BACKGROUND
gene expression analysis artefacts
as part of our research on pancreatic beta cell biology, our group has been investigating the transcripts originating from the insulin loci using both microarrays and rna-sequencing platforms.
on several occasions we have noticed issues with the way overlapping transcripts are handled in gene expression analysis pipelines, and this sparked the interest for looking further into the underlying reasons for the problems.
our initial observations were as follows:
in dna microarray analysis different results will be obtained for the genes in the genomic region around ins  depending on the mapping scheme used.
in extreme cases ins itself will disappear from the analysis and all its signal would instead be mapped to ins-igf <dig> .
the reason for this artefact turned out to be that certain widely used enhanced remapping schemes for affymetrix probes  are targeting the longest transcript in the region.
in most cases this will not cause an issue, since all the transcripts variants will in the end be mapped to the same underlying gene.
however, in the case of ins the issue is that a fusion transcript, ins-igf <dig>  is spanning the entire region , including both insulin exons as well as part of the adjacent igf2-locus.
this will lead to all signal in the region being mapped to ins-igf <dig> and that ins will “disappear” from the analysis, and in certain cases so would igf <dig> .
this will happen even if there are no probes targeting the unique part of the fusion transcript.fig.
<dig> rna sequencing read depth in the ins/igf <dig> genomic region.
plot of the genomic region of chromosome  <dig> around the ins and igf <dig> loci  with probesets from the affymetix hg-u133a array and the main transcript variants of ins, ins-igf <dig> and igf <dig> indicated below the plot.
all shown transcripts are encoded on the antisense strand —for an overview of all known transcript variants, please see additional file 1: figure s <dig> .
the y-axis shows the read depth of the rna sequencing study from nica et al.
<cit> —notice that read depth was capped at  <dig>  .
from the plot it is clearly seen that few reads maps to the ins-igf <dig> exons in the  <dig> area  and almost all signal assigned to ins-igf <dig> by nica et al.
<cit>  originates from the first coding exon which is shared with ins .
all positional information on this plot is from ensembl v. <dig>
for rna sequencing analysis a related problem is encountered.
the individual reads will typically be mapped to a set of transcripts from the organism in question, and will be assigned multiple times to transcripts sharing sequences.
in most cases this is the desired behaviour, and will be a way to handle splicing variants of a given gene .
however, in the case of transcripts spanning several genes, there is a risk that the signal from one gene bleeds into the overlapping transcript, and this may not be apparent when the results are reported.
with this in mind, we decided to re-investigate the observation by nica et al.
<cit>  that the ins-igf <dig> fusion transcript was found to be the second most abundant mrna in human beta cells, an observation that has generated much interest in the beta cell biology field since ins-igf <dig> has previously been annotated to be translated  <cit>  and moreover, recently proposed as a novel autoantigen in type  <dig> diabetes   <cit> .
case background: beta cell biology
the pancreatic beta cell is a key component in regulating blood glucose homeostasis as it represents our sole source of insulin, which is required for peripheral tissues to internalize and utilize glucose as an energy source.
lack of adequate functional beta cell mass leading to relative insulin insufficiency is the common denominator of all forms of diabetes.
t1d is characterized by an absolute loss of beta cells as a result of autoimmune destruction.
type  <dig> diabetes  is where a relative beta cell insufficiency results from failure of compensatory upregulation of insulin production capacity in response to increasing peripheral insulin resistance.
therefore much effort in, both preventive and curative, diabetes research has aimed at understanding the molecular networks, both at the level of transcriptional and translational regulation of genes controlling development and at the function and survival of the pancreatic beta cell.
recent advancements in the ability to purify single cell types from the islet of langerhans combined with omics’ approaches have led to detailed information of the transcriptomic environment of beta cells.
gene-knockouts, and animal models, in particular targeting transcription factors combined with genome-wide association studies, have in the past decade provided us with a comprehensive map of genes and loci that may cause or contribute to diabetes, and it is evident that better understanding of molecular control of functional beta cell mass will be key to design strategies to defeat diabetes.
all classical studies, not surprisingly, report a very high abundance of insulin mrna, and insulin represents one of the most abundant cell specific mrna’s known in our body.
it was therefore surprising to realize that the second most abundant beta cell mrna, recently reported in facs purified human beta cells  <cit> , was encoding ins-igf <dig>  values comparable to glucagon mrna levels in purified human alpha cells was reported for ins-igf <dig> suggesting that a putative and highly abundant beta cell protein could have been overlooked.
moreover, recent studies suggested that ins-igf <dig> could be yet another beta cell specific antigen recognized by autoantibodies in t1d  <cit> .
