Linkage disequilibrium (LD) between genes at linked or independent loci can occur at gametic and zygotic levels known asgametic LD and zygotic LD, respectively. Gametic LD is well known for its roles in fine-scale mapping of quantitative trait loci, genomic selection and evolutionary inference. The less-well studied is the zygotic LD and its components that can be also estimated directly from the unphased SNPs.This study was set up to investigate the genome-wide extent and patterns of zygotic LD and its components in a crossbred cattle population using the genomic data from the Illumina BovineSNP50 beadchip. The animal population arose from repeated crossbreeding of multiple breeds and selection for growth and cow reproduction. The study showed that similar genomic structures in gametic and zygotic LD were observed, with zygotic LD decaying faster than gametic LD over marker distance. The trigenic and quadrigenic disequilibria were generally two- to three-fold smaller than the usual digenic disequilibria (gametic or composite LD). There was less power of testing for these high-order genic disequilibria than for the digenic disequilibria. The power estimates decreased with the marker distance between markers though the decay trend is more obvious for the digenic disequilibria than for high-order disequilibria.This study is the first major genome-wide survey of all non-allelic associations between pairs of SNPs in a cattle population. Such analysis allows us to assess the relative importance of gametic LD vs. all other non-allelic genic LDs regardless of whether or not the population is in HWE. The observed predominance of digenic LD (gametic or composite LD) coupled with insignificant high-order trigenic and quadrigenic disequilibria supports the current intensive focus on the use of high-density SNP markers for genome-wide association studies and genomic selection activities in the cattle population. The recent advancement in molecular biology has enabled the rapid development of single nucleotide polymorphism (SNP) genotyping technology, thereby making the genotyping of cheap and abundant SNP markers possible in many livestock species . CommercWith the availability of high-density SNPs, many studies have also conducted population genetic analysis of gametic LD in cattle and other animal species e.g., -8). Howe. Howe8])In this study, we investigate the genome-wide extent and patterns of LD in a crossbred cattle population using the genomic data typed with the Illumina BovineSNP50 beadchip. The animals in this study are the progenies of three synthetic lines that were maintained separately at the University of Alberta Kinsella Research Ranch during 1960 to 1989  and wereThe Kinsella beef composite population has been the subject of numerous breeding and genomic studies e.g., -17). How. How17])The estimates of power of chi-square tests for zygotic LD and individual genic disequilibria were plotted against the marker distances of ≤ 50 Mb for all SNP pairs on 29 autosomes Figure . This plSimilar trend of LD decay was observed on individual chromosomes. However, given the limited numbers of SNP pairs over the nine intervals within the short distance of ≤ 5 Mb on individual chromosomes, the estimates of power of chi-square test statistic for gametic, composite and zygotic LDs are presented for two groups of SNP pairs, those with a distance of ≤ 50 Mb (Linked Group) and those with a distance of > 50 Mb (Unlinked Group) Table . As in tThe estimates of power of the chi-square tests for trigenic and quadrigenic components of the zygotic LD are given for the Linked (≤ 50 Mb) and Unlinked (> 50 Mb) Groups Table . For a gPresented in Table The mean values of LDs and power estimates for chi-square tests for gametic, composite, trigenic, quadrigenic and zygotic LD were summarized for all syntenic marker pairs (intra-chromosome pairs) and all non-syntenic pairs (inter-chromosome pairs) Table . The meaThe power of chi-square tests for individual genic disequilibria was estimated for syntenic marker pairs belonging to nine classes of minor allele frequency (MAF) with three MAF intervals  at each of the two loci on each of 29 chromosomes as well as for non-syntenic marker pairs on two different chromosomes. The power estimates for non-syntenic marker pairs were calculated on all 406 [29(29-1)/2] chromosome pairs. In Table The power estimates of chi-square tests for digenic, trigenic, and quadrigenic disequilibria increased with the increasing MAF at both loci, whereas those for zygotic LD decreased with the increasing MAF Table . For exaThis study represents the first major genome-wide survey of high-order genic disequilibria between three or four genes at pairs of loci in a farmed animal species. We chose the Kinsella composite beef population for such a survey because continued crossbreeding and selection for growth and cow reproduction would have made the population to stay in a HWD condition, thereby providing an excellent opportunity for uncovering the high-order genic disequilibria. The survey showed that the trigenic and quadrigenic disequilibria were generally two to three times smaller than the usual digenic disequilibria (gametic or composite LD) Table . CorrespNe) as a major cause of LD in cattle populations. The effective population size was large  before domestication, but was drastically declined to 1,000-2,000 after domestication. In many cattle breeds, this number was further declined to approximately 100 after recent breed formation. This sharp decline in Ne causes some LD to exist at long distances. The strong effects of selection and population admixture expected in our crossbred cattle population would also contribute further to greater LD. It should be recognized that the effect of selection on LD involves markers or genes that are localized at certain parts of the genome and thus selection-induced LD would have no or little relation with physical distance.The power estimates for zygotic LD and its components Tables  and 3 weMost studies have focused on gametic LD for individual pure-breed cattle populations. Our estimates of gametic LD for the Kinsella composite beef population are similar to those reported for Holstein and other pure-breed cattle in the recent literature -8. In far et al.  used a so et al.  calculatIt is somewhat surprising to see similar values of gametic LD in our crossbred population and in those pure-bred populations as described above. In the pure-breed studies, the focus has been on gametic LD that is estimable often under the HWE assumption . We suggTo the best of our knowledge, the only other survey of high-order genic disequilibria was made by Liu et al. . Using tOur study showed that digenic disequilibria (gametic or composite LD) were much more important than trigenic and quadrigenic disequilibria in terms of magnitudes and test power. This observation coupled with the similarity of the two digenic disequilibria (gametic and composite LD) is consistent with the low level of HWD in our beef population (only 8.2% of SNPs had a significant HWD as shown in Table A3). Under HWE, all non-gametic associations would be zero and thus composite LD would equal to gametic LD and three- and four-gene disequilibrium would be negligible ,20. MoreOur study is the first empirical evaluation of the dependence of LD on allele frequency. The power estimates of chi-square tests for digenic, trigenic and quadrigenic disequilibria increased with the increasing gene frequency at both loci, but those for zygotic LD decreased with the increasing gene frequency. Weir and Cockerham  used extad hoc measure of non-allelic associations (r2) only when the chi-square statistics are calculated from a 2 × 2 contingency table   . It is a, (J-1)] , 20]) t) tad hocOur study has practical implications. The main result from our study is the predominance of digenic disequilibria coupled with insignificant high-order disequilibria. This result supports the current intensive effort of using gametic LD for GWAS and genomic selection in cattle and other animal species. It has been demonstrated  that gaThis study is the first major genome-wide survey of high-order genic disequilibria between three or four genes at pairs of 50K SNP markers in a farmed animal species. The survey showed that the trigenic and quadrigenic disequilibria were generally insignificant and two- to three-fold smaller than the usual digenic disequilibria (gametic or composite LD). The powers of tests for these high-order genic disequilibria dropped rapidly even at a very short distance between SNPs. These results support the current intensive focus on the use of gametic LD for GWAS and genomic selection activities in the Kinsella composite beef population.The Kinsella beef composite population has been described in our recent studies on QTL mapping, candidate gene identification and genomic selection . Here we recapitulate the essential details of this population. It was produced by crossing between Angus, Charolais, or University of Alberta hybrid bulls and a hybrid dam line. The hybrid dam line was obtained by crossing among three composite cattle lines, namely beef synthetic 1 (SY1), beef synthetic 2 (SY2) and dairy × beef synthetic (SD) for more than 10 years after 30 years (1960-1990) single-sire crossbreeding. SY1 was composed of approximately 33% each of Angus and Charolais, 20% Galloway, 5% Brown Swiss, and small amounts of other breeds. SY2 was composed of approximately 60% Hereford and 40% other beef breeds mainly including Augus, Charolais and Galloway. SD was composed of approximately 60% dairy cattle  and approximately 40% of other breeds, mainly including Angus and Charolais . The bloA total of 51,828 SNP markers were originally obtained in the genotyped data. These markers were distributed across 29 autosomes and one sex chromosome in the entire bovine genome. For our analyses, we only used 43,124 SNPs after removing those markers (i) with monomorphism, (ii) with unknown genomic position and (iii) on the sex chromosome, (iv) with minor allele frequency (MAF) of ≤ 2% [A and a at locus A and B and b at locus B, there are nine possible genotypes (ten if the coupling and repulsion double heterozygotes are distinguishable). Following Yang [uy and vz with uv = A or a, and yz = B or b. The genotypic frequencies at individual loci are the marginal totals of the appropriate two-locus genotypic frequencies. For example, the frequency of genotype AA is,For two loci, each with two alleles, ing Yang , we wrotA, the frequency of allele A is, a is pa = 1- pA.With the genotypic frequencies at locus A are, B are, Departures from HWE at locus DA = DB = 0). In a non-random mating population, nonzero HWD is measured by the fixation index which can be either positive when there is inbreeding or negative when inbreeding is avoided. For example, the HWD at locus A can be written as DA = fApApa, where A, with -1 ≤ fA ≤ +1.In a random mating population, HWD disappears  is the deviation of a frequency from that based on random association of genes and accounting for any lower order disequilibria. The usual gametic LD  in our unphased SNP data could not be distinguished, we used the composite LD (ΔAB) and a composite quadrigenic component (ΔAABB) in place of gametic and quadrigenic disequilibria. Thus, the zygotic LD for genotype AABB (Since the two types of double heterozygote (whereandIt should be noted from equations (1) and (2) that the two trigenic disequilibria in (2) were rewritten without superscripts for notational simplicity.Following Weir and Cockerham  and WeirA over replicate samples of size n would be, However, the ML estimates might be biased because they would involve quadratic terms of multinomial variables. For example, the expectation of the squared gene frequency of allele DA is the HWD measure at locus A[n = 1023 animals) in our data set, we invoked large-sample theory for statistical inference about genic disequilibria. Thus, we ignored the possible biases of order 1/n.where t locus A. With thD or Δ, along with its sampling variance, [Var(With a ML estimate (0: D = 0 or H0: Δ = 0). Assuming the asymptotic normality of the ML estimate, X2 under the hypothesis of zero disequilibrium would be distributed as chi-square with one degree of freedom.to test the hypothesis of zero disequilibrium  or a false hypothesis may not be rejected (Type II error). The probability of Type I error is measured by the significance level whereas the probability of Type II error is often related to the power of the test. Generally, as the power is the probability of rejecting a false hypothesis, it equals to one minus the probability of Type II error. In the present study, however, we adopted a different use of the power as proposed by Weir and Cockerham r2) has been routinely used as a measure of gametic LD (i = GLDCLD or ZLG) to test for the significance of the LD estimate. It is known from the literature [In the past, the squared correlation  markers (m) and chromosome length  for 29 bovine autosomes (BTA 1 to BTA 29) in the Kinsella composite beef population. Mean, standard deviation (SD), minimum and maximum distances (in base pairs) between all pairs of adjacent markers are also presented. Table A2. The proportion of syntenic SNP pairs with out-of-bound estimates of generalized measures of squared correlation for trigenic and quadrigenic disequilibria in the Kinsella composite population. Table A3. Summary statistics on single-locus heterozygosity, fixation index and Hardy-Weinberg disequilibrium (HWD) averaged over all SNP markers on 29 bovine autosomes (BTA 1 to BTA 29) in the Kinsella composite beef population. Appendix: Sampling variances of individual genic disequilibria in zygotic LD.Click here for file


