BACKGROUND
biological processes are underlain by interactions between various genes and their products through defined pathways in the molecular network, in which molecules cross communicate in hitherto unknown ways under both healthy and disease conditions.
learning gene expression patterns on a genomic scale would substantially help deconvolute these complex processes.
exhaustive identification of human genes during the human genome project has made such studies possible.
by global gene expression profiling in cells and tissues under either physiological or in vitro conditions, our understanding of the correlation between gene functions and their phenotypic effects could be significantly enhanced.
the advent of the microarray-based high-throughput rna detection system  <cit>  has made it possible to profile gene expression patterns for the entire transcriptome.
however, to detect gene transcripts very specifically, one needs to discriminate them from closely related sequences including:  the corresponding gene sequences.
although contamination of gene sequences may not be a concern for applications using purified mrna, gene sequences must be taken into consideration for applications directly using cell lysate without rna extraction.
this becomes especially important when the studied transcripts are present at low abundance;  pseudogenes and their possible transcripts.
the number of pseudogenes in the human genome was estimated to be  <dig>  to  <dig> , which are widely expressed  <cit> .
these sequences usually share a high degree of sequence identity with the closely related genes;  unprocessed rna containing the same exons as those of the corresponding mrna.
so far, no system has addressed the above issue very effectively.
among the microarray-based platforms, genechip is a commonly used system and has been improved significantly since it was invented, and has contributed to understanding the complex gene expression network in a great deal.
however, since this technology is limited by its high degree of nonspecificity and insensitivity, its application has been limited in molecular network integration.
results from a recent analysis  <cit>  indicated that on the affymetrix genechip u95a/av <dig> array,  <dig>   probes were nonspecific, which could cross-hybridize to multiple genes, and  <dig>   probes missed the target transcript sequences.
the numbers of nonspecific and mis-targeted probes on the u133a array were comparable, which were  <dig>   and  <dig>  , respectively  <cit> .
these ~20% of problematic probes certainly and substantially compromise the data accuracy, decrease the value of microarray data, and are not acceptable for the studies of molecular network integration.
it was also found that some probe sets representing the same genes on affymetrix microarrays could show significant discrepancy because of the non-specific hybridization  <cit>
in most applications, gene expression profiling with microarrays including genechip requires amplification of sample rna, regardless of how much material is available.
normally,  <dig> to  <dig> μg of rna is required for each assay  <cit> .
however, high-throughput gene expression profiling with superior sensitivity is becoming more and more demanded, and has its wide applications.
for example, in breast cancer research, analysis of specimens from microdissection may provide important information about genes involved in different cancer development stages and for understanding the molecular mechanisms underlying cancer development  <cit> .
specimens from fine needle biopsy are also important in diagnostic procedures and in evaluating therapeutic effects.
the ability to analyze a large number of genes in single cells may help understand the origin and clonality of cancer development and learn the molecular details involved in different stages of the cell cycle.
current methodologies for gene expression profiling in small rna samples, especially those from single cells, are very limited.
many of these protocols  <cit>  require multiple enzymatic reactions that may seriously reduce the sensitivity and compromise the specificity.
rna preparation in most of applications also involves a number of steps, which is rather lengthy, tedious, and requires highly skilled personnel.
to solve the above problems, we have developed a highly specific and sensitive gene expression profiling system.
with this system, primers are specially designed to amplify mrna sequences very specifically.
probes used for microarray detection are designed only to hybridize to sequences amplified from mrna.
in conjunction with the high-throughput multiplex amplification protocol developed in our laboratory lately  <cit> , a large number of mrna species directly released from very few cells or even single cells can be amplified to a detectable amount without rna isolation.
amplified products can then be detected by the single-base extension <cit>  assay on an oligonucleotide microarray  <cit> .
RESULTS
experimental system used in the study
to establish a cancer gene expression array, a panel of cancer-related genes were selected based on their known functions and/or cancer-associated expression patterns from published literature  <cit> .
all amplicon sequences were subjected to computational screening to ensure their uniqueness.
primers and probes were selected according to a series of criteria as specified in materials and methods.
most primer pairs amplify sequences in two neighboring exons separated by large introns.
the intron lengths ranged from  <dig> bp to  <dig> kb with an average of  <dig>  kb and 97% of the introns are longer than  <dig> bp.
initially  <dig>  genes were used as the input for the primer and probe design program.
primers and probes were selected for  <dig>   of these genes.
the remaining  <dig> % had either no introns or no suitable sequences for primers and/or probes.
fifteen of these remaining genes with important functions in cancer development were included in the panel.
primers and probes were designed based on the unique sequences in these genes, and were not required to have introns internally located within the amplified sequences.
therefore, a total of  <dig>  genes were included in our multiplex assay.
microarray-based single-base extension  assay has been used to genotype single nucleotide polymorphisms   <cit>  in our laboratory.
in the present study, sbe was adapted for gene expression profiling.
to simplify the analysis, all probes were designed to terminate immediately before a 'g' base in the templates.
in this way, the probes were extended by a single base, dideoxynucleoside triphosphate  that was fluorescently labeled.
by using one color, the bias associated with different dyes was also eliminated.
the detection procedure is schematically illustrated in fig.
