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Paper text:
digital gene expression sequencing , namely dge - seq , refers to the use of high - throughput sequencing technologies to sequence cdna in order to get information about rna content of a sample ( 1 )
. it can provide researchers with a powerful tool to obtain unbiased and unparalleled information about gene transcripts 2 , 3 .
currently , computational methods are being developed to identify and annotate these transcripts with alternative splice forms 4 , 5 .
although most dge - seq studies have identified expression outside of known loci ( in intronic or intergenic regions ) 6 , 7 , 8 , 9 , 10 , few attempts have been made to ab initio define the read - enriched regions ( rers ) in detail and compare them with known gene models .
here , we present gene2dge , a free perl software package for rer detection and gene model update .
this novel method consists of rer definition based on read clustering followed by annotation comparison with known gene models .
the input of gene2dge is the file of mapped reads from rna - seq data and a gene annotation file of the corresponding genome .
in addition , a cmap file needs to be prepared for application to different species to correct the chromosome numbers .
the output of gene2dge includes a text file containing a set of rers and a series of text files containing annotated information of the eligible rers .
the gene2dge package is freely available at http://bighapmap.big.ac.cn/. we developed gene2dge as an ab initio tool to annotate the transcriptome using mapped reads from the solid platform ( applied biosystems ) and annotation information downloaded from ensembl .
first , we filter the  uniquely mapped  reads from the aligned results of the solid whole transcriptome pipeline .
a uniquely mapped read is defined as one with a max scoring alignment to the genome scoring at least 24 and at least four higher than any of the other alignments of that read to the genome ( 11 ) .
considering the restrictions of computer memory , this process will be performed for each chromosome in order , so it is relatively convenient for use on any personal computer .
second , based on uniquely mapped reads , we construct the rers by grouping overlapped reads with a number greater than a threshold ( at least four reads ) ( 12 ) .
we list each rer including start position , end position and the number of mapped reads .
maximal distance between rers  , defined by the start positions of rers minus the start positions of the first one upstream .
it can be customized according to the specific requirement of the experiment ( the default value is 50  bp ) .
finally , we compare the rers to existing gene models , and generate a catalogue of candidate genes with new annotation information , including exon extension , possible additional exons , and novel genes .
the file of existing gene models in gtf format can be downloaded from the ensembl website for the candidate species .
we picked out eligible rers and then checked their overlap with known gene models . as a result
, a series of annotated files will be output and then can be used in further analysis .
we applied gene2dge to the rna - seq data from the mouse blastomere dataset obtained from a single - cell whole transcriptome ( 13 ) .
the mrna - seq short reads were analyzed using whole - transcriptome software tools ( applied biosystems , http://www.solidsoftwaretools.com/ ) .
the reads generated were mapped to the mouse genome ( mm9 , ncbi build 37 ) .
we got more than 6.6 million reads that could be uniquely aligned to the mouse genomic reference (  uniquely mapped reads  ) .
based on ensembl annotation ( ncbi m37.61 ) , 89% reads ( 5.9 million ) were mapped to annotated regions in exons including coding sequences ( cds ) and untranslated regions ( utr ) , which is significantly higher than those mapped to intronic ( 0.3 million , 5% ) and intergenic ( 0.4 million , 6% ) regions ( figure 1a ) . across the mouse genome , 98,532 rers were identified and each contained more than 4 reads .
a total of 62.3% of rer boundaries were within 10  bp of the ends for the corresponding exons ( figure 1b ) .
meanwhile , we identified 2,217 exon ends with remarkable extension into un - annotated regions ( > 50  bp ) , suggesting that the mouse transcriptome was more complex than we expected .
the transcript levels for rers overlapping with known exons ( exonic rers ) were significantly higher than those of novel rers ( mann - whitney u test , p<10 ) .
we detected 12,277 expressed transcripts ( with at least 1 rer across the genic region ) , in which 11,261 ( 92% ) transcribed genes contained at least one exonic rer .
for the 72,628 ( 74% of all 98,532 rers ) exonic rers , we found that the known gene models were well defined by the ab initio method .
for example , read distribution on chr 7 ( 56900000 - 57200000 ) revealed sharp boundaries of rer regions ( figure 2 ) .
furthermore , we detected a certain proportion of rers ( 25,904 , 26% of all rers identified ) , which are located outside of the annotated regions in this transcriptome dataset . among them , 13,291 intronic rers ( about 13% of all ) were identified in 4,449 genes , indicating possible additional exons .
interestingly , about 1,016 genes ( 23% ) only had transcripts detected in the intronic regions but not in the exonic regions .
as a result , we renewed 4,788 gene models , which account for 39% of 12,277 transcribed genes in total .
the remaining 12,613 rers are located in the intergenic regions , suggesting possible presence of novel genes outside of the existing gene models .
we developed gene2dge as an ab initio tool to annotate the transcriptome using mapped reads from the solid platform ( applied biosystems ) and annotation information downloaded from ensembl .
first , we filter the  uniquely mapped  reads from the aligned results of the solid whole transcriptome pipeline . a uniquely mapped read is defined as one with a max scoring alignment to the genome scoring at least 24 and at least four higher than any of the other alignments of that read to the genome ( 11 ) . considering the restrictions of computer memory , this process will be performed for each chromosome in order , so it is relatively convenient for use on any personal computer .
