Juvenile hormone (JH) contributes to the regulation of larval molting and metamorphosis in insects. Herein, we comprehensively identified 55 genes involved in JH biosynthesis, metabolism and signaling in the silkworm ( Bombyx mori) as well as 35 in Drosophila melanogaster, 35 in Anopheles gambiae, 36 in Apis mellifera, 47 in Tribolium castaneum, and 44 in Danaus plexippus. Comparative analysis showed that each gene involved in the early steps of the mevalonate (MVA) pathway, in the neuropeptide regulation of JH biosynthesis, or in JH signaling is a single copy in B. mori and other surveyed insects, indicating that these JH-related pathways or steps are likely conserved in all surveyed insects. However, each gene participating in the isoprenoid branch of JH biosynthesis and JH metabolism, together with the FPPS genes for catalyzing the final step of the MVA pathway of JH biosynthesis, exhibited an obvious duplication in Lepidoptera, including B. mori and D. plexippus. Microarray and real-time RT-PCR analysis revealed that different copies of several JH-related genes presented expression changes that correlated with the dynamics of JH titer during larval growth and metamorphosis. Taken together, the findings suggest that duplication-derived copy variation of JH-related genes might be evolutionarily associated with the variation of JH types between Lepidoptera and other insect orders. In conclusion, our results provide useful clues for further functional analysis of JH-related genes in B. mori and other insects.
In insects, the sesquiterpenoid juvenile hormone (JH) is synthesized and released from the corpora allata (CA) and cooperates with the steroid 20-hydroxyecdysone (20E) that is synthesized and released from the prothoracic glands to orchestrate insect molting, growth, metamorphosis, via stage-specific changes in the titers of these two endocrine hormones ( Dubrovsky, 2005). JH activity is elevated early in each larval instar to maintain larval shape and characteristics, whereas the titer of 20E is always increased at the end of each larval instar to trigger the transition instar from larva to larva ( Bownes and Rembold, 1987; Riddiford, 1994; Wyatt and Davey, 1996; Futahashi and Fujiwara, 2008). In the final larval instar, the JH titer is remarkably decreased and the 20E titer is increased to a very high level enough to initiate a metamorphic transition from larva to pupa. In addition, JH has been showed to regulate aging and reproduction in insects ( Riddiford, 2012; Yamamoto et al., 2013 ; Zou et al., 2013 ).
The dynamic change in JH titer is mainly modulated through biosynthetic and metabolic pathways that are catalyzed by different sets of endogenous enzymes ( Li et al., 2004 ; Minakuchi et al., 2006 ; Noriega et al., 2006 ; Kinjoh et al., 2007 ). As summarized in Figure S1, JH biosynthesis involves the mevalonate (MVA) pathway and the isoprenoid branch. The MVA pathway includes eight enzymatic steps and uses acetyl-CoA to generate farnesyl diphosphate (FPP) as a JH precursor. Then, the isoprenoid branch converts the FPP into JH through several continuous steps of oxidization and epoxidation ( Kinjoh et al., 2007 ). In addition, allatotropin (AT) and allatostatin (AS), which belong to the neuropeptide hormone family, promotes and inhibits, respectively, the JH biosynthesis by affecting CA activity ( Kataoka et al., 1989 ; Kramer et al., 1991 ; Bogus and Scheller, 1996). Furthermore, proper nutritional signals can affect the release of AT and AS by the brain and further results in the activation or inhibition of JH biosynthesis ( Noriega, 2004). Moreover, the decrease in JH titer is controlled through its metabolism, which is mainly catalyzed by JH esterase (JHE), JH epoxide hydrolase (JHEH), and JH diol kinase (JHDK). Particularly, several genes involved in JH biosynthesis, metabolism, and signaling have been previously analyzed in insects ( Noriega et al., 2006 ; Kinjoh et al., 2007 ; Hua-Jun et al., 2011 ).
Deciphering JH signaling in insects has been attracting increasing attention worldwide. Although the nature of JH signaling has not been completely uncovered, some molecules have been demonstrated to be involved in JH signaling, including JH binding protein (JHBP), methoprene-tolerant (Met), the 20E receptor EcR, Ultraspiracle (USP), Krüppel homolog 1 (Kr-h1), FKBP39, and Chd64 ( Riddiford, 2008; Jindra et al., 2013 ). Notably, Met protein is a bHLH-PAS transcription factor and has been confirmed as a potential JH receptor in some insect species ( Jindra et al., 2013 ). In Drosophila melanogaster and Bombyx mori, Met paralog, germ-cell expressed (Gce) or Met2 protein functions as a partner of Met in modulating JH signaling ( Abdou et al., 2011 ; Guo et al., 2012 ).
Intriguingly, there are eight types of natural JHs characterized in insects, including JH0, JHI, JHII, JHIII, JHIII skipped bisepoxide (JHSB3), JHIII bisepoxide (JHB3), methyl farnesoate (MF), and iso JH0 ( Minakuchi et al., 2006 ; Daimon and Shinoda, 2013). Currently, only JHIII is ubiquitous in all insects. The other four JH variants, including JH0, iso JH0, JHI, and JHII, have been found exclusively in Lepidoptera ( Furuta et al., 2013 ). JHSB3 and JHB3 are specific to Hemiptera and Diptera, respectively. MF is found to be present in both Diptera and Coleoptera. However, little is known about how genes involved in JH biosynthesis, metabolism, and signaling vary among insects.
As noted above, some of the genes (referred to as JH-related genes) participating in JH-related pathways (biosynthesis, metabolism, and signaling) have been characterized in various insect species. However, with the availability of whole-genome sequence, the number, structure, and evolution of all JH-related genes have not yet been investigated and compared systematically at a genome-wide level among insects. The silkworm ( B. mori) belongs to the order Lepidoptera. In this study, based on the current B. mori genome assembly ( Xia et al., 2008 ), we performed a genome-wide identification of genes involved in JH bio-synthesis, metabolism, and signaling in B. mori; we then evolutionarily compared the B. mori genes with their orthologs in other insects.
The B. mori genome sequences and the predicted proteins were downloaded from the SilkDB database and were used in our analysis. The predicted protein sets for D. melanogaster, Anopheles gambiae, Apis mellifera, Tribolium castaneum, and Danaus plexippus were downloaded from NCBI, Ensembl, or specific databases such as FlyBase for D. melanogaster, BeeBase for A. mellifera ( Munoz-Torres et al., 2011 ), MonarchBase for D. plexippus ( Zhan and Reppert, 2013), and the Butterfly Genome Database for Heliconius melpomene ( Heliconius Genome, 2012).
We used protein sequences or conserved domains of known JH-related genes to query against the predicted protein sets of B. mori and of other insects, using the BLAST program with an E-value threshold of less than 1e-6. In addition, an online SMART program was used to search for the functional domains of predicted proteins. Multiple candidate members of a JH-related gene were identified on the basis of agreement with both the E-value threshold and the existence of typical domains. Regarding the nomenclature, candidate genes were defined with an original name if the biological properties (such enzymatic activities) had been confirmed or if the genes had only one copy in each insect surveyed. If a JH-related gene had multiple copies and no functional attributes, we refer them as original-like genes.
The chromosomal distribution of JH-related genes in B. mori was determined using a B. mori genetics linkage map constructed using single-nucleotide polymorphism (SNP) markers ( Yamamoto et al., 2008 ). The multiple alignments of the complete amino acid sequences or functional domains of JH-related genes were performed using ClustalX ( Thompson et al., 1997 ). Based on the multiple sequence alignment results, neighbor-joining phylogenetic trees for JH-related genes from all surveyed insects were constructed using MEGA4.0 ( Tamura et al., 2007 ) with a bootstrap of 1000 replicates.
The spatio-temporal expression patterns of JH-related genes in B. mori were first surveyed using the microarray method. Microarray gene expression data of multiple larval tissues from B. mori larvae at the third day of the fifth instar and related analytical methods from our previous report ( Xia et al., 2007 ) were used to profile the tissue-specific expression of JH-related genes.  We retrieved the microarray data for B. mori JH-related genes from the active gene selection to examine their tissue expression profiles.
The developmental expression pattern was analyzed using microarray data of B. mori gene expression during metamorphosis (unpublished data), including 19 developmental time points during the larva-pupa-adult transitions, namely, V4 (fourth day of the fifth larval instar), V5, V6, V7, W0 (beginning of wandering), W12 (12 hours after wandering), W24, W36, W48 (completing spinning), W60 (immediately after pupation), W72, W96, W120, W144, W168, W192, W216, W240, and adulthood. Gene expression in B. mori larvae at V3 (third day of the fifth larval instar) was set as the common reference. The ratio between the experimental and reference intensities for a JH-related gene was used to evaluate expression changes during the larva-pupa-adult transitions of B. mori. The related analytical method was based on our previous reports ( Xia et al., 2007 ; Huang et al., 2009 ). Tissue and developmental expression patterns from the microarray analysis were visualized using the GeneCluster2.0 program ( Reich et al., 2004 ).
We also used a real-time quantitative RT-PCR approach to examine expression patterns of JH-related genes during the larval growth of B. mori. The B. mori strain Dazao was reared under a temperature of 25 °C. B. mori larvae were collected at ten time points during the larval feeding and molting stages from the fourth instar to the fifth instar, including IV0 (0 hour after the third larval molt, namely, the beginning of the fourth instar), IV1 (day 1 after the third molt), IV2 (day 2 after the third molt), IV3 (day 3 after the third molt), IV4 (day 4 after the third molt), IVM (just initiating the fourth larval molt), V0 (0 hours after the fourth molt, namely, the beginning of the fifth instar), and V1 (day 1 of the fifth instar).
Total RNA was extracted using TRIzol reagent (Invitrogen, USA) and was reverse transcribed into cDNA with M-MLV reverse transcriptase (Promega, USA). Real-time RT-PCR was conducted as described in our previous study ( Wang et al., 2008 ). The B. mori ribosomal protein L3 ( RpL3) was used as an internal control. All primers used are listed in Table S1.
We used the amino acid sequences of known insect JH-related genes to search against the predicted B. mori proteins using the BLAST program. Initially, 55 JH-related genes were identified, including 34 for JH biosynthesis, 13 for JH metabolism, and eight for JH signaling ( Table 1). Several JH-related genes exhibited multiple copies, including farnesyl diphosphate synthase ( FPPS), farnesyl phosphatase ( FPPase), aldehyde dehydrogenase (ALDH), JH acid methyltransferase ( JHAMT), farnesoic acid O-methyltransferase ( FAMeT), JHE, JHEH, and JHDK. All JH-related genes for B. mori mapped to different chromosomes except for the FPPase gene and allatostatin receptor ( ASR) gene ( Figure 1 and Table 1). Intriguingly, the copies of several JH-related gene with multiple copies were distributed on the same chromosome in a tandem manner, for example, FPPS on chromosome 12, JHDK on chromo-some 3, FAMeT on chromosomes 5 or 6, JHAMT on chromosome 12, JHE on chromosome 25, and JHEH on chromosome 28.
Inventory of JH-related genes in the B. mori genome.
| lefttop11MVA pathway of JH biosynthesis | lefttop11Acetoacetyl CoA thiolase | centertop11Acat | centertop11BGIBMGA011029 | centertop11405 | centertop11nscaf3015 | centertop1123 |
| lefttop11 | lefttop11Hydroxymethylglutaryl-CoA synthase | centertop11HMGS | centertop11BGIBMGA004001 | centertop11456 | centertop11nscaf2767 | centertop1119 |
| lefttop11 | lefttop11Hydroxymethylglutaryl-CoA reductase | centertop11HMGR | centertop11BGIBMGA003229 | centertop11785 | centertop11nscaf2623 | centertop112 |
| lefttop11 | lefttop11Mevalonate kinase | centertop11MevK | centertop11BGIBMGA013075 | centertop11410 | centertop11nscaf3058 | centertop1116 |
| lefttop11 | lefttop11Phosphomevalonate kinase | centertop11MevPK | centertop11BGIBMGA001556 | centertop11186 | centertop11nscaf2136 | centertop1121 |
| lefttop11 | lefttop11Diphosphomevalonate decarboxylase | centertop11MevPPD | centertop11BGIBMGA007459 | centertop11383 | centertop11nscaf2886 | centertop113 |
| lefttop11 | lefttop11Isopentenyl-diphosphate delta-isomerase | centertop11IPPI | centertop11BGIBMGA004904 | centertop11251 | centertop11nscaf2822 | centertop1125 |
| lefttop11 | lefttop11Farnesyl diphosphate synthase 1 | centertop11FPPS1 | centertop11BGIBMGA001926 | centertop11427 | centertop11nscaf2204 | centertop1119 |
| lefttop11 | lefttop11Farnesyl diphosphate synthase 2 | centertop11FPPS2 | centertop11BGIBMGA001927 | centertop11382 | centertop11nscaf2204 | centertop1119 |
| lefttop11 | lefttop11Farnesyl diphosphate synthase 3 | centertop11FPPS3 | centertop11BGIBMGA014635 * | centertop11385 | centertop11nscaf2204 | centertop1119 |
| lefttop11Isoprenoid branch of JH biosynthesis | lefttop11Farnesyl phosphatase-like protein 1 | centertop11FPPase-l1 | centertop11BGIBMGA011595 | centertop11251 | centertop11nscaf3028 | centertop11- |
| lefttop11 | lefttop11Farnesyl phosphatase-like protein 2 | centertop11FPPase-l2 | centertop11BGIBMGA011596 | centertop11247 | centertop11nscaf3028 | centertop11- |
| lefttop11 | lefttop11Farnesol dehydrogenase | centertop11FOHSDR | centertop11BGIBMGA005248 | centertop11254 | centertop11nscaf2827 | centertop118 |
| lefttop11 | lefttop11Aldehyde dehydrogenase-like protein 1 | centertop11ALDH-l1 | centertop11BGIBMGA001966 | centertop11750 | centertop11nscaf2204 | centertop1119 |
| lefttop11 | lefttop11Aldehyde dehydrogenase-like protein 2 | centertop11ALDH-l2 | centertop11BGIBMGA001965 | centertop11440 | centertop11nscaf2204 | centertop1119 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase | centertop11JHAMT | centertop11BGIBMGA010391 | centertop11250 | centertop11nscaf2993 | centertop1112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 1 | centertop11JHAMT-l1 | centertop11BGIBMGA008032 | centertop11136 | centertop11nscaf2889 | centertop119 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 2 | centertop11JHAMT-l2 | centertop11BGIBMGA010392 | centertop11266 | centertop11nscaf2993 | centertop1112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 3 | centertop11JHAMT-l3 | centertop11BGIBMGA010393 | centertop11168 | centertop11nscaf2993 | centertop1112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 4 | centertop11JHAMT-l4 | centertop11BGIBMGA010563 | centertop11137 | centertop11nscaf2993 | centertop1112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 5 | centertop11JHAMT-l5 | centertop11BGIBMGA010564 | centertop11121 | centertop11nscaf2993 | centertop1112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase-like protein 6 | centertop11JHAMT-l6 | centertop11BGIBMGA014014 | centertop11267 | centertop11nscaf3099 | centertop1128 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 1 | centertop11FAMeT-l1 | centertop11BGIBMGA002604 | centertop11443 | centertop11nscaf2529 | centertop115 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 2 | centertop11FAMeT-l2 | centertop11BGIBMGA002314 | centertop11248 | centertop11nscaf2330 | centertop1126 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 3 | centertop11FAMeT-l3 | centertop11BGIBMGA006513 | centertop11229 | centertop11nscaf2853 | centertop116 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 4 | centertop11FAMeT-l4 | centertop11BGIBMGA002684 | centertop11206 | centertop11nscaf2529 | centertop115 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 5 | centertop11FAMeT-l5 | centertop11BGIBMGA002605 | centertop11338 | centertop11nscaf2529 | centertop115 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 6 | centertop11FAMeT-l6 | centertop11BGIBMGA006319 | centertop11224 | centertop11nscaf2852 | centertop116 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase-like protein 7 | centertop11FAMeT-l7 | centertop11BGIBMGA006318 | centertop11829 | centertop11nscaf2852 | centertop116 |
| lefttop11 | lefttop11Cytochrome P450 15C1 | centertop11Cyp15 C1 | centertop11BGIBMGA011708 | centertop11288 | centertop11nscaf3031 | centertop1111 |
| lefttop11Neuropeptide regulation of JH biosynthesis | lefttop11Allototropin | centertop11AT | centertop11BGIBMGA011850 | centertop11291 | centertop11nscaf3031 | centertop1111 |
| lefttop11 | lefttop11Allatostatin | centertop11AS | centertop11BGIBMGA014377 | centertop11150 | centertop11scaffold416 | centertop1114 |
| lefttop11 | lefttop11Allatotropin receptor | centertop11ATR | centertop11BGIBMGA004429 | centertop11255 | centertop11nscaf2795 | centertop1120 |
| lefttop11 | lefttop11Allatostatin receptor | centertop11ASR | centertop11BGIBMGA005708 | centertop11362 | centertop11nscaf2830 | centertop11- |
| lefttop11JH metabolism | lefttop11Juvenile hormone esterase | centertop11JHE | centertop11BGIBMGA000772 | centertop11567 | centertop11nscaf1705 | centertop1125 |
| lefttop11 | lefttop11Juvenile hormone esterase-like protein 1 | centertop11JHE-l1 | centertop11BGIBMGA000774 | centertop11566 | centertop11nscaf1705 | centertop1125 |
| lefttop11 | lefttop11Juvenile hormone esterase-like protein 2 | centertop11JHE-l2 | centertop11BGIBMGA000775 | centertop11560 | centertop11nscaf1705 | centertop1125 |
| lefttop11 | lefttop11Juvenile hormone esterase-like protein 3 | centertop11JHE-l3 | centertop11BGIBMGA000776 | centertop11572 | centertop11nscaf1705 | centertop1125 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase | centertop11JHEH | centertop11BGIBMGA013930 | centertop11461 | centertop11nscaf3099 | centertop1128 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase-like protein 1 | centertop11JHEH-l1 | centertop11BGIBMGA011468 | centertop11401 | centertop11nscaf3027 | centertop1123 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase-like protein 2 | centertop11JHEH-l2 | centertop11BGIBMGA009211 | centertop11510 | centertop11nscaf2943 | centertop1114 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase-like protein 3 | centertop11JHEH-l3 | centertop11BGIBMGA013994 | centertop11637 | centertop11nscaf3099 | centertop1128 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase-like protein 4 | centertop11JHEH-l4 | centertop11BGIBMGA013793 | centertop11395 | centertop11nscaf3097 | centertop1128 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase-like protein 5 | centertop11JHEH-l5 | centertop11BGIBMGA013929 | centertop11355 | centertop11nscaf3099 | centertop1128 |
| lefttop11 | lefttop11Juvenile hormone diol kinase | centertop11JHDK | centertop11BGIBMGA008814 | centertop11183 | centertop11nscaf2925 | centertop113 |