Panitumumab is a fully human antibody against the epidermal growth factor receptor that is indicated for the treatment of metastatic colorectal cancer (mCRC) after disease progression on standard chemotherapy. The purpose of this analysis was to examine the immunogenicity of panitumumab and to evaluate the effect of anti-panitumumab antibodies on pharmacokinetic and safety profiles in patients with mCRC receiving panitumumab in combination with oxaliplatin- or irinotecan-based chemotherapies.Three validated assays  were used to detect the presence of anti-panitumumab antibodies in serum samples collected from patients enrolled in four panitumumab combination chemotherapy clinical trials. The impact of anti-panitumumab antibodies on pharmacokinetic and safety profiles was analyzed using population pharmacokinetic analysis and descriptive statistics, respectively.KRAS and in patients receiving oxaliplatin- or irinotecan-based chemotherapies. No evidence of an altered pharmacokinetic or safety profile was found in patients who tested positive for anti-panitumumab antibodies.Of 1124 patients treated with panitumumab in combination with oxaliplatin- or irinotecan-based chemotherapy with postbaseline samples available for testing, 20 (1.8%) patients developed binding antibodies and 2 (0.2%) developed neutralizing antibodies. The incidence of anti-panitumumab antibodies was similar in patients with tumors expressing wild-type or mutant The immunogenicity of panitumumab in the combination chemotherapy setting was infrequent and similar to the immunogenicity observed in the monotherapy setting. Panitumumab immunogenicity did not appear to alter pharmacokinetic or safety profiles. This low rate of immunogenicity may be attributed to the fully human nature of panitumumab.NCT00339183 (study 20050181), NCT00411450 (study 20060277), NCT00332163 (study 20050184), and NCT00364013 (study 20050203).ClinicalTrials.gov:  Panitumumab is indicated as monotherapy for the treatment of metastatic colorectal cancer (mCRC) after disease progression on fluoropyrimidine, oxaliplatin, and irinotecan chemotherapy regimens in the United States (US) and European Union (EU) [KRAS mutations in codon 12 or 13 is not recommended [KRAS [KRAS.Panitumumab is a high affinity Kd = 5 × 011 M fuled [KRAS  in patieAn important concern with the administration of therapeutic proteins is the potential to induce an immune response. Immune responses against biologics can affect their pharmacokinetics , safety (by eliciting injection-site reactions or hypersensitivity), or reduce efficacy . TherefoN-glycolylneuraminic acid has been demonstrated on cetuximab, which is introduced by the manufacturing process [Cetuximab, an anti-EGFR chimeric mouse-human monoclonal antibody, had a reportedly low incidence of anti-chimeric antibodies as measured by a radiometric assay in early phase clinical trials ,11. Howe process . Most or process .The fully human nature of panitumumab was expected to decrease the rate of immunogenicity compared with therapeutic antibodies containing nonhuman coding sequences . However® assay [The immunogenicity of panitumumab when administered as monotherapy was evaluated in clinical trials of patients with mCRC and other solid tumors. The incidence of binding antibodies to panitumumab (excluding predose and transient positive patients) was < 1% as detected by the acid dissociation enzyme-linked immunosorbent assay (ELISA)  and 4.6%® assay . The incKRAS status (wild-type or mutant) on efficacy endpoints in patients receiving panitumumab plus FOLFIRI as second-line therapy for mCRC [Serum samples for anti-panitumumab antibody testing were collected from mCRC patients enrolled in 4 panitumumab clinical trials . Patients in these studies received irinotecan-based (including FOLFIRI) or oxaliplatin-based (FOLFOX) chemotherapies with or without panitumumab. Study 20050184 (STEPP) was a phase 2, open-label, randomized trial to compare pre-emptive skin toxicity therapy with reactive treatment in patients with mCRC receiving panitumumab plus irinotecan or FOLFIRI . Study 2Per the study protocols, serum samples for immunogenicity assessments were collected from all panitumumab-treated patients prior to study treatment (baseline samples) and from all patients at the safety follow-up visit . Serum samples used for the measurement of panitumumab concentration (pharmacokinetic assessments) were collected from patients enrolled in study 20050181 before dosing on cycle 1 day 1 and cycle 2 day 1, every 8 weeks starting at week 8, and at the safety follow-up visit (30 ± 3 days after administration of the last dose).KRAS mutation status was determined using DNA isolated from fixed tumor samples. Mutations in KRAS were detected using a KRAS mutation kit  as previously described [KRAS status was available from 87 (95%) patients in study 20050184, 109 (95%) patients in study 20060277, 1083 (91%) patients in study 20050181, and 1096 (93%) patients in study 20050203.escribed . KRAS stPatients receiving both doses of panitumumab (6.0 mg/kg Q2W and 9.0 mg/kg Q3W) were included in the immunogenicity and safety analyses.These studies were conducted in accordance with the principles for human experimentation as defined in the International Conference on Harmonization Good Clinical Practice guidelines and the principles of the Declaration of Helsinki. All studies were approved by the corresponding Investigational Review Boards, and informed consent was obtained from each patient after being advised of the potential risks and benefits as well as the investigational nature of the study.Antibody samples were evaluated for the presence of anti-panitumumab antibodies according to the testing strategy depicted in Figure The assays and sample collection strategy were optimized to reduce drug interference with antibody detection. The performance of the immunogenicity assays was monitored by implementing a trending process utilizing Westgard multirules that tracked negative control and positive control values for each assay performed . The obsPanitumumab concentrations in human serum were measured by a validated ELISA. Briefly, panitumumab was captured in microplate wells precoated with mouse anti-panitumumab antibody . Horseradish peroxidase-labeled rabbit polyclonal anti-panitumumab antibody (Amgen Inc.) was added to the wells and allowed to react with the captured panitumumab. A colorimetric signal was produced after the addition of tetramethylbenzidine-peroxidase substrate solution. The optical density (OD) of the signal, measured at 450-650 nm, was proportional to the amount of captured panitumumab. The conversion of OD units to concentrations for the assay quality controls and samples was achieved through a computer software-mediated comparison to a standard curve on the same assay run, which was regressed according to a 5 PL (Auto Estimate) regression model with a weighting factor of 1/Y. The lower limit of quantitation was 400 ng/mL in human serum.A population pharmacokinetic (PopPK) modeling and simulation approach was performed to evaluate the impact of immunogenicity on panitumumab pharmacokinetics by comparing the observed panitumumab concentrations of antibody-positive patients from study 20050181 with the predicted pharmacokinetic profiles based on PopPK parameters for antibody-negative patients.A 2-compartment model with parallel linear and nonlinear (Michaelis-Menten) elimination pathways has been used to describe the disposition of panitumumab ,22. A prThe impact of immunogenicity on safety was evaluated through the review and assessment of the incidence of adverse events, potential infusion reactions, reasons for discontinuation from therapy, and total number of doses received while on study for panitumumab-treated antibody-positive patients and anti-panitumumab antibody-negative patients.KRAS .A total of 1325 patients were tested for anti-panitumumab antibodies, including 558 patients who were treated with panitumumab plus oxaliplatin-based chemotherapy (study 20050203) and 767 patients treated with panitumumab plus irinotecan-based chemotherapy . Of these, 1225 patients  had baseline samples available and 1124 patients  had postbaseline samples available for testing. Over half of the patients were men and the population was predominantly white. Overall, 53% of the patients had tumors expressing wild-type KRAS . The incidence of developing antibodies was low in patients treated with oxaliplatin-based chemotherapy  and in patients treated with irinotecan-based chemotherapy . Pre-existing binding and neutralizing antibodies were detected in 3.8% and 0.4% of all patients before the start of any investigational product, respectively.The development of anti-panitumumab antibodies in patients receiving panitumumab in combination with chemotherapy  occurred infrequently: 1.8% of patients developed binding antibodies and 0.2% of patients developed neutralizing antibodies  from the hypothesized proportions (Table P = 0.8807), suggesting that no marked difference in the observed panitumumab concentrations was observed between the antibody-positive and antibody-negative patients.Among 38 observed concentrations from the antibody-positive patients, 2 (5%) were below, 5 (13%) were above, and 31 (82%) were within the 90% prediction interval derived from pharmacokinetic profiles of antibody-negative patients. The proportions were not statistically different  was observed between patients who tested positive for anti-panitumumab antibodies and those who tested negative (Table KRAS status (wild-type or mutant) or combination chemotherapy regimen .The panitumumab immunogenicity testing strategy utilized two validated screening immunoassays to detect the presence of all antibodies capable of binding to panitumumab. The screening immunoassays were chosen to provide the optimal combination of sensitivity and drug tolerance (ELISA) and the ability to detect antibodies of various affinities (Biacore) . A cell-Pre-existing binding and neutralizing antibodies were detected prior to the administration of panitumumab in 3.8% and 0.4% of patients, respectively. Positive results from these baseline samples may be due to the presence of cross-reacting antibodies generated against antigens that share a similar epitope