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Identification of putative odorant receptors from Epiphyas postvittana 118 These results were then compared with TM predictions using five other programs (as stated in section 4.2.16). Not all of these programs predicted the classical topology of 7TMs for ORs. This could in part be due to the lack of structural information in the protein database for closely related proteins. Therefore, a consensus of the output from the different prediction programs was taken in order to assign TM domains to EpOR34. The placement of these TM domains correlate with the TM domains predicted for EpOR1, 2 and 3 in Jordan et al. (2009), and are shown in numerals on Figure 4.4. To draw a topology map of EpOR34, the TM predictions produced by the consensus (numbers I to VII on Figure 4.8) was used. A short C-terminus was predicted by both SPLIT and HMMTOP, comparable to the short C-terminus predicted for the topologies of EpOR1, EpOR2 and EpOR3, perhaps a feature conserved in insects (Jordon, 2006). Some Drosophila ORs are also predicted to have short C-termini (Clyne et al., 1999; Gao and Chess, 1999; Dobritsa et al., 2003; Kiely, 2008). This could just be an artefact of the prediction algorithms used and only the solved structure of such a protein will be able to confirm this theoretical observation. N Figure 4.11: Theoretical membrane topology of EpOR34 from the consensus of the predictions of seven different TM prediction algorithms. N = N- terminus and C = C- terminus. C
Identification of putative odorant receptors from Epiphyas postvittana 119 4.4 Discussion A total of 52 ORs have so far been identified using three different methods. Sanger sequencing identified three ORs, 454 transcriptome sequencing identified 29 ORs and 47 ORs were identified from low coverage whole genome sequencing of E. postvittana. Some ORs were identified by all three sequencing methods (three ORs), some by two (21 ORs) and some by only one method (28 ORs), as summarised in Table 4.6. Sanger sequencing gives longer sequence fragments hence contig assembly is easier and results in long contigs being assembled; however the drawback of this sequencing technology is the low depth of coverage, with only three ORs being identified from Sanger sequencing of E. postvittana antennal cDNA (Jordan et al., 2009). ORs are lowly expressed genes and due to their low copy number in cDNA populations are not efficiently picked up in shallow Sanger sequencing. 454 transcriptomics was more efficient at identifying E. postvittana ORs, as it was able to identify the three ORs identified by Sanger sequencing and a further 26 new ORs. The drawback of this system was the short read lengths obtained hence the OR sequences were in small fragments. Low coverage whole genome sequencing was able to identify 47 ORs. This is consistent with recovery of ORs from other moths such as B. mori where whole genome sequencing recovered most of the ORs. However, due to the presence of introns in insect ORs, prediction of coding regions of genes becomes a challenge. The degenerate PCR approach taken to identify new putative ORs from E. postvittana did not yield any significant results. This may be attributed to the low sequence homology between insect ORs, as only a few ORs have been identified using this method thus far (Mitsuno et al., 2008; Patch et al., 2009). Regions of homology among ORs are limited and result in high levels of degeneracy in designed primers. This leads to non-specific binding and amplification of undesirable genes, or genes present in high copy numbers in cells. In the Lepidoptera B. mori, 68 ORs (from both adult and larvae) have been identified so far, which is higher than the number of ORs identified in E. postvittana to date. Both these lists may be incomplete and further ORs might be identified from both these moths, however, for the purpose of this discussion, the 68 ORs identified in B.
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Abstract Abstract Olfaction or the
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Acknowledgements Acknowledgements I
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Contents v Contents Abstract……
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Contents 4.2.5 Degenerate PCR .....
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List of Figures List of Figures Fig
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List of Tables List of Tables Table
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List of Abbreviations gDNA Genomic
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1.1 General overview 1 General Intr
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General Introduction 3 moth in loca
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General Introduction 5 Figure 1.1:
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General Introduction 7 1.5 Componen
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General Introduction 9 OBPs have al
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General Introduction 11 A model has
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General Introduction 15 Tanaka et a
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General Introduction 17 Table 1.1:
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General Introduction 21 et al., 200
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General Introduction 23 the attract
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General Introduction 25 leaves and
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General Introduction 29 Expression
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General Introduction 31 BmOr2 HvOr2
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General Introduction 33 for lepidop
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Functional characterisation of Epip
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3.1 Introduction 3 The roles of Epi
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The roles of Epiphyas postvittana G
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Page 151 and 152: Appendix B 135 Buffered TB (Sambroo
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Page 161 and 162: Appendix E 145 VII continued Figure
Page 163 and 164: References 147 Ansebo, L., Ignell,
Page 165 and 166: References 149 Butenandt, A., Beckm
Page 167 and 168: References 151 Fedurco, M., Romieu,
Page 169 and 170: References 153 Große-Wilde, E., St
Page 171 and 172: References 155 Hrdy, I., F. Kuldova
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Page 177 and 178: References 161 Lopez-Gomez, R. and
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Page 181 and 182: References 165 Pell, J. K., Macaula
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References 169 Stowers, L. and Loga
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References 171 Turner, C. T., Davy,
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References 173 Vogt, R. G., Riddifo
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References 175 Widmayer, P., Heifet
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