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Gene expression in chromosomal Ridge domains : influence on transcription,
mRNA stability, codon usage, and evolution
Gierman, H.J.
Publication date
2010
Link to publication
Citation for published version (APA):
Gierman, H. J. (2010). Gene expression in chromosomal Ridge domains : influence on
transcription, mRNA stability, codon usage, and evolution.
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Introduction: Gene Regulation by
Chromosomal Domains
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Introduction: Gene Regulation by Chromosomal Domains
Hinco J. Gierman and Rogier Versteeg
Department of Human Genetics, Academic Medical Center, University of Amsterdam, P.O. Box 22700, 1100 DE Amsterdam, the Netherlands.
Published in part as: Clustering of highly expressed genes in the human genome. Encyclopedia of Life Sciences. 2008 Apr;30:a0005931 John Wiley & Sons, Ltd: Chichester.
1.1 Introduction
Gene expression is the most fundamental of all biological processes and can be viewed as the sum of mechanisms that transcribe DNA into RNA, into protein. As important as the function of a protein, is the place, the time and the quantity of expression. The cellular mechanisms that underlie these three determinants are what make up ‘the regulation of gene expression’. Together, they control in which cells (the place), at what point during development (the time) and how many molecules (the quantity) of any protein is produced. This control ensures the correct expression of all genes during development. When the regulation of these genes is disturbed, e.g. by mutations in the DNA, diseases like cancer can arise.
Identifying and understanding the mechanisms involved in gene regulation is essential for understanding how cancer arises. Many cellular mechanisms are known that regulate the expression of individual genes. In this thesis we asked, whether in addition to these well-known mechanisms, genes are also regulated at the level of chromosomal domains called ‘Ridges’ (abbreviated from ‘Regions of IncreaseD Gene Expression’). In this thesis, we show that Ridges increase transcription by a domain-wide mechanism, that Ridge genes have an increased messenger RNA (mRNA) stability and finally, that Ridge messenger RNA (mRNA) have codons that facilitate highly efficient translation. We propose that this system provides a highway enabling an expansion of the protein expression range in the genome and we discuss the implications of the Ridge system for the evolution of the human genome.
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1.2 The Human Transcriptome Map
The expression of genes is regulated in the first instance by transcription factor complexes. These complexes bind to regulatory sequences, usually in the promoter region of a gene. The concentration and composition of these complexes determine the amount of mRNA that is produced. This system of individual gene regulation in principle allows genes to be randomly positioned throughout a genome, and this was long assumed to be the case for most genes. However, if clustering of genes with similar activity or related function occurs, this predicts that chromosomal regions would either show differences in average activity, or co-expression under specific conditions or in certain tissues.
With the emergence of high-throughput screening of mRNA levels (within this context commonly referred to as expression profiling), it became possible to analyze the expression levels of thousands of different genes at once. One of the techniques used to this end was Serial Analysis of Gene Expression (SAGE) (Velculescu 1995). In short, concatemers of 3’ fragments of mRNA molecules are cloned into bacterial plasmids. Sequencing of 50,000 to 100,000 of these 3’ tags yielded a quantitative expression profile of a cell or tissue. In the same year, the first complete genomic sequence of a free living organism was published: Haemophilus influenzae Rd. (Fleischmann 1995). The convergence of these two techniques, expression profiling and whole genome sequencing, allowed mapping the expression of every gene onto its chromosomal position. These so-called ‘transcriptome maps’ allowed to test whether genes of similar activity or function show clustering. This was first done for the budding yeast Saccharomyces cerevisiae (Velculescu 1997). The study showed some clustering of co-expressed genes, but found no clusters of high or low expression on any chromosome. A second study looked deeper into the clustering of these co-expressed genes in yeast and concluded that yeast possesses small chromosomal domains of gene expression (Cohen 2000). They found that clusters of 2–3 genes, adjacent and non-adjacent, showed co-expression.
