Gene promoters show chromosome-specificity and reveal chromosome territories in humans
© Gagniuc and Ionescu-Tirgoviste; licensee BioMed Central Ltd. 2013
Received: 18 June 2012
Accepted: 26 February 2013
Published: 24 April 2013
Gene promoters have guided evolution processes for millions of years. It seems that they were the main engine responsible for the integration of different mutations favorable for the environmental conditions. In cooperation with different transcription factors and other biochemical components, these regulatory regions dictate the synthesis frequency of RNA molecules. Predominantly in the last decade, it has become clear that nuclear organization impacts upon gene regulation. To fully understand the connections between Homo sapiens chromosomes and their gene promoters, we analyzed 1200 promoter sequences using our Kappa Index of Coincidence method.
In order to measure the structural similarity of gene promoters, we used two-dimensional image-based patterns obtained through Kappa Index of Coincidence (Kappa IC) and (C+G)% values. The center of weight of each promoter pattern indicated a structure similarity between promoters of each chromosome. Furthermore, the proximity of chromosomes seems to be in accordance to the structural similarity of their gene promoters. The arrangement of chromosomes according to Kappa IC values of promoters, shows a striking symmetry between the chromosome length and the structure of promoters located on them. High Kappa IC and (C+G)% values of gene promoters were also directly associated with the most frequent genetic diseases. Taking into consideration these observations, a general hypothesis for the evolutionary dynamics of the genome has been proposed. In this hypothesis, heterochromatin and euchromatin domains exchange DNA sequences according to a difference in the rate of Slipped Strand Mispairing and point mutations.
In this paper we showed that gene promoters appear to be specific to each chromosome. Furthermore, the proximity between chromosomes seems to be in accordance to the structural similarity of their gene promoters. Our findings are based on comprehensive data from Transcriptional Regulatory Element Database and a new computer model whose core is using Kappa index of coincidence.
Inside the body, somatic cells exercise their overall functions in G0 phase (the period between cell divisions) [1–3]. During this phase, individual chromosomes are impossible to distinguish by light or electron microscopy. For instance, when cells are terminally differentiated, some of them enter in a permanent (quiescent state) G0 phase, such as myocyte cells, the majority of neuronal cell types or pancreatic beta cells. Other types of cells exhibit a temporary G0 phase, such as glial cells or hepatocyte cells, which divide under controlled conditions. However, less is known of the precise location of chromosomes and their relationship with the internal nuclear membrane and nuclear pores through which the traffic of molecules is made. Inside the nucleus of specialized cells, spatial arrangements of chromosomes in G0 phase play an important role in the regulation of gene expression patterns [4, 5]. The nucleus lacks of membrane compartmentalization [6, 7]. In telophase, mitotic chromosomes unfold into chromatin state [8, 9]. Immediately after nuclear membrane is formed, heterochromatin is allocated to the nuclear periphery whereas euchromatin is generally contained towards the nuclear interior. In G0 phase, chromatin shows different states of condensation, such as constitutive heterochromatin, facultative heterochromatin and euchromatin [10, 11]. Constitutive heterochromatin consists of permanently condensed DNA, usually containing multiple short repeats and low gene density. Facultative heterochromatin represents a temporary DNA condensation state, located in heterochromatin landscape surface [12, 13]. The active part of the nucleus (gene rich areas), where the transcription of DNA to mRNA is made, is represented by euchromatin domain. In order to initiate the transcription process, the relaxed structure of euchromatin allows regulatory proteins and RNA polymerase complexes to bind to DNA for transcription initiation and elongation of mRNA . Euchromatin domains which are never stored as facultative heterochromatin are usually under active transcription and contain housekeeping genes, otherwise crucial for basic cell functions . Genes embedded inside facultative heterochromatin can transit to and from euchromatin, depending on different functions that the cell needs to perform, in certain time intervals or under the action of certain external stimuli. It is recognized that many active genes that are brought into or near heterchromatin landscapes become repressed and their transcriptional reactivation is made by reallocation to the nuclear interior [16–18]. Nevertheless, other studies show that some genes are transcriptionally active close to nuclear periphery [19–21]. Electron microscopy images show a lack of heterchromatin around nuclear pores . Although active inside euchromatin, some inducible genes from the nuclear interior are relocated near nuclear pores for a fast response under the action of certain stimuli [23–27]. However, facultative heterochromatin represents one of many methods through which cells, start or stop the expression of certain genes. Heterochromatin is also critical in morphogenesis and differentiation. In embryogenesis, chromatin establishes different structural landscapes depending on cell specialization. For instance, Hox gene clusters [28, 29] are responsible for the spatial structure of the body. In humans, these genes are located on chromosome 7 (HOXA gene clusters), 17 (HOXB gene clusters), 12 (HOXC gene clusters) and 2 (HOXD gene clusters). In embryogenesis, Hox genes are brought to the surface into euchromatin domain in order to be expressed in a sequential manner [30, 31]. Polycomb-group proteins and other biochemical mechanisms reshape chromatin depending on the cell type, allowing a favorable positioning of these genes inside euchromatin domain . In terminally differentiated somatic cells, Hox genes are permanently silenced by their inclusion inside heterochromatin domain. Moreover, modulation of gene expression through chromatin structure is not limited only to single genes or gene clusters. For instance, in female morphogenesis an X chromosome is silenced through its condensation inside facultative heterochromatin [33–35] (the Barr body), while the active X chromosome is included in euchromatin domain. In G0 phase, genes of common function can colocalize inside the nuclear space in order to share the same transcription machinery . Thus, these genes may be incorporated into the same transcription factory or in close neighboring transcription factories [37, 38]. It appears that these active regions are positioned between chromosome territories.