RESULTS
transcriptome analysis
in our reanalysis of the rna sequencing data from nica et al.
<cit>  we did not map the reads to transcripts but rather investigated an unbiased mapping of the reads to the genomic region on chromosome  <dig> containing the ins, igf <dig> and ins-igf <dig> transcripts.
by visual inspection of the distribution of the reads , it is clearly observed that the regions specific to ins-igf <dig> are lowly expressed, whereas the ins specific exons are  highly expressed.
both coding exons of ins being expressed at the same order of magnitude is a clear indication that  most reads mapped to the exon that is shared by both ins and ins-igf <dig> belong to the ins- <dig> transcript, and  the perceived high expression of the ins-igf <dig> transcript is due to the read count being assigned to both genes, where the difference in level is due to the different lengths of the two genes.
the data analysis artefact is especially pronounced in this case, since ins in itself constitutes a large part of the transcript pool in beta cells.
in our own experiments using the human beta cell line endoc-βh <dig> we observe the same trends, both with rna sequencing and micro-array analysis .
both rna sequencing and dna micro-arrays are measuring sequence fragments, therefore we decided to take the analysis one step further and devised a qpcr strategy based on splice-form specific primers in order to provide a more direct measurement of the individual unfragmented mrna species, in both endoc-βh <dig> cells and human islets.
in both cases the observations are the same; the ins-igf <dig> fusion transcript is expressed at a level > <dig>  fold lower than the ins transcript , and is hence barely detectable.table  <dig> qpcr analysis of ins-igf <dig>  ins and igf2
relative expression of ins-igf <dig>  ins and igf <dig> determined by qpcr for endoc-βh <dig> cells and human islets.
all mrnas were analysed in  <dig> independent preparations, each in technical duplicate and the average of each duplicate is shown for each preparation .
gapdh was used as input control.
it is clear that ins-igf <dig> is expressed at very low levels compared to insulin, i.e.
in the order of > <dig>  fold less in human islets and  <dig>  fold less in the human beta cell line endoc-βh <dig>
proteome analysis
to finalise our conclusion that ins-igf <dig> expression levels have been vastly overestimated, we investigated the abundance of the ins-igf <dig> fusion protein using a strategy involving both immunochemical detection and mass spectrometry.
for the immuno-chemical work we used the only commercially available antibody  raised against full-length ins-igf <dig>  this spans the preproinsulin signal-peptide, the entire b-chain of insulin and the first  <dig> amino acids of the c-peptide .
as can be seen from fig.
<dig>  the commercial antibody readily detects the expression of recombinant ins-ifg <dig> in transduced hek- <dig> cells and in transduced endoc-βh <dig> cells.
it is important to note that this antibody  show strong cross-reaction to proinsulin in endoc-βh <dig> cells whereas it only detects a band with the expected mw of ins-igf <dig> in transduced cells .
we thus observe that the protein level of ins-igf <dig> in endoc-βh <dig> is below detection limit by western blotting.fig.
<dig> protein level sequence comparison between unprocessed preproinsulin and the ins-igf <dig> fusion protein.
the epitope of the proinsulin specific monoclonal antibody gs-9a <dig> is indicated  <cit> .
the bo1p antibody also used in this study was raised against the full length ins-igf <dig> protein.
fig.
<dig> immunoblot analysis and immunostaining of human pancreas.
a western blots investigating the presence of proinsulin-immunoreactivity  and ins-igf <dig> fusion protein immunoreactivity  in the human beta cell line endoc-βh <dig> and hek, non transduced, gfp transduced or ins-igf <dig> transduced.
endogenous proinsulin is marked with  and ins-igf <dig> with .
notice that ins-igf <dig> is only reliably detected in cells transduced with ins-igf <dig> construct.
we titrated the levels of transduced hek <dig> cell extract to give comparable band intensities on endoc-βh <dig> proinsulin and hek293-ins-igf <dig> .
ins-igf <dig> transduction of endoc-βh <dig> leads to relative lower expression of ins-igf2-protein compared to proinsulin .
this low-level expression of ins-igf <dig> protein in transduced endoc-βh <dig> is readily detected using the ins-igf <dig> antibody while untransduced cells are completely negative .
thus we conclude that the expression of ins-igf <dig> protein in endoc-βh <dig> is below detection limits of this assay.