with panitumumab. The presence of pre-existing antibodies in panitumumab-treated patients did not appear to affect the postdose antibody state of these patients. In addition, patients who tested positive for pre-existing antibodies did not appear to have altered safety profiles.The broad, nonspecific cytotoxic effects of chemotherapy have the potential to impair the immune system, which could reduce the incidence of anti-panitumumab antibodies in patients receiving panitumumab in combination with chemotherapy. Both oxaliplatin and irinotecan have gastrointestinal toxicities ,25, and max, and Cmin between patients who developed anti-panitumumab antibodies and those who did not [Based on available pharmacokinetic data from study 20050181, the phase 3 study of panitumumab plus FOLFIRI for second-line treatment of mCRC, no evidence of an altered panitumumab pharmacokinetic profile was found in patients who received panitumumab 6.0 mg/kg Q2W and tested positive for pre-existing or developing anti-panitumumab antibodies. The results from study 20050181 were in agreement with previously published observations that there were no apparent differences in steady-state AUC, C did not ,22. A seOverall, there did not appear to be an association between the development of antibodies and safety outcomes. Higher incidences of adverse events observed in patients who were antibody negative at baseline and developed antibodies during the conduct of the study (n = 21) compared with those who were antibody negative throughout the study (n = 1317) may be related to the small sample size. Grade 5 events in antibody-positive patients occurred in the setting of disease progression, and serious adverse events were similar in type and nature to those reported in patients who did not develop anti-panitumumab antibodies.Although panitumumab was expected to have a low rate of immunogenicity compared to therapeutic antibodies containing nonhuman coding sequences, unique sequences in the CDRs could still be immunogenic. An in silico analysis to evaluate the potential risk of panitumumab sequence-associated immunogenicity suggested that panitumumab light and heavy chains do not contain any non-tolerant agretopes predicted to be able to bind to the eight most common HLA-DRB1 alleles. The low risk of panitumumab immunogenicity was confirmed by the results of antibody testing in combination chemotherapy clinical trials, which indicated that patients treated with panitumumab in combination with irinotecan- or oxaliplatin-based chemotherapy infrequently developed antibodies against panitumumab.In summary, the immunogenicity of panitumumab in the combination chemotherapy setting was infrequent and was similar to the immunogenicity observed in the monotherapy setting. This low rate of immunogenicity may be attributed to the fully human nature of panitumumab. Additionally, the presence of anti-panitumumab antibodies did not appear to alter pharmacokinetic or safety profiles of panitumumab.All authors are employees and shareholders of Amgen Inc.DW and JJP developed the methods and coordinated the implementation of binding and neutralizing antibody testing. AC performed the PopPK analysis and interpreted results. CYW, JJPR, and BBY made substantial contributions to the PopPK analysis planning and interpreted the results. KZ performed the statistical analysis of the antibody data. JW performed the analysis of the impact of immunogenicity on safety. AK and SG supervised development and implementation of the neutralizing antibody testing method. SJS contributed to the interpretation of antibody data. NC and MS developed and implemented the immunogenicity testing strategy and made substantial contributions to data interpretation. All authors contributed to the writing of the manuscript or critically reviewing the manuscript for technical and intellectual content. All authors approved the final draft of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6904/11/17/prepub


USH1C gene encodes the PDZ containing scaffold protein harmonin which is expressed in form of numerous alternatively spliced variants. Hamonin binds directly to all USH1/2 proteins and is a key organizer of USH protein networks in photoreceptor cells. So far no effective treatment for the ophthalmic component of USH exists. Translational read-through was introduced as an innovative therapy option for several non-ocular diseases caused by nonsense mutations leading to a premature termination stop. Here we compare the potential of translational read-through inducing drugs (TRIDs), namely PTC124  as well as the designer aminoglycoside NB30 and NB54 as a treatment option for patients carrying a nonsense mutation in the USH1C gene causing USH1. We examined read-through in cell culture, retinal cultures and in vivo in murine retinas. Restoration of the harmonin function was tested by GST pull-downs and actin filament bundling. The TRIDs recovered functional harmonin protein and showed an excellent biocompatibility in retinal cultures with read-through vs. toxicity evidently superior for NB54 and PTC124. In vivo administration of NB54 and PTC124 to mice induced recovery of full-length harmonin. The high biocompatibility combined with the sustained read-through efficacies of these novel drugs emphasizes the potential of TRIDs in treating nonsense mutations in USH as well as in other ciliopathies.The Usher syndrome (USH) is the most frequent cause of inherited combined deaf-blindness. The ciliopathy is clinically and genetically heterogeneous, assigned to three clinical USH types of which the most severe type is USH1. The


New viruses pathogenic to plants continue to emerge due to mutation, recombination, or reassortment among genomic segments among individual viruses. Tospoviruses cause significant economic damage to a wide range of crops in many parts of the world. The genetic or molecular basis of the continued emergence of new tospoviruses and new hosts is not well understood though it is generally accepted that reassortment and/or genetic complementation among the three genomic segments of individual viruses could be contributing to this variability since plants infected with more than one tospovirus are not uncommon in nature.Iris yellow spot virus (IYSV) and Tomato spotted wilt virus (TSWV), were investigated for inter-virus interactions at the molecular level in dually-infected plants. Datura (Datura stramonium) is a permissive host for TSWV, while it restricts the movement of IYSV to inoculated leaves. In plants infected with both viruses, however, TSWV facilitated the selective movement of the viral gene silencing suppressor (NSs) gene of IYSV to the younger, uninoculated leaves. The small RNA expression profiles of IYSV and TSWV in single- and dually-infected datura plants showed that systemic leaves of dually-infected plants had reduced levels of TSWV N gene-specific small interfering RNAs (siRNAs). No TSWV NSs-specific siRNAs were detected either in the inoculated or systemic leaves of dually-infected datura plants indicating a more efficient suppression of host silencing machinery in the presence of NSs from both viruses as compared to the presence of only TSWV NSs.Two distinct and economically important tospoviruses, Bunyaviridae family.Our study identifies a new role for the viral gene silencing suppressor in potentially modulating the biology and host range of viruses and underscores the importance of virally-coded suppressors of gene silencing in virus infection of plants. This is the first experimental evidence of functional complementation between two distinct tospoviruses in the  Bunyaviridae consists of five genera and viruses with negative-stranded RNA genomes. All but one genera cause serious diseases in animals and humans Tospovirus, in this family consists of viruses that infect plants. Tospoviruses cause some of the most destructive diseases in important crop plants and world-wide annual losses could be as high as U.S. $1 billion Tomato spotted wilt virus (TSWV) was the first tospovirus described and is one of the most-studied tospoviruses The virus family Tospovirus was thought to be a monotypic genus consisting of only TSWV until a second tospovirus, Impatiens necrotic spot virus (INSV), was described Iris yellow spot virus (IYSV) was the third tospovirus to be reported Groundnut ring spot virus (GRSV) in tomato in Florida For many years, genus i.e. the exchange of genomic segments among different parents. This is facilitated by the presence of mixed infections in plants under natural conditions.The increasing diversity of tospoviruses has been attributed to shifts in crop production, differing specificity of thrips vectors, and the segmented nature of the viral genome which could result in genetic reassortants. Moreover, it is generally accepted that tospoviruses, like other RNA viruses, show high mutation rates because of the lack of proofreading ability of their replicases N/GC) in antisense orientation. The S RNA codes for a non-structural protein (NSs) in sense direction and the nucleocapsid protein (N) in antisense direction. The NSm and GN/GC proteins coded by the M RNA play important roles in cell to cell virus movement in plant host, and in vector transmission, respectively The genome of tospoviruses consists of three RNAs, large (L), medium (M) and small (S). The L RNA is organized in negative sense orientation, whereas the M and S RNAs are in ambisense The segmented genome of tospoviruses facilitated genetic reassortment studies to map genetic determinants for symptomatology Citrullus lanatus) plants by Groundnut bud necrosis virus (GBNV) and Watermelon bud necrosis virus (WBNV) under field conditions in central India. Similarly, TSWV and IYSV were shown to infect and co-exist in onion plants under field conditions in Georgia, where 7% of the onion (Allium cepa) plants tested were dually infected with these two distinct tospoviruses Datura stramonium) is a differential host for IYSV and TSWV. It is considered a permissive host for TSWV and a restrictive host for IYSV with respect to virus movement following infection  (N/GC and RdRp) of these two RNAs could be amplified from inoculated leaves but not from uninoculated systemic leaves (data not shown); further confirming that IYSV was restricted to only inoculated leaves  . By 20–2on (DPI) . The viron (DPI) . This waD. stramonium plants, when mechanically inoculated with TSWV, first show a few small concentric ring symptoms, 10–12 DPI on inoculated leaves (N/GC) and L (RdRp) RNA were amplified using gene-specific primers. Both inoculated  were analyzed for IYSV and TSWV N and NSs gene expression using gene-specific cDNA probes  in the USA due to genome reassortment of two viruses, GRSV and Tomato chlorotic spot virus (TCSV), with the large (L) and small (S) RNAs coming from GRSV and the medium (M) RNA from TCSV . This exchange of genetic material and interaction between co-infecting viruses resulting in synergism or complementation could lead to changes in biological properties and increased diversity of viruses, especially those with segmented genomes due to genetic reassortment Mixed infections of plants with viruses is a natural phenomenon, and the outcome of this inter-virus interaction is influenced by several factors including the host plant's genetic background and growth stage, genetic relatedness of the viruses, and environmental conditions. The outcomes include elimination of one virus from the mixed infection by the second virus, co-existence and continued replication of both viruses for the remainder of the plant's life, or increased titer of one virus resulting in more severe symptoms (synergism). Mixed infections could also result in genetic recombination or genetic reassortment between the co-infecting viruses that could lead to generation of new viruses or strains with a subsequent expansion of the host range Tospovirus.Synergistic interactions between viruses leading to more severe disease have been described for positive-stranded