In this paper we tried to identify some structural features of gene promoters located on different chromosomes in the human genome. Our hypothesis was based on the fact that promoter sequences are more exposed to the biochemical transcription machinery and therefore may reflect the chromosome boundaries much better. Previously, approaches towards promoter analysis include motif sequences and other structural parameters, such as DNA curvature, bendability, stability, nucleosome positioning or comparison of various DNA sequences [39–46]. Nevertheless, a clear association between promoter nucleotide sequences and chromosome territories was never hypothesized. The purpose of our work was to establish a possible functional significance of promoter sequences which may explain the dynamic relationship between different chromosome territories.
In our approach we used 1200 promoter sequences (50 random promoters from each chromosome) from Transcriptional Regulatory Element Database [47, 48]. We were mainly interested in the regions flanking the putative TSS, ranging from -700b to 299b. We used Visual Basic to develop a software program for promoter analysis - called PromKappa (Promoter analysis by Kappa). The source code implementation of this program is attached to our Additional file 1. We used sliding window approach to extract two types of values, namely Kappa Index of Coincidence (Kappa IC) and (C+G)%.
Kappa index of coincidence
With small changes, the same method for measuring the Index of Coincidence has been applied for only one sequence, in which the sequence was actually compared with itself, as shown below in the algorithm implementation.
T = 0
N = length(A) - 1
for u = 1 to N
B = A[u + 1] … A[N]
for i = 1 to length(B)
If A[i]= B[i] then C = C + 1
T = T + (C / length(B) × 100)
C = 0
IC = Round((T / N), 2)
Where N is the length of the sliding window, A represents the sliding window content, B contains all variants of sequences generated from A (from u+1 to N), C counts the number of coincidences occurring between sequence B and sequence A, and T variable counts the total number of coincidences found between sequences of B and the sequence A.
Cytosine and guanine content
Where CG SW represents the percentage of cytosine and guanine from the sliding window. In this stage, CG SW value is relative to CG TOT . The expression (A+T+C+G) TOT represents the sum of occurrences of A, T, C and G from the sliding window sequence. (C+G) SW represents the sum of C and G occurrences in the sliding window sequence. Nevertheless, in our implementation we also included the option to extract CG SW values without considering CG TOT .
We first investigated if some promoter patterns occur more often on certain chromosomes. Secondly we determined if chromosome territories could be revealed by using Kappa IC. In the third analysis we examined the distribution of Kappa IC values against the number of genetic diseases associated with each chromosome.
Gene promoters show chromosome-specificity
Initially, our first observation regarding promoter-chromosome specificity originated from a direct correlation between their Kappa IC values and (C+G)% (Additional file 4). For the majority of chromosomes, promoter regions show almost proportional Kappa IC and CG% values relative to each other (Figure 2A). Promoters with the largest Kappa Index of Coincidence are placed on chromosome 4, while promoters from chromosomes 11 and 16 have almost the same Kappa index of coincidence and relatively close variations of cytosine and guanine content. Promoters with the lowest index of coincidence are located on chromosome Y (Figure 2B). The order of chromosomes by promoter Kappa index of coincidence is shown in Figure 2C,D. Interestingly, chromosomes X and Y contain promoters with the lowest CG% and Kappa index of coincidence values. Promoter regions with the highest Kappa Index of Coincidence values (ie. chromosomes 4,5,7,21) contain various SSRs and STRs structures (Figure 2B). This further suggests that in their evolution, promoters located on these chromosomes experienced few point mutations and accumulated more Slipped Strand Mispairing (SSM) mutations .
