The non-homologous end-joining pathway of S. cerevisiae works effectively in G1-phase cells,and religates cognate ends correctly and non-randomly

DNA double-strand breaks (DSBs) are potentially lethal lesions repaired by two major pathways: homologous recombination (HR) and non-homologous end-joining (NHEJ). Homologous recombination preferentially reunites cognate broken ends. In contrast, non-homologous end-joining could ligate together any two ends, possibly generating dicentric or acentric fragments, leading to inviability. Here, we characterize the yeast NHEJ pathway in populations of pure G1 phase cells, where there is no possibility of repair using a homolog. We show that in G1 yeast cells, NHEJ is a highly effective repair pathway for gamma-ray induced breaks, even when many breaks are present. Pulsed-field gel analysis showed chromosome karyotypes following NHEJ repair of cells from populations with multiple breaks. The number of reciprocal translocations was surprisingly low, perhaps zero, suggesting that NHEJ preferentially re-ligates the “correct” broken ends instead of randomly-chosen ends. Although we do not know the mechanism, the preferential correct ligation is consistent with the idea that broken ends are continuously held together by protein–protein interactions or by larger scale chromatin structure.     

BTEVAL: a server for evaluation of beta-turn prediction methods

This paper describes a web server BTEVAL, developed for assessing the performance of newly developed beta-turn prediction method and it's ranking with respect to other existing beta-turn prediction methods. Evaluation of a method can be carried out on a single protein or a number of proteins. It consists of clean data set of 426 non-homologous proteins with seven subsets of these proteins. Users can evaluate their method on any subset or a complete set of data. The method is assessed at amino acid level and performance is evaluated in terms of Qtotal, Qpredicted, Qobserved and MCC measures. The server also compares the performance of the method with other existing beta-turn prediction methods such as Chou-Fasman algorithm, Thornton's algorithm, GORBTURN, 1-4 and 2-3 Correlation model, Sequence coupled model and BTPRED. The server is accessible from http://imtech.res.in/raghava/bteval/     

Both ATM and ATR promote the efficient and accurate processing of programmed meiotic double-strand breaks

The ATM and ATR protein kinases play central roles in the cellular response to double-strand breaks (DSBs) by regulating DNA repair, cell-cycle arrest and apoptosis. During meiosis, SPO11-dependent DSBs are generated, initiating recombination between homologous chromosomes. Previous studies in mice and plants have shown that defects in ATM result in the appearance of abnormally fragmented chromosomes. However, the role of ATR in promoting normal meiosis has not yet been elucidated. Employing null Arabidopsis mutants of ATR and ATM , we demonstrate here that although atr mutants display no obvious defects in any phase of meiotic progression, the combination of defects in atr and atm exacerbates the fragmentation observed in the atm single mutant, prevents complete synapsis of chromosomes, and results in extensive and persistent interactions between non-homologous DNAs. The observed non-homologous interactions require the induction of programmed breaks: the combination of either the atm single or the atr atm double mutant with a spo11 defect eliminates the ectopic interactions observed in the double mutant, as well as significantly reducing the fragmentation seen in atm or in atr atm . Our results suggest that ATM is required for the efficient processing of SPO11-dependent DSBs during meiosis. They also indicate that ATM and ATR act redundantly to inhibit sustained interactions between non-homologous chromatids, and that these ectopic interactions require SPO11 activity.     

Is it better to combine predictions?

We have compared the accuracy of the individual protein secondary structure prediction methods: PHD, DSC, NNSSP and Predator against the accuracy obtained by combing the predictions of the methods. A range of ways of combing predictions were tested: voting, biased voting, linear discrimination, neural networks and decision trees. The combined methods that involve 'learning' (the non-voting methods) were trained using a set of 496 non-homologous domains; this dataset was biased as some of the secondary structure prediction methods had used them for training. We used two independent test sets to compare predictions: the first consisted of 17 non-homologous domains from CASP3 (Third Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction); the second set consisted of 405 domains that were selected in the same way as the training set, and were non-homologous to each other and the training set. On both test datasets the most accurate individual method was NNSSP, then PHD, DSC and the least accurate was Predator; however, it was not possible to conclusively show a significant difference between the individual methods. Comparing the accuracy of the single methods with that obtained by combing predictions it was found that it was better to use a combination of predictions. On both test datasets it was possible to obtain a approximately 3% improvement in accuracy by combing predictions. In most cases the combined methods were statistically significantly better (at P = 0.05 on the CASP3 test set, and P = 0.01 on the EBI test set). On the CASP3 test dataset there was no significant difference in accuracy between any of the combined method of prediction: on the EBI test dataset, linear discrimination and neural networks significantly outperformed voting techniques. We conclude that it is better to combine predictions.     

