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From the Department of Biology, University of Padua, Italy.
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Abstract |
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 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
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METHODS. Original software was used for the retrieval and analysis of records from UniGene (http://www.ncbi.nlm.nih.gov/UniGene/) pertaining to selected cDNA libraries from adult human retina.
RESULTS. The 4974 genes reported so far to be expressed in retina were included in a catalog available on the Internet. For each entry, an estimation of the level of expression of the corresponding gene in the retina was provided. A high-resolution genomic map of the human retina was built up by inclusion of 3152 genes showing a precise and unique map assignment. The correspondence was established between 53 gene–orphan retinal diseases and clusters of genes expressed in the retina.
CONCLUSIONS. The in silico reconstruction of the transcriptional profile of the adult human retina provides preliminary information on the pattern of genomic expression in this tissue. The chromosomal location of many retinal genes, combined with their expression data, should speed up the identification of genes involved in retinal diseases.
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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We report on an attempt to computationally reconstruct the transcriptional profile of the adult human retina and to produce the first on-line high-resolution genomic map of genes expressed in this tissue.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Records were collected from UniGene by the software and merged in a single data set, removing redundancy. Different fields of each record were analyzed, and entries were sorted out according to given criteria (e.g., mapping information or EST content). Details of the process have been described elsewhere.6
The basic assumption underlying the reconstruction of the transcriptional profile of the retina was that the larger the number of retinal ESTs reported per entry, the more active the corresponding gene should be in the tissue. Thus, to estimate the abundance of each transcript in the retinal mRNA population,1 6 7 8 9 10 we used the number of ESTs reported for each given entry. The relative contribution of a given gene to the retinal transcriptional activity (expression level) was obtained by the ratio between the number of ESTs corresponding to that gene and the total number of ESTs corresponding to all the genes included in the data set. The expression of each retinal gene in other human tissues was evaluated by recording the number and the type of nonretinal ESTs reported for that gene.
The genomic map of genes expressed in human retina was constructed by collecting the chromosomal localization of all the mapped UniGene clusters included in the retina dataset. Genes showing multiple map locations were excluded. The detailed procedure for building the transcript map has been reported elsewhere.11
To calculate the expected distribution of genes by chromosome, we used
the Human Gene Map database,12
which includes more than
30,000 human genes. The statistical significance of the deviation from
the expectation was tested by a 
2
goodness-of-fit test with 22 and 1 df, when analyzing the
genomic distribution of genes and the deviation of a given chromosome,
respectively. The level of significance was set to 0.002, according to
the Bonferroni correction13
for multiple tests.
The RETNet Web site (release of January 25, 2000) was searched for accurately mapped gene–orphan retinal diseases. The megabase interval corresponding to the cytogenetic localization of each disease was established according to the LDB database.14 UniGene clusters corresponding to genes expressed in retina and mapped to the locus of a retinal disease were then identified.
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Results |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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The catalog entries were classified, according to the level of expression of the corresponding genes: 443 corresponded to highly expressed genes (more than 0.05% of the detected transcriptional activity, more than eight reported ESTs per entry), 1162 to moderately expressed genes (0.04%–0.015%), and 3369 to weakly expressed genes (less than 0.015%).
Approximately 89% of the retinal genes were found to be expressed in at least one additional tissue, and approximately 74% in more than four additional tissues. Of note, approximately 70% of the retinal genes were found to be expressed also in adult brain.
Taking together the 536 putative retina-specific genes and the 443 genes highly expressed in retina, a set of 979 transcripts may be obtained that characterizes the adult human retina.
More than 60% of the genes included in the catalog (3152 genes) showed a precise and unique map assignment and were used to build a comprehensive high-resolution genomic transcript map of human retina also available on the Internet (http://telethon.bio.unipd.it/GETMaps/retina/). The confidence interval of each gene localization resulted less than 2 megabases (Mb) for 1126 entries and less than 3 Mb for 1422 entries.
The observed distribution of retinal genes by chromosome significantly
deviated from the expectation (2 = 70.5, 22
df, P = 6 x 10-7;
Table 1
). In particular, a highly significant excess of genes was
observed for chromosomes 17 (2 = 25.1, 1
df, P = 5 x 10-7) and 19
(2 = 6.8, 1 df, P =
0.0089).
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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The quality of the data analyzed and produced by the present study is partially dependent on the quality of UniGene data. Although UniGene is the less redundant among the gene indexing databases,15 some UniGene clusters can include sequences of chimeric clones belonging to different genes, and very large genes can be represented in UniGene by two or more clusters. For this reason, before constructing the genomic map of transcripts, we decided to discard all the UniGene clusters showing multiple chromosomal locations.