| lefttop11 | lefttop11Juvenile hormone diol kinase-like protein 1 | centertop11JHDK-l1 | centertop11BGIBMGA008813 | centertop11182 | centertop11nscaf2925 | centertop113 |
| lefttop11 | lefttop11Juvenile hormone diol kinase-like protein 2 | centertop11JHDK-l2 | centertop11BGIBMGA008815 | centertop11179 | centertop11nscaf2925 | centertop113 |
| lefttop11JH signaling | lefttop11Juvenile hormone binding protein | centertop11JHBP | centertop11BGIBMGA011549 | centertop11243 | centertop11nscaf3027 | centertop1123 |
| lefttop11 | lefttop11FKBP39 | centertop11FKBP39 | centertop11BGIBMGA001490 | centertop11402 | centertop11nscaf2136 | centertop1121 |
| lefttop11 | lefttop11Chd64 | centertop11Chd64 | centertop11BGIBMGA007092 | centertop11174 | centertop11nscaf2865 | centertop1117 |
| lefttop11 | lefttop11Methoprene-tolerant 1 | centertop11Met1 | centertop11BGIBMGA005416 | centertop11455 | centertop11nscaf2828 | centertop118 |
| lefttop11 | lefttop11Methoprene-tolerant 2 | centertop11Met2 | centertop11BGIBMGA000657 | centertop11661 | centertop11nscaf1690 | centertop111 |
| lefttop11 | lefttop11Ecdysone receptor | centertop11EcR | centertop11BGIBMGA006767 | centertop11496 | centertop11nscaf2855 | centertop1110 |
| lefttop11 | lefttop11Ultraspiracle | centertop11USP | centertop11BGIBMGA006183 | centertop11270 | centertop11nscaf2847 | centertop114 |
| lefttop11 | lefttop11Kruppel homolog 1 | centertop11Kr-h1 | centertop11BGIBMGA003160 | centertop11348 | centertop11nscaf2589 | centertop114 |
Note:
indicates new gene assembly.
indicates unknown.
Chromosomal distribution of JH-related genes in B. mori. Based on the assembly of the whole-genome sequence and single-nucleotide polymorphism (SNP) markers linkage map for B. mori, a total of 52 JH-related genes were mapped on the different chromosomes of B. mori. Several different copies of each of the JH-related genes with multiple copies are clustered in tandem on the chromosomes.
To determine comprehensively the evolution of JH-related genes among insects, we further identified JH-related genes in other insects, namely, 35 in D. melanogaster, 35 in A. gambiae, 36 in A. mellifera, 47 in T. castaneum, and 44 in D. plexippus ( Table 2, Table S2). Some JH-related genes in these five insects had at least two copies, including three genes ( Farnesol dehydrogenase ( FOHSDR), JHE, and JHEH) in D. melanogaster, three ( FOHSDR, JHE, and JHEH)in A. gambiae, four ( FPPase, FOHSDR, FAMeT, and JHE)in A. mellifera, five ( FPPase, FOHSDR, ALDH, JHAMT, and JHEH) in T. castaneum, and six ( FPPS, FPPase, ALDH, FAMeT, JHEH, and JHDK) in D. plexippus. Moreover, the copies of several JH-related genes in these insects were distributed in tandem on a chromosome, including the JHEHs in D. melanogaster; the JHEHs and FOHSDRs in A. gambiae; the JHAMTs and JHEHs in T. castaneum; and the FPPSs, FPPases, FAMeTs, JHEHs, and JHDKs in D. plexippus. On the basis of these and similar observations in B. mori, we speculate that the JH-related genes with multiple copies were duplicated during the evolution of B. mori and other insects.
Copy number of JH-related genes in B. mori and the other insects.
| lefttop11MVA pathway of JH biosynthesis | lefttop11Acetoacetyl CoA thiolase | centertop11ACAT | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Hydroxymethylglutaryl-CoA synthase | centertop11HMGS | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Hydroxymethylglutaryl-CoA reductase | centertop11HMGR | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Mevalonate kinase | centertop11MevK | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Phosphomevalonate kinase | centertop11MevPK | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Diphosphomevalonate decarboxylase | centertop11MevPPD | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Isopentenyl-diphosphate delta-isomerase | centertop11IPPI | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Farnesyl diphosphate synthase | centertop11FPPS | centertop113 | centertop111 | centertop111 | centertop116 | centertop111 | centertop112 |
| lefttop11Isoprenoid branch of JH biosynthesis | lefttop11Farnesyl phosphatase | centertop11FPPase | centertop112 | centertop111 | centertop111 | centertop112 | centertop113 | centertop112 |
| lefttop11 | lefttop11Farnesol dehydrogenase | centertop11FOHSDR | centertop111 | centertop116 | centertop116 | centertop112 | centertop117 | centertop111 |
| lefttop11 | lefttop11Aldehyde dehydrogenase | centertop11ALDH | centertop112 | centertop111 | centertop111 | centertop111 | centertop116 | centertop112 |
| lefttop11 | lefttop11Juvenile hormone acid methyltransferase | centertop11JHAMT | centertop117 | centertop111 | centertop111 | centertop111 | centertop113 | centertop111 |
| lefttop11 | lefttop11Farnesoic acid O-methyltransferase | centertop11FAMeT | centertop117 | centertop111 | centertop111 | centertop112 | centertop111 | centertop115 |
| lefttop11 | lefttop11Cytochrome P450 15A1 | centertop11Cyp15A1 | centertop11- | centertop11- | centertop11- | centertop111 | centertop111 | centertop11- |
| lefttop11 | lefttop11Cytochrome P450 15C1 | centertop11Cyp15C1 | centertop111 | centertop11- | centertop11- | centertop11- | centertop11- | centertop111 |
| lefttop11Neuropeptide regulation of JH biosynthesis | lefttop11Allototropin | centertop11AT | centertop111 | centertop11- | centertop111 | centertop11- | centertop111 | centertop111 |
| lefttop11 | lefttop11Allatostatin | centertop11AS | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Allototropin receptor | centertop11ATR | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Allatostatin receptor | centertop11ASR | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11JH metabolism | lefttop11Juvenile hormone esterase | centertop11JHE | centertop114 | centertop112 | centertop112 | centertop112 | centertop111 | centertop111 |
| lefttop11 | lefttop11Juvenile hormone epoxide hydrolase | centertop11JHEH | centertop116 | centertop113 | centertop113 | centertop111 | centertop115 | centertop118 |
| lefttop11 | lefttop11Juvenile hormone diol kinase | centertop11JHDK | centertop113 | centertop111 | centertop111 | centertop111 | centertop111 | centertop112 |
| lefttop11JH signaling | lefttop11Juvenile hormone binding protein | centertop11JHBP | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11FKBP39 | centertop11FKBP39 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Chd64 | centertop11Chd64 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Methoprene-tolerant/Methoprene-tolerant 1 | centertop11Met/Met1 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Germ cell expressed/Methoprene-tolerant 2 | centertop11Gce/Met2 | centertop111 | centertop111 | centertop11- | centertop11- | centertop11- | centertop111 |
| lefttop11 | lefttop11Ecdysone receptor | centertop11EcR | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Ultraspiracle | centertop11USP | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
| lefttop11 | lefttop11Kruppel homolog 1 | centertop11Kr-h1 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 | centertop111 |
Note: - represents no identification.
The upstream mevalonate (MVA) pathway of JH biosynthesis is responsible for producing the JH precursor farnesyl diphosphate (FPP). As shown in Figure S1, the MVA pathway involved eight enzymatic steps. Interestingly, each of the enzyme-encoding genes involved in the first seven steps of the MVA pathway, which produce the FPP precursor isopentenyl diphosphate (IPP), existed as a single copy in B. mori and five other surveyed insects and showed a 1:1:1:1:1:1 orthologous relationship ( Table 2).
Farnesyl diphosphate synthase (FPPS) catalyzes the final reaction of the MVA pathway, converting IPP into the JH precursor FPP. Three transcripts of the FPPS gene have been identified in B. mori ( Kinjoh et al., 2007 ). We noted that only two FPPS transcripts matched well with two predicted genes for B. mori, namely, FPPS1 for BGIBMGA001926 and FPPS2 for BGIBMGA001927. We further used the complete cDNA sequence of the FPPS3 transcript to search against the B. mori genome assembly using the BLASTn algorithm. In this search, we found that the FPPS3 transcript matched the downstream genomic region of the FPPS2 gene; therefore, we defined FPPS3 as BGIBMGA014635 for a supplement of the B. mori predicted genes. Strikingly, a comparative analysis revealed a copy number variation in the FPPS genes among the surveyed insects. In addition to three copies in B. mori, there were six copies in A. mellifera, two in D. plexippus, and one each in D. melanogaster, A. gambiae, and T. castaneum. From the phylogenetic tree of the FPPS and FPPS-like genes that were identified here and collected from online resources for other insects ( Figure 2), we observed that all FPPS and FPPS-like genes from B. mori and other lepidopterans, including D. plexippus, Heliconius melpomene, Choristoneura fumiferana, Mythimna unipuncta, and Agrotis ipsilon, clustered into two groups, and different copies from each insect were separately grouped, indicating that the FPPS duplication in lepidopterans may have occurred after their separation from other insect species and before their separation from each other. However, all six FPPS-like genes in A. mellifera grouped well together, suggesting that the FPPS genes from A. mellifera may have been duplicated after the separation of A. mellifera from other insects. The FPPS genes from other five insect species, including Aedes aegypti, Culex quinquefasciatus, Anthonomus grandis, Dendroctonus jeffreyi, and Nasonia vitripennis, also existed as a single copy and clustered together with the FPPS genes from D. melanogaster, A. gambiae, and T. castaneum.
Phylogenetic tree of the FPPS genes from B. mori and other insects. Based on the multiple alignments of the amino acid sequences of FPPS proteins from B. mori and other insects, a phylogenetic tree was constructed using the neighbor-joining method with 1000bootstrap replicates after removing the highly divergent sequences at the N- or C-terminus. Bootstrap values > 60% are marked. Bm, Bombyx mori; Dm, Drosophila melanogaster; Aga, Anopheles gambiae; Am, Apis mellifera; Tc, Tribolium castaneum; Dp, Danaus plexippus; Cf, Choristoneura fumiferana; Hm, Heliconius melpomene; Mu, Mythimna unipuncta; Agi, Agrotis ipsilon; Aa, Aedes aegypti; Cq, Culex quinquefasciatus; Agr, Anthonomus grandis; Dj, Dendroctonus jeffreyi; Nv, Nasonia vitripennis.
The downstream isoprenoid branch pathway of JH biosynthesis converts FPP to JH ( Minakuchi et al., 2006 ). Recently, in insects, three types of catalytic enzymes, including farnesyl pyrophosphate phosphatase (FPPase), farnesol dehydrogenase (FOHSDR), and aldehyde dehydrogenase (ALDH), have been successfully identified as being responsible for the sequential conversion of FPP into farnesol, farnesal, and farnesoic acid (FA) ( Mayoral et al., 2009 ; Nyati et al., 2013 ; Rivera-Perez et al., 2013 ). In addition to the previous prediction of these genes in several insects, we identified two FPPase-like genes, one FOHSDR gene, and two ALDH-like genes in D. plexippus. Although each of these genes exhibited a different number of copies among the surveyed insects, the copy number of each gene was the same in B. mori and D. plexippus as well as in D. melanogaster and A. gambiae ( Table 2 and Table S2).
The conversion of FA into JH is completed via two catalytic reactions in insects, namely, epoxidation and methyl esterification. Notably, this conversion can occur in two ways ( Figure S1). One involves FA oxidation by Cyp15C1 to form JH acid (JHA), after which JHA is methylated by juvenile hormone acid methyltransferase (JHAMT) to synthesize JH. Another way is that FA is methylated to form methyl farnesoate (MF) by farnesoic acid O-methyltransferase (FAMeT), after which MF is oxidized by Cyp15A1 to produce JH.
Cyp15C1 and Cyp15A1, the two genes involved in FA epoxidation, belong to the Cyp15 subfamily of cytochrome P450 enzymes. The Cyp15C1 gene has been identified in B. mori and D. plexippus, and the Cyp15A1 gene has been characterized in T. castaneum and A. mellifera ( Daimon et al., 2012 ; Daimon and Shinoda 2013). No Cyp15C1 or Cyp15A1 was identified in D. melanogaster. We performed a BLASTp search against the genome of H. melpomene (Lepidoptera) and identified a homolog of the B. mori Cyp15C1 gene, namely, HMEL006305, further indicating that Cyp15C1 may be Lepidoptera-specific.
JHAMT and FAMeT are considered two catalytic enzymes for the methyl esterification of FA. One authentic JHAMT enzyme was first characterized in B. mori ( Shinoda and Itoyama, 2003). As listed in Table 1, the gene (BGIBMGA010391) encoding the authentic JHAMT and six JHAMT-like genes (from JHAMT-l1 to JHAMT-l6) were found in the B. mori genome, and each contains a methyltransf_12 domain. Furthermore, three JHAMT copies (including authentic JHAMT, JHAMT-l1, and JHAMT-l2) were predicted in T. castaneum, whereas only one copy of JHAMT gene was identified in four other insects ( Table 2 and Table S2). A phylogenetic tree revealed that the different copies of the JHAMT gene in B. mori and D. plexippus grouped well together, and that the three JHAMT copies in T. castaneum also grouped into a clade ( Figure S2), suggesting that the JHAMT gene in B. mori or T. castaneum was duplicated after their separation from other insect species.
FAMeT has been found to exist in insects and crustaceans ( Hui et al., 2010 ), and evidence from D. melanogaster has suggested that FAMeT has a minor role in JH biosynthesis, but it may play a major role in JH signaling ( Burtenshaw et al., 2008 ; Zhang et al., 2010 ). Our data revealed that in the B. mori genome, there are seven FAMeT-like genes, each of which contains two typical Methyltransf_FA and DM9 domains. Comparatively, FAMeT exists as a single copy in T. castaneum as well as in two Diptera insects but as two copies in A. mellifera and five copies in D. plexippus ( Table 2 and Table S2). A phylogenetic tree of insect FAMeT or FAMeT-like genes was constructed using their coding sequences containing two functional domains ( Figure S2). In this tree, with the exception of A. mellifera, one copy of the FAMeT gene from each of the five remaining insects grouped into a clade. Other copies of the FAMeT gene from B. mori, A. mellifera, and D. plexippus grouped together into an additional clade in an irregular manner. This phylogenetic relationship indicates that the duplication of the different FAMeT copies may have occurred after insect radiation and subsequently undergone a rapid sequence diversification during insect evolution.
Insect JH biosynthesis is also modulated by two neuropeptides, namely, allatotropin (AT) and allatostatin (AS). AT and AS play antagonistic roles during JH bio-synthesis, with the former being a stimulator and the later being an inhibitor of CA activity ( Stay, 2000). As listed in Table 1, from the B. mori genome, we retrieved four genes that respectively encode AT, AS, the AT receptor (ATR), and the AS receptor (ASR), which have been previously reported in other insects ( Secher et al., 2001 ; Park et al., 2002 ; Roller et al., 2008 ; Yamanaka et al., 2008 ; Horodyski et al., 2011 ). In addition, AS, ASR, and ATR were all identified in five other insects, whereas AT gene was predicted only in A. gambiae, T. castaneum, and D. plexippus in our analysis. Notably, each of the identified genes related to the neuropeptide regulation of JH bio-synthesis appears to exist as a single copy in B. mori and the other surveyed insects ( Table 2).
The metabolic degradation of JH contributes to the reduction of JH titer and is catalyzed by three enzymes, namely, JHE, JHEH, and JHDK. As shown in Figure S1, JHE catalyzes the conversion of JH into JH acid (JHa) or the conversion of JH diol (JHd) into JH acid diol (JHad). A previous report characterized one JHE gene encoding an authentic JHE enzyme in B. mori ( Hirai et al., 2002 ). Here, in addition to the known JHE gene, three JHE-like genes (namely, JHE-l1, JHE-l2, and JHE-l3) were identified from the B. mori genome ( Table 1). Moreover, we retrieved different copies of the JHE gene in five other insects, namely, 2, 2, 2, 1, and 1 for D. melanogaster, A. gambiae, A. mellifera, T. castaneum, and D. plexippus, respectively ( Table 2 and Table S2). All the identified JHE genes contain a COesterase domain. A phylogenetic analysis showed that the JHE genes in Lepidoptera, Hymenoptera, Diptera, or Coleoptera separately grouped well together ( Figure S3), consistent with the classical phylogeny of these insect species. Notably, different copies of the JHE gene in D. melanogaster grouped first together, as did those in A. gambiae and A. mellifera, suggesting that JHE duplication in these three species occurred after their separation. Nevertheless, in Lepidoptera, JHE from B. mori grouped first with JHE from D. plexippus and then with the grouping clade of JHE-l1 and JHE-l2 from B. mori, suggesting that JHE in both B. mori and D. plexippus may have a common ancestor, and the other three JHE-like genes in B. mori may have undergone a great sequence diversification after their duplication from JHE.
JHEH catalyzes the conversion of JH into JHa or the conversion of JHa into JHad. According to previous reports in B. mori ( Zhang et al., 2005 ; Seino et al., 2010 ),in addition to an authentic JHEH, there are five JHEH-like genes in the B. mori genome ( Table 1). The copy numbers of the JHEH genes vary, with three in D. melanogaster, three in A. gambiae, one in A. mellifera, five in T. castaneum, and seven in D. plexippus ( Table 2 and Table S2). On the phylogenetic tree of the JHEH genes ( Figure S3), different copies of the JHEH gene from each of four insect species ( D. melanogaster, A. gambiae, A. mellifera, and T. castaneum) grouped first together, indicating that the JHEH gene from these four species may have undergone species-specific duplication after their separation from the other insects. Moreover, the copies of the JHEH genes from two lepidopterans, B. mori and D. plexippus, grouped into four clades, and each clade contained different copies from both of these species, suggesting that JHEH duplication in Lepidoptera may have occurred before their radiation.
JHDK is required for the conversion of JHd into JH diol phosphate (JHdp). To date, JHDK has been functionally characterized in two Lepidoptera insects, namely, B. mori and Manduca sexta ( Maxwell et al., 2002 ; Li et al., 2005 ). Here, three copies of the JHDK gene were identified in the B. mori genome ( Table 1), including one authentic JHDK and two JHDK-like genes, each of which contains an EF-hand domain. Furthermore, as listed in Table 2 and Table S2, there were two copies of the JHDK gene in another lepidopteran, D. plexippus, but only one copy was identified in four other surveyed insects. Phylogenetic analysis showed that the JHDK copies from Lepidoptera grouped into two clades, and the JHDK genes from other insects grouped well together ( Figure S3), suggesting that JHDK duplication in Lepidoptera may have also occurred before their separation.
