar · View at Scopus
  23. J. A. E. Söderberg, R. T. Birse, and D. R. Nässel, “Insulin production and signaling in renal tubules of Drosophila is under control of tachykinin-related peptide and regulates stress resistance,” PLoS ONE, vol. 6, no. 5, Article ID e19866, 2011. View at Google Scholar · View at Scopus
  24. S. J. Broughton, M. D. W. Piper, T. Ikeya et al., “Longer lifespan, altered metabolism, and stress resistance in Drosophila from ablation of cells making insulin-like ligands,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 8, pp. 3105–3110, 2005. View at Publisher · View at Google Scholar · View at Scopus
  25. J. Clements, K. Hens, C. Francis, A. Schellens, and P. Callaerts, “Conserved role for the Drosophila Pax6 homolog Eyeless in differentiation and function of insulin-producing neurons,” Proceedings of the National Academy of Sciences of the United States of America, vol. 105, no. 42, pp. 16183–16188, 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. C. Geng and P. M. Macdonald, “Imp associates with squid and Hrp48 and contributes to localized expression of gurken in the oocyte,” Molecular and Cellular Biology, vol. 26, no. 24, pp. 9508–9516, 2006. View at Publisher · View at Google Scholar · View at Scopus
  27. K. L. M. Boylan, S. Mische, M. Li et al., “Motility screen identifies Drosophila IGF-II mRNA-binding protein—zipcode-binding protein acting in oogenesis and synaptogenesis,” PLoS Genetics, vol. 4, no. 2, article e36, 2008. View at Publisher · View at Google Scholar · View at Scopus
  28. J. J. Fabrizio, C. A. Hickey, C. Stabrawa et al., “Imp (IGF-II mRNA-binding protein) is expressed during spermatogenesis in Drosophila melanogaster,” Fly, vol. 2, no. 1, pp. 47–52, 2008. View at Publisher · View at Google Scholar · View at Scopus
  29. T. Ikeya, M. Galic, P. Belawat, K. Nairz, and E. Hafen, “Nutrient-dependent expression of insulin-like peptides from neuroendocrine cells in the CNS contributes to growth regulation in Drosophila,” Current Biology, vol. 12, no. 15, pp. 1293–1300, 2002. View at Publisher · View at Google Scholar · View at Scopus
  30. S. Grönke, D.-F. Clarke, S. Broughton, T. D. Andrews, and L. Partridge, “Molecular evolution and functional characterization of Drosophila insulin-like peptides,” PLoS Genetics, vol. 6, no. 2, Article ID e1000857, 2010. View at Publisher · View at Google Scholar · View at Scopus
  31. K. L. Farina, S. Hüttelmaier, K. Musunuru, R. Darnell, and R. H. Singer, “Two ZBP1 KH domains facilitate β-actin mRNA localization, granule formation, and cytoskeletal attachment,” The Journal of Cell Biology, vol. 160, no. 1, pp. 77–87, 2003. View at Publisher · View at Google Scholar · View at Scopus
  32. K. B. Jensen, K. Musunuru, H. A. Lewis, S. K. Burley, and R. B. Darnell, “The tetranucleotide UCAY directs the specific recognition of RNA by the Nova K-homology 3 domain,” Proceedings of the National Academy of Sciences of the United States of America, vol. 97, no. 11, pp. 5740–5745, 2000. View at Publisher · View at Google Scholar · View at Scopus
  33. S. Broughton, N. Alic, C. Slack et al., “Reduction of DILP2 in Drosophila triages a metabolic phenotype from lifespan revealing redundancy and compensation among DILPs,” PLoS ONE, vol. 3, no. 11, Article ID e3721, 2008. View at Publisher · View at Google Scholar · View at Scopus
  34. R. Böhni, J. Riesgo-Escovar, S. Oldham et al., “Autonomous control of cell and organ size by CHICO, a Drosophila homolog of vertebrate IRS1–4,” Cell, vol. 97, no. 7, pp. 865–875, 1999. View at Publisher · View at Google Scholar · View at Scopus
  35. D. H. Moralejo, S. Wei, K. Wei et al., “Identification of quantitative trait loci for non-insulin-dependent diabetes mellitus that interact with body weight in the Otsuka Long-Evans Tokushima Fatty rat,” Proceedings of the Association of American Physicians, vol. 110, no. 6, pp. 545–558, 1998. View at Google Scholar · View at Scopus
  36. K. Sugiura, T. Miyake, Y. Taniguchi et al., “Identification of novel non-insulin-dependent diabetes mellitus susceptibility loci in the Otsuka Long-Evans Tokushima Fatty rat by MQM-mapping method,” Mammalian Genome, vol. 10, no. 12, pp. 1126–1131, 1999. View at Publisher · View at Google Scholar · View at Scopus
  37. H. Kose, Y. Bando, K. Izumi, T. Yamada, and K. Matsumoto, “Epistasis between hyperglycemic QTLs revealed in a double congenic of the OLETF rat,” Mammalian Genome, vol. 18, no. 8, pp. 609–615, 2007. View at Publisher · View at Google Scholar · View at Scopus
