Turkish Journal of Biology Turk J Biol (2014) 38: 880-897 http://journals.tubitak.gov.tr/biology/ © TÜBİTAK Research Article doi:10.3906/biy-1404-1

Identification of new required for the maintenance of integrity in Drosophila melanogaster

1 1 2, Francesca CEPRANI , Franco SPIRITO , Roberto PIERGENTILI * 1 Department of Biology and Biotechnologies, Sapienza University of Rome, Rome, Italy 2 Institute of Biology, Molecular Medicine, and Nanobiotechnologies at the National Research Council (CNR), Sapienza University of Rome, Rome, Italy

Received: 01.04.2014 Accepted: 21.07.2014 Published Online: 24.11.2014 Printed: 22.12.2014

Abstract: Although genome-wide RNA interference (RNAi) screens for mitotic genes are not new in the literature, most of them lack the cytological characterization of the cell karyotype as for chromosome integrity. Here, the effects of RNAi on chromosome structure in S2 cultured cells of Drosophila melanogaster were analyzed. The cytological phenotype of 1132 genes selected by coexpression with known mitotic genes was scored. Cytological and statistical analysis of the treated cells allowed the identifying of 81 loci whose inactivation brings a level of chromosome breakage significantly higher than in the control. Many of the genes characterized in the present work had never been associated with a cellular function; in other cases, their putative role is apparently unrelated to the chromosome breakage phenotype. These results suggest novel biological roles for the encoded by the identified genes and indicate that the number of loci required for chromosome integrity is much larger than expected. Moreover, these results strongly suggest that the compilation of a list of coexpressed genes for any given function would result in a largely incomplete set of data, and that quite surprisingly a more complete collection of loci may be obtained using screening criteria different from selection.

Key words: Cancer, functional coexpression, genome instability, karyotype, S2 cultured cells, segmental aneuploidy, RNAi

1. Introduction – evolved very early and was already present in the first, RNA-interference (RNAi) is experimentally used for primitive eukaryotes; as a result, organisms not showing silencing via a double-stranded RNA (dsRNA) targeting a RNAi probably lost it during evolution (Cerutti and Casas- complementary messenger RNA (mRNA) and promoting Mollano, 2006). The use of RNAi has been largely and its degradation by a nuclease-dependent cut. Although successfully used for the analysis of single gene silencing this acronym was first used by Fire et al. (1998) in studying as well as for the screening of genome-wide collections the model organism Caenorhabditis elegans, this biological of genes, showing that the resulting phenotype is usually phenomenon had already been observed before, though highly specific and penetrant (Mohr et al., 2010). This not completely understood, in several organisms such as approach allowed achieving extremely important results, transgenic plants (Ecker and Davis, 1986; Napoli et al., especially in the investigation of basic cell life phenomena 1990), Neurospora crassa (Romano and Macino, 1992), such as metabolism, mitosis and cytokinesis, chromosome Caenorhabditis elegans (Guo and Kemphues, 1995), structure and behavior, and mitotic spindle functions. and Drosophila melanogaster (Pal-Bhadra et al., 1997), Remarkably, in most screenings RNAi is not used to indicating that RNAi is widely present in most eukaryotes. identify genes required to maintain mitotic chromosome Notably, some eukaryotes lack all or most of the RNAi integrity, principally because this type of analysis cannot machinery; among others, these include some protozoa be automated (Conrad and Gerlich, 2010). Thus, genome- (Robinson and Beverley, 2003; DaRocha et al., 2004), and wide screenings for this phenotype are largely missing several fungi including Saccharomyces cerevisiae (Aravind from the scientific literature. et al., 2000; Nakayashiki et al., 2006; Drinnenberg et al., The DNA of living cells is subject to many types of 2009). Some researchers suggest that this mechanism – molecular lesions, including base modifications, single- probably a defense against exogenous, potentially harmful and double-strand breaks, and intra- and interstrand cross- dsRNA such as that of viruses or transposable elements links between bases. Double-stranded DNA breaks (DSBs)

* Correspondence: [email protected] 880 CEPRANI et al. / Turk J Biol are probably the most deleterious lesions, as they can with polyploidy than aneuploidy; although chromosome result in chromosome aberrations (CAs), cell death, and number abnormalities are frequently associated with the neoplastic transformation (Khanna and Jackson, 2001; van neoplastic transformation (Torres et al., 2008; Williams Gent et al., 2001; Mills et al., 2003). To counteract the effects and Amon, 2009), aneuploidy is a potential tool to target of DSBs, living organisms have evolved 2 main mechanisms cancer cells, since even transformed cells are sensitive to for repairing their DNA: homologous recombination (HR) genomic unbalances (Bannon and Mc Gee, 2009; Williams (San Filippo et al., 2008) and nonhomologous end joining and Amon, 2009). As a general mechanism, aneuploidy – (NHEJ) (Lieber, 2010). In the HR pathway the broken ends including segmental aneuploidy – leads to alterations of undergo a recombinational process with the undamaged the gene copy number, and these alterations may influence sequence of either the sister chromatid or the homologous not only the gene itself (and/or the it encodes) chromosome, which is used as a template for accurate DSB but also its molecular or functional interactors (Torres repairs. In the NHEJ pathway, after a limited degradation et al., 2008; Veitia et al., 2008; Henrichsen et al., 2009), (Huertas, 2010), broken ends are ligated irrespective of which leads to the potential deregulation of tens of genes. homology, thus resulting in a small sequence deletion at In this perspective, it becomes crucial to identify those the joining site. The latter mechanism is intrinsically error- genes that determine the genome stability by controlling prone, and in addition to the aforesaid deletion it may also the chromosome integrity, since the effects of even a lead to various types of chromosomal rearrangements, single un- or misrepaired DNA break may have harmful such as transpositions and reciprocal translocations consequences. Of great help is the fact that these genes are (Lieber et al., 2006; Weinstock et al., 2006). Experimental widely conserved in most eukaryotes, so it is conceivable analyses using ionizing radiation and restriction enzymes that studying them in a model system, such as cultured have shown that DSBs are the principal lesions leading Drosophila S2 cells interfered with by RNAi, might provide to the formation of CAs (Natarajan and Obe, 1978; Obe important suggestions about the role of their human et al., 1992; Vamvakas et al., 1997; Richardson and Jasin, orthologs, with the advantage that in Drosophila the 2000; Obe et al., 2002; Tsai and Lieber, 2010). Interestingly, interference is easily achieved and the karyotype is simpler after a first burst, a second round of radiation-derived CAs than in humans due to a reduced chromosome number. may appear several cell generations after the first genomic In 2008 Somma et al. identified a number of genes insult, indicating that its effects on genome stability might having a role in mitosis. To achieve this result, they created become evident even after a long time (Streffer, 2010). a list of genes coexpressed with other, known mitotic genes. Because of the lack of homology, the erroneous ligation In order to evaluate the coexpression, they used the Pearson of 2 centromere-containing broken DNA ends by NHEJ correlation coefficient and, since this variable goes between leads to the formation of a dicentric chromosome able to –1.00 and + 1.00 and its highest values express increasing start the break-fusion-bridge cycle (McClintock, 1951), levels of positive correlation, they focused on the range which in turn makes CAs more complex. CAs were of [0.85, 1.00]. Specifically, Somma et al. evaluated the associated with neoplastic transformation in man a long frequency of contemporary expression of a reference gene time ago (Nowell and Hungerford, 1960; Levan, 1967; (first variable) against any other gene (second variable) of Rowley, 1973; Zech et al., 1976; Fukuhara et al., 1979; the D. melanogaster genome using microarray data from Hatano et al., 1981; Tsujimoto et al., 1984; Finger et al., 89 different experiments. They repeated this analysis 6 1986; Rabbitts et al., 1988; Le Beau et al., 1993), frequently times, using 6 reference genes connected to mitosis, and because of up-, down- or misregulation of genes important created a merged table of coexpression using the average for DNA replication, DNA repair, checkpoint control, value of each gene against the 6 reference genes. Finally, and mature ribonucleoprotein (mRNP) biogenesis they analyzed the first approximately 1000 genes that had (Aguilera and Gomez-Gonzalez, 2008; Clémenson and a Pearson correlation coefficient in the above mentioned Marsolier-Kergoat, 2009; Kerzendorfer and O’Driscoll, range. The screening was performed by studying the 2009; Mitelman et al., 2010). Acentric fragments, lacking cytological phenotype of cultured S2 cells after RNAi a centromeric region, are not able to correctly segregate targeting of these genes. In the present work we applied during the cell division and can either be inherited by RNAi against the same genes, but specifically focused on any of the daughter cells – irrespective of their gene the presence of chromosome instability as a consequence content – or be lost. In most cases, the final output of gene silencing. Our approach allowed the identification is the formation of a cell having a quantity of DNA of a group of at least 81 genes whose silencing results in a that is larger or smaller than the normal complement; chromosome breakage phenotype. Surprisingly, only less this situation is usually called segmental aneuploidy than one-third of them can be directly related to DNA because only a fraction of one or a few chromosome(s) metabolism, i.e. DNA replication and/or repair, nucleotide is genetically unbalanced. Interestingly, cells cope better biosynthesis, and chromosome structure. This indicates