b immunoreactivity for ins-igf <dig>  and glucagon  , and for proinsulin  and glucagon   on adjacent sections of human pancreas.
scale bar 100 µm.
the control-antibody gs-9a <dig> , a well characterized proinsulin-specific antibody binding a linear epitope spanning the b-c junction  show full cross-reaction to recombinant ins-igf <dig> —as would be expected with the intact proinsulin-b-c junction preserved in the ins-igf <dig> protein .
from band intensities in western blotting experiments we conclude that the commercial polyclonal antibody boa <dig> has higher affinity towards ins-igf <dig> than for proinsulin and yet it fails to detect any ins-igf2-like immunoreactivity in native human endoc-βh <dig>  in transduced endoc-βh <dig> the expression of ins-igf <dig> is much lower than proinsulin.
yet a weaker band is readily detected by boa <dig> but completely absent in native human endoc-βh <dig>  similarly, the gs-9a <dig> antibody having a presumed equal high affinity for both proinsulin and ins-igf <dig> completely fails to detect an ins-igf <dig> band in native human endoc-βh <dig>  in summary, these data are in line with the low levels of transcript we see in the human beta cell line, endoc-βh <dig>  which again raise the question do the protein exist?
we do observe that the antibody raised against ins-igf <dig>  indeed stain human beta cells on section of human pancreas , but we cannot deduce if this is only due to the expected cross-reaction to proinsulin.
in fact, the two antibodies, gs-9a <dig> and bo1p display very similar staining of proinsulin-like immuno-reactivity in human beta cells .
in order to further investigate the abundance of the ins-igf <dig> protein level we conducted a comprehensive analysis of both endoc-βh <dig> cells as well as isolated human islets using high-resolution mass spectrometry.
human islets were digested by trypsin and fractionated by either hydrophilic interaction chromatography  or strong cation exchange  chromatography prior to reverse phase liquid chromatography tandem mass spectrometry .
our 2d fractionation method combined with high resolution ms allowed us to identify a total of  <dig>  distinct human islet proteins.
as expected, we were able to identify human insulin with five unique peptides and a high mascot protein score .
moreover, we did identify proteins known to be expressed at a notoriously low level including transcription factors , nuclear receptors  and nuclear receptor coactivators .
however, even though we identified close to  <dig>  proteins in our analysis we were not able to identify peptides specific to the ins-igf <dig> protein in the samples.
this indicates that ins-igf <dig> is at most expressed in exceedingly low abundance in human islets.
in the proteomic analysis of the human beta cell line endoc-βh <dig> we again identified a large number of distinct proteins  including insulin and low abundant proteins but again, we were not able to identify peptides specific to the ins-igf <dig> protein.
however, the caveat one has to keep in mind with ms-based proteomics experiments is the fact that absence of evidence is not evidence of absence.
therefore, in order to ensure that the ins-ifg <dig> protein could indeed be identified by our proteomics approach, hek cells transduced with either ins-igf <dig> or a control construct were subjected to the same analysis.
both samples were analysed by lc–ms and peptides specific for ins-igf <dig> were readily observed only in the sample transduced with the ins-igf <dig> construct.
the missing evidence of ins-igf <dig> protein in human islets and in endoc-βh <dig> cells is therefore not related to our lc–ms approach.
in summary, based on sensitive proteomic and immunologic detection methods using adequate positive controls, we conclude that ins-igf <dig> protein is expressed in exceedingly low abundance in normal human islet beta cells as well as in endoc-βh <dig>  this finding correlates well with the exceedingly low expression level of the ins-igf <dig> mrna.
discussion
we see the significance of the observations presented here to be two-fold:to increase the awareness of the type of data interpretation artefacts fusion transcripts  can inflict upon gene expression analysis for both rna sequencing and micro-array experiments.
in our opinion, the main problem is that the analysis artefacts can go unnoticed, which can lead to the publication of misleading results and wasted efforts in follow-up experimental work.
in addition to the issue with the abundance of ins-igf <dig> being over-reported, we have seen several published micro-array studies, where ins wrongly was reported to be missing on the array .
the problem with over-reporting of overlapping transcripts may actually be more prevalent than immediately evident, as most cases are likely to be much less extreme than the case of insulin and ins-igf <dig> in beta cells and thus go unnoticed.
in fact, there are in total  <dig> human protein-coding transcripts that share exons in ensembl  <dig>  that could potentially be affected by the same misassignment as reported here.
