ependymoma arise from ependymal cells which line the ventricles of the brain and center of the spinal cord .
they are soft , grayish or red tumors with cyst or mineral calcifications and are infratentorial or supratentorial in origin .
young adults and children show its predominance , in whom they account for approximately 10% of all brain tumors
histopathologically they have been classified into four sub - groups and world health organization ( who ) has classified into three grades gradei , ii and iii . myxopapillary- and sub - ependymomas are slow growing ( who - grade - i ) tumors occurring in the lower part of the spinal column and near ventricles of the brain respectively .
ependymomas and anaplastic ependymomas are fast growing who - grade - ii and iii tumors occurring in posterior fossa regions ( palm et al . , 2009 ) .
these studies have showed association of notch and sonic hedgehog pathways to intracranial ependymomas , and homeobox - containing ( hox ) family genes to extracranial ependymomas ( korshunov et al . , 2003 ,
some reports have differentiated inra- versus extra - cranial ependymomas and normal tissue versus posterior fossa tumors on the basis of transcripts ( lukashova - v zangen et al .
additionally , dysregulation of developmental pathways were identified in anaplastic ependymomas ( palm et al . , 2009 ) .
however , ependymoma molecular characterization has been done to large extent but then also tumor - specific molecules are needed across diverse areas of oncology for use in early detection , diagnosis , prognosis and therapy . to address this issue , we performed isoseq sequencing on histopathologically , immunohistochemically and molecularly classified ependymoma ( who grade - ii ) , ( singh et al . , 2015 ) a posterior fossa tumor from a 2  year - old - male with informed consent .
we identified four and twelve transcript cluster ids ( hta array 2.0 ) in level-2 and level-3 go terms assignment .
further , when correlated these transcript cluster ids with gene - level expression ( ge ) and transcript - level ( te ) track data obtained through rna seq analysis , only gene pnmt , snn and lamb1 showed rpkm of 26.24929 , 36.68109 and 3.376959 respectively and transcripts pnmt_1 , snn_1 , lamb1_3 , lamb1_1 showed rpkm 28.29116 , 36.68109 , 2.838438 and 0.93592 respectively .
total rna extracted ( chomczynski and sacchi , 1987 ) from tumor tissue ( ependymoma ) with rin ( rna integrity number )  >  8.0 was used for library preparation .
the library was constructed as per clontech smarter - pcr cdna synthesis sample preparation guide  ( zhu et al . , 2001 ) .
12  kb libraries were selected on 0.8% agarose gel , purified , end repaired and blunt end smartbell adapters were ligated .
the libraries were quantified using qubit ( invitrogen ) and validated for quality by running a labchip ( caliper life sciences ) subsequently sequencing was done in 8-well - smart cell v3 in pacbiorsii .
the isolated rna of ependymoma tumor was further compared to normal control i.e. posterior fossa tissue from the normal trauma patient .
the tissues were obtained after informed consent and the study was ethically approved by the institutional ethics committee of the king george 's medical university .
the detailed procedure of obtaining cel files through affymetrix hta 2.0 arrays using 500  ng of total rna according to the manufacturer 's recommendations ( affymetrix , santa clara , calif ) has been previously documented by singh et al .
the cel files generated by these arrays were converted into rma-gene-ful.chp and rma-alt-splice-dabg.chp files through affymetrix expression console software ( version 1.3 ) and the data was analyzed through transcriptome analysis console v3.0 .
the generated raw sequences were processed for quality control checks including filtering of high - quality reads based on the score value , removal of primer / adaptor sequence reads and trimming of read - length using celera assembler followed by quiver ( chin et al . , 2013 ) .
putative function of the assembled contigs was deduced by using them as queries against the swissprot and the non - redundant ( nr)-protein database in the blastx - program using a cut off e - value was set at 1e-6 and only the top gene - id and name were initially assigned to each contig .
gene ontology ( go ) annotation analysis was performed in blast2go ( http://www.blast2go.org/ ) version 2.5.0 ( conesa et al . , 2005 ) for the assignment of gene ontology terms .
after gene - id mapping , go term assignment , annotation augmentation and generic go - slim process the final annotation file was produced and the results were categorized with respect to biological process , molecular function , and cellular component at level 2 .
pathway analyses of unique sequences were carried out based on the kyoto encyclopedia of genes and genomes ( kegg ) database using the online kegg automatic annotation server ( kaas ) ( http://www.genome.jp/tools/kaas/ ) by using bi - directional best hit ( bbh ) method ( moriya et al . , 2007 ) .
enzyme commission ( ec ) numbers were obtained and were putatively mapped for protein sequences to a specific biochemical pathway .
we also analyzed our clean data through rna - seq tool ( clc genomics workbench - version ) to produce mrna expression levels for genes and/or transcripts , from samples of ependymoma-(m)rna reads .