second , based on uniquely mapped reads , we construct the rers by grouping overlapped reads with a number greater than a threshold ( at least four reads ) ( 12 ) .
we list each rer including start position , end position and the number of mapped reads . in addition
maximal distance between rers  , defined by the start positions of rers minus the start positions of the first one upstream .
it can be customized according to the specific requirement of the experiment ( the default value is 50  bp ) . finally , we compare the rers to existing gene models , and generate a catalogue of candidate genes with new annotation information , including exon extension , possible additional exons , and novel genes .
the file of existing gene models in gtf format can be downloaded from the ensembl website for the candidate species .
we picked out eligible rers and then checked their overlap with known gene models . as a result
, a series of annotated files will be output and then can be used in further analysis .
we applied gene2dge to the rna - seq data from the mouse blastomere dataset obtained from a single - cell whole transcriptome ( 13 ) .
the mrna - seq short reads were analyzed using whole - transcriptome software tools ( applied biosystems , http://www.solidsoftwaretools.com/ ) .
the reads generated were mapped to the mouse genome ( mm9 , ncbi build 37 ) .
we got more than 6.6 million reads that could be uniquely aligned to the mouse genomic reference (  uniquely mapped reads  ) .
based on ensembl annotation ( ncbi m37.61 ) , 89% reads ( 5.9 million ) were mapped to annotated regions in exons including coding sequences ( cds ) and untranslated regions ( utr ) , which is significantly higher than those mapped to intronic ( 0.3 million , 5% ) and intergenic ( 0.4 million , 6% ) regions ( figure 1a ) . across the mouse genome ,
a total of 62.3% of rer boundaries were within 10  bp of the ends for the corresponding exons ( figure 1b ) .
meanwhile , we identified 2,217 exon ends with remarkable extension into un - annotated regions ( > 50  bp ) , suggesting that the mouse transcriptome was more complex than we expected .
the transcript levels for rers overlapping with known exons ( exonic rers ) were significantly higher than those of novel rers ( mann - whitney u test , p<10 ) .
we detected 12,277 expressed transcripts ( with at least 1 rer across the genic region ) , in which 11,261 ( 92% ) transcribed genes contained at least one exonic rer .
for the 72,628 ( 74% of all 98,532 rers ) exonic rers , we found that the known gene models were well defined by the ab initio method .
for example , read distribution on chr 7 ( 56900000 - 57200000 ) revealed sharp boundaries of rer regions ( figure 2 ) .
furthermore , we detected a certain proportion of rers ( 25,904 , 26% of all rers identified ) , which are located outside of the annotated regions in this transcriptome dataset . among them , 13,291 intronic rers ( about 13% of all ) were identified in 4,449 genes , indicating possible additional exons .
interestingly , about 1,016 genes ( 23% ) only had transcripts detected in the intronic regions but not in the exonic regions .
as a result , we renewed 4,788 gene models , which account for 39% of 12,277 transcribed genes in total .
the remaining 12,613 rers are located in the intergenic regions , suggesting possible presence of novel genes outside of the existing gene models .
here we have developed an exploratory tool , gene2dge , which can be employed to determine the rers and improve genome annotation . the package and methods
can be applied to analyze other sources of any mapped short read counts from rna - seq data , such as results of sequencing by ab solid platform and illumina solexa platform .
moreover , gene2dge can be used on any personal computer with a low requirement for computer memory capacity , since data are processed for all chromosomes in order with one chromosome at a time . in this study , we provide an example of gene2dge usage to illustrate its application in transcriptome analysis
. gene2dge has also been applied to analyze datasets from other mouse tissues or tissues from other species ( data not shown ) .
all these results indicate that gene2dge is a suitable tool for the renewal of known gene models by ab initio prediction in transcriptome dissection .
dz , jl , yw , qz , xl and gl collected the dataset and participated in data analysis and visualization .
dz , jl , yw , qz , xl and gl collected the dataset and participated in data analysis and visualization .
for transcriptome analysis , it is critical to precisely define all the transcripts across the whole genome . 
 more and more digital gene expression ( dge ) scannings have indicated the presence of huge amount of novel transcripts in addition to the known gene models . however , almost all these studies still depend crucially on existing annotation . here 
 , we present gene2dge , a perl software package for gene model renewal with dge data . 
 we applied gene2dge to the mouse blastomere transcriptome , and defined 98,532 read - enriched regions ( rers ) by read clustering supported by more than four reads for each base pair . 
 taking advantage of this ab initio method , we refined 2,104 exonic regions ( 4% of a total of 48,501 annotated transcribed regions ) with remarkable extension into un - annotated regions ( > 50  bp ) . for 5% of 
 uniquely mapped reads falling within intron regions , we identified 13,291 additional possible exons . as a result 
 , we renewed 4,788 gene models , which account for 39% of a total of 12,277 transcribed genes . 
 furthermore , we identified 12,613 intergenic rers , suggesting the possible presence of novel genes outside the existing gene models . in this study , therefore , we have developed a suitable tool for renewal of known gene models by ab initio prediction in transcriptome dissection . 
 the gene2dge package is freely available at http://bighapmap.big.ac.cn/.