The sequencing of the human genome had been underway for a decade by then, and was nearing its completion. Our lab used an early radiation hybrid map of the human genome (Deloukas 1998) to map expression data from SAGE libraries (Caron 2001). The resulting Human Transcriptome Map (HTM) revealed an unexpected organization in the human genome: Highly expressed genes were found to cluster in so-called Regions of IncreaseD Gene Expression (Ridges). A more detailed mapping using the first draft human genome sequence (Lander 2001), revealed that poorly expressed genes also clustered in separate regions termed anti-Ridges (Versteeg 2003). Figure 1 shows a transcriptome map of the q-arm of chromosome 1. Each black vertical bar represents a gene. The height of each bar indicates the activity of the domain surrounding that gene. To measure the activity of a domain, the median expression over a window of genes is calculated. A window encompasses the gene itself and an equal number of adjacent genes on both sides. The domain activity was calculated for all genes on each chromosome, by sliding the window one gene at a time. In Figure 1, the typical window size of 49 genes was used. Comparable results are obtained for window sizes ranging from 19 to 59 genes. Figure 1 shows that a
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number of domains have a high expression: These are Ridges (shaded red). Equally so, the anti-Ridges (shaded blue) clearly have a lower overall expression.
On average, Ridges and anti-Ridges consist of 80–90 genes, but these domains can range from 30 to 500 genes in size. There are about 30 Ridges and 30 anti-Ridges in the human genome. Although the exact number depends on the window size and statistical threshold used, almost every chromosome has at least one Ridge or anti-Ridge. Roughly 20–25% of all human genes reside within a Ridge and 10– 15% are in an anti-Ridge. The bulk of the human genome however, is made up of domains of intermediate gene expression harboring the remaining 60–70% of genes. Chromosomes are thus an assemblage of different expression domains that form a higher-order organization of the human genome.
Many other studies have investigated gene clustering. For example, in mice domains exist with dense or sparse transcription (Carninci 2005). However, most studies have focused on chromosomal clustering of co-expressed genes. This has been found to occur in various organisms like S. cerevisiae (Velculescu 1997; Cohen 2000; Burhans 2006), Drosophila (Spellman 2002), C. elegans (Roy 2002) and Arabidopsis (Williams 2004; Ren 2005), mice (Mijalski 2005) and humans (Bortoluzzi 1998; Vogel 2005) (see also Lee 2003; Hurst 2004). These clusters are conserved during evolution, indicating the importance of the chromosomal organization of these genes (Singer 2005; Sémon 2006).
1.3 Gene Expression in Ridges: Housekeeping and Tissue-specific Genes
Ridges are enriched for highly expressed genes, but medium and poorly expressed genes populate Ridges as well. Also, many highly expressed genes are found outside Ridges. Genes can be categorized into tissue-specific and ubiquitously expressed genes. Genes that are expressed throughout all tissues are called housekeeping
Figure 1. Physically mapped transcriptome profile of the q-arm of human chromosome 1. Giemsa banding
is illustrated below the transcriptome map (centromere/heterochromatic region is green and marked ‘cen’). Ridges are shaded red and marked with an ‘R’, anti-Ridges are shaded blue and marked ‘AR’. Black vertical bars represent genes and their height indicates domain activity for a moving median window of 49 genes (MM49) in 133 pooled SAGE libraries from different tissues. Below is the chromosomal position in megabases (UCSC Genome Build HG18). Illustration adapted from Gierman et al. (Figure 1; Gierman 2007).