<dig>  resulting data have been deposited to the ncbi's gene expression omnibus   <cit>  and are accessible through geo series accession number gse <dig>
reproducibility of the high-throughput gene expression profiling system
to test the reproducibility of our system, gene expression was profiled for three duplicated 100-cell samples from an ovarian cancer cell line, nci/adr-res  <cit>  and two 100-cell samples from a breast cancer cell line, mcf- <dig>  resulting microarray data are supplied in additional file  <dig>  table  <dig> summarizes the numbers of gene transcripts detected from different samples.
as shown,  <dig> ,  <dig> , and  <dig>  gene transcripts were detected from the three 100-cell samples of nci/adr-res, respectively.
of these transcripts,  <dig>  were detected from all three duplicates.
signal intensities for the  <dig>  genes were strongly correlated between the duplicates .
fig.
2a shows a scatter plot of two duplicates.
of the  <dig> transcripts detected in all three nci/adr-res 100-cell samples, only  <dig> ,  <dig> , and  <dig>  transcripts had their signal intensities differing by > <dig> fold between each two of these three duplicates.
twenty-six transcripts were detected from only one or two of the three samples.
the signal intensities for these transcripts were low.
only one transcript in one sample had its signal intensity > <dig> , indicating that the inconsistence among the duplicates was due to low signals of these transcripts.
*adr: nci/adr-res
for the two 100-cell samples from mcf- <dig>   <dig>  and  <dig>  gene transcripts were detected, respectively, with  <dig>  detected in both.
of these  <dig> transcripts,  <dig>  had signal intensities differing less than two fold.
similar to the situation with nci/adr-res samples, all  <dig> transcripts that were detected in only one sample but not the other had low signal intensities with only nine genes whose signal intensities were > <dig>  in one of the two samples.
because samples prepared from a large number of cells are usually associated with high reliability, we further compared the microarray results of the nci/adr-res 100-cell samples with those from a  <dig> -cell sample of the same cell line.
resulting data also show a high degree of correlation .
as shown in table  <dig>   <dig>  of the  <dig> gene transcripts detected from all the 100-cell samples were also detected from the  <dig> -cell sample.
sixty-three gene transcripts were detected in at least one of the three 100-cell samples but not in the  <dig> -cell sample, or vice versa.
of these  <dig> gene transcripts,  <dig> had signal intensities below  <dig>  in all the three 100-cells.
however, the change from  <dig> to  <dig>  cells did enhance the detection of  <dig> gene transcripts whose signal intensities were > <dig> fold greater in the  <dig> -cell sample than those in the 100-cell samples.
among these  <dig> transcripts, six had signal intensities in the  <dig> -cell sample more than  <dig> fold greater than the average intensities of the corresponding genes in the three 100-cell samples, indicating that using  <dig>  cells may have significantly increased the copy numbers of these transcripts or changed their absence status to presence.
these data indicate that our system not only can produce very reliable results even with as few as  <dig> cells but also is very sensitive to the copy number change for the low-copy-number gene transcripts.
sensitivity of the high-throughput gene expression profiling system
to further test the sensitivity of our high-throughput gene expression profiling system, single nci/adr-res cell samples were prepared and used for multiplex gene expression assay of the  <dig>  mrna species.
microarray results from three of these samples are listed in additional file  <dig>  the numbers of gene transcripts detected from the three single-cell samples were  <dig>   <dig>  and  <dig>  respectively.
of these transcripts,  <dig> were detected from all single cells.
of the  <dig>   <dig>  were also detected from all non-single-cell  samples, indicating a prevalent expression of these genes in most, if not all, cells at relatively high levels.
on the other hand, the detection range of gene transcripts from the three single-cell samples was wider compared to the non-single-cell samples.
as shown in table  <dig>   <dig> transcripts were undetectable in all three single cell samples, a number which is not greater than that  for the three 100-cell samples and is comparable to that  for all non-single-cell samples.
the number of undetectable gene transcripts from all single and non-single cell samples is  <dig>  this number means that from single cells, we not only detected a comparable number of genes, but also detected a new set of 449- <dig> =  <dig> genes that could not be detected with non-single-cell samples of the same cell line.
the robustness of gene expression profiling with single-cell samples was also demonstrated by the signal intensities.
as described above, most transcripts that were detected from some but not all non-single-cell samples had low signal intensities and very few were > <dig> .
the scenario with single cells is very different.
of the  <dig> gene transcripts detected from all single cells,  <dig> were detected in one to three non-single-cell samples but not all four.
all  <dig> but one have signal intensity > <dig>  in at least one of the three single-cell samples.
of the  <dig> transcripts that were only detected from one or two single-cell samples,  <dig>  had signal intensity > <dig> .
the strong and robust signal intensities detected from single-cell samples indicate that our system is very sensitive.
unlike the gene transcripts detected from all non-single-cell samples which account for more than 95% of gene transcripts detected from each of these samples, the  <dig> gene transcripts detected from single cells only account for  <dig>  3%,  <dig> % and  <dig> % of the transcripts detected from individual single-cell samples, respectively.