881 CEPRANI et al. / Turk J Biol that the majority of the loci we identified could not be with DAPI (Vector) to stain DNA. Images were captured predicted to produce such a phenotype upon silencing. using a CoolSnap CCD camera (Photometrics, Tucson, We were able to group some of them into discrete classes, AZ, USA) connected to a Nikon Eclipse E600 fluorescence according to their function, and to identify a new phenotype, microscope equipped with an HBO 50-W mercury lamp. which we called multifragmented cells, showing extensive 2.3. Statistical methods chromosome breakage upon RNAi-mediated silencing, For the proportion of cells with aberrations, the and that is particularly strong for genes that have DNA comparison between each line with interference and the replication-related functions. Unexpectedly, another class control entails the analysis of a 2 × 2 contingency table. of genes was also highlighted by our experiments; they are The chi-square value with Yates’ correction for continuity apparently involved in the mitosis/apoptosis cell fate, but and its associated probability were calculated. When the also destabilize the chromosome structure after silencing. expected number in 1 or more of the table cells was less Taken together, our results suggest that the genes involved than 10, Fisher’s exact test was carried out and the 2-sided in genome integrity are much more numerous than probability values were calculated using the method of expected. small P-values, as described (Agresti, 1992). The expected number of aberrations per cell in every 2. Materials and methods pair of samples compared (the treated line considered and 2.1. Double-stranded RNA synthesis and cell treatment the control) was calculated assuming that the 2 samples Genes were amplified by polymerase chain reaction were extracted from the same population with a Poisson (PCR) either using a mixed embryonic cDNA library distribution. The chi-square test (which is based on the (Brown and Kafatos, 1988) or genomic DNA. Each difference between observed and expected values) was gene-specific primer used contained the 35-nt performed using Yates’ correction. When the expected sequence for the T7 RNA polymerase binding site number of aberrations was less than 10 in at least 1 of (5’-TAATACGACTCACTATAGGGAGG-3’) at the 5’ the cells of the table, the exact test based on the binomial end. dsRNA was synthesized with an average length distribution was performed. Additionally, in this case of 750 bp (minimum length: 600 bp) and analyzed as the 2-sided probability was calculated with the method previously described (Somma et al., 2002, 2008). S2 cells of small P-values. For genes whose interference caused were cultured at 25 °C in Shields and Sang M3 medium a significant effect, the possible nonrandom distribution (Sigma) supplemented with 10% heat-inactivated fetal inside the coexpression list was checked by the Mann– bovine serum (FBS, Invitrogen). Cells reared at 25 °C in Whitney test, while the possible nonrandom location complete medium were centrifuged, then resuspended at within the chromosome bands was established evaluating a concentration of 106 cells/mL with serum-free medium the significance of the deviations from a Poisson and finally plated in a 6-well culture dish (Sarstedt). Each distribution (variance test). culture was subsequently inoculated with 15 µg of dsRNA. Finally, whenever multiple tests were involved, in order Control cultures were prepared in the same way, in parallel, to achieve a protection against errors of the first type, but no dsRNA was added. After 1 h of incubation at 25 °C, Holm’s sequential Bonferroni procedure was applied to 2 mL of medium supplemented with 15% FBS was added check the statistical significance at the level of a P ≤ 0.05, to each culture. Both dsRNA-treated and control cells were as described (Holm, 1979). grown for 72 h at 25 °C. 2.2. Cytological preparations and image collection 3. Results Cells from 3-mL cultures were interfered with for 3 days 3.1. Preliminary screening and then resuspended in the medium, and 1 mL of cell Our initial analysis of S2 cells revealed that there is a suspension was treated for 2 h with colchicine (colcemid considerable number of spontaneous CAs, including at a final concentration of 10–5 M). Cells were then both chromatid/chromosome breaks and exchanges. This centrifuged at 1000 rpm for 5 min. Pelleted cells were phenotype is not influenced by the use of non-Drosophila washed in 10 mL of phosphate-buffered saline, spun down random dsRNA. In order to evaluate the absolute number by centrifugation, and resuspended in 5 mL of hypotonic of CAs and their variation, we performed a series of 45 solution (0.5 M sodium-citrate) for 7 min. After further different control experiments, in parallel with RNAi centrifugation at the same speed, pelleted cells were fixed treatments, using cells grown for the same time and with in 5 mL of methanol and acetic acid (3:1), spun down the same medium, but without adding dsRNA. The results again, and resuspended in the small volume of fixative left of these experiments are listed in Table 1. As shown, after the gentle removal of the supernatant. Ten microliters controls averaged 21 aberrant cells (ACs) and 23.7 CAs of this suspension was dropped onto a microscope slide per 100 scored metaphases – the latter number being and air-dried. All slides were mounted in Vectashield higher since occasionally 2 CAs are present in the same

882 CEPRANI et al. / Turk J Biol

Table 1. Control S2 cells without dsRNA treatment (total: 45 independent experiments). Each row summarizes the results of a single experiment, performed in parallel with the RNAi; the last row (bold font) shows the total values (columns 1, 2, and 4) and the average values (columns 3 and 5) of the experiments. ACs: Aberrant cells; CAs: chromosome aberrations.

Number of metaphases ACs per 100 scored CAs per 100 scored Number of ACs Total CAs scored per experiment metaphases metaphases 80 17 21.3 22 27.5 55 13 23.6 14 25.5 100 23 23.0 26 26.0 100 23 23.0 29 29.0 65 13 20.0 15 23.1 56 12 21.4 14 25.0 30 5 16.7 6 20.0 50 11 22.0 12 24.0 50 12 24.0 12 24.0 50 11 22.0 12 24.0 55 13 23.6 14 25.5 40 8 20.0 8 20.0 100 23 23.0 23 23.0 80 17 21.3 22 27.5 56 12 21.4 14 25.0 30 5 16.7 6 20.0 50 12 24.0 12 24.0 50 11 22.0 12 24.0 50 11 22.0 12 24.0 50 9 18.0 9 18.0 40 9 22.5 10 25.0 50 11 22.0 13 26.0 40 9 22.5 10 25.0 20 6 30.0 6 30.0 22 3 13.6 4 18.2 31 7 22.6 7 22.6 20 3 15.0 3 15.0 30 4 13.3 6 20.0 25 5 20.0 6 24.0 30 6 20.0 7 23.3 20 4 20.0 4 20.0 65 13 20.0 15 23.1 100 23 23.0 23 23.0 56 5 8.9 6 10.7 100 22 22.0 26 26.0 20 4 20.0 5 25.0 70 17 24.3 20 28.6 11 2 18.2 2 18.2 20 4 20.0 4 20.0 30 5 16.7 6 20.0 58 12 20.7 14 24.1 40 4 10.0 6 15.0 20 5 25.0 5 25.0 30 6 20.0 7 23.3 20 4 20.0 4 20.0 2165 454 21.0 513 23.7