Recently, additional evidence has shown that the bHLH-PAS transcription factor Met is a potential receptor for JH signaling ( Jindra et al., 2013 ). Met and its paralogous gene Gce were first identified in D. melanogaster ( Wilson and Fabian, 1986; Baumann et al., 2010b ), in which they were partially redundant in mediating JH signaling ( Baumann et al., 2010a ; Abdou et al., 2011 ). Two copies of the Met gene, Met1 and Met2, have been characterized in B. mori ( Li et al., 2010 ; Guo et al., 2012 ; Kayukawa et al., 2012 ). Intriguingly, our analysis also identified two copies of the Met gene in two other lepidopteran insects, D. plexippus and H. melpomene, namely DpMet-l1 and DpMet-l2 in D. plexippus ( Table 2 and Table S2) and HmMet-l1 (HMEL011931) and HmMet-l1 (HMEL009818) in H. melpomene. However, only one copy of the Met gene was identified in A. gambiae, A. mellifera, and T. castaneum ( Table 2 and Table S2). Phylogenetic analysis revealed that Met and Gce from D. melanogaster grouped together ( Figure 3). In Lepidoptera, Met1 and Met-l1 grouped into one clade, whereas Met2 and Met-l2 grouped into another, indicating that the Met duplication in Lepidoptera may have occurred before their separation.
Phylogenetic tree of the Met genes in B. mori and other insects. The amino acid sequences encoding by Met genes from seven insect species, including Bombyx mori (Bm), Drosophila melanogaster (Dm), Anopheles gambiae (Aga), Apis mellifera (Am), Tribolium castaneum (Tc), Danaus plexippus (Dp), and Heliconius melpomene (Hm), were used to build a phylogenetic tree. See Figure 2 for a detailed description of the approaches for constructing phylogenetic tree.
In addition, some molecules, including JHBP, FKBP39, Chd64, EcR, USP, and Kr-h1, have been demonstrated to be involved in JH signaling ( Dubrovsky, 2005; Li et al., 2007 ; Jindra et al., 2013 ). Our results showed that each of these six genes was identified as having one copy in B. mori and five other insect species ( Table 2 and Table S2).
Using microarray data of gene expression in multiple tissues of B. mori larvae on the third day of the fifth instar when JH titer is present ( Sakurai and Niimi, 1997; Xia et al., 2007 ), we investigated the tissue expression of JH-related genes. As a result, 36 of 55 JH-related genes were detected in at least one tissue ( Figure 4). Among JH bio-synthesis-related genes, Acat, MevPK, IPPI, FPPS2, ALDH-l1, JHAMT-I6, FAMeT-I4, and Cyp15C1 were expressed in the head (mainly containing CA, CC, and brain), which may be directly involved in JH biosynthesis. In particular, several JH biosynthesis-related genes showed either high expression in other larval tissues or ubiquitous expression, such as Acat and MevPK in all surveyed tissues; FAMeT-l1, FAMeT-l5, and FAMeT-l7 in the midgut; and JHAMT-l4, JHAMT-l5, and JHAMT-l6 in the fat body and integument. This indicates that these genes may function in other biological processes.
Expression pattern of JH-related genes in multiple tissues from B. mori larvae. Microarray data of genome-wide gene expression in multiple tissues from B. mori larvae on the third day of the fifth instar were downloaded from the B. mori genome database. Each tissue sample was analyzed with at least two biological repeats. If a JH-related gene was estimated to have an average expression signal intensity of more than 400 in any tissue, it was considered to be expressed in that tissue. F, female; M, male. A/MSG, anterior/median silk gland; PSG, posterior silk gland.
Some genes involved in JH metabolism are mostly expressed in the midgut or Malpighian tubule ( Figure 4). For example, five genes, namely, JHE-l1, JHEH, JHEH-l4, JHDK, and JHDK-l1, were expressed in both the midgut and Malpighian tubule. JHEH-l1 and JHDK-l2 were expressed in the midgut and Malpighian tubule, respectively. JHE-l3 and JHEH-l2 expression was enriched in both the A/MSG and PSG, whereas JHEH6 was highly expressed in all tissues with the exception of hemocytes. JHEH-l2 was specifically expressed in the A/MSG. In addition, among the genes involved in the JH signaling pathway, JHBP, Met1, EcR, FKBP39, and Chd64 were all weakly expressed in at least one larval tissue. In particular, FKBP39 and Chd64 were expressed in all analyzed tissues. However, from the microarray data, the expression of three genes, USP, Met2, and Kr-h1, was not observed in any tissue. It is possible that the expression levels for these three transcription factors may be too low at day 3 of the fifth larval instar and were therefore difficult to be detected.
Based on microarray data for gene expression at 19 developmental points during B. mori metamorphosis (unpublished data), we found that 42 of 55 JH-related genes were expressed during at least one developmental point ( Figure 5). Among the genes involved in the MVA pathway of JH biosynthesis the majority were highly expressed during the pupa-adult transition, with the exception of MevK, whose expression was detected in the female on the fourth day of the fifth larval instar (V4). In particular, Acat and IPP1 displayed a high expression in males, whereas FPPS1 and FPPS3 were highly expressed in females. Among the genes involved in the isoprenoid branch of JH biosynthesis, only ALDH-l1, Cyp15C1, and several copies of JHAMT and FAMeT were detected during metamorphosis, and they were highly expressed before wandering and during the pupa-adult transition ( Figure 5). In particular, FAMeT-l2 and FAMeT-l4 exhibited a male-specific expression pattern during the pupa-adult transition. Further studies will be required to decipher the roles of these two FAMeT genes during the development of B. mori males.
Expression profiles of JH-related genes during metamorphosis in B. mori. The developmental expression profiles of JH-related genes for B. mori were analyzed using microarray data of genome-wide gene expressions at 19 time points during B. mori metamorphosis. The ratio was calculated by comparing the signal intensity of the mRNA expression level for each JH-related gene at each time point to that in the common reference of larvae on the third day of the fifth instar in B. mori. Subsequently, the expression change of each JH-related gene was evaluated by this expression ratio and visualized using the GeneCluster2.0 program. Plus and minus denote up- and down-regulation, respectively.
Microarray data of gene expression during B. mori metamorphosis also revealed that among the genes involved in JH metabolism, JHE and JHE-l1 were highly expressed during pupation. JHEH, JHEH-l2, JHEH-l4, JHEH-l5, JHDK-l1, JHDK, and JHDK-l2 were mainly expressed before wandering. JHEH-l1 and JHEH-l3 displayed a high expression in females during pupa-adult transition. Among the genes involved in JH signaling, JHBP, FKBP39, Chd64, and Met1 exhibited ubiquitous expression during B. mori metamorphosis. Met2 expression was detected only in males during pupa-adult transition, and EcR and USP were highly expressed before wandering. Kr-h1 presented a high expression during the late stage of the pupa-adult transition.
Because JH biosynthesis and JH metabolism are initiated during larval feeding and molting, respectively, we used real-time quantitative RT-PCR experiments to further check the consistency between JH titer and the expression profiles of several JH-related genes with multiple copies during B. mori larval growth. As shown in Figure 6, FPPS1 expression was highly during B. mori larval molting and gradually decreased during larval feeding, which was consistent with the changes in JH titer. Interestingly, FPPS1 expression at the beginning of the feeding stages was higher in the fifth instar larvae than in the fourth instar larvae. Several copies of the genes involved in the isoprenoid branch of JH biosynthesis, including JHAMT-l3, JHAMT-l4, FAMeT-l2, and FAMeT-l5, exhibited a high expression during larval feeding and subsequently decreased during larval molting, also indicating consistency with the changes in the JH titer. Moreover, four copies of the genes involved in JH metabolism, including JHE-l1, JHE-l3, JHDK, JHDK-l1, JHDK-l2, JHEH-l1, JHEH-l3, and JHEH-l5, showed an increased expression during larval feeding and were obviously decreased during larval molting. The expression of these genes was also consistent with the change in JH titer during B. mori larval feeding and molting.
Expression patterns of JH-related genes with multiple copies during larval growth and molting in B. mori. Quantitative analysis of the gene expression of JH-related genes with multiple copies during larval growth and molting in B. mori was performed by real-time RT-PCR. The B. mori ribosomal protein L3 ( RpL3) gene was used as an internal control. IV0, immediately after completion of the third larval molting and the beginning of feeding in the fourth larval instar; IV1, one day after feeding in the fourth larval instar; IV2, two days after feeding in the fourth larval instar; IV3, three days after feeding in the fourth larval instar; IV4, four days after feeding in the fourth larval instar; IVM, the fourth larval molting; V0, immediately after completion of the fourth larval molting and the beginning of feeding in the fifth larval instar; V1, one day after feeding in the fifth larval instar.
JH plays key roles in the regulation of various aspects of insect growth and development. Previous studies have reported the genome-wide identification of genes involved in JH biosynthesis, metabolic degradation, or signaling in several insect species, such as the JH biosynthesis-related genes in B. mori ( Kinjoh et al., 2007 ; Xia et al., 2008 ), JHEs in A. aegypti ( Bai et al., 2007 ), and JHEHs in T. castaneum ( Seino et al., 2010 ). To understand comprehensively the evolutionary conservation and variation of JH-related genes in insects, we systematically identified and compared JH-related genes in B. mori and five other insect species whose whole genomes have been sequenced, including the recently completed D. plexippus (Lepidoptera) genome sequence.
The developmental changes in JH titer in insects are mainly controlled by the processes of biosynthesis in the CA and metabolic degradation in the targeting tissues. Here, we observed an evolutionary divergence of the genes involved in JH biosynthesis among B. mori and other insects. First, the genes related to the upstream seven steps of the MVA pathway of JH biosynthesis, which is responsible for producing IPP as FPP precursor, all existed as a single copy and displayed a rigorous orthologous relationship among the analyzed insects ( Table 2 and Table S2), indicating that the process of IPP production was conserved during insect evolution. Second, the FPPS gene involved in the last step of the MVA pathway (production of JH precursor FPP) and all identified genes participating in the isoprenoid branch for producing JH showed a variation in copy number or gene class among B. mori and other insects ( Table 2 and Table S2), which may be a consequence of gene duplication. In fact, JH types also varied between Lepidoptera and other insect orders, and more types of JH variants are present in Lepidoptera ( Minakuchi et al., 2006 ; Riddiford, 2008; Goodman and Cusson, 2012; Daimon and Shinoda, 2013; Jindra et al., 2013 ). Thus, we speculate that the copy variation among the genes involved in the FPP production from IPP and in the isoprenoid branch may reflect the functional divergence of the associated gene products, and is likely linked to the diversity of JH types among insects. Our comparison raised two additional issues regarding the relationship between the variations in JH-related genes and in JH types. One issue is that FPPS genes from Lepidoptera may have undergone a species-specific divergence ( Figure 2), which agrees with previous findings ( Kinjoh et al., 2007 ). Therefore, we hypothesize that FPPS-mediated enzymatic reactions may be the first step leading to the diversity of JH types among insects. Undoubtedly, whether all the predicted FPPS genes are authentically involved in JH biosynthesis needs to be investigated by more enzymatic experiments. However, JHAMT and FAMeT, two enzymes involved in the methyl esterification of FA, were predicted in B. mori and other insects ( Table 2 and Table S2). Previous studies in D. melanogaster have reported that FAMeT was likely not involved in JH biosynthesis ( Burtenshaw et al., 2008 ; Zhang et al., 2010 ). However, another analysis speculated that FAMeT-mediated methyl esterification should exist in insects and crustaceans ( Hui et al., 2010 ). Undoubtedly, more evidence is required to resolve the controversial functions of FAMeTs in JH biosynthesis. Furthermore, Cyp15C1 and Cyp15A1 were confirmed to be involved in two routes of FA epoxidation ( Daimon and Shinoda, 2013). However, several surveyed insects do not contain either Cyp15C1 or Cyp15A1 ( Table 2 and Table S2). Thus, additional experiments are needed to address whether both epoxidation routes occur in insects with no Cyp15C1 or no Cyp15A1 or whether other Cyp genes whose functions have yet to be identified catalyze one or the other route. Finally, all identified genes involved in neuropeptide regulation of JH biosynthesis existed as a single copy, implying that their regulatory mechanism is also conserved among insects.
The metabolic degradation of JH is catalyzed mainly by JHE, JHEH, and JHDK. Our results showed that each of the genes encoding these three enzymes may have undergone duplication in Lepidoptera ( Table 2 and Table S2). In particular, JHDK has multiple copies in Lepidoptera but one copy in the other surveyed insects. Given the existence of more JH types in Lepidoptera, we propose that, as was true of copy variation among several JH biosynthesis-related genes, the duplication and divergence of JH metabolism-related genes may also be a functionally adaptive evolution to the diversity of JH types in insects.
The nature of JH signaling has been the subject of an increasing number of experimental studies. To date, it has been confirmed that seven genes, namely, JHBP, FKBP39, Chd64, EcR, USP, Met, and Kr-h1, are implicated in JH signaling ( Li et al., 2007 ; Suzuki et al., 2011 : Jindra et al., 2013 ). Except for Met, each of the other genes existed as a single copy in B. mori and other surveyed insects ( Table 2 and Table S2). The Met protein is a bHLH-PAS transcription factor and has been characterized as a JH receptor in insects ( Wilson and Fabian, 1986; Jindra et al., 2013 ). Unlike the single copy of the Met gene in A. gambiae, A. mellifera, and T. castaneum, two copies of the Met gene have been identified previously in other insects, namely, Met and Gce in Drosophila ( Baumann et al., 2010b ) and Met1 and Met2 in B. mori ( Li et al., 2010 ; Guo et al., 2012 ; Kayukawa et al., 2012 ). Our analysis also identified two copies ( Met-l1 and Met-l2) of the Met gene in two other lepidopterans, D. plexippus and H. melpomene. Although current evidence is not sufficient to elucidate why Met was duplicated in these insects, two copies of the Met gene have been demonstrated to cooperatively modulate JH signaling via a protein-protein interaction in D. melanogaster ( Baumann et al., 2010a ; Abdou et al., 2011 ) and in B. mori ( Guo et al., 2012 ; Kayukawa et al., 2012 ). Together with the findings from the phylogenetic tree of insect Met genes ( Figure 3) and the functional redundancy of two copies of the Met gene, we propose that the JH signaling cascade is also evolutionarily conserved across insects.
Given that multiple copies were predicted for several genes involved in JH biosynthesis and metabolism, it was important to determine whether these copies were functional. Our microarray data and quantitative RT-PCR experiments in B. mori showed that some copies of the JH-related genes exhibited moderate expression in the head (mainly containing CA, CC, and brain) or in a dynamic manner that correlated with the temporal changes in JH titer, such as FPPS1, FPPS2, JHAMT-l3, JHAMT-l4, JHE-l1, JHEH-l5, JHDK, and JHDK-l2. Previous studies have confirmed the enzymatic activities or physiological functions of several JH-related genes in B. mori, such as JHAMT ( Shinoda and Itoyama, 2003), JHE ( Tan et al., 2005 ), JHEH ( Seino et al., 2010 ), and JHDK ( Li et al., 2005 ). One copy of the JHAMT gene has also been verified to be activated functionally in JH biosynthesis in T. castaneum (Minakuchi and Riddiford, 2008). Furthermore, most enzyme-encoding genes with multiple copies appear to be expressed in other larval tissues excluding head (mainly containing CA, CC, and brain), during developmental stages with no JH activities, or in one or other sex ( Figures 4, 5 and 6). These observations indicate that the copies of the JH-related genes may play roles in other physiological processes. Nevertheless, further enzymatic activity assays are undoubtedly required to assess whether multiple copies of the JH-related genes encode authentic enzymes involved in JH biosynthesis and metabolism or encode proteins involved in other physiological processes.
In summary, we first performed a systematic identification of the genes involved in JH biosynthesis, metabolism, and signaling in insects, including two lepidopterans ( B. mori and D. plexippus), two dipterans ( D. melanogaster and A. gambiae), one hymenopteran ( A. mellifera), and one coleopteran ( T. castaneum). A comparative analysis concluded that the early steps of the MVA pathway and neuro-peptide regulation of JH biosynthesis, as well as JH signaling, are apparently conserved among B. mori and other surveyed insects. However, most genes involved in the last step of the MVA pathway and the isoprenoid branch of JH biosynthesis, as well as JH metabolism, seem to have undergone duplication, resulting in multiple copies in Lepidoptera. This duplication may be functionally and evolutionarily relevant to the variation of JH types among Lepidoptera and other insect species. Although some copies of several JH-related multi-copy genes show a specific spatio-temporal expression correlated to JH activity in B. mori, it remains to be confirmed whether their enzymatic activities are associated with JH biosynthesis and metabolism. Taken together, the results of our analysis provide new clues for understanding the genetic basis of JH bio-synthesis, metabolism, and signaling in insects.
This work was supported by grants from the National Basic Research Program of China (No. 2012CB114600), the National Hi-Tech Research and Development Program of China (No. 2011AA100306), the National Natural Science Foundation of China (No. 31172267 and No. 31272503), and the Municipal Natural Science Foundation of Chongqing (No. cstc2012jjA80023).
Associate Editor: Houtan Noushmehr
The following online material is available for this article:
Table S1 - RT-PCR Primers used in this study.
Table S2 - JH-related genes in the other surveyed insects.
Figure S1 - Summary of insect JH-related pathways.
Figure S2 - Phylogenetic tree of the JHAMT and FAMeT genes.
Figure S3 - Phylogenetic tree of the JHE, JHEH, and JHDK genes.
This material is available as part of the online article from


