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SCHIP: Statistics for Chromosome Interphase Positioning |
3.1 Select a table of pairwise chromosome yields.
3.1.1 Select provided table
3.1.2 Upload a new table
3.2 Select a set of chromosome clusters
3.2.1 Select a previously reported clusters.
3.2.2 Select a previously reported recurrent translocation found in lymphoblastic leukemia.
3.2.3 Upload a new cluster (s).
4.1.1 How to select one of the provided pairwise chromosome yields and a cluster /recurrent aberration.
4.1.2 How to select one of the provided tables of pairwise chromosome yields and upload a new chromosome cluster(s)/recurrent aberration(s).
4.1.3 How to upload a new table of pairwise chromosome yields and a new cluster(s)/recurrent aberration(s).
This software helps test for suspected clusters of chromosomes in the interphase cell nucleus. During the G0/G1 phase of the cell cycle individual chromosomes occupy their own sub-nuclear volumes called chromosome territories (reviewed in Cremer & Cremer, 2001). It is believed that positions of the chromosome territories follow a non-random radial arrangement, are determined at mitosis, and do not change markedly during the cell cycle (reviewed in Parada and Misteli 2002; Gerlich et al., 2003; Walter et al. 2003). These observations are complemented by observations that analyze the relative position of chromosomes. The latter studies have found an overall random organization (Cornforth et al. 2002; Arsuaga et al. 2004) modulated by some clustering. Clustering has been associated with different biological phenomena such as gene content (Boyle et al. 2001), gene expression (Arsuaga et al. 2004, Parada and Misteli 2002 ), or cancer (Lukasova et al. 1997, 1999; Roix et al. 2003). For example it is likely that the nucleolus chromosomes (13; 14; 15; 21; 22) are generally closer to each other than randomness would predict, i.e. form a cluster.
Ionizing radiation helps approach the problem of the relative position of chromosomes. When ionizing radiation tracks (gamma rays, X-rays, high energy alpha particles, etc…) cross the cell nucleus they release enough energy to disrupt the molecular structure of the DNA (directly or indirectly) and induce DNA double stranded-breaks (DSBs). When DSB free ends are rejoined with free ends different from their original partners, chromosome aberrations are introduced. If the two misrejoined free ends are on different chromosomes, the chromosome aberration is called an interchange, and the number of interchanges observed for each chromosome pair can help indicate chromosome positioning in the nucleus. The main advantages of using ionizing radiation for quantitative studies of chromosome aberrations are the following:
i.- The timing of damage induction can be controlled.
ii.- The number of DSBs is proportional to the dose. The dose is measured in Gray (Gy), with 1 Gy = 1 Joule/kilogram. The number of DSBs per Gy has been estimated to be between 30 and 50. (Löbrich et al. 1994)
iii.- The spatial distribution of DSBs is determined by the radiation type. Some kinds of radiation (e.g. gamma rays) produce a pattern of random breakages across the genome. For other kinds (e.g. alpha particles), there may be many DSBs clustered along each radiation track in stochastic patterns whose details depend on the type and energy of the radiation; owing to the phenomenon of chromosome territories, clustering in space along a radiation track leads to clustering of DSBs within the genome. (reviews: Sachs et al. 2004; Sachs and Brenner, 2003. It has been observed that for doses < 5Gy a large majority of the DSBs are repaired (correctly at least to the 1Mb level of resolution used in most aberration studies -Radivoyevitch et al. 1998). Most of the remainder form chromosome aberrations. It is believed that chromosomes that are in close proximity tend to form more interchange aberrations than those that are further apart (reviewed in Sachs et al 2004). Chromosome aberrations involving chromosome segments larger than ~1Mb can be detected by fluorescent in-situ hybridization techniques (FISH). Specially informative are combinatorial painting techniques such as multiplex FISH (mFISH, Speicher et al. 1996) and Spectral Karyotyping (SKY, Schröck et al. 1996). Both techniques paint every pair of homologous chromosomes the same (pseudo)-color but paint heterologous chromosomes different (pseudo)-colors. Under these multicolor hybridization techniques chromosome interchanges other than those involving homologues can be observed as color junctions. This software makes use of color junctions to determine the relative positioning of chromosomes.