883 CEPRANI et al. / Turk J Biol metaphase. Analysis of these data using the chi-square and a corresponding amount of dsRNA was added to the test demonstrated that these numbers are very similar cells, which were treated for an equivalent time. In total, among different experiments (P > 0.9999 for both ACs the chromosome complement of 1132 interfered genes and CAs), so the variability of this parameter is very low. was cytologically analyzed. The quantitative data were then In conclusion, it can be assumed that the basal level of studied using the chi-square test with Yates’ correction. We ACs and CAs is a characteristic feature of this cell lineage found that none of the tested dsRNA was able to lower the and may be considered as a constant when evaluating the number of either ACs or CAs compared to our controls. possible clastogenic effects of RNAi on a particular gene. Instead, genes increasing the number of CAs and/or ACs As a starting point for the search for genes that are upon interference, with a P-value of ≤0.05 in the single important for chromosome integrity, the experiments comparison with the control, are reported in Table 2. described by Somma et al. (2008) were replicated to For each cell lineage, at least 50 metaphases in at least 2 reproduce the same working conditions, i.e. the same different experiments were examined. The experiments interfering RNA obtained with the same primers was used, characterized by less than 50 metaphases are those for

Table 2. List of the genes that impair chromosome integrity upon RNAi-mediated silencing, with 137 genes identified by RNAi and validated using the chi-square test with Yates’ correction. ACs: Aberrant cells; MCs: multifragmented cells; CAs: chromosome aberrations. Columns – 1: Rank of the gene according to the list by Somma et al. (2008); 2: identifier according to FlyBase; 3: other names of the gene/locus, according to the available literature; 4: human orthologous gene; 5: function of the gene as reported in FlyBase, Release FB2013_04 (see below for the meaning of each code); 6: total number of scored metaphases; 7: cells having at least one chromosome break/rearrangement; 8: number of cells with multiple, unscorable breaks and already counted in Column 7; 9: the asterisk marks loci positive for ACs after applying the Holm–Bonferroni correction; 10: total number of CAs, excluding those in MCs; 11: the asterisk marks loci positive for CAs after applying the Holm–Bonferroni correction. Rows in bold text highlight genes/loci that are positive only for ACs or for CAs according to chi-square test with Yates’ correction. Codes for the genetic functions in alphabetical order – A: General RNA metabolism; C: chromatin/chromosome structure; D: DNA damage repair, DNA recombination; E: import-export from nucleus; K: protein phosphorylation and dephosphorylation; M: mitotic spindle assembly; N: nucleotide/nucleoside metabolism; O: other functions; P: phagocytosis, engulfment; R: DNA replication; S: splicing, mRNA maturation/modification; T: transcription; U: ubiquitin and sumo metabolism, protein degradation; X: unknown function; Y: apoptosis; Z: translation. Each functional class was arbitrarily created when at least 3 genes fell inside it; in all other cases, the genes were assigned to the O (other functions) class.

Holm– Holm– Locus Human Scored Bonferroni Total Bonferroni Rank identifier Aliases orthologous Function ACs MCs metaphases correction for CAs correction for (CG) gene ACs CAs 0 control --- 2165 454 0 --- 513 ---

4 9193 mus209 PCNA M R 257 111 17 * 163 *

5 15220 RPA3 --- R 100 38 8 47 *

11 8975 rnrS RRM2 N Y 165 90 7 * 168 *

12 10159 BEAF-32 --- C T 120 47 0 * 65 *

18 4978 mcm7 MCM7 R 174 121 24 * 164 *

20 9273 rpA2 RPA2 R 103 31 1 35

41 3178 rrp1 APEX1 D 142 47 2 62 *

46 8142 --- RFC4 O 100 23 0 35

84 7055 dalao SMARCE1 C T 113 35 0 35

104 1966 acf1 BAZ1A C 181 54 1 72 *

112 3642 clipper CPSF4L A 20 9 0 10

120 11979 rpb5 POLR2E T 83 31 0 45 *

126 2925 noisette SF3A3 E M 183 84 3 * 126 *

135 14999 rfC4 RFC4 C D R 142 51 0 79 *

142 9241 mcm10 MCM10 C R 104 35 0 40

151 12359 ulp1 SENP1 U 170 88 0 * 101 *

884 CEPRANI et al. / Turk J Biol

Table 2. (Continued).

152 4206 mcm3 MCM3 R 71 24 2 30

159 5553 DNApolα60 --- R 110 36 0 47

161 4654 dp TFDP1 T Y 322 110 2 * 128 * snRNP-U1- 164 8749 SNRNP70 M S 100 28 0 35 70K 168 12050 --- WDR75 X 213 116 2 * 141 *

183 12113 intS4 INTS4 A 36 15 0 20

202 5452 dnk ENS400000260851 N 103 49 0 * 80 *

219 8068 su(var)2-10 PIAS1 C 250 84 2 * 143 *

231 13427 ------X 126 55 0 * 80 *

245 2848 trn-SR TNPO3 E S 156 54 1 68 *

264 7769 piccolo DDB1 D 201 72 5 * 99 *

271 11920 --- NDOR1 X 80 26 1 31

276 18528 --- GTPBP3 A 150 39 0 54

277 9633 rpA-70 RPA1 M R 70 63 47 * 54 *

294 10354 rat1 XRN1 O 274 99 3 * 133 *

300 31671 tho2 THOC2 A E 91 31 0 44 *

306 5198 holn1 CD2BP2 P 44 16 0 21

307 7833 orc5 ORC5L C M R 150 45 0 70 *

312 6349 DNApolα180 POLA1 R 159 76 1 * 106 *

337 17938 midway DGAT1 Y 125 54 0 * 58 *

353 14749 GLE1 GLE1 A E 151 64 1 * 78 *

386 17383 jigr1 --- T 237 80 0 * 101 *

387 6011 prp18 PRPF18 S 43 16 0 20

391 10667 orc1 ORC1 R 91 33 1 36

395 3736 okra RAD54B D 152 68 2 * 104 *

406 11906 ------X 151 63 0 * 76 *

407 7989 wicked UTP18 A 191 81 0 * 94 *

414 6249 csl4 EXOSC1 A 100 29 0 38

419 2260 --- WDR46 X 130 52 1 * 63 *

420 6121 tip60 KAT5 C D 100 36 0 45 *

422 2199 ------X 200 54 1 79 *

426 33095 ------X 105 28 0 36

427 8274 megator TPR M 86 43 0 * 79 *

429 5965 woc --- C O T 156 61 0 * 80 *

430 7993 --- RPF2 X 100 31 0 55 *

445 8711 cullin-4 CUL4A E U 200 108 8 * 204 *

454 9348 taf6 TAF6 T 198 79 0 * 106 *

456 8962 paf-AHα PAFAH1B3 O 150 49 0 57

462 9677 int6 EIF3E P Z 280 149 4 * 175 *

474 5370 dcp-1 CASP2 U Y 117 51 1 * 67 *

490 8989 his3.3b HIST1H3B C 188 90 2 * 125 *

885 CEPRANI et al. / Turk J Biol

Table 2. (Continued).