on a more fundamental level, we recognize that biology is complicated and it is difficult to devise one true interpretation of the transcripts.
furthermore, a complicating factor is that as more and more transcripts variants are sequenced and deposited into the genomic databases , the risk of encountering this kind of problems is therefore likely to increase.
part of this problem is, in essence, that these variants will carry the same weight in the analysis, even if some of them are exceedingly rare.
on a more technical note, there is also the issue of what is classified as a gene in its own right as opposed to a transcript variant.
in the case of ins-igf <dig> part of the problem is that it’s listed as an independent gene and not as a splice variant of ins, as the analysis artefact could otherwise be side-stepped by aggregating the signal at the gene level.
while devising a “perfect” solution to the problem with overlapping genes is far from trivial, following an approach of listing which other transcripts may contribute to the signal of any given gene, could help to bring potential problems out in the open.
lastly, it should be mentioned that several recent publications of islet transcriptomics data do not report on a faulty ins-igf <dig> expression as they specifically handle this issue.
eizirik et al.
<cit>  used the flux capacitor approach  <cit>  to specifically handle the problem of reads mapping to exonic regions shared by multiple transcripts.
moran et al.
<cit>  addressed the multiple transcript mapping issue by applying custom parameters in the rna sequencing pipeline.
the issue of handling exons from multiple transcripts is highly dependant on the software tool used, including its version and default parameters.
for example, for users of the tophat <dig> software package it should be noted, that the default settings for handling multiple transcript mapping was changed around september  <dig>  <cit> .
<dig>  in the more specific case of ins-igf <dig> it is important to avoid a chase for an elusive transcript for the many groups of scientists working with beta cells and islet biology.
however, the big question remains on how important this transcript is?
and does it indeed lead to the production of a novel beta cell specific protein?
we show that the ins-igf <dig> antibody as well as our proinsulin-specific antibody recognize an expected band of mw  <dig>  in ins-igf <dig> transduced cells , as well as the native proinsulin band from the human beta cell line.
the work of kanatsuna et al.
<cit>  concludes that ins-igf <dig> represents a novel autoantigen in t1d, as they use in vitro translated/labeled ins-igf <dig> to detect specific autoantibodies in t1d patients.
however, “pre-proinsulin” autoantibodies would possibly also cross-react effectively in this assay, and such autoantibodies are well known in t1d.
as an example, we show that proinsulin-b/c junction specific antibody fully cross-reacts to ins-igf <dig>  more specific reagents, such as antibodies raised against the unique c-terminal fragment of the predicted ins-igf <dig> protein, are required in order to detect the protein specifically by immunocytochemical techniques.
finally, our data failed to demonstrate the existence of the ins-igf <dig> mrna and protein in endoc-βh <dig> cells.
this was further supported by lack of detection of the protein by proteomics analysis, both in human islets and the beta cell line.
CONCLUSIONS
overlapping sequence features are problematic to handle in expression analysis pipelines.
this challenge potentially leads to situations were some variants appears to be much higher expressed than data can support, or in the extreme case to completely mask out other genes in the vicinity.
a large part of the problem is the “black box” nature of the gene expression analysis pipeline in the eyes of researchers not experts in bioinformatics, and that such errors may therefore go unnoticed.
while the underlying mapping issue is far from trivial to solve, we suggest that by bringing the problem out in the open , it will be easier to flag potential problems with a given data set, and to help avoid over-, or underestimation of gene expression levels.
our in-depth analysis concludes that ins-igf <dig> abundance is > <dig>  times lower or undetectable at the level of mrna and protein, respectively, compared to previous reported findings in human beta cells.
finally, we suggest that pre-proinsulin antibodies  will also cross-react to recombinant ins-igf <dig> protein, as exemplified by a proinsulin-b-c junction specific monoclonal antibody, gs9a <dig>
in conclusion, we suggest that more specific antibody reagents  need to be developed to facilitate and support investigations into whether ins-igf <dig> fusion protein actually might be induced to elicit an autoantigen response in t1d.