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genes. In general, Ridge genes are broadly expressed over different tissue types (Lercher 2002). Lercher et al. proposed that Ridges are formed by clustering of housekeeping genes (Lercher 2002). For the calculation of Ridges, the average expression of each gene in a collection of SAGE libraries of different tissue types is used (Versteeg 2003). This means that genes that are ubiquitously highly expressed will have the highest average expression. Conversely, genes that are highly expressed in just one or a few tissues will have high tissue-specific expression but a low average expression. This raises the question whether the only difference between Ridge genes and other genes is the broad expression, or whether Ridge genes are also more highly expressed. Figure 2A shows that also the maximal tissue-specific expression of genes follows the pattern of Ridges and anti-Ridges (Versteeg 2003). Ridge genes are thus both more highly and more broadly expressed. This probably reflects that many housekeeping genes are both broadly and highly expressed. Nevertheless, genes in Ridges are subject to tissue-specific regulation. Figure 2B shows the variation in individual gene expression of genes on chromosome 9 over 62 different SAGE libraries from different tissues. Ridge domains thus appear to be favorable for genes with a high and/or ubiquitous expression, but equally allow for tissue-specific regulation of genes.
1.4 Ridges and anti-Ridges Differ in Organization, GC Content and Chromatin
Detailed analysis of the Human Transcriptome Map showed that many physical parameters of the genome correlate with Ridges (Versteeg 2003). Many of these correlations confirmed earlier observations (Bernardi 1985a). The clearest correlation is with gene density and can be observed in Figure 1: As each vertical black bar marks the position of a single gene, the density of bars directly indicates the gene density. Figure 3 shows this more clearly with a direct comparison of gene density and gene expression (panels E and F). Ridges also have shorter genes and shorter introns (panel D) and most repeats (e.g. LINEs) are less frequent in Ridges, with the exception of SINEs which are more abundant (panels A and B). An important genomic feature is the genomic GC content (i.e. the ratio of G/C versus A/T bases), which is also higher in Ridges (panel C).
The genome of warm-blooded vertebrates (i.e. birds and mammals), display a strong variation in the GC content of large chromosomal regions, also known as isochores (Bernardi 1985a; Costantini 2006). These regions can be hundreds of kilobases long and in humans their GC content varies from 30% to 60%. Isochores are predominantly the result of the accumulation of changes caused by a mutation bias (Duret 2009). The mutation bias most likely arose to compensate for the hypermutability of methylated cytosines, which spontaneously deaminate to thymines. C/G pairs thus frequently mutate into T/G mispairs, and the base excision repair system has become strongly biased towards repairing G/T mispairs in favor of the guanine to compensate for this (Brown 1987; Brown 1988; Brown 1989). This repair system thus increases the GC content of loci where T/G or A/G mispairs originate from A/C pairs. Conversely, despite the bias in repair, cytosines that are methylated will disappear over time. This is because as the cytosine is continuously mutated, eventually the T/G mispair will be repaired in favor of the thymine, creating a T/A pair instead of the original
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G/C. This repair occurs during meiotic recombination producing the so-called ‘biased gene conversion’ which has shaped isochores (Filipski 1987; Sueoka 1988; Wolfe 1989; Press 2006; Duret 2008 and reviewed by Duret 2009). This mutational bias affects the GC content of all sequences in isochores, including the coding sequences of genes (Bernardi 1985b; Cruveiller 2004). Recombination is thus thought to drive the formation of isochores, and the non-uniform distribution of GC content is likely formed to some extent by the different rates of recombination throughout the genome (Fullerton 2001; Kong 2002; Montoya-Burgos 2003; Meunier 2004). Analysis of the mouse Fxy gene has shown that GC content can increase rapidly. For the third codon position (i.e. the wobble base for which a base pair change often encodes the same amino acid), GC content increased from 50% to 73% in 3 million years (Perry
Figure 2. Transcriptome maps of chromosome 9. (A) Moving median of the height of average expression
(blue) and tissue-specific expression (red) per 100,000 tags. Expression values were determined in a collection of 57 SAGE libraries of 50,000 tags or more. Blue and red bars indicate anti-Ridge and Ridge. Genes are sequentially ordered according to chromosomal position, but not physically spaced (window size 49 genes). (B) Individual gene expression over 62 SAGE libraries of 50,000 or more tags (horizontal lines). Each vertical line is a gene. The levels of expression are given by a color code, ranging from zero (blue) to 25 (purple) or more tags/100,000 transcript tags in a library. Illustrations adapted from Figure 5 and 1G Versteeg et al. (Versteeg 2003).