this has been done by mapping the reads to reference genome ( homo sapiens - hg18 ) that includes gene annotations and ( optionally ) mrna annotations .
rna seq report is generated for the query sequences giving the information of read sequences , reference sequences , total no of genes and transcripts in reference sequence , graph showing the number of transcripts per gene , graph showing the number of exons per transcript and graph showing the distribution of transcript length .
further , the mapped results were output as a reads track at the gene and transcript level showing expression values at the gene and transcript level , respectively in the form of unique count , total count and reads per kilobase per million ( rpkm ) .
importantly , the maximum number of hits for a read parameter was set for 1 to consider uniquely mapped reads .
the number of reads and reads per million were determined using the clc mapping program .
using celera assembler followed by quiver , a total of 1,19,313 raw sequence reads with maximum length of 5580  bp length were generated encompassing about 577  mb of sequence data in fastq format .
a total of 19,878 contigs ( with a length of 5003000  bp ) had significant blastx hit corresponding to 2952 unique protein accessions in the nr protein database ( table 1 and fig .
gene ontology ( go ) analysis of these 2952 unique proteins resulted in a total of 50,596 go terms including 27,484 ( 54.32% ) biological process terms , 10,518 ( 20.78% ) molecular function terms and 12,594 ( 24.89% ) cellular component terms . among the biological process category 4592 , 3980 and 3662 genes
were related to cellular processes ( go:0008150 ) , single - organism process ( go:0008150 ) and metabolic process respectively ; a significant numbers of genes were also identified from biological regulation ( 2961 ) , response to stimulus ( 2136 ) , localization ( 1748 ) , cellular component organization or biogenesis ( 1616 ) , multicellular organismal process ( 1615 ) , developmental process ( 1492 ) and signaling ( 1402 ) sub - categories . similarly under molecular function category ,
3724 genes were involved in the binding process ( go : 0005488 ) and 1676 genes in the catalytic activity ( go : 0003824 ) ; whereas under the cellular component category , 4925 genes from cell ( go : 0005623 ) , and 3570 genes corresponded to organelle ( go:0043226 ) , 1768 genes corresponded to macromolecular complex ( go : ) and 1692 genes corresponded to membrane ( go : ) were the most represented categories ( fig .
2 ) . enzyme commission ( ec ) numbers were assigned with 442 enzyme codes for 1172 unique sequences ( fig .
307 kegg pathways were represented by 2952 unique transcripts ( supplementary table 1 ) including cancer - related ( ko052000 : 39 transcripts coding 35 genes ) ( fig .
4 ) , transcriptional misregulation ( ko0502 : 35 transcripts coding 21 genes ) , microrna ( ko0520622 : 22 transcripts coding 18 genes ) and proteoglycans in cancer ( 28 transcripts coding 26 genes ) pathways .
statistical distribution showed majority of blastx - hit sequences of ependymoma transcript produced similarities with homo sapiens followed by other species like macaca fasicularis and macaca mulatta ( fig .
the nucleotide sequence of the infratentorial ependymoma has been deposited in ncbi / sra under accession no .
additionally , when we screened go terms of second and third level in alternative splicing data obtained through hta array2.0 .
the identified transcript clusters showed linear gene fold change based on the average of all the eligible exons probe specific regions ( psrs ) intensities in that gene between ependymoma and control samples .
we identified four and twelve transcript cluster ids in level-2 and level-3 respectively with alternative splicing index supplementary table 2 .
the four transcript clusters of level-2 of hmcn2 , ces1p1 , lilrb4 and srrd genes owed to various biological processes like metabolic process , response to stimulus , immune system process and rhythmic process . while twelve transcript clusters of level-3 of il2rg , gal3st2 , antxr2 , ulbp2 , lamb1 , pon3 , tdh , ifitm5 , tph2 , hdgfrp3 , snn and pnmt genes owed to reproductive process , response to external stimulus , response to biotic stimulus , biosynthetic process , antigen processing and presentation , methylation , circadian rhythm , immune response , cell proliferation , response to stress , cellular metabolic process and cell adhesion . the various isoforms of the identified transcript clusters of level-2 and level-3 has been depicted in supplementary table 3 and supplementary figs . 1
( a  d ) and 2 ( a  l ) . this shows that identified transcripts in 12  kb fragments of ependymoma sequence show differential regulation at gene level and alternative splicing index on comparison with normal sample .
most of the proteins predicted include the major pathways of hallmarks of cancer ( hanahan and weinberg , 2011 ) . through rna - seq analysis ( mapping statistics ) we identified that out of 4 , 69 , and 559 fragments , 1 , 83 , and 302 were counted and 2 , 86 , and 257 were uncounted fragments . in counted fragments 1 , 77 , 550 fragments uniquely mapped to reference human genome ( hg18 ) and 5,752 non - specifically mapped ( supplementary table 4 ) .