 gene expression analysis artefacts as part of our research on pancreatic beta cell biology, our group has been investigating the transcripts originating from the insulin loci using both microarrays and rna-sequencing platforms. on several occasions we have noticed issues with the way overlapping transcripts are handled in gene expression analysis pipelines, and this sparked the interest for looking further into the underlying reasons for the problems. our initial observations were as follows: in dna microarray analysis different results will be obtained for the genes in the genomic region around ins depending on the mapping scheme used. in extreme cases ins itself will disappear from the analysis and all its signal would instead be mapped to ins-igf. the reason for this artefact turned out to be that certain widely used enhanced remapping schemes for affymetrix probes are targeting the longest transcript in the region. in most cases this will not cause an issue, since all the transcripts variants will in the end be mapped to the same underlying gene. however, in the case of ins the issue is that a fusion transcript, ins-igf is spanning the entire region, including both insulin exons as well as part of the adjacent igf2-locus. this will lead to all signal in the region being mapped to ins-igf and that ins will “disappear” from the analysis, and in certain cases so would igf. this will happen even if there are no probes targeting the unique part of the fusion transcript.fig.  rna sequencing read depth in the ins/igf genomic region. plot of the genomic region of chromosome around the ins and igf loci with probesets from the affymetix hg-u133a array and the main transcript variants of ins, ins-igf and igf indicated below the plot. all shown transcripts are encoded on the antisense strand —for an overview of all known transcript variants, please see additional file 1: figure s. the y-axis shows the read depth of the rna sequencing study from nica et al. —notice that read depth was capped at. from the plot it is clearly seen that few reads maps to the ins-igf exons in the area and almost all signal assigned to ins-igf by nica et al. originates from the first coding exon which is shared with ins. all positional information on this plot is from ensembl v. for rna sequencing analysis a related problem is encountered. the individual reads will typically be mapped to a set of transcripts from the organism in question, and will be assigned multiple times to transcripts sharing sequences. in most cases this is the desired behaviour, and will be a way to handle splicing variants of a given gene. however, in the case of transcripts spanning several genes, there is a risk that the signal from one gene bleeds into the overlapping transcript, and this may not be apparent when the results are reported. with this in mind, we decided to re-investigate the observation by nica et al. that the ins-igf fusion transcript was found to be the second most abundant mrna in human beta cells, an observation that has generated much interest in the beta cell biology field since ins-igf has previously been annotated to be translated and moreover, recently proposed as a novel autoantigen in type diabetes. case background: beta cell biology the pancreatic beta cell is a key component in regulating blood glucose homeostasis as it represents our sole source of insulin, which is required for peripheral tissues to internalize and utilize glucose as an energy source. lack of adequate functional beta cell mass leading to relative insulin insufficiency is the common denominator of all forms of diabetes. t1d is characterized by an absolute loss of beta cells as a result of autoimmune destruction. type diabetes is where a relative beta cell insufficiency results from failure of compensatory upregulation of insulin production capacity in response to increasing peripheral insulin resistance. therefore much effort in, both preventive and curative, diabetes research has aimed at understanding the molecular networks, both at the level of transcriptional and translational regulation of genes controlling development and at the function and survival of the pancreatic beta cell. recent advancements in the ability to purify single cell types from the islet of langerhans combined with omics’ approaches have led to detailed information of the transcriptomic environment of beta cells. gene-knockouts, and animal models, in particular targeting transcription factors combined with genome-wide association studies, have in the past decade provided us with a comprehensive map of genes and loci that may cause or contribute to diabetes, and it is evident that better understanding of molecular control of functional beta cell mass will be key to design strategies to defeat diabetes. all classical studies, not surprisingly, report a very high abundance of insulin mrna, and insulin represents one of the most abundant cell specific mrna’s known in our body. it was therefore surprising to realize that the second most abundant beta cell mrna, recently reported in facs purified human beta cells, was encoding ins-igf values comparable to glucagon mrna levels in purified human alpha cells was reported for ins-igf suggesting that a putative and highly abundant beta cell protein could have been overlooked. moreover, recent studies suggested that ins-igf could be yet another beta cell specific antigen recognized by autoantibodies in t1d.  transcriptome analysis in our reanalysis of the rna sequencing data from nica et al. we did not map the reads to transcripts but rather investigated an unbiased mapping of the reads to the genomic region on chromosome containing the ins, igf and ins-igf transcripts. by visual inspection