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1999). This is an evolutionary short period of time: humans and their closest living relative the chimpanzee, diverged 5–7 million years ago (Patterson 2006).
There is a straightforward linear correlation between the GC content and gene expression of e.g. a window size of 49 genes (R2 = 0.51, P < 10-99; Versteeg 2003,
data not shown). The difference in GC content between Ridges and anti-Ridges, applies to all of the genomic sequence, including the coding sequences of genes. The GC content of most anti-Ridge mRNA lies between 40% and 50%, whilst Ridge mRNA typically have a GC content of 50% to 65% (see also chapter 3 and 4). But not only the composition of DNA is different in Ridges. DNA is packaged into chromatin, which consists of histone proteins. These histones can be modified on a multitude of residues, mostly by phosphorylation, methylation and acetylation. These modifications influence transcription in two ways: directly, by binding transcriptional complexes and indirectly, by changing the chromatin structure. Recent studies using chromatin immunoprecipitation (ChIP) of histone modifications show that Ridges are associated with active histone marks associated with transcription (Bernstein 2005; Roh 2005; Barski 2007). Importantly, Ridges were also found to have an open chromatin structure throughout their entire domain, even where genes in Ridges are not expressed (Gilbert 2004; Goetze 2007). Open chromatin facilitates gene expression and could be a consequence of the increased transcription in Ridges. However, the broad open chromatin structure of Ridges might also contribute to the expression of genes in Ridges (Sproul 2005).
1.5 Nuclear Organization and Ridges
Just as genes are not randomly distributed over the genome, the chromatin fiber is not randomly packaged into the nucleus. Many studies have shown that active genes usually reside more towards the nuclear center than inactive genes (reviewed by Cremer 2001; Lanctôt 2007). It has been suggested that the nuclear localization of chromosomal domains contributes to the regulation of their expression. For example, it has been shown for Drosophila that hundreds of inactive genes cluster and interact with the lamina at the nuclear periphery (Pickersgill 2006). These genes are characterized by inactive histone marks, which could be caused by the histone deacetylase activity present at the nuclear lamina (Somech 2005). However, induction of gene expression disrupts the interaction with the lamina, suggesting that localization at the nuclear periphery is a consequence of low gene expression rather than a cause (Pickersgill 2006). Similarly, induction of gene expression in the human major histocompatibility complex (Volpi 2000), CFTR locus (Zink 2004), or Hox cluster (Morey 2009), was also found to drive nuclear position. Transcription itself might not be directly responsible for the looping and repositioning of chromosomal regions. Rather, the increase in histone acetylation that occurs upon induction of transcription, might contribute to the behavior of the chromatin fiber (Tumbar 1999; Belmont 1999).
In humans, Lamina Associated Domains (LADs) with low overall gene expression were also discovered and reported to cover 40% of the genome (Guelen 2008;
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Wen 2009). LADs coincide with gene poor regions (Guelen 2008), and there is a good correspondence between LADs and anti-Ridges (data not shown). LADs are also enriched for histone marks associated with heterochromatin (Guelen 2008). Domains of heterochromatin have been proposed to act as organizing centers that might help position active euchromatic domains within the nuclear center (van Driel 2004).
Goetze et al. showed for six different cell lines that a specific Ridge on chromosome 11 was always more in the nuclear interior than an anti-Ridge on the same chromosome. Although there were clear differences in expression levels for individual genes in the
Figure 3. Profiles showing gene expression and physical parameters for chromosome 9: (A) Inverse LINE
density, (B) SINE density, (C) GC content, (D) inverse intron length, (E) gene density (F), average gene expression. All profiles are moving medians over the parameter values per gene for a window size 49. Bars indicate anti-Ridge (AR) and Ridge (R). Genes are sequentially ordered according to chromosomal position, but not physically spaced (window size 49 genes). Illustration adapted from Figure 1 Versteeg et al. (Versteeg 2003).