further , counted fragments were divided into different types like reads that mapped completely to exon ; reads that mapped across an exon junction and reads that completely mapped to introns . the gene - level expression ( ge ) track holds information about counts , length as annotated and expression values for each gene involved in ependymoma on using one reference sequence per transcript ( supplementary table 5a ) .
the expression values are expressed as total count ( sum of total number of reads mapped to the gene and total number of reads mapped to the reference sequence ( un - annotated references ) ) , unique count ( total number of reads mapped to the gene ) and normalized rpkm ( reads per kilobase of exon model per million mapped reads ) .
it also shows unique ( number of reads that match uniquely to the gene ) and total gene reads ( number of reads that match uniquely to the gene and reads that map to more positions in the reference other than the gene ) , annotated ( based on mrna annotations ) and detected transcripts ( no of annotated transcripts to which reads have been assigned ) .
similarly , it also expresses unique exonic reads ( number of reads that match uniquely to the exons including across exon 
exon junctions ) and total exon reads ( number of reads mapped to this gene that fall entirely within an exon or in exon 
exon ( reads that uniquely match across an exon  exon junction of the gene ) and total exon
 exon reads ( reads that uniquely match across an exon  exon junction of the gene as well as multiple matches that were assigned to an exon  exon junction of this gene ) . besides exonic , unique intron 
 exon reads ( maps across an intron  exon boundary of the gene ) are also depicted in the ge track ( supplementary table 5a ) .
each row in the transcript - level expression ( te ) track table corresponds to an mrna annotation in the mrna track used as reference ( supplementary table 5b ) .
it holds information about counts i.e. 11 , 202 transcripts for 20 , 274 genes , length as annotated and expression values as rpkm and relative rpkm ( rpkm for the transcript divided by the maximum of the rpkm values among all transcripts of the same gene ) for each transcripts involved in ependymoma ( supplementary table 5b ) .
the track also depicts information about unique ( number of reads in the mapping for the gene that are uniquely assignable to the transcript ) and total transcript reads (  unique transcript read 's plus the remaining ( non - unique ) transcript reads which are assigned randomly to one of the transcripts to which they match ) , annotated ( number of transcripts based on the mrna annotations on the reference ) and detected transcripts ( no of annotated transcripts to which reads have been assigned ) .
importantly , genes that mapped distinctly at gene level ( ge track ) did not mapped uniquely to particular transcript i.e. were non - specific at transcript level ( te track ) , hence suggestive of transcript isoforms of the particular gene involved in ependymoma ( supplementary table 5a and b ) .
the identified four and twelve transcript cluster ids ( hta array 2.0 ) in level-2 and level-3 go terms when correlated with ge and te track data obtained through rna seq , only gene pnmt , snn and lamb1 showed rpkm of 26.24929 , 36.68109 and 3.376959 respectively and transcripts pnmt_1 , snn_1 , lamb1_3 , lamb1_1 showed rpkm 28.29116 , 36.68109 , 2.838438 and 0.93592 respectively ( supplementary table 6a and b ) .
involvement of phenylethanolamine n - methyltransferase ( pnmt ) has been reported in neuroendocrine differentiation ( yang et al . , 2013 ) and
its differential regulation has also been reported in neuroblastoma ( castro - vega et al . ,
paraganglioma ( castro - vega et al . , 2015 , castro - vega et al . , 2015 ) and different subgroups of breast cancer ( dai et al . , 2014 ) .
snn ( stannin ) , a protein coding gene associated with the disease - cavernous hemangioma , a collection of small blood vessels ( capillaries ) in the central nervous system ( cns ) shows its mrna expression in brain tissue ( snn gene cards ) .
laminin b1 ( lamb1 ) , involved in the organization of the laminar architecture of cerebral cortex .
it is most likely also required for the integrity of the basement membrane / glia limitans that serves as an anchor point for the end feet of radial glial cells and as a physical barrier to migrating neurons .
radial glial cells play a central role in cerebral cortical development , where they act both as the proliferative unit of the cerebral cortex and a scaffold for neurons migrating toward the gial surface ( lamb1 gene cards ) .
lamb1 has also been identified in diffuse intrinsic pontine glioma ( dipg ) a highly morbid form of pediatric brainstem glioma ( saratsis et al . , 2014 ) .
as per the gene cards the expression images based on data from illumina human bodymap show mrna expression of all the three genes in brain tissue as well as cerebellum .
hence , after streamlining the data through both hta array 2.0 and isoseq analysis , we report the involvement of brain - specific genes  pnmt , snn and lamb1 in ependymoma .