RNA viruses and DNA viruses We utilized a model system wherein the experimental host, datura, responds differentially to two distinct tospoviruses, IYSV and TSWV. While this host is susceptible to infection by both viruses, it is a permissive host to TSWV (where the virus invades the plant and causes systemic infection), whereas IYSV infection is confined to inoculated leaves and fails to move to younger, uninoculated leaves Datura plants inoculated with IYSV alone showed symptoms of infection only on the inoculated leaves, with younger systemic leaves remaining symptomless. On the other hand, TWSV inoculation resulted in symptoms on the inoculated as well as systemic leaves . This waD. stramonium. NSs have been reported as the silencing suppressor in tospoviruses Dual infection of datura plants with IYSV and TSWV resulted in an increase in the symptom severity of the inoculated as well as the systemic leaves with plants succumbing to the virus 40 days post-inoculation (dpi) as compared to 80 dpi in the case of single infection with TSWV. In addition, the IYSV NSs was selectively expressed in the younger, uninoculated leaves of dually infected Availability of antisera specific to each of the TSWV and IYSV N proteins and the IYSV NSs protein enabled us to determine the expression of these genes in individually and dually infected plants. While the relative levels of these proteins as reflected by the absorbance values varied among individual plants within a treatment, we were able to consistently detect these proteins. TSWV N could be detected in inoculated as well as systemic leaves as expected. IYSV N and NSs could be found only in inoculated leaves in singly infected plants (since the virus is confined to inoculated leaves in datura). In case of dually infected plants, the IYSV NSs protein was expressed in uninoculated leaves, albeit to a lower level.Tospovirus spp. including TSWV and a tomato-infecting strain of Tomato yellow ring virus (TYRV-t) using partial N gene sequences. They showed that transgenic resistance against TYRV-t does not hold against the soybean strain (TYRV-s) and is broken by TYRV-t when co-inoculated with TYRV-s. TYRV-t could be detected in the systemic leaves of a resistant line in co-inoculated plants implying a transcomplementation event involving a protein of TYRV-s. They further showed that the presence of TYRV-s encoded silencing suppressor (NSs) was crucial for rescuing of TYRV-t. The severe symptoms in datura plants dually infected with TSWV and IYSV, compared to those individually infected either with TSWV or IYSV, could be explained by the fact that the level of the silencing suppressor, NSs, of both viruses was much higher in dually infected than in singly infected Datura  (Tomato chlorotic spot virus (TCSV) has recently been described Tobacco mosaic virus and Cucumber mosaic virus produce a synergistic disease with severe malformations Tospovirus spp. such as TYRV and IYSV with N gene variation of only 10 to 15%.Genetic reassortment has long been accepted as one of the means by which new viruses or strains are generated among viruses with segmented genomes. Such a naturally occurring genetic reassortant between GRSV and The model system we developed facilitates further studies on the nature of protein-protein interactions between the silencing suppressors of distinct tospoviruses in dually infected plants, the nature of the plant factors that interact with the viral proteins, and the effect of dual infection on the profile of virus-specific small RNAs produced as a result of host-induced gene silencing.Arachis hypogaea) plants, were maintained on experimental hosts, Datura stramonium and Nicotiana benthamiana under controlled conditions in a greenhouse.IYSV and TSWV, originally isolated from naturally infected onion and peanut (D. stramonium and N. benthamiana were dusted with silicon carbide (600 mesh) and the homogenate was manually applied using cotton buds. Inoculated plants were maintained at 25/18°C (day/night), 14 h day light and observed for development of symptoms. For establishing mixed infections, leaves from D. stramonium plants individually infected with TSWV or IYSV were homogenized together in equal amount of tissue and mechanically inoculated on to healthy D.stramonium and N. benthamiana plants as stated earlier. All experiments were repeated at least three times. The inoculated as well as systemic leaves of both hosts were harvested 25–30 days after inoculation, and stored at 4°C for further analysis.Virus-infected tissue was homogenized by grinding in 0.01 M sodium phosphate buffer (pH 7.0) containing 0.4% β-Mercaptoethanol and the homogenate was used as the inoculum for mechanical inoculation to experimental hosts. Fully expanded leaves (25–30 days old) of E. coli-expressed NSs protein which was used in a direct antigen-coated ELISA format Virus infection of inoculated plants was confirmed by ELISA using commercially available kits for TSWV and IYSV  following manufacturer's instructions. IYSV NSs-specific polyclonal antiserum was made to Total plant RNA was extracted separately from the symptomatic and asymptomatic IYSV and TSWV-infected plant tissue using the Plant RNeasy mini kit . RT-PCR was performed to detect the presence of various genomic RNAs  of TSWV and IYSV using gene-specific primers .8000/NaCl as described previously Symptomatic tissues were collected from inoculated and systemic leaves from co-infected datura plants and snap frozen immediately in liquid nitrogen. Frozen leaf tissue was homogenized in liquid nitrogen using a mortar and pestle. Total RNA was extracted using TRIZOL reagent  following the manufacturer's instructions. Low molecular weight RNAs were selectively precipitated by PEG32P dATP. Small RNA was separated on a 17% polyacrylamide- 7M urea gel and transferred to positively charged nylon membrane  by the semi-dry blot method 32P-radiolabeled probes by end-labelling with T4 polynucleotide kinase enzyme for oligo probes and random-priming method with Megaprime kit  for larger double-stranded DNA probes following manufacturer's instructions. The radiolabeled probes were column-purified. The blots were washed twice in 2× SSC, 0.1% SDS at 40°C for 10 minutes, exposed to X-ray film , and the film was developed. Blots were stripped in boiling 2× SSC, 0.1% SDS for 10–15 minutes, and verified for residual radiation by overnight exposure before re-probing with a different probe.Total RNA (20 ug) from plant samples was subjected to Northern blot analysis


In this paper we present the detailed clinical and cytogenetic analysis of a prenatally detected complex Congenital Diaphragmatic Hernia (CDH) patient with a mosaic unbalanced translocation . High-resolution whole genome SNP array confirmed a low-level mosaicism (20%) in uncultured cells, underlining the value of array technology for identification studies. Subsequently, targeted Fluorescence In-Situ Hybridization in postmortem collected tissues demonstrated a similar low-level mosaicism, independently of the affected status of the tissue. Thus, a higher incidence of the genetic aberration in affected organs as lung and diaphragm cannot explain the severe phenotype of this complex CDH patient. Comparison with other described chromosome 5p and 12p anomalies indicated that half of the features presented in our patient (including the diaphragm defect) could be attributed to both chromosomal areas. In contrast, a few features such as the palpebral downslant, the broad nasal bridge, the micrognathia, microcephaly, abnormal dermatoglyphics and IUGR better fitted the 5p associated syndromes only. This study underlines the fact that low-level mosaicism can be associated with severe birth defects including CDH. The contribution of mosaicism to human diseases and specifically to congenital anomalies and spontaneous abortions becomes more and more accepted, although its phenotypic consequences are poorly described phenomena leading to counseling issues. Therefore, thorough follow–up of mosaic aberrations such as presented here is indicated in order to provide genetic counselors a more evidence based prediction of fetal prognosis in the future. Congenital Diaphragmatic Hernia (CDH) is a severe birth defect characterized by defective formation of the diaphragm, lunghypoplasia and pulmonary hypertension. Its overall prevalence is 1/3000 live births and the majority are left sided. Associated anomalies  are involved in 60% of cases. The mortality rate is still high: 10–20% for isolated and up to 40% for non-isolated cases. CDH is increasingly detected by structural ultrasound in the second trimester of pregnancy showing features like a mediastinal cardiac shift away from the side of the defect and an intra-thoracic stomach bubble 229850 with over 80% of the patients showing CDH, though its locus remains elusive. Finally, CDH caused by tissue-limited mosaicism, specifically of tetrasomy 12p, is rather common within the Pallister-Killian syndrome (PKS) identified in a complex-CDH patient. The identification of this specific chromosome aberration with high resolution whole genome SNP array on umbilical cord blood shows the value of array technology for identification studies, also in cases of low mosaicism. Furthermore, we hypothesized in the patients' affected tissues a higher contribution of abnormal cells, which was assessed by FISH analysis in several tissues. Finally, results of phenotype-genotype correlations of each characteristic in this patient are presented.Ethics approval was provided by the Medical Ethics Committee of the Erasmus Medical Centre, Rotterdam, The Netherlands. A written informed consent was obtained from all participants in this study.Sixteen ml of amniotic fluid (AF) was cultured using the in situ method in BD Falcon Culture slides  and subsequently used for both GTG-banded karyotyping and fluorescence in situ hybridization (FISH). Karyotyping of the parents was executed on GTG banded metaphase spreads obtained from peripheral blood cultures. Karyograms were reported according the ISCN rules. Fetal skin and umbilical cord tissue were cultured according to standard techniques and used for FISH analysis in a postnatal diagnostic setting.http://genome.ucsc.edu/cgi-bin/hgGateway, assembly March 2006) and purchased from BACPAC Resources . BAC probes (http://www.cytocell.com/products/aquarius/micro/cri.asp) respectively.FISH experiments were performed according to standard protocols with minor modifications and analyzed with an Axioplan 2 Imaging microscope . Images were captured using Isis software . BAC clones were selected from the UCSC genome browser . MLPA analyses were performed using the SALSA P036 and P070 kits of MRC-Holland . These kits contain probes for all subtelomeric p-and-q arm regions of all chromosomes. In addition, a specific aneuploidy sensitive kit (P095) and a mental retardation focused kit harbouring 6 probes in the 5p15 telomeric region were executed. MLPA reactions were performed using the manufacturer's protocol with minor modifications http://www.illumina.com/applications). CNVs were detected by comparison to the common Illumina-reference set of 87 CEU samples specific for the Q610 array and visualized in Nexus (version 4.1) software as log2 ratios (http://www.biodiscovery.com/index/nexus). The analysis settings were as follow: SNP rank segmentation with a significance threshold of 1×10-6 and log-ratio-thresholds of 0.2 and −0.2 for duplication and deletion respectively. Mosaic changes were assessed by looking for aberrations in probe intensities along with a shift in genotype frequencies of the SNP probes .High-resolution whole genome analysis was performed on umbilical-cord blood derived DNA, using the Illumina Quad610 genotyping bead chip  according to the manufacturer's protocol. This array contains 598 821 SNP probes distributed genome wide and an additional 21 890 intensity-only probes in regions where SNP coverage is poor. Image intensities were extracted using the Illumina's