of the distribution of the reads, it is clearly observed that the regions specific to ins-igf are lowly expressed, whereas the ins specific exons are highly expressed. both coding exons of ins being expressed at the same order of magnitude is a clear indication that most reads mapped to the exon that is shared by both ins and ins-igf belong to the ins- transcript, and the perceived high expression of the ins-igf transcript is due to the read count being assigned to both genes, where the difference in level is due to the different lengths of the two genes. the data analysis artefact is especially pronounced in this case, since ins in itself constitutes a large part of the transcript pool in beta cells. in our own experiments using the human beta cell line endoc-βh we observe the same trends, both with rna sequencing and micro-array analysis. both rna sequencing and dna micro-arrays are measuring sequence fragments, therefore we decided to take the analysis one step further and devised a qpcr strategy based on splice-form specific primers in order to provide a more direct measurement of the individual unfragmented mrna species, in both endoc-βh cells and human islets. in both cases the observations are the same; the ins-igf fusion transcript is expressed at a level > fold lower than the ins transcript, and is hence barely detectable.table  qpcr analysis of ins-igf ins and igf2 relative expression of ins-igf ins and igf determined by qpcr for endoc-βh cells and human islets. all mrnas were analysed in independent preparations, each in technical duplicate and the average of each duplicate is shown for each preparation. gapdh was used as input control. it is clear that ins-igf is expressed at very low levels compared to insulin, i.e. in the order of > fold less in human islets and fold less in the human beta cell line endoc-βh proteome analysis to finalise our conclusion that ins-igf expression levels have been vastly overestimated, we investigated the abundance of the ins-igf fusion protein using a strategy involving both immunochemical detection and mass spectrometry. for the immuno-chemical work we used the only commercially available antibody raised against full-length ins-igf this spans the preproinsulin signal-peptide, the entire b-chain of insulin and the first amino acids of the c-peptide. as can be seen from fig.  the commercial antibody readily detects the expression of recombinant ins-ifg in transduced hek- cells and in transduced endoc-βh cells. it is important to note that this antibody show strong cross-reaction to proinsulin in endoc-βh cells whereas it only detects a band with the expected mw of ins-igf in transduced cells. we thus observe that the protein level of ins-igf in endoc-βh is below detection limit by western blotting.fig.  protein level sequence comparison between unprocessed preproinsulin and the ins-igf fusion protein. the epitope of the proinsulin specific monoclonal antibody gs-9a is indicated. the bo1p antibody also used in this study was raised against the full length ins-igf protein. fig.  immunoblot analysis and immunostaining of human pancreas. a western blots investigating the presence of proinsulin-immunoreactivity and ins-igf fusion protein immunoreactivity in the human beta cell line endoc-βh and hek, non transduced, gfp transduced or ins-igf transduced. endogenous proinsulin is marked with and ins-igf with. notice that ins-igf is only reliably detected in cells transduced with ins-igf construct. we titrated the levels of transduced hek cell extract to give comparable band intensities on endoc-βh proinsulin and hek293-ins-igf. ins-igf transduction of endoc-βh leads to relative lower expression of ins-igf2-protein compared to proinsulin. this low-level expression of ins-igf protein in transduced endoc-βh is readily detected using the ins-igf antibody while untransduced cells are completely negative. thus we conclude that the expression of ins-igf protein in endoc-βh is below detection limits of this assay. b immunoreactivity for ins-igf and glucagon, and for proinsulin and glucagon on adjacent sections of human pancreas. scale bar 100 µm. the control-antibody gs-9a, a well characterized proinsulin-specific antibody binding a linear epitope spanning the b-c junction show full cross-reaction to recombinant ins-igf —as would be expected with the intact proinsulin-b-c junction preserved in the ins-igf protein. from band intensities in western blotting experiments we conclude that the commercial polyclonal antibody boa has higher affinity towards ins-igf than for proinsulin and yet it fails to detect any ins-igf2-like immunoreactivity in native human endoc-βh in transduced endoc-βh the expression of ins-igf is much lower than proinsulin. yet a weaker band is readily detected by boa but completely absent in native human endoc-βh similarly, the gs-9a antibody having a presumed equal high affinity for both proinsulin and ins-igf completely fails to detect an ins-igf band in native human endoc-βh in summary, these data are in line with the low levels of transcript we see in the human beta cell line, endoc-βh which again raise the question do the protein exist? we do observe that the antibody raised against ins-igf indeed stain human beta cells on section of human pancreas, but we cannot deduce if this is only due to the expected cross-reaction to proinsulin. in fact, the two antibodies, gs-9a and bo1p display very similar staining of proinsulin-like immuno-reactivity in human beta cells. in order to further investigate the abundance of the ins-igf protein level we conducted a comprehensive analysis of both endoc-βh cells as well as isolated human islets using high-resolution mass spectrometry. human islets were digested by