493 1078 fip1 FIP1L1 A 150 58 0 * 67 *

495 2161 regena CNOT2 T 121 60 0 * 86 *

502 7014 rpS5b RPS5 Z 80 28 1 39 *

516 8878 ------K 171 71 1 * 91 *

517 4281 ------X 188 63 0 79 *

519 4788 ------X 150 43 0 54

520 13329 cid --- M 50 20 1 22

523 6340 --- RSRC2 X 85 26 0 32

529 9900 mit(1)15 ZW10 O 10 6 0 11 *

539 10754 --- 3F3A2 M 102 45 1 * 66 *

555 6197 --- XAB2 P S 70 25 1 40 *

561 2213 msd5 --- M 139 40 0 48

562 8426 l(2)NC136 CNOT3 T 106 35 6 40

585 5649 kin17 KIN S 150 39 0 56

595 17161 grapes CHEK1 D K M 61 24 1 28

596 3181 ts TYMS N 135 62 1 * 98 *

605 31111 --- TBRG1 X 233 69 0 78

607 11266 caper RBM39 S 251 72 0 100 *

611 5193 TfIIB GTF2B T 140 51 1 * 63 *

613 6693 --- DNAJC9 X 90 27 0 35

622 8950 --- GTF3C3 X 151 45 0 48

627 1017 Mfap1 MFAP1 O S 35 10 0 15

632 6453 --- PRKCSH X 225 65 1 84

652 8980 niPp1 PPP1R8 K 50 21 0 27 *

656 10689 l(2)37Cb DHX8 A 50 25 1 * 39 *

661 9473 MED6 MED6 T 75 24 0 32

672 8243 --- SMAP1 O 268 110 0 * 139 *

674 32708 --- ABT1 X 85 20 0 32

677 13849 nop56 NOP58 X 50 20 0 24

686 1939 dpck DCAKD O 160 67 0 * 85 *

689 18041 dgt1 KANSL2 X 50 24 0 * 38 *

693 17446 cfp1 CXXC1 C 99 39 0 * 50 *

708 5786 peter pan PPAN X 180 89 0 * 107 *

715 10542 bre1 RNF20 C P 100 31 0 40

725 10903 --- WBSCR22 X 118 37 0 51

729 5933 ime4 METTL3 A 210 81 0 * 91 *

734 5149 --- TLDC1 X 80 25 0 32

743 12135 c12.1 CWC15 M 146 80 1 * 123 *

758 9601 --- PNKP X 200 62 0 73

760 6946 glorund --- C Z 252 113 0 * 129 *

763 6480 frg1 FRG1 X 200 103 0 * 110 *

886 CEPRANI et al. / Turk J Biol

Table 2. (Continued).

768 6937 --- NIFK X 245 91 0 * 129 *

772 7757 prp3 PRPF3 S 180 80 0 * 133 *

788 10042 MBD-R2 --- T 201 95 6 * 205 *

807 3351 mRpL11 MRPL11 Z 138 39 0 51

808 2685 --- WBP11 S 150 59 0 * 73 *

810 15019 ------X 121 36 0 45

811 12249 miranda --- O 93 32 1 36

823 4916 me31B DDX6 A 175 60 0 66

824 1676 cactin CACTIN X 301 107 0 * 121 *

829 4326 mRpS17 --- Z 86 24 0 36

843 6686 --- SART1 X 90 28 0 28

850 5408 tribbles TRIB1 K 189 59 0 68

853 6057 SMC1 SMC1A C 180 63 1 * 77 *

860 13625 --- BUD13 S 82 29 1 44 *

862 2177 zip103B SLC39A9 O 150 48 0 62 *

867 10139 ------X 160 46 0 50

878 7003 msh6 MSH6 D 138 50 0 * 62 *

882 32066 CG6487 FAM49A X 159 73 0 * 107 *

883 5102 daughterless --- D T 265 82 0 99 *

885 5923 DNApolα73 POLA2 R 164 50 0 56

893 4449 ------X 300 107 4 * 139 *

900 4785 intS14 VWA9 X 80 35 1 * 58 *

927 17528 --- DCX K 110 41 0 50 *

930 3735 --- DIEXF X 110 29 0 48

932 4173 septin-2 SEPT11 O 109 34 0 43

949 1710 hcf HCFC1 C T 130 46 0 51

967 17068 ------X 126 41 0 59 *

978 6854 CTP synthase CTPS1 N 120 54 0 * 91 *

983 6977 cadherin 87a --- O 140 40 0 53

986 7656 --- UBE2R2 U 76 20 2 28

994 4866 --- IMP3 Z 102 36 1 42

995 7081 pex2 PEX2 O 170 42 0 59

998 8169 pms2 PMS2 D 125 40 0 58 *

1002 18005 beag IK O 122 49 1 * 56 *

1021 6744 --- EXD2 D 157 42 0 52

1023 2050 modulo --- X 234 86 0 * 110 *

1057 18190 --- MAPRE1 O 152 48 0 61

1061 5454 snRNP-U1-C SNRPC M S 218 65 1 79

1073 9680 dbp73D DDX51 A 176 52 0 62

887 CEPRANI et al. / Turk J Biol which the interfered cells show a mitotic index much lower the karyotype structure. In conclusion, the number of than that of the control; in this case, RNAi was performed genes important to maintain the stability of the genome is at least 3 times (and up to 4 times) and, if metaphases were much greater than expected. still not enough, data were also analyzed using Fisher’s For the majority of the identified genes (117/137, exact test (for ACs) and binomial distribution (for CAs) 85.4%), both the number of ACs and the number of CAs to confirm the results of the chi-square test. This allowed per 100 metaphases is significantly increased, compared to the identification of 137 genes (i.e. more than 12% of the control, using the chi-square test. However, for 20 genes 1132 scored) in which the number of ACs, the number of (14.6%), this is not true (Table 2, see the genes highlighted CAs, or both are significantly higher than in the control (P in bold font). Of them, 16 (11.7%) showed a significant ≤ 0.05 in the single test). It is noteworthy that more than increase only in CA absolute number, and 4 (2.9%) only in 80% of these genes (112 / 137) have a human counterpart the number of ACs. An analysis of the function of these 20 (Table 2). Of great interest is the discovery that 34 of them genes indicates that also in this case, many (8/20, 40%) are (~25%), to date, have a completely unknown function, and of unknown function, and only a few of them (2/20, 10%) 66 (~48%) have a function not directly related to DNA are directly related to DNA metabolism. Thus, also in these metabolism, since their annotation in FlyBase, the fruit cases it would have been impossible to guess their role fly database, does not report (as to Release 2013_04) for in genome stability without some types of experimental them a role in any of the following groups: i) chromatin/ evidence. chromosome structure, ii) DNA damage repair, iii) DNA Finally, we also identified a phenotype that is not present recombination, iv) DNA replication, v) nucleotide/ in control cells and that we called multifragmented cells nucleoside metabolism (Table 2). Consequently, only 27% (MCs), i.e. cells showing such a high number of CAs that it (37/137) of the genes in the list could have been predicted, does not allow the discerning of single . This on the basis of their established function or of their phenotype is easily recognizable: an average karyotype homology with other known genes, as capable of altering of S2 cells contains 12 chromosomes (Figure 1a), while

Figure 1. Cytology of S2 cells. A) Untreated control cell; note the chromosome complement, composed of 12 elements. B) An aberrant cell (AC) showing 1 chromosome involved in 2 rearrangements (CAs) at the same time, an X-type symmetric exchange (arrow) and a U-type asymmetric exchange (arrowhead). C) A multifragmented cell (MC); each asterisk marks a chromosome aberration (CA), either a single or a double chromatid break. Metaphases in panels B and C come from mus209-interfered cells. D, E, F) MC cells from rpA70- interfered cells; note the increasing level of chromosome fragmentation.

888 CEPRANI et al. / Turk J Biol in these cells the number of chromosomal structures, 3.2. Identification of new genes involved in chromosome including acentric fragments, is far higher that 20 (our integrity arbitrary threshold to separate ACs and MCs). Notably, In the previous paragraph, the results of single comparisons in control cells this phenotype was never scored in more between each interfered line and the control were shown. than 2000 metaphases. Instead, during the screening it was However, the analysis of hundreds of tests may cause the possible to identify 49/137 genes (35.8%) positive for this emergence of several false positives by chance. In order to phenotype, up to a MC/AC ratio value of ~75% (47/63) obtain protection against an inflated error of the first type, as in the case of the RpA-70 coding gene (Tables 2 and 3; and to maintain a P-value of ≤0.05 as our level of statistical Figure 1). Notably, in previous reports this phenotype was significance, Holm’s sequential Bonferroni procedure for identified only in RNAi experiments targeting RpA-70. multiple testing was used. Genes significant at the 0.05

Table 3. Genes showing the MC phenotype after RNAi-mediated silencing. Genes are ranked according to their descending MC/AC ratio. Column 1: Gene locus; Column 2: gene aliases (FlyBase, Release 2013_04); Column 3: functions (they are the same as in Table 2); Column 4: MC/AC ratio; Column 5: Holm–Bonferroni correction positivity.