  38. H. Kose, T. Yamada, and K. Matsumoto, “Single diabetic QTL derived from OLETF rat is a sufficient agent for severe diabetic phenotype in combination with leptin-signaling deficiency,” Experimental Diabetes Research, vol. 2012, Article ID 858121, 5 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  39. T. Fukumura, H. Kose, C. Takeda et al., “Genetic interaction between hyperglycemic QTLs is manifested under a high calorie diet in OLETF-derived congenic rats,” Experimental Animals, vol. 60, no. 2, pp. 125–132, 2011. View at Publisher · View at Google Scholar · View at Scopus
  40. M. Akhi, H. Kose, and K. Matsumoto, “Fine mapping of the hyperglycemic and obesity QTL by congenic strains suggests multiple loci on rat chromosome 14,” The Journal of Medical Investigation, vol. 52, no. 1-2, pp. 109–113, 2005. View at Publisher · View at Google Scholar · View at Scopus
  41. A. Brunetti, E. Chiefari, and D. Foti, “Recent advances in the molecular genetics of type 2 diabetes mellitus,” World Journal of Diabetes, vol. 5, pp. 128–140, 2014. View at Google Scholar
  42. J. Pendse, P. V. Ramachandran, J. Na et al., “A Drosophila functional evaluation of candidates from human genome-wide association studies of type 2 diabetes and related metabolic traits identifies tissue-specific roles for dHHEX,” BMC Genomics, vol. 14, no. 1, article 136, 2013. View at Publisher · View at Google Scholar · View at Scopus
  43. N. D. Palmer, M. O. Goodarzi, C. D. Langefeld et al., “Quantitative trait analysis of type 2 diabetes susceptibility loci identified from whole genome association studies in the insulin resistance atherosclerosis family study,” Diabetes, vol. 57, no. 4, pp. 1093–1100, 2008. View at Publisher · View at Google Scholar · View at Scopus
  44. M. J. Groenewoud, J. M. Dekker, A. Fritsche et al., “Variants of CDKAL1 and IGF2BP2 affect first-phase insulin secretion during hyperglycaemic clamps,” Diabetologia, vol. 51, no. 9, pp. 1659–1663, 2008. View at Publisher · View at Google Scholar
  45. N. Dai, J. Rapley, M. Ange, F. M. Yanik, M. D. Blower, and J. Avruch, “mTOR phosphorylates IMP2 to promote IGF2 mRNA translation by internal ribosomal entry,” Genes and Development, vol. 25, no. 11, pp. 1159–1172, 2011. View at Publisher · View at Google Scholar · View at Scopus
  46. V. Schaeffer, K. M. Hansen, D. R. Morris, R. C. LeBoeuf, and C. K. Abrass, “RNA-binding protein IGF2BP2/IMP2 is required for laminin-β2 mRNA translation and is modulated by glucose concentration,” The American Journal of Physiology—Renal Physiology, vol. 303, no. 1, pp. F75–F82, 2012. View at Publisher · View at Google Scholar · View at Scopus
  47. T. P. Munro, S. Kwon, B. J. Schnapp, and D. St Johnston, “A repeated IMP-binding motif controls oskar mRNA translation and anchoring independently of Drosophila melanogaster IMP,” The Journal of Cell Biology, vol. 172, no. 4, pp. 577–588, 2006. View at Publisher · View at Google Scholar · View at Scopus
  48. H. Toledano, C. D'Alterio, B. Czech, E. Levine, and D. L. Jones, “The let-7-Imp axis regulates ageing of the Drosophila testis stem-cell niche,” Nature, vol. 485, no. 7400, pp. 605–610, 2012. View at Publisher · View at Google Scholar · View at Scopus
  49. N. Wierup, F. Sundler, and R. Scott Heller, “The islet ghrelin cell,” Journal of Molecular Endocrinology, vol. 52, no. 1, pp. R35–R49, 2013. View at Publisher · View at Google Scholar · View at Scopus
  50. S. J. F. Laulederkind, G. T. Hayman, S.-J. Wang et al., “The Rat Genome Database 2013—data, tools and users,” Briefings in Bioinformatics, vol. 14, no. 4, Article ID bbt007, pp. 520–526, 2013. View at Publisher · View at Google Scholar · View at Scopus
  51. M. Tsai, H. D. Wang, J. Shiang et al., “Sequence variants of ADIPOQ and association with type 2 diabetes mellitus in Taiwan Chinese Han population,” The Scientific World Journal, vol. 2014, Article ID 650393, 7 pages, 2014. View at Publisher · View at Google Scholar
  52. S.-J. Kwak, S.-H. Hong, R. Bajracharya, S.-Y. Yang, K.-S. Lee, and K. Yu, “Drosophila adiponectin receptor in insulin producing cells regulates glucose and lipid metabolism by controlling insulin secretion,” PLoS ONE, vol. 8, no. 7, Article ID e68641, 2013. View at Publisher · View at Google Scholar · View at Scopus
  53. P. Lasko, “Diabetic flies? Using Drosophila melanogaster to understand the causes of monogenic and genetically complex diseases,” Clinical Genetics, vol. 62, no. 5, pp. 358–367, 2002. View at Publisher · View at Google Scholar · View at Scopus
  54. K. Kannan and Y.-W. C. Fridell, “Functional implications of Drosophila insulin-like peptides in metabolism, aging, and dietary restriction,” Frontiers in Physiology, vol. 4, article 288, 2013. View at Publisher · View at Google Scholar