RAD51 supports spontaneous non-homologous recombination in mammalian cells, but not the corresponding process induced by topoisomerase inhibitors

The RAD51 protein has been shown to participate in homologous recombination by promoting ATP-dependent homologous pairing and strand transfer reactions. In the present study, we have investigated the possible involvement of RAD51 in non-homologous recombination. We demonstrate that overexpression of CgRAD51 enhances the frequency of spontaneous non-homologous recombination in the hprt gene of Chinese hamster cells. However, the rate of non-homologous recombination induced by the topoisomerase inhibitors campothecin and etoposide was not altered by overexpression of RAD51. These results indicate that the RAD51 protein may perform a function in connection with spontaneous non-homologous recombination that is not essential to or not rate-limiting for non-homologous recombination induced by camptothecin or etoposide. We discuss the possibility that the role played by RAD51 in non-homologous recombination observed here may not be linked to non-homologous end-joining.     

定量PCR的非同源对照模板的构建

建立了HCV RNA和hTERT mRNA的竞争定量PCR系统。对照模板的构建方法是：利用计算机辅助优选设计连接引物,低严紧型扩增大肠杆菌DNA,回收并克隆预期的DNA片段。该片段与靶序列除两端引物序列完全相同外,无同源性,因此可作为非同源对照模板,这种构建同源对照模板的方法,简便易行,适应面广。     

Synapsis and recombination in inversion heterozygotes

Inversion heterozygotes are expected to suffer from reduced fertility and a high incidence of chromosomally unbalanced gametes due to recombination within the inverted region. Non-homologous synapsis of the inverted regions can prevent recombination there and diminish the deleterious effects of inversion heterozygosity. The choice between non-homologous and homologous synapsis depends on the size of inversion, its genetic content, its location in relation to the centromere and telomere, and genetic background. In addition, there is a class of inversions in which homologous synapsis is gradually replaced by non-homologous synapsis during meiotic progression. This process is called synaptic adjustment. The degree of synaptic adjustment depends critically on the presence and location of the COs (crossovers) within the inversion loop. Only bivalents without COs within the loop and those with COs in the middle of the inversion can be completely adjusted and became linear.     

What we talk about when we talk about access deficits

Semantic impairments have been divided into storage deficits, in which the semantic representations themselves are damaged, and access deficits, in which the representations are intact but access to them is impaired. The behavioural phenomena that have been associated with access deficits include sensitivity to cueing, sensitivity to presentation rate, performance inconsistency, negative serial position effects, sensitivity to number and strength of competitors, semantic blocking effects, disordered selection between strong and weak competitors, correlation between semantic deficits and executive function deficits and reduced word frequency effects. Four general accounts have been proposed for different subsets of these phenomena: abnormal refractoriness, too much activation, impaired competitive selection and deficits of semantic control. A combination of abnormal refractoriness and impaired competitive selection can account for most of the behavioural phenomena, but there remain several open questions. In particular, it remains unclear whether access deficits represent a single syndrome, a syndrome with multiple subtypes or a variable collection of phenomena, whether the underlying deficit is domain-general or domain-specific, whether it is owing to disorders of inhibition, activation or selection, and the nature of the connection (if any) between access phenomena in aphasia and in neurologically intact controls. Computational models offer a promising approach to answering these questions.     

A neural network method for prediction of beta-turn types in proteins using evolutionary information