Positive after Holm–Bonferroni Locus (CG) Aliases Function MC/AC × 1000 correction 9633 rpA-70 M R 746 yes 15220 --- R 211 yes 4978 mcm7 R 198 yes 8426 l(2)NC136 T 171 no 9193 mus209 M R 153 yes 7656 --- U 100 no 4206 mcm3 R 83 no 8975 rnrS N Y 77 yes 8711 cullin-4 E U 74 yes 7769 piccolo D 69 yes 10042 MBD-R2 T 63 yes 13329 cid M 50 no 3178 rrp1 D 43 yes 17161 grapes D K M 42 no 6197 --- P S 40 yes 10689 l(2)37Cb A 40 yes 11920 --- X 38 no 4449 --- X 37 yes 2925 noisette E M 36 yes 7014 rpS5b Z 36 yes 13625 --- S 34 yes 9273 rpA2 R 32 no 12249 miranda O 31 no 10354 rat1 O 30 yes 10667 orc1 R 30 no 3736 okra D 29 yes 4785 --- X 29 yes

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Table 3. (Continued).

4866 --- Z 28 no 9677 int6 P Z 27 yes 8068 su(var)2-10 C 24 yes 8989 his3.3b C 22 yes 10754 --- M 22 yes 5370 dcp-1 U Y 20 yes 5193 TfIIB T 20 yes 18005 beag O 20 yes 1966 acf1 C 19 yes 2848 trn-SR E S 19 yes 2260 --- X 19 yes 2199 --- X 19 yes 4654 dp T Y 18 yes 12050 --- X 17 yes 14749 GLE1 A E 16 yes 3181 Ts N 16 yes 6057 SMC1 C 16 yes 6453 --- X 15 no 5454 snRNP-U1-C M S 15 no 8878 --- K 14 yes 6349 DNApola180 R 13 yes 12135 c12.1 M 13 yes level after this correction are indicated by an asterisk in The first variable is their ranking position inside the Table 2. This allowed the identification of at least 81 genes original list created by Somma et al. (2008) (reported in with the same characteristics, i.e. either CAs only or both Table 2, Column 1). Their original work was based on ACs and CAs are significantly higher than in the control the coexpression of genes having a role in mitosis, with after RNAi. Their relative proportions as for the functions the rationale that genes involved in the same biological resulted similarly to those previously described, and also process tend to be transcriptionally coexpressed. The in this shorter list more than 80% of identified genes has a ranking position of any given gene (Somma et al., 2008) human ortholog. Interestingly, and differently from what consequently reflects its average coexpression value with was found with the single comparisons described before, respect to 6 reference genes. To get a general picture of with this statistical method none of the identified loci the present data, the 1132 selected genes were arbitrarily show a significant increase of ACs only. Consequently, at split into 11 blocks of 103 genes (with the exception of the the moment it is not possible to assess whether the increase last block, which contains 102 genes) and the number of of ACs only is a true phenotype for some silenced genes, or genes positive for ACs and/or CAs after RNAi treatment if it is just a byproduct of randomness. was evaluated. As shown in Figure 2, the genes seem to be 3.3. Genes causing AC-CA are randomly distributed as almost uniformly distributed and there is no evidence of a for ranking and map position tendency to concentrate in any portion of the coexpression To find out whether there is any correlation among the list. A comparison between the distribution of the 81 loci 81 genes identified in the present screening, 3 different and that of the remaining 1051 genes using the Mann– variables were analyzed separately using statistical Whitney test confirmed the above intuitive conclusion approaches. (P = 0.1168). Therefore, genes causing genome instability

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16 14 14

12 10 9 9 8 8 8 8 7 7 6 6 5

Number of genes 4 2 0 0 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 103 206 309 412 515 618 721 824 927 1030 1132 Rank poston Figure 2. Distribution of the genes causing chromosome breakage upon RNAi. The genes analyzed in the present screening were split into 11 classes of 103 genes each (with the exception of the last class, which has 102 genes) according to their rank position. For each class, the numbers of genes positive after applying the Holm–Bonferroni correction are reported. Note that the identified genes are almost uniformly distributed as for their rank position (see text for the statistical analysis). upon silencing are randomly and uniformly distributed did not show any significant deviation (the 1-sided p-value throughout the original list. equals 0.4648). Similarly, the number of positive genes on The second variable considered is the mapping position any given chromosome arm was proportional to the overall of the identified genes inside the D. melanogaster genome, number of protein-coding genes mapped on that arm to investigate if they share their chromosomal location, (Table 4), the single gene on the fourth chromosome being creating syntenic groups (Figure 3). For this purpose the excluded in computing the p-value; the chi-square test available data from FlyBase about the 102 chromosomal did not show any significant deviation from the expected bands that characterize the polytene chromosomes of the numbers (P = 0.5487). In conclusion, the 81 genes causing fruit fly were collected. In particular, the focus was on genome instability upon silencing are not clustered inside the number of protein-coding genes, which are the target the genome of D. melanogaster. of RNAi experiments. In order to check whether the 81 3.4. Identification of gene clusters inside the list according significant genes tend to concentrate on particular bands, to their cellular function an analysis was performed on the possible presence of The third variable evaluated is the cellular function of departures from a Poisson distribution. The variance test the 81 genes identified in the present screening, to check

Figure 3. Genes required for the chromosome integrity are not clustered inside the D. melanogaster genome. Asterisks mark the approximate cytogenetic position of the 81 genes positive after applying the Holm–Bonferroni correction for multiple tests; note the almost uniform distribution of the genes along the polytene chromosomes of the fruit fly.

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Table 4. Map distribution – chromosome arms (euchromatin only). Data according to FlyBase, Release FB2010_06.