The complementary situation (different UniGene clusters for a unique human gene) is also possible, especially when dealing with different UniGene clusters showing no similarity with any known sequence and mapped to the same position. However, this situation is expected to be rather rare.
The total number of genes expressed in retina is probably between 10,000 and 30,000.2 Presumably, fewer than 70,000 genes are active in a differentiated tissue. Therefore, the sample of 4974 individual transcripts considered by the present study corresponds, at worst, to approximately 7% of the presumed total number of genes expressed in retina, an adequate size for statistical inference.
The computational approach to the analysis of transcriptional profiles is based on the assumption that the level of activity of a given gene may be inferred from the information regarding the number of the corresponding ESTs. The impossibility to detect differences in gene expression resulting from posttranscriptional regulatory processes is a strong limitation of this approach, but the same bias is shared by all the present methods for estimating individual gene expression on a large scale.
EST sequencing, from which the in silico approach is derived, is intrinsically inadequate to identify truly rare genes. However, when the sample size is sufficiently large, a fairly good quantitative estimation of the transcription level of highly or moderately expressed genes is possible.16 On the contrary, quantitative hybridization on high-density cDNA array fails to detect 80% of the transcripts identified in a given tissue by EST sequencing.17
The transcriptional profile of the retina is characterized by a low number of highly expressed genes, accounting for less than 10% of the total number of genes, but for approximately 50% of the detected transcriptional activity. The percentage of tissue-specific genes (9.8%) is higher than previously reported in human adipose tissue10 and five times higher than observed in skeletal muscle.6 The difference could be ascribed to the high specialization of the retinal tissue and/or to the relative absence of contaminant tissues in the sample from which the cDNA libraries were prepared. The subsample including highly expressed genes and genes found exclusively in retina could be profitably used for monitoring major changes in the transcriptional profile, after physiological or pathologic modifications.
Data on the transcriptional profile of the human retina have been reported in two independent studies. However, the small size of the sample reported in BodyMap3 and the different type of source cDNA library4 make it impossible to perform a statistical comparison with the present data.
More than 60% of genes included in the catalog showed a precise and unique map assignment. The distribution of genes by chromosome significantly differed from the expectation. In a preliminary study, we observed a peculiar concentration of retinal genes on chromosome 17.18 This finding is confirmed by the present investigation, based on a much larger number of map entries, which suggests also a concentration of retinal genes on chromosome 19. The short arm of chromosome 17 is known to be a hot spot to which several phenotypically distinct retinal disorders have been mapped.19 The most recent version of the Human Gene Map (HGM)13 show that chromosome 17 is richer in genes than expected under the hypothesis of a constant gene density along the human genome. In the present study the expected distribution of genes by chromosome was calculated according to HGM data. Therefore, the hypothesis of a particularly high concentration of retinal genes on chromosomes 17 and 19 is even stronger. A selective concentration of genes in specific chromosomes was observed also in human skeletal muscle.11 18
Chromosomal maps showing the location of genes expressed in retina represent a novel and important resource for positional cloning of genes involved in retinal disorders. Most mapping information obtained from UniGene resulted from radiation hybrids (RH) mapping, which is, at present, the most precise method of gene mapping, if we exclude the direct localization on the genomic DNA sequence. The presence of several genes mapped to the same megabase distance from the p-telomere probably reflects the actual concentration of genes in short chromosomal segments. However, the width of the interval corresponding to a single point of the present map is variable, because the physical distance between the two flanking markers may be different. In spite of this, the present genomic map of retinal genes is, at the moment, the most precise representation of their cluster formations along each human chromosome. Moreover, the resolution of the map is adequate to detect which group of genes corresponds to a given interval to which a human disease was mapped by linkage studies.
The in silico reconstruction of the transcriptional profile of the adult human retina and the building of the genomic map of genes expressed in this tissue provides for the first time a resource in which functional and structural genomics of retina are integrated on a large scale. It is hoped that this resource will speed up the identification of genes involved in retinal disorders and will enable innovative approaches to the study of retinal development, physiology, and diseases.
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Footnotes |
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Submitted for publication February 28, 2000; revised May 5, 2000; accepted May 22, 2000.
Commercial relationships policy: N.
Corresponding author: Gian Antonio Danieli, Department of Biology, University of Padua, via U. Bassi 58B, 35131 Padova, Italy. danieli{at}bio.unipd.it
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References |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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