BeadScan software. Data for each BeadChip were self-normalized in Beadstudio GT (version 3.0+) using information contained within the array  to control probe signal  and an intrathoracic liver A 22-year old Moroccan patient was referred to our tertiary centre for follow up and genetic counseling of a CDH detected in her unborn child by 20-weeks structural ultrasound in her first pregnancy. The medical history was unremarkable. There was no family history of congenital anomalies; however she and her partner were consanguineous in the 2Routine cytogenetic analysis confirmed the clinical suspicion of a chromosomal abnormality and revealed a high-mosaic deletion of chromosome 5 in cultured amniocytes which was confirmed by FISH with probes specific for chromosome 5: the karyotype on cultured AF cells was 46,XX,del(5)(p13.3)Based on the ultrasound and cytogenetic findings, the parents decided to terminate the pregnancy at 23 1/7 weeks of gestation. A female fetus was delivered vaginally and postmortem physical examination showed a normally proportioned but intra-uterine growth (length) restricted fetus; weight , crown-rump length  and foot-length 3.5 cm . Dysmorphological features were significant for the following: convex eye globes, abnormal palpebral (down) slant, hypertelorism, wide nasal bridge, flat philtrum, thin upperlip, micro-and-retrognathia and nuchal wideness. Abnormal external ear development on both sides and aberrant posterior rotation of the ears were noted as well. Concerning the extremities, a palmar crease on the right was seen and also an abnormal positioning of the anus with short perineum and sacral dimple. Inspection of the internal organs presented a large left diaphragmatic defect of the Bochdalek type with herniation of stomach, duodenum and parts of colon, liver and spleen. Further, this fetus showed severe lung hypoplasia  and left kidney-agenesis with compensatory right kidney hyperplasia. Finally, autopsy demonstrated normal morphology of all remaining organs and no structural aberrations of the brain on postmortem MRI.The prenatally identified mosaicism 46,XX,del(5)(p13.3) in cultured amniotic fluid cells was confirmed by postmortem cytogenetic analysis in umbilical cord and skin tissue, yet in a much lower frequency than expected . BecauseHigh-resolution whole genome SNP array on DNA from umbilical cord blood confirmed the 5p deletion and indeed identified a coexisting chromosome 12p13.2 duplication by using information of both log2 intensities and B-allele frequency as described recently  [29]. ThConsidering the big difference between mosaic rates of cultured amniocytes and umbilical cord blood as well as uncultured AF-cells, we hypothesized that the genetic aberration rate could be high in affected tissues  and lower in normal ones . Therefore we screened 7 different paraffin embedded tissues sections with FISH using specific BAC clones. Results are summarized in Structural aberrations of chromosome region 5p  and 12p (featuring as PK syndrome or a pure mosaic trisomy 12p) are both associated with CDH. Yet, for chromosome 5p diaphragmatic hernia has only been associated with Brachmann-de-Lange patients and not with those featuring Cri-du-Chat. Subsequently, the diaphragmatic candidate region on 5p most likely overlaps with the critical region of CdLS, taking into account that CdLS patients are genetically heterogenous as well. Hulinksy et al In this case report we present the detailed clinical and cytogenetical analysis of a unique low-mosaic der (5) t aberration identified in a CDH patient with multiple congenital anomalies. Classification of the true chromosome abnormality was possible only after performance of a high-resolution whole genome SNP array on uncultured umbilical cord blood. Application of this technology in the identification of mosaic aberrations was reviewed very recently Because the mosaic aberration was present in both placenta- and embryonic material we suggest that the translocation  occurred as a very early mitotic event in an initially normal diploid zygote. More specifically, this may have occurred at least before differentiation of trophoblast and inner cell mass in the 16-cell stage. To explain the phenotypic variability at the tissue level, we speculated that the malformations of lungs, diaphragm and kidneys would associate with a much higher level of mosaicism than the normally developed tissues of heart and liver. This would thus mirror a situation in which the post zygotic mutation arose in an important lung-and diaphragm specific precursor cell population and time window. However, such a linear correlation between level of mosaicism and tissue pathophysiology could not be confirmed in our case. Associations between the severity of the (whole) clinical phenotype and the percentage of abnormal cells are generally known for the most common autosomal aneuploidy (trisomy 21), yet the mechanism by which this aneuploidy results in the complex heterogeneous phenotype cannot be attributed to mosaicism alone and is therefore still under discussion Finally, uncultured tissues are in general better able to reveal true chromosomal mosaicism frequencies as compared to cultured tissues, since culturing may introduce a selection bias that distorts the percentages of abnormal cells. However we were not able to detect the low-mosaic der (5) in uncultured AF-cells using MLPA, yet did detect a high-mosaic der(5) in cultured AF cells. From this it can be concluded that the level of mosaicism in uncultured cells was probably too low to be detected with MLPA. These kind of discrepancies have been described in some areas of tissue-specific mosaicism, like mosaic trisomy 20 Chromosomal abnormalities are detected in 9.5%–34% of prenatally diagnosed CDH cases We also compared our patients remaining characteristics to the features described in literature for both genomic areas. Based on this comparison half of the features presented in our patient could be attributed to both chromosomal areas, while some were more associated with the 5p region. Hulinksy et al. Focusing on CDH and genetic mosaicism: the earlier mentioned Pallister-Killian syndrome is the most common CDH-associated syndrome caused by tissue-limited mosaicism. In a small study more than ten years ago, Donnenfeld et al In general it is very difficult to estimate the true incidence and significance of genetic mosaicism in human congenital anomalies. The application of high-resolution SNP arrays allows for an easier and more sensitive detection of this type of genetic aberrations for several reasons. First, SNP arrays are shown to be able to detect levels of mosaicism as low as 5% using the B-allele frequency as a more sensitive measurement compared to the more difficult detection of subtle down- or up crease of log R ratios (which only can be used in Oligo based arrays). Second, the possible use of low amounts of DNA from any kind of (uncultured) tissue diminishes the technical failures due to the in-vitro cell culturing process Table S1Molecular-Cytogenetic results of the mosaic unbalanced translocation  in several affected and un-affected tissues.(XLS)Click here for additional data file.Table S2Phenotypic comparison of our patients' characteristics with clinical info of the involved chromosomal regions known from literature.(XLS)Click here for additional data file.


However, the association between nucleosome occupancy and polyadenylation site usage is still unclear.It has been reported that 3' end processing by slowing down transcription speed. Both conserved distal polyadenylation sites and constitutive sites showed stronger nucleosome depletion near polyadenylation sites and had intrinsically better positioned downstream nucleosomes. Finally, there was a higher accumulation of RNA polymerase II downstream of the polyadenylation sites, to guarantee gene transcription termination and recognition of the last polyadenylation sites, if previous sites were missed.By systematic analysis of high-throughput sequencing datasets from the human genome, we found that nucleosome occupancy patterns are different around the polyadenylation sites, and that the patterns associate with both transcription termination and recognition of polyadenylation sites. Upstream of proximal polyadenylation sites, RNA polymerase II accumulated and nucleosomes were better positioned compared with downstream of the sites. Highly used proximal polyadenylation sites had higher upstream nucleosome levels and RNA polymerase II accumulation than lowly used sites. This suggests that nucleosomes positioned upstream of proximal sites function in the recognition of proximal polyadenylation sites and in the preparation for 3' end processing.Our study indicates that nucleosome arrays play different roles in the regulation of the usage of polyadenylation sites and transcription termination of protein-coding genes, and form a dual pausing model of RNA polymerase II in the alternative polyadenylation sites’ region, to ensure effective 3 Formation of the 3′ end of precursor messenger RNA (pre-mRNA) is an essential step in the procedure of eukaryotic gene expression. Inappropriate 3′ end formation of human mRNAs can have a tremendous impact on health and disease ,2; howevet al. (2005) have found that the DNA sequence is still tethered to RNAP II when the 3′ end is cleaved, and that the 3′ end processing is fast and efficient when coupled to transcription in vitro[et al. (2008) have proposed a dual pausing model, where elongation arrests near the transcription start site and in the 3′ flank to allow co-transcriptional processing by factors recruited to the RNAP II ternary complex [Recent evidence has indicated that 3′ end processing is coupled to transcription and splicing, as well as termination -8, and t in vitro. Glover- complex .et al. (2011) have suggested that a compacted chromatin downstream of the polyA sites can slow down the elongating transcription, thus facilitating the folding of nascent mRNA in a favorable structure at the polyA site during transcription [et al. demonstrated that compared with lowly expressed genes, highly expressed genes had a lower nucleosome level around the polyA sites, indicating that transcriptional activity has an additional impact on the nucleosome level around the polyA sites [Epigenetic modifications, including DNA methylation at CpG islands  and H3K3cription . Ji et ayA sites . Our preyA sites . AlterinyA sites ,25.Over half of the genes in the human genome have alternative polyA sites . Howeverin vivo and in vitro .The height of the nucleosome occupancy peak downstream of constitutive polyA sites was higher than that downstream of alternative sites Figure A. We quain vivo, nucleosome levels are higher, suggesting that alternative polyA sites are more affected by the in vivo environment and can be adjusted easily.Also, we applied the DNA sequences-base nucleosome prediction tool developed by the Segal laboratory , to predet al. [in vivo and further confirmed that transcription activation can regulate nucleosome levels. In highly expressed genes, the reduction in downstream nucleosome levels was smaller compared with that in upstream ones, and there was a much greater accumulation of RNAP II downstream of polyA sites than upstream. Therefore, it is reasonable to postulate that a nucleosome downstream of constitutive sites is expelled by RNAP II more frequently when a gene is highly expressed, and that it is better positioned when a gene is unexpressed in vivo. Downstream nucleosomes may be a huge barrier for RNAP II to pass and promote transcription termination.To explore the regulatory role of the nucleosome in polyA site usage, the relationship between nucleosome level and the usage of polyA site was analyzed. In the case of constitutive polyA sites, the gene expression level in the cell reflects the site usage, i.e., in highly expressed genes (RPKM > 10) the site usage is high compared with that in lowly expressed genes (RPKM < 0.1). The nucleosome level