1.1 Purpose, Authority, Issuance
1.3 Agency Acquisition Regulations
1.5 Agency and Public Participation
1.6 Career Development, Contracting Authority, and Responsibilities
1.7 Determinations and Findings
3.2 Contractor Gratuities to Government Personnel
3.3 Reports of Suspected Antitrust Violations
3.5 Other Improper Business Practices
3.6 Contracts with Government Employees or Organizations Owned or Controlled by Them
3.7 Voiding and Rescinding Contracts
3.8 Limitations on the Payment of Funds to Influence Federal Transactions
3.9 Whistleblower Protections for Contractor Employees
3.10 Contractor Code of Business Ethics and Conduct
4.4 Safeguarding Classified Information Within Industry
4.5 Electronic Commerce in Contracting
4.7 Contractor Records Retention
4.9 Taxpayer Identification Number Information
4.11 System for Award Management
4.12 Representations and Certifications
4.13 Personal Identity Verification
4.14 Reporting Executive Compensation and First-Tier Subcontract Awards
4.16 Unique Procurement Instrument Identifiers
4.17 Service Contracts Inventory
4.18 Commercial and Government Entity Code
4.19 Basic Safeguarding of Covered Contractor Information Systems
5.1 Dissemination of Information
5.2 Synopses of Proposed Contract Actions
5.3 Synopses of Contract Awards
5.6 Publicizing Multi-Agency Use Contracts
5.7 Publicizing Requirements Under the American Recovery and Reinvestment Act of 2009
6.2 Full and Open Competition After Exclusion of Sources
6.3 Other Than Full and Open Competition
6.4 Sealed Bidding and Competitive Proposals
7.2 Planning for the Purchase of Supplies in Economic Quantities
7.3 Contractor Versus Government Performance
7.4 Equipment Lease or Purchase
7.5 Inherently Governmental Functions
8.6 Acquisition from Federal Prison Industries, Inc.
8.7 Acquisition from Nonprofit Agencies Employing People Who Are Blind or Severely Disabled
8.8 Acquisition of Printing and Related Supplies
8.11 Leasing of Motor Vehicles
9.1 Responsible Prospective Contractors
9.2 Qualifications Requirements
9.3 First Article Testing and Approval
9.4 Debarment, Suspension, and Ineligibility
9.5 Organizational and Consultant Conflicts of Interest
9.6 Contractor Team Arrangements
9.7 Defense Production Pools and Research and Development Pools
11.1 Selecting and Developing Requirements Documents
11.2 Using and Maintaining Requirements Documents
11.4 Delivery or Performance Schedules
11.6 Priorities and Allocations
12.1 Acquisition of Commercial Items—General
12.2 Special Requirements for the Acquisition of Commercial Items
12.3 Solicitation Provisions and Contract Clauses for the Acquisition of Commercial Items
12.4 Unique Requirements Regarding Terms and Conditions for Commercial Items
12.6 Streamlined Procedures for Evaluation and Solicitation for Commercial Items
13.2 Actions At or Below the Micro-Purchase Threshold
13.3 Simplified Acquisition Methods
13.5 Simplified Procedures for Certain Commercial Items
14.4 Opening of Bids and Award of Contract
15.1 Source Selection Processes and Techniques
15.2 Solicitation and Receipt of Proposals and Information
15.5 Preaward, Award, and Postaward Notifications, Protests, and Mistakes
16.3 Cost-Reimbursement Contracts
16.5 Indefinite-Delivery Contracts
16.6 Time-and-Materials, Labor-Hour, and Letter Contracts
17.4 Leader Company Contracting
17.6 Management and Operating Contracts
18.1 Available Acquisition Flexibilities
18.2 Emergency Acquisition Flexibilities
19.3 Determination of Small Business Status for Small Business Programs
19.4 Cooperation with the Small Business Administration
19.5 Set-Asides for Small Business
19.6 Certificates of Competency and Determinations of Responsibility
19.7 The Small Business Subcontracting Program
19.8 Contracting with the Small Business Administration (The 8(a) Program)
19.13 Historically Underutilized Business Zone (HUBZone) Program
19.14 Service-Disabled Veteran-Owned Small Business Procurement Program
19.15 Women-Owned Small Business Program.
22.3 Contract Work Hours and Safety Standards Act
22.4 Labor Standards for Contracts Involving Construction
22.5 Use of Project Labor Agreements for Federal Construction Projects
22.6 Contracts For Materials, Supplies, Articles, and Equipment Exceeding $15,000
22.8 Equal Employment Opportunity
22.9 Nondiscrimination Because of Age
22.10 Service Contract Labor Standards
22.11 Professional Employee Compensation
22.12 Nondisplacement of Qualified Workers Under Service Contracts
22.13 Equal Opportunity for Veterans
22.14 Employment of Workers with Disabilities
22.15 Prohibition of Acquisition of Products Produced by Forced or Indentured Child Labor
22.16 Notification of Employee Rights Under the National Labor Relations Act
22.17 Combating Trafficking in Persons
22.18 Employment Eligibility Verification
22.19 Establishing a Minimum Wage for Contractors
23.1 Sustainable Acquisition Policy
23.2 Energy and Water Efficiency and Renewable Energy
23.3 Hazardous Material Identification and Material Safety Data
23.4 Use of Recovered Materials and Biobased Products
23.6 Notice of Radioactive Material
23.7 Contracting for Environmentally Preferable Products and Services
23.8 Ozone-Depleting Substances and Hydrofluorocarbons
23.9 Contractor Compliance with Environmental Management Systems
23.10 Federal Compliance with Right-to-Know Laws and Pollution Prevention Requirements
23.11 Encouraging Contractor Policies to Ban Text Messaging While Driving
24.1 Protection of Individual Privacy
24.2 Freedom of Information Act
25.2 Buy American—Construction Materials
25.3 Contracts Performed Outside the United States
25.5 Evaluating Foreign Offers—Supply Contracts
25.6 American Recovery and Reinvestment Act—Buy American statute—Construction Materials
25.8 Other International Agreements and Coordination
25.10 Additional Foreign Acquisition Regulations
25.11 Solicitation Provisions and Contract Clauses
26.2 Disaster or Emergency Assistance Activities
26.3 Historically Black Colleges and Universities and Minority Institutions
26.4 Food Donations to Nonprofit Organizations
27.3 Patent Rights under Government Contracts
27.4 Rights in Data and Copyrights
27.5 Foreign License and Technical Assistance Agreements
28.1 Bonds and Other Financial Protections
28.2 Sureties and Other Security for Bonds
30.3 CAS Rules and Regulations [Reserved]
30.4 Cost Accounting Standards [Reserved]
30.5 Cost Accounting Standards for Educational Institutions [Reserved]
31.2 Contracts with Commercial Organizations
31.3 Contracts with Educational Institutions
31.6 Contracts with State, Local, and Federally Recognized Indian Tribal Governments
31.7 Contracts with Nonprofit Organizations
32.1 Non-Commercial Item Purchase Financing
32.2 Commercial Item Purchase Financing
32.3 Loan Guarantees for Defense Production
32.4 Advance Payments for Non-Commercial Items
32.5 Progress Payments Based on Costs
32.10 Performance-Based Payments
32.11 Electronic Funds Transfer
34.2 Earned Value Management System
36.2 Special Aspects of Contracting for Construction
36.3 Two-Phase Design-Build Selection Procedures
36.6 Architect-Engineer Services
37.1 Service Contracts—General
37.2 Advisory and Assistance Services
37.3 Dismantling, Demolition, or Removal of Improvements
37.4 Nonpersonal Health Care Services
37.5 Management Oversight of Service Contracts
37.6 Performance-Based Acquisition
38.1 Federal Supply Schedule Program
38.2 Establishing and Administering Federal Supply Schedules
39.2 Electronic and Information Technology
41.2 Acquiring Utility Services
41.5 Solicitation Provision and Contract Clauses
42.2 Contract Administration Services
42.3 Contract Administration Office Functions
42.4 Correspondence and Visits
42.6 Corporate Administrative Contracting Officer
42.11 Production Surveillance and Reporting
42.12 Novation and Change-of-Name Agreements
42.13 Suspension of Work, Stop-Work Orders, and Government Delay of Work
42.15 Contractor Performance Information
42.16 Small Business Contract Administration
42.17 Forward Pricing Rate Agreements
44.3 Contractors’ Purchasing Systems Reviews
44.4 Subcontracts for Commercial Items and Commercial Components
45.2 Solicitation and Evaluation Procedures
45.3 Authorizing the Use and Rental of Government Property
45.4 Title to Government Property
45.5 Support Government Property Administration
45.6 Reporting, Reutilization, and Disposal
46.2 Contract Quality Requirements
46.4 Government Contract Quality Assurance
46.6 Material Inspection and Receiving Reports
46.8 Contractor Liability for Loss of or Damage to Property of the Government
47.2 Contracts for Transportation or for Transportation-Related Services
47.3 Transportation in Supply Contracts
47.4 Air Transportation by U.S.-Flag Carriers
47.5 Ocean Transportation by U.S.-Flag Vessels
49.2 Additional Principles for Fixed-Price Contracts Terminated for Convenience
49.3 Additional Principles for Cost-Reimbursement Contracts Terminated for Convenience
49.5 Contract Termination Clauses
49.6 Contract Termination Forms and Formats
50.1 Extraordinary Contractual Actions
50.2 Support Anti-terrorism by Fostering Effective Technologies Act of 2002
51.1 Contractor Use of Government Supply Sources
51.2 Contractor Use of Interagency Fleet Management System (IFMS) Vehicles
52.1 Instructions for Using Provisions and Clauses
52.2 Text of Provisions and Clauses
52.3 Provision and Clause Matrix