The basic data is in the form of a table of pairwise chromosome yields where each row and column represents a pair of homologous chromosomes (since chromosome interchanges between homologous chromosomes cannot be detected by mFISH or SKY). The entry located at row i and column j is given by the number of cells that contain at least one color junction between chromosomes i and j (denoted by f(i,j)). Assuming complete randomness, each f(i,j) can be thought as a sample of a Poisson distribution of mean given by the product of two terms g(i)g(j) where each member of the product represents a normalized quantity of the number of times that a chromosome is involved in chromosome interchanges. Each of these terms can be estimated by solving the equation ∑ f(i,j) = g(j) ∑ g(i). Pairwise deviations from randomness are estimated by the auxiliary statistic Delta(i,j) defined as f(i,j)-g(i)g(j)/(g(i)g(j))^1/2 which measures the difference between the observed and the estimated value. For a given candidate cluster, the null hypothesis of random chromosome-chromosome spatial association is assessed by perturbation analysis. That is, each of the entries in the table that correspond to a chromosome pair in the candidate cluster is re-sampled while leaving the rest of the entries fixed. These perturbations allow estimating p-values for the chromosome cluster being tested. Our method is designed to circumvent any theoretical assumptions about aberration formation mechanisms and radiosensitivity (as well as size) of individual chromosomes and it is robust with respect to radiation dose, distributions of cells in different metaphases and sex of donors. (Cornforth et al. 2002; Arsuaga et al. 2004).
In order to test significance of specific chromosome clusters the following two steps are required.
3.1 Select a table of pairwise chromosome yields.
There are two options for uploading the table of pairwise chromosome yields:
3.1.1 Select provided table
3.1.2 Upload a new table
3.2 Select a set of chromosome clusters
There are three options to choose from for selecting the set of chromosome clusters.
3.2.1 Select a previously reported clusters.
3.2.2 Select a previously reported recurrent translocation found in lymphoblastic leukemia, considered as a 2-chromosome cluster.
3.2.3 Upload a new cluster.
Each table of pairwise chromosome yields refers to radiation induced interchanges between pairs of heterologous chromosomes, typically observed by multiplex fluorescence in-situ hybridization (mFISH). This set can either be uploaded or selected from one of the five data sets described below.
In giving the descriptions below we use the fact that the various types of radiation are often placed into two broad categories, sparsely ionizing radiations (e.g. gamma rays, high energy electrons, etc.) and densely ionizing radiations (e.g. alpha particles, fully ionized atoms of higher atomic number, etc.).
This data set contains a total of 1587 peripheral blood lymphocytes irradiated in vitro, derived from two male donors at the University of Texas Medical Branch (Galveston, TX), and from five donors (two female, three male) at the Technical University of Munich (Munich, Germany). Cells from the Texas laboratory were irradiated at 1Gy (238 cells), 2Gy (341 cells) and 4Gy (179 cells). Cells from the Munich laboratory were irradiated at the single dose of 3Gy. Experimental details can be found (Loucas and Cornforth 2001 and Greulich et al. 2000). Theoretical details concerning chromosome positioning as well as chromosome aberration formation mechanisms can be found in (Cornforth et al. 2002; Arsuaga et al. 2004; Vazquez et al. 2002 and Levy et al. 2004).
This data set extends that of Cornforth and colleagues (Cornforth et al 2002). A new data set of peripheral blood lymphocytes from one male donor from the Munich laboratory was added. A total of 1998 cells were irradiated at different doses (255 cells at 3Gy; 1144 cells at 4Gy and 599 cells at 5Gy). Experimental and theoretical details can be found in (Arsuaga et al. 2004).
This data set includes 976 human peripheral lymphocytes, derived from a single female donor, irradiated with iron ions at different doses: 191 cells were irradiated at 0.2Gy, 180 cells at 0.4Gy, 197 cells at 0.7Gy and 408 at 1Gy.Details of the irradiation conditions have already been published and can be found in (Durante et al. 2002).
This data set includes 310 human fibroblasts irradiated with alpha particles at different doses: 90 cells were irradiated at 0.1 Gy, 94 cells at0.2 Gy, 72 cells at 0.4 Gy and 54 at 0.6 Gy. Fibroblasts belong to cell line AG1521 (NIA Aging Cell Culture Repository at the Coriell Institute for Medical Research). Details of the irradiation conditions can be found in (Cornforth et al. 1991).
A new table of pairwise chromosome yields can also be uploaded in ASCII format. For female cells, the file should contain a 23 x 23 table (or (N+1) x (N+1) table; N=number of autosomes of the organism been studied). The entries for the first row and first column are the chromosome labels for each of the 22 autosomes in human cells (N if another organism is studied). Entries are non-zero above the diagonal only. Each of the entries show the yield of interchanges between chromosomes (i.e. the number of cells with one or more color junctions), denoted f(i,j), for the chromosome in row i and the chromosome in column j. Columns should be separated by tab key (\t) and rows by a return key (\n). We recommend including one carriage return (\n) at the end of the file. Figure 1 illustrates an example.