pairwise comparison of the results from the single-cell samples yielded correlation coefficients of  <dig> ,  <dig> , and  <dig> , respectively, compared with =  <dig>  for the non-single-cell samples.
from all single and non-single-cell samples,  <dig> gene transcripts were detected, of which  <dig>  were detected from some but not all samples.
this is in contrast with the scenario of non-single-cell samples from which gene transcripts that were only detected from some but not all samples were a very small portion .
furthermore, of these  <dig> transcripts,  <dig>  were either detected from only single cells or from non-single cell samples.
the high degree of concordance among the results from the non-single-cell samples, and the significant differences among those from single cells, and between single cells and non-single-cell samples indicate that most, if not all, of these differences are real.
as mentioned above, this is further supported by the robustness of the signal intensities detected from single-cell samples for the gene transcripts that were detected differently between the single cells and non-single-cell samples.
it is conceivable that heterogeneity in clonality and/or genetic alterations in the cells of a cell line could be major factors contributing to the differences.
in addition, a considerable portion of the cells may be at different cycle stages during which groups of genes are expressed differently.
therefore, while gene expression in single cells could differ in various aspects,  <dig> cells may well represent the entire cell population because, after all, the cell line cells are from the same tissue and the same donor.
therefore, genes that are detectable in a cell population may not be expressed or expressed at very low levels in certain single cells.
conversely, genes that are detectable in particular single cell samples may not be expressed or expressed at very low levels in the majority of the cell population.
differential gene expression in the two cell lines, nci/adr-res and mcf-7
when the gene expression profiles of nci/adr-res were compared with those of mcf- <dig>  a considerable number of genes were shown to be expressed differentially in these two cell lines.
of the  <dig>  gene products,  <dig>  were detected from samples of both cell lines .
seventy-five gene transcripts were detected in all nci/adr-res non-single-cell samples, but not in the mcf- <dig> samples, and  <dig> were detected in the opposite way.
of the  <dig> differentially expressed genes,  <dig> were shown to be expressed with more than 10-fold difference .
of the  <dig> genes,  <dig>  were detected as strongly or relatively strongly expressed in mcf- <dig>  but weakly or not expressed in nci/adr-res, and  <dig> were detected in the opposite way.
to validate the gene expression data,  <dig> of these  <dig> genes, and another  <dig> gene transcripts detected with various microarray signal intensities different between the samples of the two cell lines were randomly selected  and subjected to rt-pcr amplification individually.
the amplified products were resolved by gel electrophoresis.
the signal intensities of the respective bands were quantified with a gel documentation system.
part of results from microarrays and gel assays are shown in fig.
<dig>
note:  <dig>  signal intensities of microarray are averages of those respective non-single cell samples.
<dig>  adr: nci/adr-res.
specificity of the high-throughput gene expression system
the specificity of our high-throughput gene expression system was demonstrated by the results from different cell line samples and by those from different single cells as described above.
to further demonstrate the specificity of our system, human genomic dna samples were amplified with the same multiplex rt-pcr procedure and analyzed by microarray.
very few probes  were shown to have signals above background , indicating that our system is very specific and can discriminate between the target mrna sequences from their genomic counterparts, and therefore, the unprocessed transcripts.
our previous experience also showed that in the absence of specific templates, a few primer sets may amplify non-specific sequences.
however, such non-specific amplification may become undetectable in the presence of specific templates because the specific sequences are much stronger in competition.
in addition, using specially designed probes also enhanced the specificity.
discussion
compared with other existing gene expression profiling methods, our approach has the following advantages:
highly specific
to date, no other high-throughput system has been reported to be highly discriminative of mrna from other related dna and rna sequences.
using primers amplifying sequences across intron and probes consisting of sequences in adjacent exons is a critical enhancement to achieve such high specificity.
furthermore, all primer, probe and amplicon sequences were subjected to exhaustive searches against the databases of the entire human genome and transcriptome to ensure these sequences are unique.
such a step was proven very effective for enhancing the specificity  <cit> .
experimentally, when genomic dna was used as samples, signals were only detected for only  <dig> or  <dig> genes  out of the  <dig>  genes.
based on our previous studies, these signals may become undetectable in the presence of specific sequences which may compete out the nonspecific amplification.
highly sensitive
we showed previously that our multiplex amplification system could detect > <dig>  single-copy sequences simultaneously from single haploid sperm cells  <cit> .
the fact that >90% of these sequences are detectable indicates that with our specially designed primers, most, if not all, sequences may be well amplified parallelly with very limited, if any, interaction among the primers.
since the primers used for gene profiling are designed in the same way, it is reasonable to believe that most gene transcripts are also amplified parallelly.
however, since the copy number of different gene transcripts in the cells varies in a wide range, the outcome of amplification would be different from that using single-copy sequences.
when only single-copy sequences are used in multiplex amplification, most, if not all, sequences may reach the detectable amount before the system is saturated.
however, when gene transcripts are amplified, whether a transcript reaches a detectable amount before the system is saturated depends on its copy number in the sample, and not all sequences may reach a detectable amount at the end of amplification.