| Package | Description |
|---|---|
| org.apache.cayenne |
Contains persistence APIs directly accessible by users.
|
| org.apache.cayenne.access |
Contains classes that make up Cayenne ORM stack.
|
| org.apache.cayenne.access.translator.ejbql | |
| org.apache.cayenne.ejbql | |
| org.apache.cayenne.map |
Contains O/R mapping classes that store relational database
metadata information and map it to Java classes.
|
| org.apache.cayenne.query |
Defines standard queries supported by Cayenne and extension mechanism to create
custom queries.
|
| org.apache.cayenne.reflect | |
| org.apache.cayenne.reflect.generic | |
| org.apache.cayenne.reflect.valueholder | |
| org.apache.cayenne.util |
General utility classes.
|
| Class and Description |
|---|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| LifecycleCallbackRegistry
A registry of lifecycle callbacks for all callback event types.
|
| PropertyDescriptor
Defines bean property API used by Cayenne to access object data, do faulting
and graph maintenance tasks.
|
| Class and Description |
|---|
| Accessor
An accessor of a property value.
|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| Class and Description |
|---|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| Class and Description |
|---|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| Class and Description |
|---|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| ClassDescriptorMap
An object that holds class descriptors for mapped entities, compiling new
descriptors on demand using an internal chain of descriptor factories.
|
| LifecycleCallbackRegistry
A registry of lifecycle callbacks for all callback event types.
|
| Class and Description |
|---|
| ArcProperty
A Property that represents an "arc" connecting source node to the target node
in the graph.
|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| Class and Description |
|---|
| Accessor
An accessor of a property value.
|
| ArcProperty
A Property that represents an "arc" connecting source node to the target node
in the graph.
|
| AttributeProperty
Represents a simple object property.
|
| BaseArcProperty
A base implementation of the
ArcProperty . |
| BaseProperty
An abstract property descriptor that delegates property access to an
Accessor . |
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| ClassDescriptorFactory
A factory of
ClassDescriptor instances. |
| ClassDescriptorMap
An object that holds class descriptors for mapped entities, compiling new
descriptors on demand using an internal chain of descriptor factories.
|
| Converter
A helper class to do property type conversions.
|
| EmbeddableDescriptor |
| FaultFactory |
| PersistentDescriptor
A default ClassDescriptor implementation for persistent objects.
|
| PropertyDescriptor
Defines bean property API used by Cayenne to access object data, do faulting
and graph maintenance tasks.
|
| PropertyException
An unchecked exception thrown on errors during property access, either within a
Accessor or a Property.
|
| PropertyVisitor
A visitor for various types of properties in a ClassDescriptor.
|
| ToManyProperty
A property representing a collection of objects.
|
| ToOneProperty
An ArcProperty that points to a single graph node.
|
| Class and Description |
|---|
| Accessor
An accessor of a property value.
|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
| ClassDescriptorFactory
A factory of
ClassDescriptor instances. |
| ClassDescriptorMap
An object that holds class descriptors for mapped entities, compiling new
descriptors on demand using an internal chain of descriptor factories.
|
| FaultFactory |
| PersistentDescriptor
A default ClassDescriptor implementation for persistent objects.
|
| PersistentDescriptorFactory
A convenience superclass for
ClassDescriptorFactory implementors. |
| PropertyException
An unchecked exception thrown on errors during property access, either within a
Accessor or a Property.
|
| Class and Description |
|---|
| ClassDescriptorFactory
A factory of
ClassDescriptor instances. |
| ClassDescriptorMap
An object that holds class descriptors for mapped entities, compiling new
descriptors on demand using an internal chain of descriptor factories.
|
| PersistentDescriptor
A default ClassDescriptor implementation for persistent objects.
|
| PersistentDescriptorFactory
A convenience superclass for
ClassDescriptorFactory implementors. |
| Class and Description |
|---|
| Accessor
An accessor of a property value.
|
| ArcProperty
A Property that represents an "arc" connecting source node to the target node
in the graph.
|
| ClassDescriptor
A runtime descriptor of an persistent class.
|
Copyright © 2001–2019 Apache Cayenne. All rights reserved.