around a constitutive site negatively correlated with the gene expression, and there was a proportional relationship between RNAP II occupancy and gene expression Figure A-B. Thiset al. . To direTo evaluate alternative polyA site usage, the relative usage of downstream polyA site score (RUD) was used. Briefly, RUD is the ratio between the density of downstream reads and the density of upstream reads (see Methods). Alternative polyA sites with the lowest RUD in the gene are highly used in transcription, while those with the highest RUD in the gene are lowly used. The results showed that the changes in nucleosome levels between upstream and downstream nucleosomes were disproportional Figure C-D. For The alternative polyA sites appear in different locations, and their usage is not random. It is necessary to further explore the role of the nucleosome in the regulation of alternative polyadenylation. To this end, alternative polyA sites were divided into proximal, distal and in-between polyA sites, according to the position of the polyA site relative to the transcription start site (TSS) of the gene (see Methods). For genes with more than two polyA sites, the average distances from the three classes of polyA sites to the TSS and to the end of the gene were computed , the alternative polyA sites were divided into high-usage ones, with the lowest RUD in the gene, and low-usage ones, with the highest RUD in the gene. In the case of high-usage and low-usage distal polyA sites, the results showed that the varying tendencies of upstream and downstream nucleosome occupancy were the same, though the change in the upstream nucleosome level was smaller than that in the downstream nucleosome level . The nucleosome profile of high-usage proximal polyA sites shifted downstream compared with that of the low-usage sites. Meanwhile, RNAP II accumulated in the immediate upstream region of proximal polyA sites, and high-usage proximal polyA sites had a higher RNAP II occupancy than the low-usage sites had , and proximal polyA sites, favored in proliferating cells, tend to have limited consensus PAS features (likely weaker sites) . We also density . In addiin vivo, which makes it more difficult for RNAP II to pass. Also, accumulation of RNAP II at the 3′ end of genes correlated with the usage of polyA sites. Thus, a possible role of downstream nucleosomes is to guarantee gene transcription termination and recognition of the last polyadenylation sites if previous sites were missed.Our results specifically point out that downstream nucleosomes correlate with the usage of constitutive and distal sites. Additionally, we inferred that nucleosomes downstream of constitutive and distal polyA sites are intrinsically better positioned, to guarantee stronger polyA site recognition and facilitate the formation of a stable RNA structure at the polyA site by reducing RNAP II transcription speed. Moreover, the nucleosome occupancy curve around constitutive and distal polyA sites was much steeper than other sites Proximal polyA sites have an intrinsic advantage over the distal ones, as they are transcribed earlier and have more time to be recognized , while higher elongation rate leads to them being missed and to enhance the recognition of the distal polyA sites . AccordiTaken together, our study indicates that nucleosomes near polyA sites have various regulatory effects on polyadenylation and transcription termination Figure . Proximahttp://genome.ucsc.edu/cgi-bin/hgLiftOver) [The genomic coordinates of the polyA sites of the human genome were obtained from the PolyA_DB2 database . We usediftOver) . All polhttp://genome.ucsc.edu/cgi-bin/hgTables).In genes with alternative polyA sites, the sites were divided into proximal, distal and in-between polyA sites, according to the position of the polyA site relative to the TSS of the gene. The polyA sites closest to the TSS of a gene were proximal sites, the sites closest to the end of a gene were distal sites, and the polyA sites located between proximal and distal polyA sites were in-between sites. The coordinates of the TSS and the end of genes were obtained from the annotation of RefSeq genes in UCSC Table Browser  and analyzed . Tag cooanalyzed .p). RNAP II occupancy was calculated similarly to the nucleosome occupancy, but the score represents the average number of sequenced reads uniquely mapped to the sense strand 300 bases upstream and to the antisense strand 300 bases downstream of one locus.Nucleosome scores calculated as previously described , represeNucleosome occupancy peak calling was performed by the DANPOS algorithm , which wThe mRNA-seq data performed on nuclear extracts from human CD4+ T cells, CD8+ T cells and granulocytes (accession number GSE25133) , allowinTo evaluate polyA site usage, the density of reads mapped to upstream and downstream regions was compared, as illustrated in a previous study . The relThe authors declare that they have no competing interests.HH conceived the study and wrote the paper. HH, HDL and XS designed the bioinformatics analyses. JC collected and preprocessed data sets. All authors read and approved the final manuscript.Nucleosome distribution around constitutive and alternative polyA sites. (A-B) Nucleosome occupancy surrounding polyA sites of constitutive (con) and alternative  polyA sites across a 2000-bp window in granulocytes and CD8+ T cells. (C) Predicted nucleosome occupancy based on DNA sequence around constitutive (con) and alternative  polyA sites across a 2000-bp window.Click here for fileStatistics of the summit position distribution and fuzziness score of nucleosome peaks called by the DANPOS algorithm within 300 bp upstream and 300 bp downstream of the polyA sites. The standard deviation (std) of the distance between the summit position and polyA sites, and the average value of fuzziness score of nucleosome peaks were calculated to appraise the consistency of nucleosome positioning. The sample used for the analyses was CD4+ T cells shown in Figures Click here for fileThe relationship between the nucleosome and the usage of polyA sites. (A-B) Nucleosome distribution near constitutive polyA sites of highly expressed and lowly expressed genes in granulocytes and CD8+ T cells . (C-D) Nucleosome distribution near high-usage (blue curve) and low-usage (red curve) alternative polyA sites in expressed genes in granulocytes and CD8+ T cells (RPKM > 1). High-usage sites have the lowest RUD in the gene, and low-usage sites have the highest RUD in the gene.Click here for fileNucleosome level around constitutive polyA sites of differentially expressed genes between CD4+ T cells and granulocytes. The blue curve represents the genes that were highly expressed in CD4+ T cells (RPKM > 10) and unexpressed in granulocytes (RPKM < 0.1). The red curve represents the genes that were unexpressed in CD4+ T cells (RPKM < 0.1) and highly expressed in granulocytes (RPKM >10).Click here for fileThe average distance from the three classes of polyA sites to the TSS and to the end of the gene.Click here for fileDifferent patterns of nucleosome distribution around different alternative polyA sites. (A-B) Nucleosome occupancy around distal (d), in-between (m) and proximal (p) polyA sites across a 2000-bp window in granulocytes and CD8+ T cells. (C) Predicted nucleosome occupancy based on DNA sequence around distal (d), in-between (m) and proximal (p) polyA sites.Click here for fileRelationship between nucleosomes and the usage of proximal and distal polyA sites. (A-B) Nucleosome occupancy surrounding high-usage and low-usage distal polyA sites of expressed genes (RPKM > 1) in granulocytes and CD8+ T cells. (C-D) Nucleosome occupancy surrounding high-usage and low-usage proximal polyA sites of expressed genes (RPKM > 1) in granulocytes and CD8+ T cells. The blue curve represents high-usage sites that have the lowest RUD in the gene; and the red curve represents low-usage sites that have the highest RUD in the gene.Click here for filePercentage of distal and proximal polyA sites in high-usage and low-usage alternative polyA sites. The percentage of distal  and proximal  polyA sites in high-usage and low-usage alternative polyA sites in granulocytes (A), CD4+ T cells (B) and CD8+ T cells (C). High-usage polyA sites have the lowest RUD in expressed genes (RPKM > 1), and low-usage polyA sites have the highest RUD in expressed genes (RPKM > 1).Click here for file


Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) can identify genomic regions that bind proteins involved in various chromosomal functions. Although the development of next-generation sequencers offers the technology needed to identify these protein-binding sites, the analysis can be computationally challenging because sequencing data sometimes consist of >100 million reads/sample. Herein, we describe a cost-effective and time-efficient protocol that is generally applicable to ChIP-seq analysis; this protocol uses a novel peak-calling program termed DROMPA to identify peaks and an additional program, parse2wig, to preprocess read-map files. This two-step procedure drastically reduces computational time and memory requirements compared with other programs. DROMPA enables the identification of protein localization sites in repetitive sequences and efficiently identifies both broad and sharp protein localization peaks. Specifically, DROMPA outputs a protein-binding profile map in pdf or png format, which can be easily manipulated by users who have a limited background in bioinformatics. Identification of protein-binding sites in a genome can be achieved using chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) to clarify the biological role(s) of targeted proteins . With adChIP-seq analysis can be divided into three steps . (i) GenSaccharomyces cerevisiae or Schizosaccharomyces pombe, a greater than 10-fold sequencing depth in both the input and the ChIP fraction can be easily obtained with relatively low sequencing cost. Given enough sequencing depth in the input fraction and an equivalent number of sequence reads in the ChIP fraction, tuning the values of threshold parameters for peak calling is not troublesome. As the statistical reliability at every genomic position is large in each case, the protein-binding profile map  reflects the actual protein-binding probability at every position in the genome , such as http://genome.ucsc.edu/) to visualize the read distributions and to incorporate various genomic annotations into the data file. However, there are several disadvantages to using a web-based system when the data set is large. First, uploading a huge data set is time-consuming. Second, there is a limitation in showing multiple sets of ChIP-seq data for different projects separately. Third, the uploaded data are discarded when the user does not access the site for a given period .Quick visualization of ChIP-seq results, when presented as a ChIP read distribution or protein-binding profile map, is an invaluable means for rapidly assessing data quality and setting threshold parameters for peak calling. As available visualization protocols require installation of additional software, which may require time and effort to manage, it is difficult to show the whole-genome distribution of the mapped reads and detected peaks to a user who has little bioinformatics skill. As an alternative means of visualization, the data can be uploaded to the UCSC genome browser  for peak calling and visualization. We also developed a program named parse2wig for preprocessing map files into wig files. We validated our programs using 29 samples from three human cell lines  in a study of HDAC8 mutations in Cornelia de Lange syndrome DNA using antibodies directed against Rad21, Smc3ac and CTCF . The distribution of mapped reads is affected by various genomic features (proportion of unique and repetitive sequence and copy number variation), by the methods for ChIP and library construction and by platform-specific sequencing efficiency (DROMPA can accept multiple mapped reads (reads mapped on multiple loci of the reference genome), whereas most available peak-calling programs can only accept uniquely mapped reads (reads mapped onto the reference genome only once). This feature is clearly important for identifying peaks in repetitive sequences. Please refer to Experimental and S. cerevisiae (Drosophila melanogaster transcription factor suppressor of Hairy-wing [Su (Hw)] , due to the low mappability of uniquely mapped reads in several genomic regions. By allowing multiple mapped reads, peaks can be identified from such regions  and CTCF  may be poor if the initial amount of DNA is insufficient, for example, because of inefficient ChIP. In this situation, the number of mapped reads will not be sufficient for statistical analysis: for example, when 20 million reads are sequenced and the mapping ratio is 15%, only 3 million reads are available for analysis. The mapping results obtained here for the test data are summarized in 6 unique reads should be mapped with <20% having to be filtered out as PCR-biased reads. In our previous work  generally indicates that the sample DNA is of poor quality . Even if the number of sequenced reads is large, The number of peaks detected and the FDRs for the Rad21, Smc3-ac and CTCF samples are given in In conclusion, the programs we have developed, DROMPA and parse2wig, offer the following advantages over other ChIP-seq analysis programs:Our programs require much less memory and time than other available peak-calling programs  and when they are broad , as a consequence of the simple peak-calling strategy used.DROMPA accepts multiple mapped reads, whereas most available peak-calling programs can only use uniquely mapped reads as input. Incorporation of multiple mapped reads into the calculation improves sequencing depth (up to 25%)  methodology (http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/drompa/). In this study, we used DROMPA version 1.1.1. Check the website for the latest version.The source codes for DROMPA and parse2wig are available on the DROMPA website (http://www.ncbi.nlm.nih.gov/sra) under accession number SRA062112 , SRP005957 (D. melanogaster Suppressor of Hairy-wing), SRP006944 (HeLa cell H3K27me3 and H3K36me3) and SRP011927 .The ChIP-seq data were downloaded from The Sequence Read Archive  sequentially along a chromosome and outputs a wig-formatted file for each chromosome. Each mapped read is extended to an average, predetermined fragment length  as previously described  × 10, where E(r) is the expected value of a mapped read for each base in the strand s, that is, E(s) = Ns/L where Ns is the number of reads mapped on the strand s of the genome and L is the genome length. A similar strategy has been used for programs developed for genome mapping and repeat masking  over 6 mapped reads. Thus, the normalized read number for bin x is Rx = 106 × (rx/Ni) × (Li/108) where Ni is the total number of reads mapped onto chromosome i and Li is the length of chromosome i. The number for each bin is then smoothed with a fixed width , which provides a good approximation of the real read distribution. At this stage, the wig files can be uploaded to the UCSC genome browser if the user so desires.To compare the results of multiple ChIP experiments, parse2wig uses a modified RPKM (reads per kilobase of exon model per million mapped reads) normalization . The modDROMPA scans the reference genome with a sliding window that includes contiguous bins  to identify peak regions that satisfy simultaneously the default threshold values listed below  is >3.0.Rx) of ChIP bins in a window/the average read depth of the ChIP for the chromosome is >3.0.The maximum read intensity (The average number of control reads per window/the average read depth of the control for the chromosome is <10.0.The maximum read intensity of ChIP bins in a window is >6.0.Thresholds (i) and (ii) evaluate the significance of ChIP read enrichments against the number of control reads for each window. The Wilcoxon rank-sum test evaluates whether ChIP reads are enriched in the overall region (most of the bins) in a window. Threshold (iii) determines whether the ChIP reads mapped in a window are enriched compared with the average depth of the whole genome. When the number of control reads mapped in a window is quite large compared with the average depth of the control reads, the region is considered as a highly repetitive region, which may lead to the identification of false-positive peaks; threshold (iv) effectively filters out such peaks. Threshold (v) is useful for comparing multiple ChIP samples. The default values for these five thresholds were defined empirically.Contiguous, significantly enriched windows are then merged, and a peak list is produced. This list can be saved as a tab-delimited text file that can be handled by a text editor or Microsoft Excel. This peak file can also be used as a bed file. DROMPA can also be used to identify broad peaks by enlarging the bin size.http://www.cairographics.org/). These figures can display ChIP and control read distributions and ChIP/control enrichment ratios at different scales and can include genomic annotations. Because DROMPA can call peaks and visualize multiple ChIP samples simultaneously, it is a powerful tool for large-scale ChIP-seq analysis.DROMPA draws bar graphs of the mapped reads with chromosome-separated and/or whole-genome files in a pdf or png format  using Cairo graphics library (The memory required by DROMPA mainly depends on the size of the largest chromosome and the specified bin size and does not depend on the map file size. Thus, DROMPA can analyze sequence data of >100 million reads while using limited computation memory. The memory required by parse2wig depends on the map file size, but it is smaller than that used by other peak-calling programs. The total sizes of the binary and compressed wig files are much smaller than the map file.In our published study (MACS (PeakSeq preprocesses a map file before performing peak calling, as does the combination of parse2wig and DROMPA; we therefore considered the performance of each preprocessing step separately. For Quest, we supplied a genome-table file for the peak identification process because the process took less time than when the complete genome sequence was supplied. For comparison, we used SAM-formatted map files as input for DROMPA, MACS and PeakSeq and Bowtie-formatted files for Quest, as Quest cannot handle SAM-formatted files and PeakSeq cannot handle Bowtie-formatted files.


Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality.In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems.The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design.ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem.We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first  Protein-DNA interactions play crucial roles in many key biological processes. One of these processes is transcriptional regulation, in which transcription factors (TFs) bind to specific DNA binding sequences to either activate or repress the expression of their regulated genes. Transcription factors form a distinct group of DNA binding proteins in terms of function and binding specificity . Owning There are two key issues in general protein-DNA docking. One is a potential function for accurate evaluation of protein-DNA binding affinity. The other is conformational sampling of the complex structures. It should be noted that these two issues are related since the sampling methods generally need the energy function to guide the search. Improvement has been made in the development of knowledge-based potentials for assessing the binding affinity between protein and DNA. These knowledge-based potentials are developed based on the mean-force theory and are more attractive due to their relative simplicity and ease of use. These potentials generally vary in their resolution levels, from residue-based to atom-based potentials and in their distance scales, from distance-independent to distance-dependent ,11,12. Sad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem.We have demonstrated the effectiveness of our protein-DNA docking algorithm and its application in structure-based transcription factor binding site prediction . HoweverThe effectiveness of our new method is validated through extensive experiments. Our GPU algorithm exhibits a 28x speedup on an individual Nvidia M2070 GPU over a single 2.8GHz Xeon core, and achieves a sustained performance of 10.4 TFLOPS using a cluster of 128 GPUs, which equals the capability of a conventional cluster with 3600 CPU cores. With the benefit of such improved computation capability, we are able to increase the number of random samples for the Monte-Carlo simulation procedure and thus expand the traversal in the search space. Experimental results show that GPU acceleration leads to higher rate of successful prediction of TF-DNA complexes. We also tested our GPU method on the rigid TF-DNA docking benchmark with carefully selected 38 cases . We founA non-redundant set of 75 TF-DNA complex structures (less than 35% protein sequence identity) was generated from PDB . Each ofbindingE), the atomic van der Waals (VDW) packing energy (packingE), and the constraint energy (constraintE) as seen in Equation 1 (packing Wand constraint Ware weight factors).Figure The protein-DNA binding affinity, which dominates the docking energy, is evaluated using a knowledge-based distance-dependent amino acid-nucleotide interaction potential . The binpacking Wapproaches zero as the random walk progresses). The constraint energy is also used to guide the docking process by bringing the DNA molecule in contact with the protein surface. This energy becomes zero for correctly docked structures.The calculation of VDW packing energy uses a harmonic form with soft repulsion and attraction terms as described previously . Since tThe simulated annealing sampling of the conformational space includes translation at a step size of 0.01Å and rotation at a step size of 2 degrees. The initial temperature is set to a 0.833 acceptance rate and the cooling rate is 0.998. The simulation continues until the system converges with an acceptance rate lower than 1% or when the total number of steps reaches a pre-set maximum (1.5 million in our current work). To improve coverage on the conformational search space, we conduct multiple Monte-Carlo simulations with different random seeds.To evaluate the docking performance, we compared the docked DNA conformations with the corresponding DNA structures in the native TF-DNA complexes by fixing the protein positions. The root mean square deviation (RMSD) is computed between the predicted and the native complex using DNA backbone heavy atoms. In some TF-DNA complexes, the proteins are homodimers that bind to the same or similar DNA sequences. In these cases, if the two protein chains exchange positions in the TF-DNA complex, the new structure should also be considered as "correct". For example, 1AN2 is a dimeric transcription factor Max that binds to its recognition sequence CACGTG by direct contact Figure  22]. If. If22]. All the tests and experiments of our GPU algorithm were conducted on the 'Keeneland' GPU-based HPC system co-hosted by Georgia Institute of Technology, Oak Ridge National Lab, and the University of Tennessee . The sysOur protein-DNA docking approach exhibits three levels of parallelism: (1) multiple protein-DNA pairs can be evaluated in parallel; (2) for each protein-DNA pair, multiple Monte-Carlo simulation runs are independent of each other; and (3) for each simulation run, the DNA movement and energy calculations feature fine-grained parallelism: the calculations are applied to each atom and amino acid/DNA triplet and can be performed in parallel within each simulation step. We design our GPU program to explore all three levels of parallelism. For notational convenience, we call each Monte-Carlo simulation run a task.Our protein-DNA docking program is designed for high-performance