this is probably why some sequences were undetectable by microarray but detectable by gel assay.
with our system, a total of  <dig> gene transcripts were detected from three single cells, which is comparable to  <dig> for the three 100-cell samples and  <dig> for all non-single-cell samples from the same cell line.
the sensitivity of our system is further proved by the facts that results from 100-cell samples are very similar to each other and to those from  <dig>  cells, and that specific gene expression profiles were obtained from different cell lines using as few as  <dig> cells.
the sensitivity of our system is further illustrated by the results that a significant portion of transcripts that could not be detected from the nci/adr-res samples but were detected from the mcf- <dig> samples or single cell samples, and vice versa.
this also indicates that low microarray intensities for these transcripts were not false negatives, and they were either not present or present in very low abundance in the respective samples.
very simple
unlike other methods that involve multiple steps and use multiple enzymes, our method allows a large number of gene products amplified by a single rt-pcr step directly from cell lysates without rna extraction.
in this way, a large number of samples may be analyzed easily and cost-effectively.
our simple experimental procedure is also the basis of the high degree of sensitivity since it avoids complicated mrna extraction and processing procedures before and during amplification, which may cause mrna degradation or loss.
very safe for rna samples
when working with rna, one has to take extra precaution to prevent mrna from degradation.
our method does not need rna extraction.
once cells are lysed, rna is directly released to the rt-pcr buffer and used as template immediately.
there is almost no chance for rnase to degrade the mrna templates.
highly flexible
many studies may not need to analyze all genes in the human genome and may often need to focus on different gene groups.
therefore, flexibility of the experimental system would be highly desirable.
with our computer program, a large number of gene products can be designed into a single multiplex group.
genes can be easily organized into different subgroups upon need, and can also be re-grouped at any time without altering the reaction conditions.
new gene products can be added to an existing set easily.
the capacity of multiplex rt-pcr is another concern for high-throughput gene expression profiling because it not only makes the amplification of a large number of gene products affordable and cost-effective, but also eliminates challenges involved in quality control of rt-pcr for a large number of genes individually  <cit> .
however, the capacity of multiplex amplification was limited by interaction between primers.
a previous study reported a screening of  <dig> expressed genes using multiplex rt-pcr, but was unable to reduce the number of the reaction tubes less than eight  <cit> .
other studies multiplexed up to nine genes with nonspecific rt primers  <cit> .
studies using multiple sets of gene-specific primers in single reactions were also reported, but none of these generated enough products for the analysis of all expressed genes in the samples  <cit> .
in the present study, we report our success with multiplex rt-pcr for  <dig>  mrna species.
such a success was based on a combination of several technological developments, including computerized primer design with predicted minimal interaction, a narrow primer tm range, small amplicon sizes, and optimization of amplification conditions based on our previous experience  <cit> .
with our current protocol, it is possible to include two thousand or more gene transcripts in a single multiplex amplification group, and to analyze all human gene transcripts using several multiplexing amplification groups.
after pooling amplified products from the multiplexing groups, all genes may be analyzed with a single microarray.
with our system, large-scale gene expression profiling becomes highly affordable and cost-effective.
if the primers and probes used in the high-throughput analysis are made accessible to the research community through a distribution system, large- and genome-scale gene expression profiling may be even more affordable and cost-effective.
a major limitation of our system is the requirement of presence of large introns in genes under study.
when the introns are small, discrimination between mrna and closely related dna and rna sequences is still possible by using probes consisting of sequences in the neighboring exons.
for genes with no introns, primers and probes can be designed only to discriminate mrna sequences from related pseudogenes and their transcripts but not the corresponding gene sequences.
in this case, discrimination between mrnas and their gene sequences is only possible when the mrnas are present abundantly.
an extreme and possible application of our highly sensitive gene expression profiling system is the analysis of disseminated tumor cells in cancer research.
analysis of individual cells is necessary for understanding the early dissemination of tumor cells.
disseminated tumor cells remain in the patient bodies even after complete resection of the primary tumor, and can be obtained by bone marrow aspirates  <cit> .
with our highly sensitive system, genetic signature in these cells may be detected.
the resulting information may provide molecular basis for new therapeutic targets.
for example, erbb <dig> expression has been found to be a therapeutic target for metastatic breast carcinoma  <cit> .
identification of mrna like that of erbb <dig> in micrometastatic cells may help develop effective therapeutical approaches to preventing further development of these cells into incurable metastasis.
using mrna from a small number of microdissected frozen tissue sections without rna isolation has been demonstrated with a small number of genes  <cit> .
our system should be capable of using both microdissected and biopsy specimens for gene expression analysis on a much larger scale.
high-throughput gene expression profiling with single cells is also interesting for most laboratories studying molecular neurophysiology, but has been hampered by the capacity of multiplex pcr.
our approach can be used to examine the expression of many genes within individual neurons or other cells.
the gene expression profiles can also be correlated to the phenotypes of these cells such as morphological, electrophysiological and pharmacological features to understand the underlying molecular mechanisms.