the following are the supplementary data related to this article.supplementary table 1kegg mappings.supplementary table 2a .
biological processes related to go terms.b . go terms of second level in alternative splicing data obtained through hta array2.0.c .
gene - level expression ( ge ) track holding information about counts , length as annotated and expression values for each gene involved in ependymoma on using one reference sequence per transcript.b .
transcript - level expression ( te ) track holding information about counts , length as annotated and expression values as rpkm and relative rpkm ( rpkm for the transcript divided by the maximum of the rpkm values among all transcripts of the same gene ) for each transcripts involved in ependymoma.supplementary table 3various isoforms of the identified transcript clusters of level-2 and level-3.table 3a .
correlation between hta array - based transcript cluster i d identified in go - terms level-3 and gene expression ( ge ) track data .
b. correlation between hta array - based transcript cluster i d identified in go - terms level-3 and transcript - level expression ( te ) track data.supplementary table 4rna seq report.supplementary fig .
1transcript clusters of level-2 go terms as per alternative splicing data obtained through hta array2.0 .
a ) tc16000460.hg.1 , b ) tc09002937.hg.1 , c ) tc19000882.hg.1 , d ) tc22000170.hg.1.supplementary fig .
2transcript clusters of level-3 go terms as per alternative splicing data obtained through hta array2.0 .
a ) tc04001328.hg.1 , b ) tc07003364.hg.1 , c ) tc11003502.hg.1 , d ) tc02005017.hg.1 , e ) tc06001088.hg.1 , f ) tc17000479.hg.1 , g ) tc12000629.hg.1 , h ) tc0x001121.hg.1 , i ) tc15001766.hg.1 , j ) tc16000165.hg.1 , k ) tc08002637.hg.1 , l ) tc07001747.hg.1 .
. b. go terms of second level in alternative splicing data obtained through hta array2.0 .
a. gene - level expression ( ge ) track holding information about counts , length as annotated and expression values for each gene involved in ependymoma on using one reference sequence per transcript .
b. transcript - level expression ( te ) track holding information about counts , length as annotated and expression values as rpkm and relative rpkm ( rpkm for the transcript divided by the maximum of the rpkm values among all transcripts of the same gene ) for each transcripts involved in ependymoma .
a. correlation between hta array - based transcript cluster i d identified in go - terms level-3 and gene expression ( ge ) track data .
b. correlation between hta array - based transcript cluster i d identified in go - terms level-3 and transcript - level expression ( te ) track data .
transcript clusters of level-2 go terms as per alternative splicing data obtained through hta array2.0 .
a ) tc16000460.hg.1 , b ) tc09002937.hg.1 , c ) tc19000882.hg.1 , d ) tc22000170.hg.1 .
transcript clusters of level-3 go terms as per alternative splicing data obtained through hta array2.0 .
a ) tc04001328.hg.1 , b ) tc07003364.hg.1 , c ) tc11003502.hg.1 , d ) tc02005017.hg.1 , e ) tc06001088.hg.1 , f ) tc17000479.hg.1 , g ) tc12000629.hg.1 , h ) tc0x001121.hg.1 , i ) tc15001766.hg.1 , j ) tc16000165.hg.1 , k ) tc08002637.hg.1 , l ) tc07001747.hg.1 .
samples were provided by : bko and cs ; histopathological and immunohistochemical details : provided by mg . sample collection and nucleic acid isolation : rc and
am ; performed and analyzed the experiments : ns and dks . wrote the paper and discussion : ns .
contributed reagents / materials / analysis tools : rk . reviewed the paper : bko , cs , dkg and rk
 here , we sequenced and functionally annotated the long reads ( 12  kb ) cdnas library of an infratentorial ependymoma tumor tissue on pacbio rsii by iso - seq protocol using smrt technology . 
 577  mb , data was generated from the brain tissues of ependymoma tumor patient , producing 1,19,313 high - quality reads assembled into 19,878 contigs using celera assembler followed by quiver pipelines , which produced 2952 unique protein accessions in the nr protein database and 307 kegg pathways.additionally , when we compared go terms of second and third level with alternative splicing data obtained through hta array2.0 . 
 we identified four and twelve transcript cluster ids in level-2 and level-3 scores respectively with alternative splicing index predicting mainly the major pathways of hallmarks of cancer . 
 out of these transcript cluster ids only transcript cluster ids of gene pnmt , snn and lamb1 showed reads per kilobase of exon model per million mapped reads ( rpkm ) values at gene - level expression ( ge ) and transcript - level ( te ) track . 
 most importantly , brain - specific genespnmt , snn and lamb1 show their involvement in ependymoma . 
Introduction
Methodology
Results and discussion
Author contributions
Competing interests