---
layout: null
section-type: about
title: About
---
## About
Andrew M. Olney presently serves as Professor in both the Institute for Intelligent Systems and Department of Psychology at the University of Memphis. Dr. Olney received a B.A. in Linguistics with Cognitive Science from University College London in 1998, an M.S. in Evolutionary and Adaptive Systems from the University of Sussex in 2001, and a Ph.D. in Computer Science from the University of Memphis in 2006. His primary research interests are in natural language interfaces. Specific interests include vector space models, dialogue systems, unsupervised grammar induction, robotics, and intelligent tutoring systems.


Contrary to popular belief, Lorem Ipsum is not simply random text.
Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of "de Finibus Bonorum et Malorum" (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, "Lorem ipsum dolor sit amet..", comes from a line in section 1.10.32.
There are many variations of passages of Lorem Ipsum available
Lorem Ipsum, you need to be sure there isn't anything embarrassing hidden in the middle of text. All the Lorem Ipsum generators on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words, combined with a handful of model sentence structures
All the Lorem Ipsum generators on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words, combined with a handful of model sentence structures
All the Lorem Ipsum generators on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words, combined with a handful of model sentence structures
Virginia, looked up one of the more obscure Latin words
Distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using
Lorem Ipsum, you need to be sure there isn't anything embarrassing hidden in the middle of text. All the Lorem Ipsum generators on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words