CONCLUSIONS
this report describes a high-throughput gene expression profiling technology, which is simple, highly reproducible, specific and sensitive, and may greatly facilitate gene expression profiling of a small number of or even single cells.
it may also be applicable to many applications where the amount of material is limited, and to diagnostic assays that identify the onset of cancer and monitor its progression, remediation or response to treatments.
data discussed in this publication have been deposited in the ncbi's gene expression omnibus  <cit>  and are accessible through geo series accession number gse <dig>

 biological processes are underlain by interactions between various genes and their products through defined pathways in the molecular network, in which molecules cross communicate in hitherto unknown ways under both healthy and disease conditions. learning gene expression patterns on a genomic scale would substantially help deconvolute these complex processes. exhaustive identification of human genes during the human genome project has made such studies possible. by global gene expression profiling in cells and tissues under either physiological or in vitro conditions, our understanding of the correlation between gene functions and their phenotypic effects could be significantly enhanced. the advent of the microarray-based high-throughput rna detection system has made it possible to profile gene expression patterns for the entire transcriptome. however, to detect gene transcripts very specifically, one needs to discriminate them from closely related sequences including: the corresponding gene sequences. although contamination of gene sequences may not be a concern for applications using purified mrna, gene sequences must be taken into consideration for applications directly using cell lysate without rna extraction. this becomes especially important when the studied transcripts are present at low abundance; pseudogenes and their possible transcripts. the number of pseudogenes in the human genome was estimated to be to, which are widely expressed. these sequences usually share a high degree of sequence identity with the closely related genes; unprocessed rna containing the same exons as those of the corresponding mrna. so far, no system has addressed the above issue very effectively. among the microarray-based platforms, genechip is a commonly used system and has been improved significantly since it was invented, and has contributed to understanding the complex gene expression network in a great deal. however, since this technology is limited by its high degree of nonspecificity and insensitivity, its application has been limited in molecular network integration. results from a recent analysis indicated that on the affymetrix genechip u95a/av array, probes were nonspecific, which could cross-hybridize to multiple genes, and probes missed the target transcript sequences. the numbers of nonspecific and mis-targeted probes on the u133a array were comparable, which were and, respectively. these ~20% of problematic probes certainly and substantially compromise the data accuracy, decrease the value of microarray data, and are not acceptable for the studies of molecular network integration. it was also found that some probe sets representing the same genes on affymetrix microarrays could show significant discrepancy because of the non-specific hybridization in most applications, gene expression profiling with microarrays including genechip requires amplification of sample rna, regardless of how much material is available. normally, to μg of rna is required for each assay. however, high-throughput gene expression profiling with superior sensitivity is becoming more and more demanded, and has its wide applications. for example, in breast cancer research, analysis of specimens from microdissection may provide important information about genes involved in different cancer development stages and for understanding the molecular mechanisms underlying cancer development. specimens from fine needle biopsy are also important in diagnostic procedures and in evaluating therapeutic effects. the ability to analyze a large number of genes in single cells may help understand the origin and clonality of cancer development and learn the molecular details involved in different stages of the cell cycle. current methodologies for gene expression profiling in small rna samples, especially those from single cells, are very limited. many of these protocols require multiple enzymatic reactions that may seriously reduce the sensitivity and compromise the specificity. rna preparation in most of applications also involves a number of steps, which is rather lengthy, tedious, and requires highly skilled personnel. to solve the above problems, we have developed a highly specific and sensitive gene expression profiling system. with this system, primers are specially designed to amplify mrna sequences very specifically. probes used for microarray detection are designed only to hybridize to sequences amplified from mrna. in conjunction with the high-throughput multiplex amplification protocol developed in our laboratory lately, a large number of mrna species directly released from very few cells or even single cells can be amplified to a detectable amount without rna isolation. amplified products can then be detected by the single-base extension assay on an oligonucleotide microarray.  experimental system used in the study to establish a cancer gene expression array, a panel of cancer-related genes were selected based on their known functions and/or cancer-associated expression patterns from published literature. all amplicon sequences were subjected to computational screening to ensure their uniqueness. primers and probes were selected according to a series of criteria as specified in materials and methods. most primer pairs amplify sequences in two neighboring exons separated by large introns. the intron lengths ranged from bp to kb with an average of kb and 97% of the introns are longer than bp. initially genes were used as the input for the primer and probe design program. primers and probes were selected for of these genes. the remaining % had either no introns or no suitable sequences for primers and/or probes. fifteen of these remaining genes with important functions in cancer development were included in the panel. primers and probes were designed based on the unique sequences in these genes, and were not required to have introns internally located within the amplified sequences. therefore, a total of genes were included in our multiplex assay. microarray-based single-base extension assay has been used to genotype single nucleotide polymorphisms in our laboratory. in the present study, sbe was adapted for gene expression profiling. to simplify the analysis, all probes were designed to terminate immediately before a'g' base in the templates. in this way, the probes were extended by a single base, dideoxynucleoside triphosphate that was fluorescently labeled. by using one color, the bias associated with different dyes was also eliminated. the detection procedure is schematically