In contrast, promoter regions with the lowest Kappa Index of Coincidence values (ie. chromosomes Y,X,12,8), contain more interspersed nucleotides (A,T,C,G ≈ 25%) and less SSRs and STRs structures (Figure 2B). Acordantly, this further suggests that in their evolution, promoters located on these chromosomes have accumulated a multitude of random point mutations, thus disrupting SSR structures like poly(dA:dT) or poly(dC:dG) tracts [54, 55] in shorter elements. Although without immediate consequences, point mutations that occur in promoter regions, gradually change gene expression patterns and consequently, their gene relation within certain biological pathways.
Heterochromatin and euchromatin are two main evolutionary forces
Chromosome territories in humans
What surprised us in particular, was the symmetry of chromosome order when they are arranged by promoter Kappa IC values (Figure 2D – blue “amphora” shaped semi-circles). Generally, chromosomes were numbered according to their size. In Figure 2D we show an abstracted model in which chromosomes are ordered by Kappa IC values of promoters (colored in blue), however, in this model the blue arrows follow the order of chromosomes according to their size (starting from chromosome 4 - which contains promoters with the highest Kappa IC values). Thus, the arrows that connect more distant chromosomes in this order, show a proportional increased semi-circle radius (a radius proportional with the relative distance between them). Nevertheless, the apparent 2-fold symmetry on Y-axis (between chromosomes 4–11 and chromosomes 19-Y) further suggests that there is a correlation between chromosome length and the structure of gene promoters located on them (Figure 2D and Additional file 5). In addition, by complying with the same rules described above, when chromosomes were ordered by (C+G)% values of promoters, we could not observe any obvious symmetries (Figure 2D - red color arrows). Figure 2C shows the order of chromosomes and their position to one another when they are arranged separately by the two values.
Promoter Kappa IC values vs. genetic diseases
The haploid human genome contains a nuclear volume of approximately 1000 μm3 and 3.2 billion base pairs of compacted DNA [75–77]. Nucleosomes compact and regulate access to DNA by assuming specific positions [78, 79]. The interaction between nucleosomes that incorporate functional sequences located at great distances inside the nucleous, is provided by a favorable positioning of other nucleosomes that incorporate non-coding sequences. Accordingly, an overall picture begins to take shape, namely that the evolutionary process can not tolerate non-functional information. Although many studies show that refined mechanisms involved in the dynamics of the nucleus are ATP (adenosine-5'-triphosphate) dependent processes [80, 81], we wonderd if self-organization processes and other biophysical phenomena could be evan more involved than previously thought. Nevertheless, DNA guided self-organization processes that may concern chromatin mobility will be of utmost importance for our understanding of the dynamics of the nucleus.
In a recent study, we have suggested that eukaryotic genomes may exhibit at least 10 classes of promoters . In future research we wish to highlight the distribution of these promoter classes on each chromosome. Furthermore, we are also interested to observe the differences between Kappa IC values of introns and exons related to each chromosome in order to understand if the relative proportions presented here will remain constant.
In this paper a comprehensive analysis was undertaken for promoter sequences from Homo sapiens. In our approach we used 1200 promoter sequences (50 random promoters from each chromosome) from Transcriptional Regulatory Element Database. In order to measure the structural similarity of gene promoters, we used two-dimensional image-based patterns obtained through Kappa Index of Coincidence (Kappa IC) and (C+G)% values. The center of weight of each promoter pattern indicated an average between all SSRs and STRs present in the promoter sequence. A distribution of these average values showed that gene promoters appear to be specific to each chromosome. Furthermore, the proximity between chromosomes seems to be in accordance to the structural similarity of their gene promoters. Although chromosomes are positioned differently depending upon each cell type, they exhibit a predisposition for a standard arrangement. High Kappa IC and (C+G)% values of gene promoters were also directly associated with the most frequent genetic diseases. Taking into consideration these observations, a general hypothesis for the evolutionary dynamics of the genome has been proposed. In this hypothesis, heterochromatin and euchromatin domains exchange DNA sequences according to a difference in the rate of mutations.
This work was supported by a grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-ID-PCE-2011-3-0429.
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