computing (HPC) systems equipped with Nvidia GPU cards. Such platforms feature a 4-level hardware hierarchy: multiple computing nodes; each equipped with multiple Nvidia GPUs; each GPU contains several multiprocessors; and each of which consists of multiple processor cores. Such a hardware hierarchy maps to a 4-level software architecture: multiple MPI processes, each involving a GPU CUDA kernel, which contains multiple CUDA thread blocks. Each block consists of multiple CUDA threads. In this software architecture, the parallel tasks are mapped to different processes, simulation runs within each task are mapped to different CUDA thread blocks, and parallel operations inside each simulation step are mapped to different CUDA threads. In the design of our protein-DNA docking algorithm, the master process is responsible of dispatching tasks. The slave processes iteratively execute six operations: obtaining a task from the master, reading input data, copying data from CPU memory to GPU memory, executing the CUDA kernels, copying outputs from GPU memory to CPU memory, and writing outputs. We also include an additional pre-docking stage where the necessary information of the target protein-DNA pairs are retrieved from text files, assembled into appropriate data structures, and then stored as binary data files. With such pre-docking data ready, the master process can dispatch docking task by sending out a simple task ID, the slave process will load data file directly according to this ID. The MPI processes can thus be light-weighted, and the startup overhead can be significantly reduced.The overall structure of the CUDA kernel for our Monte-Carlo simulated annealing based docking algorithm is illustrated in Figure The computation of the VDW packing energy dominates the execution time. This interaction only affects atoms within close proximity and approaches zero as the distance increases. Consequently, in the computation, the entire 3D space is partitioned into small cells (6x6x6 Å), and for each DNA atom, we only evaluate its interaction energy with protein atoms in the same cell and in the neighboring 26 cells. Our algorithm uses 27 threads to evaluate one DNA atom with respect of its 27 neighboring cells (including the cell the atom resides). The binding affinity is evaluated between DNA triplets and protein residues. During the evaluations, the space is partitioned into lattices which are coarser-grained than cells for packing energy calculation. Since a molecule has fewer triplets/residues than atoms, the computation of binding affinity is faster than the packing energy.The rugged docking energy landscape and the statistical nature of our docking algorithm suggest that an accurate conformation can be found only if sufficient Monte-Carlo simulations are conducted assuming the energy function is accurate. We first show the importance of conducting more simulation runs and the need for computational speedups. We conducted 5400 simulation runs for each complex in our dataset of the 75 TF-DNA complexes. Sixty-three out of the 75 complexes have at least one docked conformation with RMSD less than 2 Å. The number of runs needed to produce one near native conformation is summarized in Figure We implemented our protein-DNA docking algorithm on GPU and tested the execution speed of our GPU docking program. We used a 2.8GHz Intel Xeon processor as the baseline to measure the speedup. Twenty Monte-Carlo simulation runs were conducted for each TF-DNA complex. The average speedup across all complexes is 28. A breakdown of the speedup shows that the calculation of the packing energy was accelerated by 40, and binding affinity by 35. Not surprisingly, speedups in moving the DNA and accepting new DNA positions are small due to the simplicity of these calculations. We also tested the scalability of our algorithm when executed on the GPU cluster. In the strong scaling experiment, we assigned 4256, 8512, 17024, and 34048 tasks to each GPU respectively. Figure To assess the improvement on prediction accuracy with our accelerated GPU algorithm, we ran the GPU docking algorithm with different number of Monte-Carlo simulations, 200, 400, 800, and 1600 using the data set of 75 TF-DNA complexes. The results are shown in Table We next tested our GPU accelerated sampling on the rigid TF-DNA docking benchmark . The benWe ran our GPU docking simulations on this benchmark set with the number of simulation runs at 200, 800, and 1600 respectively. The detailed docking results are shown in Table The docking simulations also produced some near-native structures ("conformation with the lowest RMSD" in Table Protein-DNA docking is a computation extensive problem. Due to the statistical nature of our Monte Carlo-based protein-DNA docking algorithm and the potentially rugged energy landscape, it is desirable to run multiple Monte-Carlo simulations with different seeds for better prediction performance. In this paper, we present a GPU-based high-performance protein-DNA docking algorithm that was designed for large scale GPU clusters. Modern GPU is not only a powerful graphics engine but also a highly parallel programmable processor featuring peak arithmetic and memory bandwidth that often substantially outpaces its CPU counterpart . Rapid iExperimental results using a non-redundant dataset demonstrated a 28x speedup using a single GPU card and close-to-linear scalability when using GPU clusters. Further testing on a rigid TF-DNA docking benchmark revealed that such improved computing capability improves the chance of finding near-native conformations for the easy cases in the benchmark, but not on the hard cases, suggesting there is a limit for improving prediction accuracy by simply increasing the number of simulation runs with our current energy function and search algorithm. There is clearly a need for developing more efficient search algorithms and more accurate interaction potentials.CUDA: compute unified device architecture; GPU: graphical processing unit; HPC: high performance computing; MPI: message passing interface; NRBC: number of residue-base contact; PDB: protein data bank; RMSD: root mean square deviation; TF: transcription factor; VDW: van der Waals.The authors declare that they have no competing interests.BH and JTG conceived the project and wrote the manuscript. JW implemented the GPU docking program and performed the docking simulation and data analysis. TT prepared the datasets and generated the pre-docking data files. All authors read and approved the final manuscript.


The ability to adapt to environments with fluctuating nutrient availability is vital for bacterial survival. Although essential for growth, few nitrogen metabolism genes have been identified or fully characterised in mycobacteria and nitrogen stress survival mechanisms are unknown.Mycobacterium smegmatis genome. Gene expression changes were mapped onto the metabolic network using Active Modules for Bipartite Networks (AMBIENT) to identify metabolic pathways showing coordinated transcriptional responses to the stress. AMBIENT revealed several key features of the metabolic response not identified by KEGG enrichment alone. Down regulated reactions were associated with the general reduction in cellular metabolism as a consequence of reduced growth rate. Up-regulated modules highlighted metabolic changes in nitrogen assimilation and scavenging, as well as reactions involved in hydrogen peroxide metabolism, carbon scavenging and energy generation.A global transcriptional analysis of the mycobacterial response to nitrogen stress, showed a significant change in the differential expression of 16% of the Application of an Active Modules algorithm to transcriptomic data identified key metabolic reactions and pathways altered in response to nitrogen stress, which are central to survival under nitrogen limiting environments. Escherichia coli have served as the model for nitrogen limitation ) and also ArrayExpress (accession number [A-BUGS-140]).The microarray was constructed by determining all unique genes from the 6887 chromosomal predicted coding sequences of http://www.bioconductor.org). Data generated from the Agilent Feature Extraction software for each sample was imported into R. Replicate probes were mean summarised and quantile normalised using the preprocess Core R package. The limma R package [t-statistics to identify differentially expressed gene between time points. Generated p-values were corrected for multiple testing using the Benjamini and Hochberg False Discovery Rate. A corrected p-value cut-off of less than 0.01 was used to determine significant differential expression.Statistical analyses of the gene expression data was carried out using the statistical analysis software environment R together with packages available as part of the Bioconductor project  [Metabolic pathway enrichment for strongly up- and down-regulated genes was assessed using the one-tailed Fisher's exact test against the KEGG pathway assignments for s (FDRs) . PathwayM. smegmatis is exposed to nitrogen stress. The active modules approach used in AMBIENT takes into account the bipartite nature of the metabolic network of reactions and metabolites to find metabolic pathways (or modules) that are co-ordinately affected at the transcriptional level due to some environmental change. Co-ordinately affected modules (connected components of the metabolic network) were found containing reactions associated with large changes in gene expression, linked by metabolites with low connectivity (i.e. linked to few other reactions).A modified active modules approach  called AIn brief, the AMBIENT method works as follows iii. Weights (negative scores) are assigned to metabolites proportional to their connectivity in the metabolic networkiv. Simulated annealing is used to find the connected components of the network with the highest scores  are minimised by the assignment of connectivity-dependent weights to their nodes in the bipartite network.AMBIENT: Active Modules for BIpartitE NeTworks; FDR: False discovery rate; GSEA: Gene set enrichment analysis; KEGG: Kyoto encyclopedia of genes and genomes; TB: Tuberculosis; GDH: Glutamate dehydrogenase; GS: Glutamine synthetase; GOGAT: Glutamate synthase; DPA: Differential producibility analysis; FBA: Flux balance analysis.The authors declare that they have no competing interests.M. smegmatis (v1.0.1) microarray, JP and WB performed the GSEA and AMBIENT analyses on the normalised array data and co-wrote the manuscript, and BR supervised the project and co-wrote the manuscript. All authors have approved the final manuscript for publication.KW designed and performed experiments, analysed the data and co-wrote the manuscript. VJ performed experiments, GB generated and formatted the normalised array data and performed statistical analyses on the data, AW designed the An Excel file containing the average expression ratios for all analysed genes in nitrogen limiting (Low) and nitrogen excess (High) conditions (n = 3).Click here for fileAn Excel file containing average fold changes (n = 3) for all significantly differentially expressed genes in nitrogen limiting conditions .Click here for fileA zip file containing illustrations of the 20 up-regulated metabolic network modules in nitrogen limitation identified by AMBIENT.Click here for fileA zip file containing illustrations of the 6 down-regulated metabolic network modules in nitrogen limitation identified by AMBIENT.Click here for fileA list of genes in each module in S3 and S4.Click here for fileUp-modules are presented in their metabolic network context, illustrating a cluster of modules around ammonium and around hydrogen peroxide. In S6.1 the nodes in a module are coloured using the original scoring scheme, while in S6.2 the nodes in each module are coloured the same.Click here for fileA table showing the qRT-PCR primers and probe sequences used for the relative quantification of gene expression in M. smegmatis  during nitrogen limitation.Click here for file