illustrated in fig. resulting data have been deposited to the ncbi's gene expression omnibus and are accessible through geo series accession number gse reproducibility of the high-throughput gene expression profiling system to test the reproducibility of our system, gene expression was profiled for three duplicated 100-cell samples from an ovarian cancer cell line, nci/adr-res and two 100-cell samples from a breast cancer cell line, mcf- resulting microarray data are supplied in additional file table summarizes the numbers of gene transcripts detected from different samples. as shown,,, and gene transcripts were detected from the three 100-cell samples of nci/adr-res, respectively. of these transcripts, were detected from all three duplicates. signal intensities for the genes were strongly correlated between the duplicates. fig. 2a shows a scatter plot of two duplicates. of the transcripts detected in all three nci/adr-res 100-cell samples, only,, and transcripts had their signal intensities differing by > fold between each two of these three duplicates. twenty-six transcripts were detected from only one or two of the three samples. the signal intensities for these transcripts were low. only one transcript in one sample had its signal intensity >, indicating that the inconsistence among the duplicates was due to low signals of these transcripts. *adr: nci/adr-res for the two 100-cell samples from mcf- and gene transcripts were detected, respectively, with detected in both. of these transcripts, had signal intensities differing less than two fold. similar to the situation with nci/adr-res samples, all transcripts that were detected in only one sample but not the other had low signal intensities with only nine genes whose signal intensities were > in one of the two samples. because samples prepared from a large number of cells are usually associated with high reliability, we further compared the microarray results of the nci/adr-res 100-cell samples with those from a -cell sample of the same cell line. resulting data also show a high degree of correlation. as shown in table of the gene transcripts detected from all the 100-cell samples were also detected from the -cell sample. sixty-three gene transcripts were detected in at least one of the three 100-cell samples but not in the -cell sample, or vice versa. of these gene transcripts, had signal intensities below in all the three 100-cells. however, the change from to cells did enhance the detection of gene transcripts whose signal intensities were > fold greater in the -cell sample than those in the 100-cell samples. among these transcripts, six had signal intensities in the -cell sample more than fold greater than the average intensities of the corresponding genes in the three 100-cell samples, indicating that using cells may have significantly increased the copy numbers of these transcripts or changed their absence status to presence. these data indicate that our system not only can produce very reliable results even with as few as cells but also is very sensitive to the copy number change for the low-copy-number gene transcripts. sensitivity of the high-throughput gene expression profiling system to further test the sensitivity of our high-throughput gene expression profiling system, single nci/adr-res cell samples were prepared and used for multiplex gene expression assay of the mrna species. microarray results from three of these samples are listed in additional file the numbers of gene transcripts detected from the three single-cell samples were and respectively. of these transcripts, were detected from all single cells. of the were also detected from all non-single-cell samples, indicating a prevalent expression of these genes in most, if not all, cells at relatively high levels. on the other hand, the detection range of gene transcripts from the three single-cell samples was wider compared to the non-single-cell samples. as shown in table transcripts were undetectable in all three single cell samples, a number which is not greater than that for the three 100-cell samples and is comparable to that for all non-single-cell samples. the number of undetectable gene transcripts from all single and non-single cell samples is this number means that from single cells, we not only detected a comparable number of genes, but also detected a new set of 449- = genes that could not be detected with non-single-cell samples of the same cell line. the robustness of gene expression profiling with single-cell samples was also demonstrated by the signal intensities. as described above, most transcripts that were detected from some but not all non-single-cell samples had low signal intensities and very few were >. the scenario with single cells is very different. of the gene transcripts detected from all single cells, were detected in one to three non-single-cell samples but not all four. all but one have signal intensity > in at least one of the three single-cell samples. of the transcripts that were only detected from one or two single-cell samples, had signal intensity >. the strong and robust signal intensities detected from single-cell samples indicate that our system is very sensitive. unlike the gene transcripts detected from all non-single-cell samples which account for more than 95% of gene transcripts detected from each of these samples, the gene transcripts detected from single cells only account for 3%, % and % of the transcripts detected from individual single-cell samples, respectively. pairwise comparison of the results from the single-cell samples yielded correlation coefficients of,, and, respectively, compared with = for the non-single-cell samples. from all single and non-single-cell samples, gene transcripts were detected, of which were detected from some but not all samples. this is in contrast with the scenario of non-single-cell samples from which gene transcripts that were only detected from some but not all samples were a very small portion. furthermore, of these transcripts, were either detected from only single cells or from non-single cell samples. the high degree of concordance among the results from the non-single-cell samples, and the significant differences among those from single cells, and between single cells and non-single-cell samples indicate that most, if not all, of these differences are real. as mentioned above, this is further supported by the robustness of the signal intensities detected from single-cell samples for the gene transcripts that were detected differently between the single cells and non-single-cell samples. it is conceivable that heterogeneity in clonality and/or genetic alterations in the cells of a cell line could be major factors contributing to the differences. in addition, a considerable portion of the cells may be at different cycle stages during which groups of genes are expressed differently. therefore, while gene expression in single cells could differ in various aspects, cells may well represent the entire cell population because, after all, the cell line cells are from the same tissue and the same donor. therefore, genes that are detectable in a cell population