trypsin and fractionated by either hydrophilic interaction chromatography or strong cation exchange chromatography prior to reverse phase liquid chromatography tandem mass spectrometry. our 2d fractionation method combined with high resolution ms allowed us to identify a total of distinct human islet proteins. as expected, we were able to identify human insulin with five unique peptides and a high mascot protein score. moreover, we did identify proteins known to be expressed at a notoriously low level including transcription factors, nuclear receptors and nuclear receptor coactivators. however, even though we identified close to proteins in our analysis we were not able to identify peptides specific to the ins-igf protein in the samples. this indicates that ins-igf is at most expressed in exceedingly low abundance in human islets. in the proteomic analysis of the human beta cell line endoc-βh we again identified a large number of distinct proteins including insulin and low abundant proteins but again, we were not able to identify peptides specific to the ins-igf protein. however, the caveat one has to keep in mind with ms-based proteomics experiments is the fact that absence of evidence is not evidence of absence. therefore, in order to ensure that the ins-ifg protein could indeed be identified by our proteomics approach, hek cells transduced with either ins-igf or a control construct were subjected to the same analysis. both samples were analysed by lc–ms and peptides specific for ins-igf were readily observed only in the sample transduced with the ins-igf construct. the missing evidence of ins-igf protein in human islets and in endoc-βh cells is therefore not related to our lc–ms approach. in summary, based on sensitive proteomic and immunologic detection methods using adequate positive controls, we conclude that ins-igf protein is expressed in exceedingly low abundance in normal human islet beta cells as well as in endoc-βh this finding correlates well with the exceedingly low expression level of the ins-igf mrna. discussion we see the significance of the observations presented here to be two-fold:to increase the awareness of the type of data interpretation artefacts fusion transcripts can inflict upon gene expression analysis for both rna sequencing and micro-array experiments. in our opinion, the main problem is that the analysis artefacts can go unnoticed, which can lead to the publication of misleading results and wasted efforts in follow-up experimental work. in addition to the issue with the abundance of ins-igf being over-reported, we have seen several published micro-array studies, where ins wrongly was reported to be missing on the array. the problem with over-reporting of overlapping transcripts may actually be more prevalent than immediately evident, as most cases are likely to be much less extreme than the case of insulin and ins-igf in beta cells and thus go unnoticed. in fact, there are in total human protein-coding transcripts that share exons in ensembl that could potentially be affected by the same misassignment as reported here. on a more fundamental level, we recognize that biology is complicated and it is difficult to devise one true interpretation of the transcripts. furthermore, a complicating factor is that as more and more transcripts variants are sequenced and deposited into the genomic databases, the risk of encountering this kind of problems is therefore likely to increase. part of this problem is, in essence, that these variants will carry the same weight in the analysis, even if some of them are exceedingly rare. on a more technical note, there is also the issue of what is classified as a gene in its own right as opposed to a transcript variant. in the case of ins-igf part of the problem is that it’s listed as an independent gene and not as a splice variant of ins, as the analysis artefact could otherwise be side-stepped by aggregating the signal at the gene level. while devising a “perfect” solution to the problem with overlapping genes is far from trivial, following an approach of listing which other transcripts may contribute to the signal of any given gene, could help to bring potential problems out in the open. lastly, it should be mentioned that several recent publications of islet transcriptomics data do not report on a faulty ins-igf expression as they specifically handle this issue. eizirik et al. used the flux capacitor approach to specifically handle the problem of reads mapping to exonic regions shared by multiple transcripts. moran et al. addressed the multiple transcript mapping issue by applying custom parameters in the rna sequencing pipeline. the issue of handling exons from multiple transcripts is highly dependant on the software tool used, including its version and default parameters. for example, for users of the tophat software package it should be noted, that the default settings for handling multiple transcript mapping was changed around september. in the more specific case of ins-igf it is important to avoid a chase for an elusive transcript for the many groups of scientists working with beta cells and islet biology. however, the big question remains on how important this transcript is? and does it indeed lead to the production of a novel beta cell specific protein? we show that the ins-igf antibody as well as our proinsulin-specific antibody recognize an expected band of mw in ins-igf transduced cells, as well as the native proinsulin band from the human beta cell line. the work of kanatsuna et al. concludes that ins-igf represents a novel autoantigen in t1d, as they use in vitro translated/labeled ins-igf to detect specific autoantibodies in t1d patients. however, “pre-proinsulin” autoantibodies