Cho et al. were the first who determined that clustered genes have the same expression levels. They identified transcripts that show cell-cycle dependent periodicity. Of those genes 25% was located in close proximity to other genes which were transcript in the same cell cycle. Cohen et al. (2000) also identified clusters of co-expressed genes.
Caron et al. (2001) made a human transcriptome map of 12 different tissues (cancer cells) and concluded that genes are not randomly distributed across the chromosomes. Instead, genes tend to cluster in groups of sometimes 39 genes in close proximity. Clusters were not only gene dense. They identified 27 clusters of genes with very high expression levels and called them RIDGEs. A common RIDGE counts 6 to 30 genes per centiray. However, there were great exceptions, 40 to 50% of the RIDGEs were not that gene dense; just like in yeast these RIDGEs were located in the telomere regions.
Lercher et al. (2002) pointed to some weaknesses in Caron's approach. Clusters of genes in close proximity and high transcription levels can easily been generated by tandem duplicates. Genes can generate duplicates of themselves which are incorporated in their neighborhood. These duplicates can either became a functional part of the pathway of their parent gene, or (because they are no longer favored by natural selection) gain deleterious mutations and turn into pseudogenes. Because these duplicates are false positives in the search for gene clusters they have to be excluded. Lercher excluded neighboring genes with high resemblance to each other, after that he searched with a sliding window for regions with 15 neighboring genes.
It was clear that gene dense regions existed. There was a striking correlation between gene density and a high CG content. Some clusters indeed had high expression levels. But most of the highly expressed regions consisted of housekeeping genes; genes that are highly expressed in all tissues because they code for basal mechanisms. Only a minority of the clusters contained genes that were restricted to specific tissues.
Versteeg et al. (2003) tried, with a better human genome map and better SAGE , to determine the characteristics of RIDGEs more specific. Overlapping genes were treated as one gene, and genes without introns were rejected as pseudogenes. They determined that RIDGEs are very gene dense, have a high gene expression, short introns, high SINE repeat density and low LINE repeat density. Clusters containing genes with very low transcription levels had characteristics that were the opposite of RIDGEs, therefore those clusters were called antiridges. LINE repeats are junk DNA which contains a cleavage site of endonuclease (TTTTA). Their scarcity in RIDGEs can be explained by the fact that natural selection favors the scarcity of LINE repeats in ORFs because their endonuclease sites can cause deleterious mutation to the genes. Why SINE repeats are abundant is not yet understood. 
Versteeg et al. also concluded that, contrary to Lerchers analysis, the transcription levels of many genes in RIDGEs (for example a cluster on chromosome 9) can vary strongly between different tissues. Lee et al. (2003) analyzed the trend of gene clustering between different species. They compared Saccharomyces cerevisiae, Homo sapiens, Caenorhabditis elegans, Arabidopsis thaliana and Drosophila melanogaster, and found a degree of clustering, as fraction of genes in loose clusters, of respectively (37%), (50%), (74%), (52%) and (68%). They concluded that pathways of which the genes are clusters across many species are rare. They found seven universally clustered pathways: glycolysis, aminoacyl-tRNA biosynthesis, ATP synthase, DNA polymerase, hexachlorocyclohexane degradation, cyanoamino acid metabolism, and photosynthesis (ATP synthesis in non plant species). Not surprisingly these are basic cellular pathways.
Lee et al. used very diverse groups of animals. Within these groups clustering is conserved, for example the clustering motifs of Homo sapiens and Mus musculus are more or less the same.
Spellman and Rubin (2002) made a transcriptome map of Drosophila. Of all assayed genes 20% was clustered. Clusters consisted of 10 to 30 genes over a group size of about 100 kilobases. The members of the clusters were not functionally related and the location of clusters didn't correlate with know chromatin structures.
This study also showed that within clusters the expression levels of on average 15 genes was much the same across the many experimental conditions which were used. These similarities were so striking that the authors reasoned that the genes in the clusters are not individually regulated by their personal promoter but that changes in the chromatin structure were involved. A similar co-regulation pattern was published in the same year by Roy et al. (2002) in C. elegans.
Many genes which are grouped into clusters show the same expression profiles in human invasive ductal breast carcinomas. Roughly 20% of the genes show a correlation with their neighbors. Clusters of co-expressed genes were divided by regions with less correlation between genes. These clusters could cover an entire chromosome arm.
Contrary to previous discussed reports Johnidis et al. (2005) have discovered that (at least some) genes within clusters are not co-regulated. Aire is a transcription factor which has an up- and down-regulation effect on various genes. It functions in negative selection of thymocytes, which responds to the organisms own epitopes, by medullary cells.
The genes that were controlled by aire clustered. 53 of the genes most activated by aire had an aire-activated neighbor within 200 Kb or less, and 32 of the genes most repressed by aire had an aire-repressed neighbor within 200 Kb; this is less than expected by change. They did the same screening for the transcriptional regulator CIITA.
These transcription regulators didnt have the same effect on al genes in the same cluster. Genes that were activated and repressed or unaffected were sometimes present in the same cluster. In this case, its impossible that aire-regulated genes were clustered because they were all co-regulated.
So it is not very clear if domains are co-regulated or not. A very effective way to test this would be by insert synthetic genes into RIDGEs, antiridges and/or random places in the genome and determine their expression. Those expression levels must be compared to each other. Gierman et al. (2007) were the first who proved co-regulation using this approach. As an insertion construct they used a fluorescing GFP gene driven by the ubiquitously expressed human phosphoglycerate kinase (PGK) promoter. They integrated this construct in 90 different positions in the genome of human HEK293 cells. They found that the expression of the construct in Ridges was indeed higher than those inserted in antiridges (while all constructs have the same promoter).
They investigated if these differences in expressions were due to genes in the direct neighborhood of the constructs or by the domain as a whole. They found that constructs next to highly expressed genes were slightly more expressed than others. But when to enlarged the window size to the surrounding 49 genes (domain level) they saw that constructs located in domains with an overall high expression had a more than 2-fold higher expression then those located in domains with a low expression level. 
They also checked if the construct was expressed at similar levels as neighboring genes, and if that tight co-expression was present solely within RIDGEs. They found that the expressions were highly correlated within RIDGEs, and almost absent near the end and outside the RIDGEs. 
Previous observations and the research of Gierman et al. proved that the activity of a domain has great impact on the expression of the genes located in it. And the genes within a RIDGE are co-expressed. However the constructs used by Gierman et al. were regulated by al full-time active promoter. The genes of the research of Johnidis et al. were dependent of the present of the aire transcription factor. The strange expression of the aire regulated genes could partly have been caused by differences in expression and conformation of the aire transcription factor itself.