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Ridge, the overall expression level of the Ridge was similar in all six cell lines. This was also the case for the anti-Ridge. These results are in agreement with the idea that the overall activity of a chromosomal domain drives nuclear organization. This might explain the apparent paradox of why an inactive gene (residing in a Ridge), can be located in the nuclear interior.
1.6 Domain-wide Regulation of Chromosomal Domains in Cancer
Ridges and anti-Ridges in general have a consistent activity throughout different tissue types. There are however, a number of smaller specialized clusters of related genes in the human genome, such as the Hox, globin and histone gene clusters. These groups of genes are known to be regulated together in a coordinated fashion. Recently, a number of studies have shown that small clusters of unrelated genes can also show co-expression throughout different tissues. Most notably a study on bladder carcinomas showed that clusters of up to 12 unrelated genes have a correlated expression pattern in a subset of bladder carcinomas (Stransky 2006). The authors demonstrate for one of these clusters that the genes are silenced by a domain-wide increase in histone methylation. The spreading of histone marks is a well known mechanism, but until now has only been implicated in particular processes, such as heterochromatin formation and the inactivation of the X chromosome. Although these clusters are smaller than Ridges, these findings show that epigenetic regulation of gene clusters might play a more important role in the genome than previously thought.
1.7 Specific Aims of This Thesis
The existence of Ridges raises the question what causes the high expression of Ridge genes: individual regulation of genes by strong promoters, or an additional domain-wide effect that up-regulates transcription? In Chapter 2 we address this
question by creating a collection of 90 clones of a human embryonal cell line with a single randomly integrated fluorescent lentiviral reporter construct. We determined the chromosomal integration site and fluorescence of each clone. Thus, we compared the transcriptional activity of clones with a Ridge-integrated reporter construct versus clones with their reporter situated in an anti-Ridge. This showed that Ridges up-regulate expression 4- to 8-fold compared to anti-Ridges.
The correspondence between Ridges and the isochore structure of the human genome, suggests that transcription of Ridge genes produces mRNAs with a distinct nucleotide composition (i.e. higher GC content). Chapter 3 investigates the
effect of GC content on the stability of Ridge mRNAs. We find that due to their high GC content, mRNAs from Ridges have higher folding stabilities as predicted by their minimal free energy. Microarray analysis on human cells treated with two transcriptional inhibitors, shows that Ridge mRNAs have 1.5–2 hour longer half-lives than anti-Ridge mRNAs.
Chapter 4 looks into the effect of GC content on the codon usage and translation
of Ridge genes. We find that the high GC content in Ridge mRNAs causes an increase in preferred codons and optimal translation initiation sites. We propose
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an evolutionary model that explains how genes can acquire extreme levels of protein expression by translocating to Ridges. The chapters 2, 3 and 4 describehow Ridges increase the transcription of their embedded genes, while mRNAs of Ridge genes are in addition more stable and also have codons that facilitate highly efficient translation. This suggests that Ridges and their physical properties enable a ‘highway’ for gene expression in the genome. Since the range of expression levels of cellular proteins is quite extreme, Ridges might contribute to very high protein expression levels by superimposing the three mechanisms proposed in chapters 2–4 to achieve an exponential system of gene expression.
Chapter 5 describes the role the histone methyltransferase enhancer of zeste
homolog 2 (EZH2) in neuroblastoma. In cancer, chromosomal domains were shown to be deregulated by chromatin modifying enzymes. This prompted us to investigate the role of EZH2 in the pediatric cancer neuroblastoma, where it is highly expressed. EZH2 belongs to the Polycomb group proteins and has been implicated in cancer as an oncogene. Here we show that EZH2 is required for cell cycle progression in neuroblastoma and is associated with a poor prognosis.
In Chapter 6 we discuss the likelihood of several well-known mechanisms as
mediators of domain-wide up-regulation of transcription by Ridges. We propose a mechanism to explain how Ridges function and the potential impact they have on evolution.
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