A Novel Resource for the Study of Genes Expressed in the Adult Human Retina

Abstract

purpose. To reconstruct the transcriptional profile of the human adult retina and the genomic map of the genes expressed in this tissue.

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.

Catalogs of genes expressed in human retina have been published based on 209, 736, 755, and 137 gene signatures. ^{1 2 3 4} Presently, more than 16,000 expressed sequence tags (ESTs; 6300 genes) from human retina cDNA libraries are reported in UniGene, the largest existing database of expressed genes (http://www.ncbi.nlm.nih.gov/UniGene/, release January 14, 2000), thus potentially enabling an in silico analysis ⁵ of the transcriptional pattern of the human retina. 

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. 

Materials and Methods

Data pertaining to four unbiased UniGene cDNA libraries obtained from normal adult retina (Lib.177; Lib.178; Lib.228; and Lib.313), were mined from UniGene by specialized software developed in our laboratory. Each UniGene record corresponds to a UniGene cluster and includes all the available ESTs, genomic clones, and/or complete mRNA pertaining to the corresponding human gene. In addition, gene name and description, function of the corresponding protein, best SwissProt (database of protein sequences) hits, mapping data, and tissue expression are provided. 

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 χ² 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 correction ¹³ 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. 

Results

The retrieval of UniGene entries belonging to the selected cDNA libraries resulted in 4974 individual records, which were included in a catalog available on the Internet (http://telethon.bio.unipd.it/GETProfiles/retina/). In the catalog, 2284 entries corresponded to known human genes and 2690 (54.1%) to EST clusters. More than two thirds of the EST clusters (1958 ESTs) showed no similarity to already known DNA sequences. 

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 (χ² = 70.5, 22 df, P = 6 × 10⁻⁷; Table 1 ). In particular, a highly significant excess of genes was observed for chromosomes 17 (χ² = 25.1, 1 df, P = 5 × 10⁻⁷) and 19 (χ² = 6.8, 1 df, P = 0.0089). 

RetNet (http://www.sph.uth.tmc.edu/Retnet/home.htm) provides a list of cloned and/or mapped genes that cause retinal diseases. So far, 122 diseases have been reported there. We excluded 55 conditions in which the involved gene was already known or for which the disease locus was mapped to a very large interval. For the remaining loci, the correspondence between cytogenetic band boundaries and megabase distances was established, according to the integrated“ gmaps” of LDB (location database). Table 2 reports the list of 53 disease loci, along with information on the number of genes and EST clusters mapped in the corresponding interval. 

Discussion

The source of data in the present work was UniGene, virtually containing all the ESTs sequenced so far from a number of different human tissues and pertaining to more than 90,000 human genes. The correspondence between UniGene entries and genes is generally assumed. 

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 tissue ¹⁰ 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 BodyMap ³ and the different type of source cDNA library ⁴ 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. 

 Supported by Ministero dell’ Università e della Ricerca Scientifica e Tecnologica (60%). Fd’A is a recipient of a fellowship from Telethon Italy.

 Submitted for publication February 28, 2000; revised May 5, 2000; accepted May 22, 2000.

 Commercial relationships policy: N.

Table 1.

 

 

Distribution by Chromosome of Genes Expressed in Adult Human Retina

Table 1.

 

Distribution by Chromosome of Genes Expressed in Adult Human Retina

Chromosome	Human Gene Map ’99	Retinal Genes			χ2
				Observed		Expected
1	3,114	341	326.4	0.7
2	2,257	227	236.5	0.4
3	2,015	173	211.2	6.9
4	1,478	141	154.9	1.2
5	1,529	139	160.2	2.8
6	1,893	167	198.4	5.0
7	1,594	147	167.1	2.4
8	1,206	124	126.4	0.0
9	1,248	113	130.8	2.4
10	1,371	135	143.7	0.5
11	1,755	191	183.9	0.3
12	1,585	187	166.1	2.6
13	703	55	73.7	4.7
14	1,047	128	109.7	3.0
15	1,029	117	107.8	0.8
16	849	98	89.0	0.9
17	1,263	190	132.4	25.1
18	523	55	54.8	0.0
19	1,114	145	116.8	6.8
20	758	92	79.4	2.0
21	305	26	32.0	1.1
22	565	64	59.2	0.4
X	874	97	91.6	0.3
Total	30,075	3,152	3,152.0	70.5

 The number of genes by chromosome reported in the Human Gene Map (HGM) database is listed in the second column. The observed number of genes, the expectation, and the associated χ² are reported, both by single chromosome and for the total. Significant (P < 0.002) χ² values are indicated in bold.