Chromosome Length Number of Protein-coding Genes positive for arm (kb) genes (all) genes AC-CA X 22775 2341 2188 12 2L 22366 2899 2626 14 2R 20973 3299 2758 19 3L 23550 2960 2719 11 3R 28842 3701 3395 24 4 1339 84 84 1 Total 119,845 15,284 13,770 81 whether it is somehow related to their rank position. AC of ≥5%), namely rpA-70 (whose ratio MC/AC equals For this aim, the function reported in FlyBase (Release 75%) CG15220 (MC/AC = 21%), mcm7 (MC/AC = 20%), FB2013_04) was used as a reference. Sixteen arbitrary and mus209 (MC/AC = 15%), are involved in the DNA functional classes were created, after setting the rule replication. Additionally, these 4 genes are also the top 4 that a class must be represented by at least 3 genes/loci; as for the strength of their MC phenotype. Looking at the in all other cases, the genes/loci were assigned to the extended list, 3 more loci fall inside the MC/AC ≥5% group, class “other functions” (Table 2). These functional classes i.e. l(2)NC136 (MC/AC = 17%), CG7656 (MC/AC = 10%), were then further grouped into 5 macroclasses, which and mcm3 (MC/AC = 8%). Of these, mcm3 (position 7 in can be related to more general metabolic and/or cellular the extended list) is involved in DNA replication as well. mechanisms. The 5 macroclasses are: i) DNA metabolism- Taken together, these data suggest that an extreme MC/ related functions; ii) RNA metabolism-related functions; AC ratio phenotype could be typical of genes involved in iii) subcellular functions; iv) cell cycle progression-related DNA replication-related processes. Interestingly, among functions; v) unknown functions (Figure 4). Interestingly, the genes inducing the appearance of MCs after silencing, the Mann–Whitney test revealed a significant deviation the number of genes involved in the mitotic spindle from randomness for the distribution of the positive genes assembly is also relatively high (5 loci positive with the belonging to 2 of the macroclasses: the DNA metabolism- Holm–Bonferroni method out of 8 total loci), although for related genes (P = 0.0070) and the cell-cycle progression- them there is no particular accumulation in any part of the related genes (P = 0.0088). This means that these genes extended list. tend to be clustered toward the higher portion of the list. To characterize further this class of genes, their rank Notably, data of these 2 classes of genes are significant at position inside the list reported in Table 2 was considered, the 0.05 level also after the Holm–Bonferroni correction in order to check if their distribution is random (Figure for multiple tests. 5). An analysis with the Mann–Whitney test revealed 3.5. Genes causing high frequencies of MCs upon that these genes are not randomly distributed (P = silencing mainly have functions related to DNA 0.0243). These data indicate that genes causing extensive replication and tend to have high rankings chromosome damage tend to be coexpressed with the As described before, genes causing extensive chromosome mitotic genes originally described by Somma et al. in 2008. fragmentation (MCs) upon RNAi-mediated silencing are well represented among those causing CAs and ACs – 4. Discussion indeed, almost half of the genes (37/81, 45.7%) show this 4.1. Overview of the screening peculiar phenotype. Genes positive for the MC phenotype In the present work, we analyzed the karyotype of S2 are reported in Table 3, which includes also those genes cells treated with dsRNA against a chosen pool of genes. that are not positive after applying the Holm–Bonferroni These genes had previously been selected based on their method (in the present section, we will refer to the entire coexpression with other genes involved in various aspects content of Table 3 as an “extended list”). Notably, 4 of the of mitosis (Somma et al., 2008). The cited study and the 8 genes positive after applying this statistical correction data shown here demonstrate that this methodology allows and with a stronger phenotype (i.e. with a ratio of MC/ the identification of genes that play a role in chromosome

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6 6 6 5 EKOPUZ 5 CDNR 5 4 4 4 3 3 3 3 33 3 3 2 2 2 2 2 2 Number of genes Number of genes 111 1 1 1 1 1 00 0 0 0 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 103 206 309 412 515 618 721 824 927 1030 1132 103 206 309 412 515 618 721 824 927 1030 1132 Rank pos t on Rank poston 6 6 5 AST 5 MY 4 4 4 4 3 3 3 3 222 2 22 2 2 2 Number of genes Number of genes 1 1 1 1 1 1 1 0 00 0 00 0 0 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 103 206 309 412 515 618 721 824 927 1030 1132 103 206 309 412 515 618 721 824 927 1030 1132 Rank pos t on Rank pos t on 6 X 5 4 3 33 3 2 2 2 Number of genes 1 1 1 1 1 0 0 0 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 103 206 309 412 515 618 721 824 927 1030 1132 Rank poston Figure 4. Function distribution. The functions identified by the 81 genes selected with the Holm–Bonferroni method (Table 2) were grouped into 5 macroclasses. Genes/loci were split into the same 11 blocks reported in Figure 2. There is not a one-to-one relationship between genes and functions: a gene having 2–3 functions in the same macroclass was scored once, while a gene having 2–3 functions in different macroclasses was scored once for each macroclass; thus, the number of functions analyzed here (98) does not correspond to the number of genes selected with the Holm–Bonferroni method (81). CDNR: DNA metabolism-related functions (for the letter meaning, see Table 2); AST: RNA metabolism-related functions; EKOPUZ: other cellular functions; MY: cell cycle progression-related functions; X: unknown functions. Note that the CDNR and MY functions are not evenly distributed along the list of coexpression (see text for the statistical analysis). 8 7 7

6 5 5 5 5 4 4 4 3 3 2 Number of genes 2 1 1 1 0 0 001- 104- 207- 310- 413- 516- 619- 722- 825- 928- 1031- 103 206 309 412 515 618 721 824 927 1030 1132 Rank poston Figure 5. Distribution of the genes causing extreme chromosome fragmentation (MCs) upon RNAi. Note that these loci tend to accumulate toward the top half of the list described by Somma et al. (2008) (see text for the statistical analysis).

893 CEPRANI et al. / Turk J Biol integrity. S2 cells show a relatively high, yet constant, level Since the coexpression-based selection worked fine for of spontaneous CAs (Table 1); this fact, and the relatively the isolation of new genes involved in mitosis (Somma et simple chromosome complement of this cell lineage, al., 2008), and since the cytogenetic methodology works makes S2 cultured cells a suitable model for the karyotype fine as well for the study of genes involved in chromosome analysis and for the identification of genes whose function structure, merging these 2 approaches (i.e. creating is related to the maintenance of chromosome integrity. In coexpression lists using genes known to be related to their original analysis, Somma et al. found a lower number chromosome integrity) should allow the identification of of genes causing chromosomal damage upon RNAi novel genes whose cellular role is still unknown. At this treatment. This difference may be explained by the different point, the goal is not trying to understand why a given statistical approach we used. In their report, positive genes gene causes a certain phenotype, but rather to identify were identified by applying a high threshold to the total how many and which genes are responsible, directly or AC/CA values, to compensate for lower cell scores. Our indirectly, for this phenotype. For example, there are increased number of observations, obtained by repeating no clues about why 7/81 (8.6%) genes have a described the interference up to 4 times per gene, allowed us to function connected to mitotic spindle assembly. However, perform a double, sequential statistical analysis, which knowing that these 7 genes may also cause chromosome permitted the identification of at least 81 genes positive for instability is certainly an important discovery and indicates this phenotype. that, potentially, other genes with the same function We are aware that, apparently, there is a main might induce a comparable phenotype on chromosomes; limitation in this screening, due to the method used to this in turn indicates that genes responsible for mitotic shrink the number of examined genes. The reference list spindle assembly are potentially able to cause neoplastic (Somma et al., 2008) relies on the average coexpression transformation by induction of segmental aneuploidy. value (evaluated with Pearson’s correlation coefficient) Similar conclusions may be drawn for the other classes of of D. melanogaster genes with other 6 mitosis-related genes described. genes. The choice of 6 reference genes is arbitrary; any The reason why these genes cause the CA phenotype other list derived averaging 6 (or even more) different is, in many cases, unknown. Several scenarios may be lists could have been used, and at the moment it is not depicted to explain these data, and probably more than one known if this would have created a significantly different should be applied to the genes here described. The easiest record of coexpressed genes. Moreover, our screening explanation is that these genes encode proteins that play was performed for a phenotype (chromosome integrity) multiple roles inside the cell, one of which is maintaining that was not straightly related to their gene selection the chromosome integrity – a function not described method. For these reasons, it is not surprising that genes before and that partly addresses the so-called “g-value directly involved in the DNA damage recognition/repair, paradox” (Hahn and Wray, 2002). This is reasonable, or in general DNA metabolism (nucleotide biosynthesis, since available analyses of mutant flies did not necessarily DNA replication, chromatin/chromosome structure), cover all aspects of cell biology. Another possibility is that are poorly represented among those identified – they are approximately 32% of the total after the Holm–Bonferroni the reported function is simply wrong. In some cases no correction. Instead, a lot of found genes either have mutants are available for a given locus, and the gene role unknown function (~21%) or are assigned to functions is inferred only on the basis of sequence similarity with not apparently related to chromosome integrity (~47%). other genes of known function. Finally, it may be also Given that segmental aneuploidy is potentially harmful for assumed that the gene function is not “directly” related to cell survival and is a recurrent step during tumorigenesis, DNA damage, and that the chromosome breakage occurs all genes causing such a phenotype are potentially only after one or more intermediate metabolic steps that, “indirect” oncogenes, since their clastogenic action is able for some reasons, are not visible in mutants (if available). to alter the genetic equilibrium of the cell. Consequently, Indeed, cell cultures are not complete organisms, and the possibility to have a list of such genes is crucial for RNAi is a very powerful technique: it is possible that the comprehension of the neoplastic transformation and these phenotypes are just not visible in mutant flies, for the study of the possible role of these genes in this either because of the presence of redundant functions, or phenomenon. Moreover, these genes may be used for because cells undergo cell cycle arrest that does not allow patient screening and as potential targets of antitumor the analysis of the karyotype, or even because some genes therapy. In addition, the fact that 2 of the reference genes are not active in certain tissues (the fruit fly karyotype encode proteins having important roles also outside of is usually analyzed in larval neuroblasts, and S2 is an mitosis (Cid/CENPA deposition occurs during the S phase undifferentiated, embryo-derived cell lineage). In any case, and EB1 plays important roles during the interphase) the conclusion is that the list of genes that potentially may further broadens the record of interesting genes found. alter the chromosome structure is surely much longer