may not be expressed or expressed at very low levels in certain single cells. conversely, genes that are detectable in particular single cell samples may not be expressed or expressed at very low levels in the majority of the cell population. differential gene expression in the two cell lines, nci/adr-res and mcf-7 when the gene expression profiles of nci/adr-res were compared with those of mcf- a considerable number of genes were shown to be expressed differentially in these two cell lines. of the gene products, were detected from samples of both cell lines. seventy-five gene transcripts were detected in all nci/adr-res non-single-cell samples, but not in the mcf- samples, and were detected in the opposite way. of the differentially expressed genes, were shown to be expressed with more than 10-fold difference. of the genes, were detected as strongly or relatively strongly expressed in mcf- but weakly or not expressed in nci/adr-res, and were detected in the opposite way. to validate the gene expression data, of these genes, and another gene transcripts detected with various microarray signal intensities different between the samples of the two cell lines were randomly selected and subjected to rt-pcr amplification individually. the amplified products were resolved by gel electrophoresis. the signal intensities of the respective bands were quantified with a gel documentation system. part of results from microarrays and gel assays are shown in fig. note: signal intensities of microarray are averages of those respective non-single cell samples. adr: nci/adr-res. specificity of the high-throughput gene expression system the specificity of our high-throughput gene expression system was demonstrated by the results from different cell line samples and by those from different single cells as described above. to further demonstrate the specificity of our system, human genomic dna samples were amplified with the same multiplex rt-pcr procedure and analyzed by microarray. very few probes were shown to have signals above background, indicating that our system is very specific and can discriminate between the target mrna sequences from their genomic counterparts, and therefore, the unprocessed transcripts. our previous experience also showed that in the absence of specific templates, a few primer sets may amplify non-specific sequences. however, such non-specific amplification may become undetectable in the presence of specific templates because the specific sequences are much stronger in competition. in addition, using specially designed probes also enhanced the specificity. discussion compared with other existing gene expression profiling methods, our approach has the following advantages: highly specific to date, no other high-throughput system has been reported to be highly discriminative of mrna from other related dna and rna sequences. using primers amplifying sequences across intron and probes consisting of sequences in adjacent exons is a critical enhancement to achieve such high specificity. furthermore, all primer, probe and amplicon sequences were subjected to exhaustive searches against the databases of the entire human genome and transcriptome to ensure these sequences are unique. such a step was proven very effective for enhancing the specificity. experimentally, when genomic dna was used as samples, signals were only detected for only or genes out of the genes. based on our previous studies, these signals may become undetectable in the presence of specific sequences which may compete out the nonspecific amplification. highly sensitive we showed previously that our multiplex amplification system could detect > single-copy sequences simultaneously from single haploid sperm cells. the fact that >90% of these sequences are detectable indicates that with our specially designed primers, most, if not all, sequences may be well amplified parallelly with very limited, if any, interaction among the primers. since the primers used for gene profiling are designed in the same way, it is reasonable to believe that most gene transcripts are also amplified parallelly. however, since the copy number of different gene transcripts in the cells varies in a wide range, the outcome of amplification would be different from that using single-copy sequences. when only single-copy sequences are used in multiplex amplification, most, if not all, sequences may reach the detectable amount before the system is saturated. however, when gene transcripts are amplified, whether a transcript reaches a detectable amount before the system is saturated depends on its copy number in the sample, and not all sequences may reach a detectable amount at the end of amplification. this is probably why some sequences were undetectable by microarray but detectable by gel assay. with our system, a total of gene transcripts were detected from three single cells, which is comparable to for the three 100-cell samples and for all non-single-cell samples from the same cell line. the sensitivity of our system is further proved by the facts that results from 100-cell samples are very similar to each other and to those from cells, and that specific gene expression profiles were obtained from different cell lines using as few as cells. the sensitivity of our system is further illustrated by the results that a significant portion of transcripts that could not be detected from the nci/adr-res samples but were detected from the mcf- samples or single cell samples, and vice versa. this also indicates that low microarray intensities for these transcripts were not false negatives, and they were either not present or present in very low abundance in the respective samples. very simple unlike other methods that involve multiple steps and use multiple enzymes, our method allows a large number of gene products amplified by a single rt-pcr step directly from cell lysates without rna extraction. in this way, a large number of samples may be analyzed easily and cost-effectively. our simple experimental procedure is also the basis of the high degree of sensitivity since it avoids complicated mrna extraction and processing procedures before and during amplification, which may cause mrna degradation or loss. very safe for rna samples when working with rna, one has to take extra precaution to prevent mrna from degradation. our method does not need rna extraction. once cells are lysed, rna is directly released to the rt-pcr buffer and used as template immediately. there is almost no chance for rnase to degrade the mrna templates. highly flexible many studies may not need to analyze all genes in the human genome and may often need to focus on different gene groups. therefore, flexibility of the experimental system would be highly desirable. with our computer program, a large number of gene products can be designed into a single multiplex group. genes can be easily organized into different subgroups upon need, and can also be re-grouped at any time without altering the reaction conditions. new gene products can be added to an existing set easily. the capacity of multiplex rt-pcr is another concern for high-throughput gene expression