Table 2.

 

 

List of Gene Orphan Retinal Disease with the Associated Mapping Interval and the Corresponding Gene Content

Table 2.

 

List of Gene Orphan Retinal Disease with the Associated Mapping Interval and the Corresponding Gene Content

Disease	OMIM	Cytogenetic Localization	Interval (Mb)	Candidate Genes	Candidate EST Clusters	Total
RP18	601414	1q13-q23	145.8–180.0	36	19	55
ARMD1	603075	1q25-q31	189.2–211.8	19	8	27
AXPC1		1q31-q32	201.9–226.1	15	7	22
CRB1, RP12	600105 604210 268030	1q31-q32.1	201.9–219.1	15	7	22
ALMS1, ALSS	203800	2p14-p13	65.9–76.8	15	16	31
RP28		2p11-p16	52.6–98.9	37	9	46
RP26		2q31-q33	174.7–216.3	19	25	44
BBS5	603650	2q31	175.1–188.4	7	10	17
USH2B	276905 600971	3p24.2-p23	24.2–32.4	3	6	9
BBS3	600151	3p13-p12	82.1–94.8	2	1	3
USH3A	276902	3q21-q25	134.8–177.0	28	23	51
OPA1	165500	3q28-q29	203.5–214.0	6	5	11
WGN1	143200	5q13-q14	76.5–100.8	7	9	16
RP25	602772	6cen-q15	65.0–95.1	9	10	19
STGD3	600110	6q11-q15	65.0–95.1	9	10	19
MCDR1, PBCRA	136550 600790	6q14-q16.2	80.5–103.3	3	3	6
RCD1	180020	6q25-q26	160.6–176.0	2	4	6
CYMD	153880	7p21-p15	19.9–34.2	11	7	18
RP9	180104	7p15-p13	21.8–49.9	11	8	19
RP10	180105	7q31.3	125.0–134.7	6	5	11
ACHM3	262300	8q21-q22	83.6–113.1	18	9	27
NCRNA	221900	10p21	56.7–69.7	4	6	10
AA	108985	11p15	0–23.8	23	16	39
USH1C	276904	11p15.1	18.9–23.8	2	1	3
BBS1	209901	11q13	68.9–89.3	17	6	23
VRNI	193235	11q13	68.9–89.3	17	6	23
EVRI, FEVR	133780	11q13-q23	68.9–129.8	37	35	72
STGD2	153900	13q34	110.9–114.0	3	7	10
LCA3		14q24	68.7–81.1	11	9	20
USH1A, USH1	276900	14q32	91.0–109.0	13	6	19
RP rec.		15q22	63.5–76.1	9	7	16
BBS4	600374	15q22.3-q23	68.2–77.9	4	5	9
MRST	602685	15q24	78.4–80.8	1	1	2
RP22	602594	16p12.1-p12.3	27.5–30.4	6	5	11
BBS2	209900	16q21	64.9–70.4	3	6	9
CORD5, RCD2	600977 601251	17p13-p12	0–16.6	15	12	27
CACD	215500	17p13	0–12.7	15	11	26
RP13	600059	17p13.3	0–7.0	7	4	11
CORD4		17q	28.0–92.0	70	57	127
RP17	600852	17q22	56.9–60.8	7	4	11
OPA4		18q12.2-q12.3	28.8–36.7	1		1
CORD1	600624	18q21.1-q21.3	46.9–65.4	9	7	16
OPA3, MGA3	258501	19q13.2-q13.3	47.1–58.8	30	23	53
RP11	600138	19q13.4	58.9–67.0	5	11	16
USH1E	602097	21q21	19.6–32.3	4		4
RP23		Xp22	0–27.8	11	1	12
AIED, OA2	300600	Xp11.4-p11.3	37.9–46.5	11	5	16
CNB4	300071	Xp11.4-p11.3	37.9–46.5	11	5	16
CSNB1	310500	Xp11.4-p11.3	37.9–46.5	11	5	16
OPA2	311050	Xp11.4-p11.2	37.9–56.8	15	5	20
COD1	304020	Xp11.4	37.9–43.1	11	5	16
RP24	300155	Xq26-q27	130.8–151.2	10	3	13

 Each disease is identified by symbol and/or OMIM number. The localization is given as cytogenetic and in megabase intervals. For each locus the number of colocalizing genes and/or of EST clusters, suggested as putative candidate genes, are shown. OMIM, Online Mendelian Inheritance in Man.