Please select the type of characters you wish to include in your password. Then click "Generate password" and choose the length you desire. To copy the generated password click "Copy to Clipboard".
Please select the type of characters you wish to include in your password. Then click "Generate password" and choose the length you desire. To copy the generated password click "Copy to Clipboard".


This scenario provides an example how mail client setup a device with supplied EAS policies. Mail client can check if current device settings are compliant with EAS policies required by EAS server. If some non-compliance settings can be changed to be compliant, mail client can apply the policy settings to the device.


public interface ICacheManager extends Closeable
| Modifier and Type | Method and Description |
|---|---|
void |
close() |
ClassLoaderOffer |
createOfferByItemName(String itemName)
Creates offer that corresponds to the specified item name
|
boolean |
deployFile(String fileName,
String offerName)
Deploys the specified file from the cache to the correct location.
|
byte[] |
getClassBytecode(String className,
String itemName)
Gets the bytecode of the specified class if it is registered in the cache.
|
String[] |
getClassesWithFiles(String itemName)
Gets the list of classes that have additional files within the item.
|
String |
getFileLocation(String fileName,
String itemName) |
String[] |
getItemNames(String className)
Gets the name of the items that contain provided class.
|
boolean |
isClassLoadedFromCache(Class<?> clazz)
Gets the value indicating if the class was loaded from cache (true)
or from the classpath of the application (false).
|
void |
registerOffer(ClassLoaderOffer offer)
Updates or registers new offer with the specified in offer parameters.
|
void |
removeOfferByName(String itemName)
Removes the offer with the specified name from the cache.
|
boolean isClassLoadedFromCache(Class<?> clazz)
clazz
- The class to determine loading source.String[] getItemNames(String className)
className
- The name of the class to get items for.String[] getClassesWithFiles(String itemName)
itemName
- The name of the item that classes with additional files should be related to.byte[] getClassBytecode(String className, String itemName)
className
- The name of the class to retrieve bytecode for.itemName
- The name of the item that should contain the specified classString getFileLocation(String fileName, String itemName)
fileName
- The name of the file to get location for.itemName
- The name of the item that should contain this file.ClassLoaderOffer createOfferByItemName(String itemName)
itemName
- The name of the item that offer should correspond to.void removeOfferByName(String itemName)
itemName
- void registerOffer(ClassLoaderOffer offer)
offer
- The offer that should be updated or registered.boolean deployFile(String fileName, String offerName)
fileName
- The name of the file to deployofferName
- The name of the offer where this file was registered.void close()
close
in interface AutoCloseable
close
in interface Closeable
Copyright © 2014. All Rights Reserved.


An abundance of
information has been compiled for MegaSquirt providing enough
information to successfully get your vehicle going on EFI and running
at its best. However, all this documentation can seem overwhelming to
wade through. This list of resources and key understandings hopefully
help you to get the answers you need. You will find it helpful to first
understand the separate components to get to the help you need.
As TunerStudio and
Megatune use the same ECU Definition ("ini") files for MS1 & MSII
the Navigation and dialog layouts are the same and the same manuals are
valid for TunerStudio. Some older firmwares have references to MegaTune
configuration, disregard these sections, but the settings for the
firmware will be the same.
MegaManual Table of Content - Index for information on assembling, trouble shooting, setup and tuning of MegaSquirt 1 and MegaSquirt 2 controllers. GPIO Documentation
- General Purpose IO board, various firmwares available to use this for
purposes from General IO to and Electronic Transmission Controller


Fines: Saving Lives or Revenue Leader?
Municipalities have budgeted R1.7 billion in revenues for the 2014 financial year. Nationwide municipalities have earned over R6 billion rand since July 2011. Have a look below at the revenue earned from each municipality.
Let's take a look at only municipalities in the Western Cape. Two municipalities seem to stick out, Laingsburg and Beaufort West.
What if we just highlighted only those municipalities through which the N1 passes?
In order not to distort that graphs, we clamped the upper values in the previous slides. Let's show the graph at full-scale. Notice Ubuntu municipality. They seem to have turned speeding fines into big business. 17% of their revenue comes from fines!
Blah 5
t
Municipality
% of revenue
Population:
X times higher than the national average.
Surprisingly, some municipalities seem to earn a large percentage of their revenue from fines. Also, the Western Cape and Northern Cape earn relatively more money from fines than other provinces.
We're also exploring the question of whether those municipalities which the N1 and N2 go through earn relatively more from fines than others. Initial results seem to confirm this. Here is a map showing fines per capita and here is one showing fines as a percentage of the total annual budget (these are just to see that relative values, the legends are on their way).
Finally, you can download our data here.
Note that large values are capped so as not to distort the graph too much.


--- title: "Simple Way to Make Quick Slow Cooker Spicy Sausage and Sweet Potato Soup Delicious" slug: slow-cooker-spicy-sausage-and-sweet-potato-soup description: "Slow Cooker Spicy Sausage and Sweet Potato Soup Recipe - This spicy sweet potato soup is a result of one of my slow cooker experiments, and my husband loves it. Great on a cool winter day with some homemade bread on the side.  Cook sausages in a skillet over high heat until browned but not cooked through, 3 to 5 minutes. Remove and pat dry with paper towels to remove excess fat.  - "Cook on High for 3 hours. Add black beans, reduce heat to Low, and cook for an additional 2 hours." categories: - "Soups Stews and Chili Recipes" - "Soup Recipes" - "Vegetable Soup Recipes" - "Sweet Potato Soup Recipes" - "Recipes" tags: - "soups stews and chili recipes" - "soup recipes" - "vegetable soup recipes" - "sweet potato soup recipes" katakunci: slow cooker spicy sausage and sweet potato soup, soups stews and chili recipes, soup recipes, vegetable soup recipes, sweet potato soup recipes, . nutrition: 581.1 calories recipecuisine: Western preptime: "P0DT0H20M" cooktime: "P0DT5H5M" totaltime: "P0DT5H25M" recipeyield: "4 servings" recipecategory: - Soups Stews and Chili Recipes - Soup Recipes - Vegetable Soup Recipes - Sweet Potato Soup Recipes quotes: Who needs inspirational quotes when you can just drink coffee? ---
Slow Cooker Spicy Sausage and Sweet Potato Soup - Hello everybody, hope you are having an incredible day today. Its me again Rika , welcome to our recipe website. Today, Im gonna show you how to make a special dish, Slow Cooker Spicy Sausage and Sweet Potato Soup. One of my favorites recipes. This time, Im gonna make it a little bit unique. This will be really delicious.
Slow Cooker Spicy Sausage and Sweet Potato Soup is This spicy sweet potato soup is a result of one of my slow cooker experiments, and my husband loves it. Great on a cool winter day with some homemade bread on the side.
Slow Cooker Spicy Sausage and Sweet Potato Soup is one of the most popular of recent trending meals in the world. It is easy, it is fast, it tastes yummy. its appreciated by millions daily. its simple, it is quick, it tastes delicious. Slow Cooker Spicy Sausage and Sweet Potato Soup is something that I have loved my entire life. They are fine and they look wonderful. They re nice and they look fantastic. Slow Cooker Spicy Sausage and Sweet Potato Soup is something which I ve loved my whole life.
To begin with this recipe, we have to first prepare a few components. You can have Slow Cooker Spicy Sausage and Sweet Potato Soup using 9 ingredients and 2 steps. Here is how you cook it.
So that is going to wrap it up with this special food Slow Cooker Spicy Sausage and Sweet Potato Soup recipe. Thank you very much for reading. Im sure you will make this at home. Theres gonna be more interesting food at home recipes coming up. Remember to save this page on your browser, and share it to your loved ones, colleague and friends. Thanks again for reading. Go on get cooking!


