S) and Cryptotermes (3 ESTs and 323 nucleotide sequences). However, there are no

S) and Cryptotermes (3 ESTs and 323 nucleotide sequences). However, there are no ESTs and only 818 nucleotide sequences deposited in NCBI databases for Odontotermes. Therefore, application of the advanced sequencing technology to characterize transcriptome and obtain more ESTs of Odontotermes is very necessary. Currently, some advanced sequencing technologies, such as Illumina sequencing and 454 pyrosequencing, have been used toTranscriptome and Gene Expression in Termitecarry out high-throughput sequencing and have rapidly improved the efficiency and speed of mining genes [13?8]. Moreover, these sequencing technologies have greatly improved the sensitivity of gene expression profiling, and is expected to promote collaborative and comparative genomics studies [19,20]. Thus, we selected the Illumina sequencing to characterize the complete head transcriptome of O. formosanus. In the present study, a total of 57,271,634 raw sequencing reads were generated from one plate (8 lanes) of sequencing. After transcriptome assembly, 221,728 contigs were obtained, and these contigs were further clustered into 116,885 unigenes with 9,040 distinct clusters and 107,845 distinct singletons. In the head transcriptome database, we predicted simple sequence repeats (SSRs), and detected putative genes involved in caste differentiation and aggression. Furthermore, we compared the gene expression purchase Deslorelin profiles of the three putative genes involved in caste differentiation and one putative gene involved in aggression among workers, soldiers and larvae of O. formosanus. The assembled, annotated transcriptome sequences and gene expression profiles provide an invaluable resource for the identification of genes involved in caste differentiation, aggressive behavior and other biological characters in O. formosanus and other termite species.to 14.95 for sequences between 100 to 500 bp (Figure 3). The result indicates that the proportion of sequences with matches in the nr database is greater among the longer assembled sequences. The E-value distribution of the top hits in the nr database ranged from 0 to 1.0E25 (Figure 4A). The similarity distribution of the top BLAST hits for each sequence ranged from 17 to 100 (Figure 4B). For species distribution, 16.0 of the distinct sequences have top matches trained with sequences from Tribolium castaneum (Figure 4C). Of all the unigenes, 22,895 (19.59 ) had BLAST hits in Swiss-Prot database and matched to 12,497 unique protein entries.Functional Classification by GO and COGGO functional analyses provide GO functional classification annotation [23]. On the basis of nr annotation, the Blast2GO program was used to obtain GO annotation for unigenes [24]. Then the WEGO software was used to perform GO functional classification for these unigenes [25]. In total, 10,409 unigenes with BLAST matches to known 1379592 proteins were assigned to gene ontology classes with 52,610 functional terms. Of them, assignments to the biological process made up the majority (25,528, 48.52 ) followed by cellular component (17,165, 32.63 ) and molecular function (9,917, 18.85 ) (Figure 5). Under the biological process category, cellular process (4,696 unigenes, 18.40 ) and metabolic process (3,726 unigenes, 14.60 ) were prominently represented (Figure 5). In the category of cellular component, cell (5,884 unigenes) and cell part (5,243unigenes) represented the Dimethylenastron price majorities of category (Figure 5). For the molecular function category, binding (4,223 unigenes) and ca.S) and Cryptotermes (3 ESTs and 323 nucleotide sequences). However, there are no ESTs and only 818 nucleotide sequences deposited in NCBI databases for Odontotermes. Therefore, application of the advanced sequencing technology to characterize transcriptome and obtain more ESTs of Odontotermes is very necessary. Currently, some advanced sequencing technologies, such as Illumina sequencing and 454 pyrosequencing, have been used toTranscriptome and Gene Expression in Termitecarry out high-throughput sequencing and have rapidly improved the efficiency and speed of mining genes [13?8]. Moreover, these sequencing technologies have greatly improved the sensitivity of gene expression profiling, and is expected to promote collaborative and comparative genomics studies [19,20]. Thus, we selected the Illumina sequencing to characterize the complete head transcriptome of O. formosanus. In the present study, a total of 57,271,634 raw sequencing reads were generated from one plate (8 lanes) of sequencing. After transcriptome assembly, 221,728 contigs were obtained, and these contigs were further clustered into 116,885 unigenes with 9,040 distinct clusters and 107,845 distinct singletons. In the head transcriptome database, we predicted simple sequence repeats (SSRs), and detected putative genes involved in caste differentiation and aggression. Furthermore, we compared the gene expression profiles of the three putative genes involved in caste differentiation and one putative gene involved in aggression among workers, soldiers and larvae of O. formosanus. The assembled, annotated transcriptome sequences and gene expression profiles provide an invaluable resource for the identification of genes involved in caste differentiation, aggressive behavior and other biological characters in O. formosanus and other termite species.to 14.95 for sequences between 100 to 500 bp (Figure 3). The result indicates that the proportion of sequences with matches in the nr database is greater among the longer assembled sequences. The E-value distribution of the top hits in the nr database ranged from 0 to 1.0E25 (Figure 4A). The similarity distribution of the top BLAST hits for each sequence ranged from 17 to 100 (Figure 4B). For species distribution, 16.0 of the distinct sequences have top matches trained with sequences from Tribolium castaneum (Figure 4C). Of all the unigenes, 22,895 (19.59 ) had BLAST hits in Swiss-Prot database and matched to 12,497 unique protein entries.Functional Classification by GO and COGGO functional analyses provide GO functional classification annotation [23]. On the basis of nr annotation, the Blast2GO program was used to obtain GO annotation for unigenes [24]. Then the WEGO software was used to perform GO functional classification for these unigenes [25]. In total, 10,409 unigenes with BLAST matches to known 1379592 proteins were assigned to gene ontology classes with 52,610 functional terms. Of them, assignments to the biological process made up the majority (25,528, 48.52 ) followed by cellular component (17,165, 32.63 ) and molecular function (9,917, 18.85 ) (Figure 5). Under the biological process category, cellular process (4,696 unigenes, 18.40 ) and metabolic process (3,726 unigenes, 14.60 ) were prominently represented (Figure 5). In the category of cellular component, cell (5,884 unigenes) and cell part (5,243unigenes) represented the majorities of category (Figure 5). For the molecular function category, binding (4,223 unigenes) and ca.

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