894 CEPRANI et al. / Turk J Biol than anticipated, and one way to compile such a list is, proteins, so the entire cellular control machinery is unexpectedly, to search for genes not related to genome impaired; ii) these genes play a role in the activation of one integrity. or more still-working checkpoints that, if not activated 4.2. Identification of gene clusters at the proper time, are not able to function anymore; iii) A great effort of the present screening was the search for the silencing of these genes destabilizes the chromosome relationships among the identified genes, especially for structure immediately before the mitotic chromosome their relative position inside the coexpression list, for condensation, so checkpoints do not have enough time to their physical position inside the genome, and for their be activated prior to the metaphase plate establishment. role inside the cell. The result is that the 81 loci found are Further analysis of these genes is required to discriminate almost evenly distributed for both their relative position in among these possibilities, or to postulate others. the coexpression list, and for their map position inside the The present study also allowed the identification of a D. melanogaster genome. This roughly uniform scattering class of genes causing extensive chromosome breakage suggests a functional and evolutionary meaning. As after RNAi and recognizable by the presence of MCs, described in Section 1, the loss of a genomic portion is a phenotype absent in controls. Analysis of these loci frequently associated with the neoplastic transformation. revealed that many of them, and particularly those Consequently, an even localization of the genes causing showing the stronger phenotype (as measured by the MC/ chromosomal breaks upon malfunction determines AC ratio), belong to the DNA replication functional class. the fact that any deletion of any genomic region will DNA replication, strictly speaking, is not a mitosis-related impair the entire genome stability. Thus, it is possible to function, but probably these genes were selected because, postulate some kind of “positional information” related as described before, 2 of the 6 reference genes also act to these genes that allows the cell to indirectly control during interphase. This fact allowed description of what the overall stability of the genome. In other words, any the effect of RNAi is on this type of genes and the drawing random genomic damage – independently of its cause – of some conclusions. First, many genes related to DNA will frequently induce the associated loss of at least one replication, after silencing, may show a similar phenotype. gene controlling the overall genomic stability; this would This may be easily verified by performing RNAi against further destabilize the genome, inducing cell death in most genes belonging to this functional group. Second, a given cases. Further studies are needed to verify if this almost gene showing, upon silencing, a high MC/AC ratio, will even distribution is typical of Drosophila or is evolutionary likely take part in DNA replication. This of course will conserved; if it is conserved, this would partly explain, be useful for genes either with an unrelated or without a among other things, why some genomic rearrangements known function, and in this case the verification should be in cancer cells are more frequent than others. based on the cytogenetic analysis of mutants (if available) When the positive genes were grouped into functional and/or on biochemical evidences (for example, interaction macroclasses, other interesting results arose. At least for with known DNA replication proteins or in vitro functional 2 macroclasses, the positive genes tend to be clustered analysis). Ideally, this should provide a role to at least some toward the top of the list: those connected to DNA genes with unknown function but similar phenotype. metabolism, and those connected to cell cycle progression. Third, according to the present data, these genes tend to The discovery of the first class of genes was not surprising, be coexpressed with each other (accumulation in the top but the second class of loci, comprising genes involved in half of the list), so in principle the creation of appropriate apoptosis and mitotic spindle assembly, was unpredictable. coexpression lists using known genes of this functional We would expect that impairing mitotic spindle assembly class should give good results in the search of new DNA would result in an activation of the spindle checkpoint replication-related loci. able to stop the cell cycle; alternatively (if this checkpoint 4.3. Final remarks and future perspectives is the interfered function), we would expect the cell to The aim of the present screening was to find genes causing go on dividing, but would also expect that a subsequent chromosome integrity failure upon silencing. The results interphase checkpoint would induce its cycle arrest. were obtained using, as a selection criterion, coexpression Similar hypotheses could be made for the genes involved with genes not related to this phenotype. Our results in apoptosis. Instead, RNAi on these genes produces a indicate that, at least in some cases, these genes encode potent effect on the chromosome integrity, and the high proteins with multiple, different roles. Indeed, this is a level of CAs that we found suggests that their formation is relatively new and not completely surprising finding: probably irrespective of other cellular control mechanisms. searching for new gene functions implies that the These results may be explained in several ways, and “previous” function should not be considered during the we suggest here 3: i) the silencing of these genes causes screening. These data in part fill the so-called “g-value an inactivation cascade targeting also other checkpoint paradox” (Hahn and Wray, 2002), according to which

895 CEPRANI et al. / Turk J Biol there are too many functions compared to the number Acknowledgments of protein-coding genes. Our data show that the genes This work was achieved thanks to the generosity and whose function is preventing chromosome breakage kindness of Emeritus Professor M Gatti (Sapienza are far more numerous than expected, and potentially University of Rome), who permitted us to use his laboratory they might be involved in tumorigenesis through the facilities and reagents to perform the experiments. We are induction of segmental aneuploidy. Since many genes are thus deeply grateful to him and his staff. We also gratefully apparently unrelated with this phenotype, a screen of the acknowledge Dr Alessandro Porrello (Lineberger entire D. melanogaster genome would be invaluable for the Comprehensive Cancer Center, University of North identification of such loci; in fact, our data strongly suggest Carolina-Chapel Hill, Chapel Hill, NC, USA) for providing that any selection criterion would result in an incomplete us with important comments and suggestions and for the record of genes. careful review of this manuscript.