profiling because it not only makes the amplification of a large number of gene products affordable and cost-effective, but also eliminates challenges involved in quality control of rt-pcr for a large number of genes individually. however, the capacity of multiplex amplification was limited by interaction between primers. a previous study reported a screening of expressed genes using multiplex rt-pcr, but was unable to reduce the number of the reaction tubes less than eight. other studies multiplexed up to nine genes with nonspecific rt primers. studies using multiple sets of gene-specific primers in single reactions were also reported, but none of these generated enough products for the analysis of all expressed genes in the samples. in the present study, we report our success with multiplex rt-pcr for mrna species. such a success was based on a combination of several technological developments, including computerized primer design with predicted minimal interaction, a narrow primer tm range, small amplicon sizes, and optimization of amplification conditions based on our previous experience. with our current protocol, it is possible to include two thousand or more gene transcripts in a single multiplex amplification group, and to analyze all human gene transcripts using several multiplexing amplification groups. after pooling amplified products from the multiplexing groups, all genes may be analyzed with a single microarray. with our system, large-scale gene expression profiling becomes highly affordable and cost-effective. if the primers and probes used in the high-throughput analysis are made accessible to the research community through a distribution system, large- and genome-scale gene expression profiling may be even more affordable and cost-effective. a major limitation of our system is the requirement of presence of large introns in genes under study. when the introns are small, discrimination between mrna and closely related dna and rna sequences is still possible by using probes consisting of sequences in the neighboring exons. for genes with no introns, primers and probes can be designed only to discriminate mrna sequences from related pseudogenes and their transcripts but not the corresponding gene sequences. in this case, discrimination between mrnas and their gene sequences is only possible when the mrnas are present abundantly. an extreme and possible application of our highly sensitive gene expression profiling system is the analysis of disseminated tumor cells in cancer research. analysis of individual cells is necessary for understanding the early dissemination of tumor cells. disseminated tumor cells remain in the patient bodies even after complete resection of the primary tumor, and can be obtained by bone marrow aspirates. with our highly sensitive system, genetic signature in these cells may be detected. the resulting information may provide molecular basis for new therapeutic targets. for example, erbb expression has been found to be a therapeutic target for metastatic breast carcinoma. identification of mrna like that of erbb in micrometastatic cells may help develop effective therapeutical approaches to preventing further development of these cells into incurable metastasis. using mrna from a small number of microdissected frozen tissue sections without rna isolation has been demonstrated with a small number of genes. our system should be capable of using both microdissected and biopsy specimens for gene expression analysis on a much larger scale. high-throughput gene expression profiling with single cells is also interesting for most laboratories studying molecular neurophysiology, but has been hampered by the capacity of multiplex pcr. our approach can be used to examine the expression of many genes within individual neurons or other cells. the gene expression profiles can also be correlated to the phenotypes of these cells such as morphological, electrophysiological and pharmacological features to understand the underlying molecular mechanisms.  this report describes a high-throughput gene expression profiling technology, which is simple, highly reproducible, specific and sensitive, and may greatly facilitate gene expression profiling of a small number of or even single cells. it may also be applicable to many applications where the amount of material is limited, and to diagnostic assays that identify the onset of cancer and monitor its progression, remediation or response to treatments. data discussed in this publication have been deposited in the ncbi's gene expression omnibus and are accessible through geo series accession number gse 
rapid progress in the field of gene expression-based molecular network integration has generated strong demand on enhancing the sensitivity and data accuracy of experimental systems. by using specially designed primers, the new system amplifies sequences in neighboring exons separated by big introns so that mrna sequences may be effectively discriminated from other highly related sequences including their genes, unprocessed transcripts, pseudogenes and pseudogene transcripts. to meet the need, a high-throughput gene profiling system of high specificity and sensitivity has been developed. highly reproducible results were obtained from duplicate samples with the same number of cells, and from those with a small number and a large number of cells. the specificity of the system was demonstrated by comparing results from a breast cancer cell line, mcf- and an ovarian cancer cell line, nci/adr-res, and by using genomic dna as starting material. it may also be used for gene expression profiling of very few or single cells.
 rapid progress in the field of gene expression-based molecular network integration has generated strong demand on enhancing the sensitivity and data accuracy of experimental systems. to meet the need, a high-throughput gene profiling system of high specificity and sensitivity has been developed.  by using specially designed primers, the new system amplifies sequences in neighboring exons separated by big introns so that mrna sequences may be effectively discriminated from other highly related sequences including their genes, unprocessed transcripts, pseudogenes and pseudogene transcripts. probes used for microarray detection consist of sequences in the two neighboring exons amplified by the primers. in conjunction with a newly developed high-throughput multiplex amplification system and highly simplified experimental procedures, the system can be used to analyze > mrna species in a single assay. it may also be used for gene expression profiling of very few or single cells. highly reproducible results were obtained from duplicate samples with the same number of cells, and from those with a small number and a large number of cells. the specificity of the system was demonstrated by comparing results from a breast cancer cell line, mcf- and an ovarian cancer cell line, nci/adr-res, and by using genomic dna as starting material.  our approach may greatly facilitate the analysis of combinatorial expression of known genes in many important applications, especially when the amount of rna is limited. 