Figure 1: Example of pairwise chromosome yields file (f(i,j)). The number of cells containing one or more interchanges between chromosome 1 and chromosome 2 is f(1,2) =44, shown in row 1, column 2.
The cluster(s) to be tested needs to be selected. In order not to reuse the data and since this is not a data mining approach (data mining will be addressed elsewhere) we consider clusters of chromosomes that have been proposed in the literature and are independent of our experiments.
The following clusters have been proposed in the literature for human lymphocytes and fibroblasts respectively.
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Reported Clusters in Lymphocytes |
| (1;16;17;19;22) Boyle et al 2001 |
| (6;7) Pombo et al 1998 |
| (8;11) Nagele et al 1999 |
| (9;22) Elliot et al 2002 |
| (13;21) Alcobia et al 2000 |
| (13;14;15;21;22) Krystosek, A 1998 |
| (14;18) Lukasova et al 1999 |
| (14;22) Alcobia et al 2000 |
| (15;17) Neves et al 1999 |
| (17;19;20) Cremer et al 2001 |
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Reported Clusters in Fibrobalsts |
| (17;18;19;20) Cremer at al 2001 |
| (18;19) Cremer et al 2001 |
All recurrent translocations found in lymphatic leukemia and reported in the Mitelman data base were included (Mitelman et al. 2004).
The format for uploading new clusters follows the Mitelman’s database notation. Figure 2 shows an example. Only one cluster per line should be introduced. Clusters or recurrent aberrations should be written in parenthesis and separated by semi colon. A return key (\n) should be included at the end of each line.
Figure 2: Example of a list of candidate clusters or recurrent aberrations proposed by the user. Candidate clusters and recurrent aberration have the same format (described in the text). In this example 3 clusters are being tested. The first one contains two chromosomes (numbers 1 and 3). The second one four chromosomes (numbers 2, 14, 15 and 17) and the third three chromosomes (numbers 14, 17 and 21).
In the next section we give several examples of how to use the program. The first example shows the case when both the table of pairwise chromosome yields and the candidate clusters are uploaded from the already existing data sets. The second example shows how to upload a new cluster of interchanges and the third example shows how to upload a new table and a new cluster.
4.1.1 How to select one of the provided pairwise chromosome yields and a cluster /recurrent aberration.
Figure 3 shows the layout of the user interface where one of the provided tables of chromosome yields (Step 1)and the option for selecting a reported cluster (Step 2) have been activated. Once the option for selecting reported clusters has been activated a list of chromosome clusters will appear on the right hand side. One or more clusters can be selected (Step 3) by clicking or by simultaneously pressing Ctrl key. To submit the data press the submit button.
Figure 3: Example of selection of one of the five tables of pairwise chromosome yields and of the reported clusters in lymphocytes.
4.1.2 How to select one of the provided tables of pairwise chromosome yields and upload a new chromosome cluster(s)/recurrent aberration(s).
This example shows the option of how to upload a new cluster (Steps 2 and 3). Once the option for uploading a new data set has been activated (Step 2) one can proceed to input the new clusters as described in section 3.2.3. Steps 1 and 2 are described in the previous section.
Figure 4: Example of how to upload new cluster(s)/chromosome aberration(s).
4.1.3 How to upload a new table of pairwise chromosome yields and a new cluster(s)/recurrent aberration(s).
Steps 2 and 3 have been described previously. By pressing the browse button it is possible to browse over the local system and upload the desired file (Step 1).
Figure 5: How to upload a new table of chromosome-chromosome interactions.
The results are determined by Monte Carlo computer simulations. Therefore a few minutes are needed to compute the p-values (depending on the server). The following page is shown while the results are being computed.
Figure 6: Screen for waiting time.
The input data (pairwise chromosome yields) denoted by f(i,j) is shown in the upper left corner of the table, the "normalized" single chromosome participation g(i) is along the diagonal and the overall deviations from the expected values assuming a random model D(i,j) are shown in the lower triangular matrix.
Figure 7: Example of output. The table contains all the information needed for the computation of the p-values.
Finally by clicking in the button "show p-values" a new window appears containing the set of p-values for the various suspected clusters to occur by chance alone. Note that the p-values printed are not corrected for multiple testing therefore when several clusters are tested a correction step should be considered.
Figure 8: Example of computed p-values. Two columns will appear. The first one contains the Cluster to be tested and the second the computed p-value.
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Questions? Comments? Send an email: jarsuaga@sfsu.edu