Our first speakers have been confirmed! We will open a CFP soon to fill in the open spots!
Pascal is a Founder of thoughtram and Software Engineer at MachineLabs. He's strongly involved with the community as a Google Developer Expert for the Angular team. Pascal likes to make electronic music and considers himself a bedroom producer.
Founder of Ultimate Angular, Google Developer Expert and pizza aficionado. Loves helping developers and teams to become experts in Angular, NGRX and TypeScript
Philippe is a professional trainer and speaker on web security. He travels the world to teach developers the ins and outs of security engineering. He holds a Ph.D. in web security from KU Leuven.


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A summary tells the main idea of the storty, the news, a report, or any information. A summary tells the most important facts or ideas. A summary is useful for many things.
 You tell only the facts that people want to hear.
In a job interview, you talk about your education and work experience.
With new friends, you can talk about your hobbies and interests.
If you give too much information, it is not a summary. A summary gives enough information to understand the main idea.
A summary is much shorter than the original text. If the original text is one paragraph, a good summary is only one or two sentences. If the original text has many paragraphs, a good summary is only one paragraph.
A summary also tells important facts and supporting ideas. Titles are useful for understanding the main idea. However, a title is not a summary. A summary uses complete sentences.
A summary uses different words from the original text. When you write a summary, use your own words. Use synonyms. Synonyms are different words that have the same meaning.
easy = simple
hard = difficult
fast = quick
great = terrific
Most common words in the English language have synony,s. A thesaurus can help you find good synonyms. Word Web Online is s useful thesaurus.
A summary is like describing a picture in one sentence. Look at each picture. Decide what is happening. Write one sentence to describe each picture.
Now read the original text.
Compare your sentences with your original text. Did your sentences tell a similar story? If so, you wrote a good summary!
Read the text. You need to understand the main idea.
Don't look at the text. Remember as many facts as you can. If you are studying with someone, tell them about what you read.
Rewrite the most important information in your own words. Include facts and ideas that support the main idea.
Janet has an important job interview. The job is a manager position. She is feeling very excited. She is also very nervous. Janet prepares for the interview. She practices interview questions every day. She learns about the company. Janet is dressed her best. She knows looking professional is important. She wears a business suit. She has nice shoes and her hair is neat. The interview goes well. Janet answers the questions directly. She gives good examples. She smiles and acts confidently. She also asks good questions. After the interview, Janet sends a thank you email. She thanks the company for the interview.
Remember as many facts as you can. Don't look at the text.
Now, look at the text. Look at the topic (beginning) and concluding (final) sentences. What is the main idea?
Main Idea: Janet has an important job interview for a job she hopes to get.
What are the supporting ideas? A T-Chart can help you organize the supporting ideas and details.
| Supporting Idea | Details |
|---|---|
| Janet prepares for the interview. | She practices interview questions everyday. She learns about the company. |
| Supporting Idea | Details | Janet is dressed her best. |
|---|
| Supporting Idea | Details | Janet answers the questions directly. She gives good examples. She smiles and acts confidently. |
|---|
| Supporting Idea | Details | After the interview. Janet sends a thank you email. |
|---|
To help you start, write just the main idea and the supporting ideas.
Main Idea: Janet has an important job interview for a job she hopes to get.
Supporting Idea #1: Janet prepares for the interview.
Supporting Idea #2: Janet is dressed her best.
Supporting Idea #3: The interview goes very well.
Supporting Idea #4: After the interview, Janet sends a thank you email.
Remember the keys to writing a summary.
Your summary should be short. The original text is one paragraph, so your summary should be one or two sentences.
Decide which supporting ideas and details are the most important. You don't have to include all of the supporting ideas.
Use your own words as much as possible.
Janet has a good job interview because she prepares well.
Janet gets ready for an important job interview. She practices questions and learns about the company.
Janet wants an important job. She prepares for the interview by practicing.
Janet prepares for a job interview. She does very well because she acts professionally.
All of these sentences are good summaries. The details are different, but the main idea is clear.
A summary is shorter than the original text. A summary tells the main idea and the most important facts. A summary uses your own words.


The same color rings look like different with different surroundings.
Koffka Ring Illusion demo (.swf) by MATLABician. source: psyche.mit.edu


Patient Quotes
MEDICAL CENTER Site is a free web template created by Web-Flash-Template.com team. This website template is optimized for 1024X768 screen resolution. It is also HTML5 & CSS3 valid.
This web template can be delivered in two packages - with PSD source files included and without them. If you need PSD source files, go to the template download page at Web-Flash-Template to leave the e-mail that you want the template ZIP package to be delivered to.


Before Change
import googleapiclient.discovery
// Create a client.
client = googleapiclient.discovery.build("cloudtasks", "v2beta2")
duration_seconds = "600s"
lease_options = {
"maxTasks": 1,
"leaseDuration": duration_seconds,
"responseView": "FULL"
}
queue_name = "projects/{}/locations/{}/queues/{}".format(
project, location, queue)
response = client.projects().locations().queues().tasks().lease(
parent=queue_name, body=lease_options).execute()
print("Leased task {}".format(response))
return response["tasks"][0]
def acknowledge_task(task):
After Change
from google.cloud import tasks_v2beta2
// Create a client.
client = tasks_v2beta2.CloudTasksClient()
// Construct the fully qualified queue name.
parent = client.queue_path(project, location, queue)
lease_duration = {"seconds": 600}
// Send lease request to client.
response = client.lease_tasks(
parent, lease_duration, max_tasks=1, response_view="FULL")
task = response.tasks[0]
print("Leased task {}".format(task.name))
return task


13.6. Discrete DistributionsThe specifications for the discrete distributions in the TR1 library give the probability of each possible value. The formula p(i)= ... means that the probability of getting the value i is given by the expression on the right-hand side of the equals sign. 13.6.1. bernoulli_distributiontemplate < class RType = double > class bernoulli_distribution { public : // distribution interface typedef int input_type ; typedef bool result_type ; explicit bernoulli_distribution ( const RType & P0 = RType (0.5)) : P( P0) {} void reset (); template < class Eng > bool operator() ( Eng & eng); // type-specific members RType p () const { return P ; } // exposition only: private : RType P; };
Instances of the template bernoulli_distribution produce sequences of random values true and false, with the probability of true equal to the stored value P. 13.6.2. binomial_distributiontemplate < class IType = int, class RType = double > class binomial_distribution { public : // distribution interface typedef /* implementation defined */ input_type ; typedef IType result_type ; explicit binomial_distribution ( IType T0 = 1, const RType & P0 = RType (0.5)) : T(T0), P(P0) {} void reset (); template < class Eng > result_type operator() ( Eng & eng); // type-specific members IType t () const { return T; } RType p () const { return P; } // exposition only: private : IType T; RType P; };
Instances of the template binomial_distribution produce random sequences of values of type IType in the closed range [0, T]. For an event whose probability of success is P, each value I in the random sequence occurs with probability equal to the probability of getting success exactly I times in T trials. 13.6.3. geometric_distributiontemplate < class IType = int, class RType = double > class geometric_distribution { public : // distribution interface typedef RType input_type ; typedef IType result_type ; explicit geometric_distribution ( const RType & P0 = RType (0.5)) : P(P0) {} void reset (); template < class Eng > result_type operator() ( Eng & eng); // type-specific members RType p () const { return P; } // exposition only: private : RType P; };
Instances of the template geometric_distribution produce sequences of random values of type IType, all of which are greater than or equal to 1. For an event whose probability of success is P, each value I in the random sequence occurs with probability equal to the probability of getting the first success on the Ith trial. 13.6.4. poisson_distributiontemplate < class IType = int, class RType = double > class poisson_distribution { public : // distribution interface typedef RType input_type ; typedef IType result_type ; explicit poisson_distribution ( const RType & M0 = RType (1)) : M( M0) {} void reset (); template < class Eng > result_type operator() ( Eng & eng); // type-specific members RType mean () const { return M ; } // exposition only: private : RType M; };
Instances of the template poisson_distribution produce random sequences of values of type IType, all of which are greater than or equal to 0. For an event that occurs at intervals whose average duration is M, each value I in the random sequence occurs with probability equal to the probability that I events will occur in an interval of duration M. 13.6.5. uniform_inttemplate < class IType = int > class uniform_int { public : // distribution interface typedef IType input_type ; tpyedef IType result_type ; explicit uniform_int ( IType min0 = 0, IType max0 = 9) : N( min0), X( max0) {} void reset (); template < class Eng > result_type operator() ( Eng & eng); // type-specific members template < class Eng > result_type operator() ( Eng & eng, result_type mx); result_type min () const { return N ; } result_type max () const { return X ; } // exposition only: private : IType N; IType X; };
Instances of the template uniform_int produce uniformly distributed random sequences of values of type IType, all of whose values are greater than or equal to the specified minimum value and less than or equal to the specified maximum value. Further, the function call operator that takes two arguments produces random sequences all of whose values are greater than or equal to the specified minimum value and strictly less than the value of the second argument.[19]
|


"Who am I?"
An exploration of identity, values and strengths
February 2019
My core values
- Adaptability – Seeking new experiences and learning new things
- Equality – Empathy and understanding for others, seeing things from multiple perspectives
- Creativity – creating, innovation, new ideas
For a while I worked as a radio producer. When you are broadcasting information out into the world you have a responsibility to carefully consider what ideas you choose to amplify and the possible outcomes of your choices.
The decisions I made were often informed by my values. I value the ability to see multiple perspectives on a topic and would aim to bring in diverse viewpoints, but this didn’t mean giving any person with a strong point of view airtime. I also think all people should be treated with respect and kindness, so decisions were often a balance of considering these factors.
Strengths and limitations
One of my main strengths is seeing the big picture and arranging. I like seeing how all the parts of a project or system come together and I'm good at planning from the top down. In some learning environments this can pose a challenge. I find it extremely difficult to learn something new if I have no concept of where it fits into the larger picture or why I'm learning it. If a class is taught sequentially, with no overview, I struggle to remain engaged. I need to know where a piece fits before I can look at that piece. Another aspect of this strength is that I like working in groups. I get a thrill out of bringing a collaborative project together. But I also have to be careful that I'm communicating well. Sometimes I have so many moving pieces in my mind that I forget to fully explain to others why I'm making certain decisions.
Another main strength in my adaptability. I love being in new environments and learning new things. Often this is very helpful when embarking on a new course of study. I tend to approach problem solving with excitement because I enjoy being in unfamiliar territory. The challenging side of this trait is that I can grow bored when things are no longer new and I sometimes have trouble finishing, especially in the final stretches of a project. In terms of my career path, this trait has lead me to working in a few quite different fields. I've come to realise that I need to work in job that has plenty of new challenges to thrive.
Working with others
Generally I really enjoy working with others. I think a group of people solving a problem together can use their different viewpoints to spark each other into really innovative places. My strength in arranging also means I get great satisfaction from different people coming together to make something cool.
A time I can remember working in a group that had challenges working together was a group project a university. One member of the group had a very methodical and somewhat anxious relationship to getting things done and I could tell my more varied approach was stressing them out. At the time I felt confident that we were going to get everything done and I found their concerns annoying. These days I would treat this differently. I now understand that the final result is not the only important factor, it's also important to understand that others work differently to you. You have to work with them to make sure that the process is as harmonious as possible for all involved.