would possibly also cross-react effectively in this assay, and such autoantibodies are well known in t1d. as an example, we show that proinsulin-b/c junction specific antibody fully cross-reacts to ins-igf more specific reagents, such as antibodies raised against the unique c-terminal fragment of the predicted ins-igf protein, are required in order to detect the protein specifically by immunocytochemical techniques. finally, our data failed to demonstrate the existence of the ins-igf mrna and protein in endoc-βh cells. this was further supported by lack of detection of the protein by proteomics analysis, both in human islets and the beta cell line.  overlapping sequence features are problematic to handle in expression analysis pipelines. this challenge potentially leads to situations were some variants appears to be much higher expressed than data can support, or in the extreme case to completely mask out other genes in the vicinity. a large part of the problem is the “black box” nature of the gene expression analysis pipeline in the eyes of researchers not experts in bioinformatics, and that such errors may therefore go unnoticed. while the underlying mapping issue is far from trivial to solve, we suggest that by bringing the problem out in the open, it will be easier to flag potential problems with a given data set, and to help avoid over-, or underestimation of gene expression levels. our in-depth analysis concludes that ins-igf abundance is > times lower or undetectable at the level of mrna and protein, respectively, compared to previous reported findings in human beta cells. finally, we suggest that pre-proinsulin antibodies will also cross-react to recombinant ins-igf protein, as exemplified by a proinsulin-b-c junction specific monoclonal antibody, gs9a in conclusion, we suggest that more specific antibody reagents need to be developed to facilitate and support investigations into whether ins-igf fusion protein actually might be induced to elicit an autoantigen response in t1d. 
for the specific case of ins-igf we conclude that the abundance of the fusion transcript/protein is exceedingly lower than previously reported, and that current immuno-reagents available for detecting ins-igf protein have a strong cross-reaction to native human proinsulin. we found that the one available commercial antibody raised against recombinant ins-igf show strong cross-reaction to native proinsulin, and we did not detect ins-igf protein in the human beta cell line endoc-βh furthermore, using highly sensitive proteomics analysis we could not demonstrate ins-igf protein in samples of human islets nor in endoc-βh through rna sequencing and variant specific qpcr analyses we demonstrate that the true abundance of ins-igf is > fold lower than ins in human beta cells, and we suggest an explanation to the nature of the artefacts which have previously led to overestimation of the gene expression level in selected studies. sequence features, such as fusion transcripts spanning multiple genes can lead to unexpected results in gene expression analysis, and care must be taken in generating and interpreting the results. in gene expression analysis, overlapping genes, splice variants, and fusion transcripts are potential sources of data analysis artefacts, depending on how the observed intensity is assigned to one, or more genes. we here exemplify this by an in-depth analysis of the ins-igf fusion transcript, which has recently been reported to be among the highest expressed transcripts in human pancreatic beta cells and its protein indicated as a novel autoantigen in type diabetes. finally, we were unable to detect ins-igf protein by proteomics analysis.
 in gene expression analysis, overlapping genes, splice variants, and fusion transcripts are potential sources of data analysis artefacts, depending on how the observed intensity is assigned to one, or more genes. we here exemplify this by an in-depth analysis of the ins-igf fusion transcript, which has recently been reported to be among the highest expressed transcripts in human pancreatic beta cells and its protein indicated as a novel autoantigen in type diabetes.  through rna sequencing and variant specific qpcr analyses we demonstrate that the true abundance of ins-igf is > fold lower than ins in human beta cells, and we suggest an explanation to the nature of the artefacts which have previously led to overestimation of the gene expression level in selected studies. we reinvestigated the previous reported findings of detection of ins-igf using antibodies both in western blotting and immunohistochemistry. we found that the one available commercial antibody raised against recombinant ins-igf show strong cross-reaction to native proinsulin, and we did not detect ins-igf protein in the human beta cell line endoc-βh furthermore, using highly sensitive proteomics analysis we could not demonstrate ins-igf protein in samples of human islets nor in endoc-βh  sequence features, such as fusion transcripts spanning multiple genes can lead to unexpected results in gene expression analysis, and care must be taken in generating and interpreting the results. for the specific case of ins-igf we conclude that the abundance of the fusion transcript/protein is exceedingly lower than previously reported, and that current immuno-reagents available for detecting ins-igf protein have a strong cross-reaction to native human proinsulin. finally, we were unable to detect ins-igf protein by proteomics analysis. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords insulinins-igf2beta cellfusion-transcriptgene expressionproteomicsantibodybioinformaticsanalysis artefactpancreatic isletsdiabetesissue-copyright-statement© the author 2015 