References

Agresti A (1992). A survey of exact inference for contingency tables. Fukuhara S, Rowley JD, Variakojis D, Golomb HM (1979). Statist Sci 7: 131–153. Chromosome abnormalities in poorly differentiated lymphocytic leukemia. Cancer Res 39: 3119–3128. Aguilera A, Gómez-González B (2008). Genome instability: a mechanistic view of its causes and consequences. Nat Rev Guo S, Kemphues K (1995). par-1, a gene required for establishing Genet 9: 204–217. polarity in C. elegans embryos, encodes a putative Ser/Thr kinase that is asymmetrically distributed. Cell 81: 611–620. Aravind L, Watanabe H, Lipman DJ, Koonin EV (2000). Lineage- specific loss and divergence of functionally linked genes in Hahn MW, Wray GA (2002). The g-value paradox. Evol Dev 4: 73–75. eukaryotes. P Natl Acad Sci USA 97: 11319–11324. Hatano M, Roberts CW, Minden M, Crist WM, Korsmeyer SJ (1991). Bannon JH, McGee MM (2009). Understanding the role of Deregulation of a homeobox gene, HOX11, by the t(10;14) in T aneuploidy in tumorigenesis. Biochem Soc Trans 37: 910–913. cell leukemia. Science 253: 79–82. Brown NH, Kafatos FC (1988). Functional cDNA libraries from Henrichsen CN, Chaignat E, Reymond A (2009). Copy number Drosophila embryos. J Mol Biol 203: 425–437. variants, diseases and gene expression. Hum Mol Genet 18: R1–R8. Cerutti H, Casas-Mollano J (2006). On the origin and functions of RNA-mediated silencing: from protists to man. Curr Genet 50: Holm S (1979). A simple sequential rejective multiple test procedure. 81–99. Scand J Statist 6: 65–70. Clémenson C, Marsolier-Kergoat MC (2009). DNA damage Huertas P (2010). DNA resection in eukaryotes: deciding how to fix checkpoint inactivation: adaptation and recovery. DNA Repair the break. Nat Struct Mol Biol 17: 11–16. (Amst) 8: 1101–1109. Kerzendorfer C, O’Driscoll M (2009). Human DNA damage response Conrad C, Gerlich DW (2010). Automated microscopy for high- and repair deficiency syndromes: linking genomic instability content RNAi screening. J Cell Biol 188: 453–461. and cell cycle checkpoint proficiency. DNA Repair (Amst) 8: 1139–1152. DaRocha W, Otsu K, Teixeira S, Donelson J (2004). Tests of cytoplasmic RNA interference (RNAi) and construction of a Khanna KK, Jackson SP (2001). DNA double-strand breaks: tetracycline-inducible T7 promoter system in Trypanosoma signaling, repair and the cancer connection. Nat Genet 27: cruzi. Mol Biochem Parasitol 133: 175–186. 247–254. Drinnenberg IA, Weinberg DE, Xie KT, Nower JP, Wolfe KH, Fink Le Beau MM, Larson RA, Bitter MA, Vardiman JW, Golomb HM, GR, Bartel DP (2009). RNAi in budding yeast. Science 326: Rowley JD (1983). Association of inv(16)(p13q22) with 544–550. abnormal marrow eosinophils in acute myelomonocytic leukemia: a unique cytogenetic-clinicopathologic association. Ecker JR, Davis RW (1986). Inhibition of gene expression in plant N Engl J Med 309: 630–636. cells by expression of antisense RNA. P Natl Acad Sci USA 83: 5372–5376. Levan A (1967). Some current problems of cancer cytogenetics. Hereditas 57: 343–355. Finger LR, Harvey RC, Moore RC, Showe LC, Croce CM (1986). A common mechanism of chromosomal translocation in T and B Lieber MR (2010). The mechanism of double-strand DNA break cell neoplasia. Science 234: 982–985. repair by the nonhomologous DNA end-joining pathway. Annu Rev Biochem 79: 181–211. Fire A, Xu S, Montgomery M, Kostas S, Driver S, Mello CC (1998). Potent and specific genetic interference by double-stranded Lieber MR, Yu K, Raghavan SC (2006). Roles of nonhomologous RNA in Caenorhabditis elegans. Nature 391: 806–811. DNA end joining, V(D)J recombination, and class switch recombination in chromosomal translocations. DNA Repair (Amst) 5: 1234–1245.

896 CEPRANI et al. / Turk J Biol

McClintock B (1951). Chromosome organization and genic Romano N, Macino G (1992). Quelling: transient inactivation of expression. Cold Spring Harb Symp Quant Biol 16: 13–47. gene expression in Neurospora crassa by transformation with homologous sequences. Mol Microbiol 6: 3343–3353. Mills KD, Ferguson DO, Alt FW (2003). The role of DNA breaks in genomic instability and tumorigenesis. Immunol Rev 194: Rowley JD (1973). Identification of a translocation with quinacrine 77–95. fluorescence in a patient with acute leukemia. Ann Genet 16: 109–112. Mitelman F, Johansson B, Mertens F, editors (2010). Mitelman Database of Chromosome Aberrations and Gene Fusions San Filippo J, Sung P, Klein H (2008). Mechanism of eukaryotic in Cancer. Bethesda, MD, USA: National Cancer Institute. homologous recombination. Annu Rev Biochem 77: 229–257. Available online at http://cgap.nci.nih.gov/Chromosomes/ Somma MP, Ceprani F, Bucciarelli E, Naim V, De Arcangelis V, Mitelman. Piergentili R, Palena A, Ciapponi L, Giansanti MG, Pellacani C, Mohr S, Bakal C, Perrimon N (2010). Genomic screening with RNAi: Petrucci R, Cenci G, Vernì F, Fasulo B, Goldberg ML, Di Cunto results and challenges, Annu Rev Biochem 79: 37–64. F, Gatti M (2008). Identification of Drosophila mitotic genes by combining co-expression analysis and RNA interference. PLoS Nakayashiki H, Kadotani N, Mayama S (2006). Evolution and Genet 4: e1000126. diversification of RNA silencing proteins in fungi. J Mol Evol 63: 127–135. Somma MP, Fasulo B, Cenci G, Cundari E, Gatti M (2002). Molecular dissection of cytokinesis by RNA interference in Drosophila Napoli C, Lemieux C, Jorgensen R (1990). Introduction of a chimeric cultured cells. Mol Biol Cell 13: 2448–2460. chalcone synthase gene into Petunia results in reversible co- suppression of homologous genes in trans. Plant Cell 2: 279– Streffer C (2010). Strong association between cancer and genomic 289. instability. Radiat Environ Biophys 49: 125–131. Natarajan AT, Obe G (1978). Molecular mechanisms involved in Torres EM, Williams BR, Amon A (2008). Aneuploidy: cells losing the production of chromosomal aberrations. I. Utilization their balance. Genetics 179: 737–746. of Neurospora endonuclease for the study of aberration Tsai AG, Lieber MR (2010). Mechanisms of chromosomal production in G2 stage of the cell cycle. Mutat Res 52: 137–149. rearrangement in the . BMC Genomics 11: S1. Nowell P, Hungerford D (1960). A minute chromosome in human Tsujimoto Y, Finger LR, Yunis J, Nowell PC, Croce CM (1984). chronic granulocytic leukemia. Science 132: 1497. Cloning of the chromosome breakpoint of neoplastic B cells Obe G, Johannes C, Schulte-Frohlinde D (1992). DNA double- with the t(14;18) chromosome translocation. Science 266: strand breaks induced by sparsely ionizing radiation and 1097–1099. endonucleases as critical lesions for cell death, chromosomal Vamvakas S, Vock EH, Lutz WK (1997). On the role of DNA double- aberrations, mutations and oncogenic transformation. strand breaks in toxicity and carcinogenesis. Crit Rev Toxicol Mutagenesis 7: 3–12. 27: 155–174. Obe G, Pfeiffer P, Savage JR, Johannes C, Goedecke W, Jeppesen P, van Gent DC, Hoeijmakers JH, Kanaar R (2001). Chromosomal Natarajan AT, Martínez-López W, Folle GA, Drets ME (2002). stability and the DNA double-stranded break connection. Nat Chromosomal aberrations: formation, identification and Rev Genet 2: 196–206. distribution. Mutat Res 504: 17–36. Veitia RA, Bottani S, Birchler JA (2008). Cellular reactions to gene Pal-Bhadra M, Bhadra U, Birchler J (1997). Cosuppression in dosage imbalance: genomic, transcriptomic and proteomic Drosophila: gene silencing of Alcohol dehydrogenase by white- effects. Trends Genet 24: 390–397. Adh transgenes is Polycomb dependent. Cell 90: 479–490. Weinstock DM, Richardson CA, Elliott B, Jasin M (2006). Modeling Rabbitts TH, Boehm T, Mengle-Gaw L (1988). Chromosomal oncogenic translocations: distinct roles for double-strand break abnormalities in lymphoid tumors: mechanism and role in repair pathways in translocation formation in mammalian tumor pathogenesis. Trends Genet 4: 300–304. cells. DNA Repair (Amst) 5: 1065–1074. Richardson C, Jasin M (2000). Frequent chromosomal translocations Williams BR, Amon A (2009). Aneuploidy: cancer’s fatal flaw? induced by DNA double-strand breaks. Nature 405: 697–700. Cancer Res 69: 5289–5291. Robinson K, Beverley S (2003). Improvements in transfection Zech L, Haglund U, Nilsson K, Klein G (1976). Characteristic efficiency and tests of RNA interference (RNAi) approaches in chromosomal abnormalities in biopsies and lymphoid-cell the protozoan parasite Leishmania. Mol Biochem Parasitol 128: lines from patients with Burkitt and non-Burkitt lymphomas. 217–228. Int J Cancer 17: 47–56.

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