MOTIVATION: The prediction of beta-turns is an important element of protein secondary structure prediction. Recently, a highly accurate neural network based method Betatpred2 has been developed for predicting beta-turns in proteins using position-specific scoring matrices (PSSM) generated by PSI-BLAST and secondary structure information predicted by PSIPRED. However, the major limitation of Betatpred2 is that it predicts only beta-turn and non-beta-turn residues and does not provide any information of different beta-turn types. Thus, there is a need to predict beta-turn types using an approach based on multiple sequence alignment, which will be useful in overall tertiary structure prediction. RESULTS: In the present work, a method has been developed for the prediction of beta-turn types I, II, IV and VIII. For each turn type, two consecutive feed-forward back-propagation networks with a single hidden layer have been used where the first sequence-to-structure network has been trained on single sequences as well as on PSI-BLAST PSSM. The output from the first network along with PSIPRED predicted secondary structure has been used as input for the second-level structure-to-structure network. The networks have been trained and tested on a non-homologous dataset of 426 proteins chains by 7-fold cross-validation. It has been observed that the prediction performance for each turn type is improved significantly by using multiple sequence alignment. The performance has been further improved by using a second level structure-to-structure network and PSIPRED predicted secondary structure information. It has been observed that Type I and II beta-turns have better prediction performance than Type IV and VIII beta-turns. The final network yields an overall accuracy of 74.5, 93.5, 67.9 and 96.5% with MCC values of 0.29, 0.29, 0.23 and 0.02 for Type I, II, IV and VIII beta-turns, respectively, and is better than random prediction. AVAILABILITY: A web server for prediction of beta-turn types I, II, IV and VIII based on above approach is available at http://www.imtech.res.in/raghava/betaturns/ and http://bioinformatics.uams.edu/mirror/betaturns/ (mirror site).     

Impacts of introduced species on the biota of an oceanic archipelago: the relative importance of competitive and trophic interactions

Introduced species negatively impact native species through competitive and trophic interactions, particularly on oceanic islands that have never been connected to any continental landmass. However, there are few studies on the relative importance of competitive interactions (resource competition with introduced species) and trophic interactions (predation or herbivory by introduced species) with respect to the negative impacts on native organisms on oceanic islands. A literature review on introduced and native species of the oceanic Ogasawara (Bonin) Islands in the western Pacific Ocean indicated that many native species (e.g., bees, beetles, damselflies, butterflies, land snails, birds, and plants) have been negatively impacted by introduced predators and herbivores (e.g., lizards, rats, flatworms, and goats). Several native plants and bees have been negatively affected by introduced competitors. However, the native species that have competed with introduced species have also suffered from either intense herbivory or predation by other introduced species. Thus, introduced predators and herbivores have had greater impacts on native species than introduced competitors in the Ogasawara Islands.     

Improved method for predicting beta-turn using support vector machine

MOTIVATION: Numerous methods for predicting beta-turns in proteins have been developed based on various computational schemes. Here, we introduce a new method of beta-turn prediction that uses the support vector machine (SVM) algorithm together with predicted secondary structure information. Various parameters from the SVM have been adjusted to achieve optimal prediction performance. RESULTS: The SVM method achieved excellent performance as measured by the Matthews correlation coefficient (MCC = 0.45) using a 7-fold cross validation on a database of 426 non-homologous protein chains. To our best knowledge, this MCC value is the highest achieved so far for predicting beta-turn. The overall prediction accuracy Qtotal was 77.3%, which is the best among the existing prediction methods. Among its unique attractive features, the present SVM method avoids overtraining and compresses information and provides a predicted reliability index.     

Protein interaction network analysis—Approach for potential drug target identification in Mycobacterium tuberculosis

In host-parasite diseases like tuberculosis, non-homologous proteins (enzymes) as drug target are first preference. Most potent drug target can be identified among large number of non-homologous protein through protein interaction network analysis. In this study, the entire promising dimension has been explored for identification of potential drug target. A comparative metabolic pathway analysis of the host Homo sapiens and the pathogen M. tuberculosis H37Rv has been performed with three level of analysis. In first level, the unique metabolic pathways of M. tuberculosis have been identified through its comparative study with H. sapiens and identification of non-homologous proteins has been done through BLAST similarity search. In second level, choke-point analysis has been performed with identified non-homologous proteins of metabolic pathways. In third level, two type of analysis have been performed through protein interaction network. First analysis has been done to find out the most potential metabolic functional associations among all identified choke point proteins whereas second analysis has been performed to find out the functional association of high metabolic interacting proteins to pathogenesis causing proteins. Most interactive metabolic proteins which have highest number of functional association with pathogenesis causing proteins have been considered as potential drug target. A list of 18 potential drug targets has been proposed which are various stages of progress at the TBSGC and proposed drug targets are also studied for other pathogenic strains.As a case study, we have built a homology model of identified drug targets histidinol-phosphate aminotransferase (HisC1) using MODELLER software and various information have been generated through molecular dynamics which will be useful in wetlab structure determination. The generated model could be further explored for insilico docking studies with suitable inhibitors.     

Numerical assessment affects aggression and competitive ability: a team-fighting strategy for the ant Formica xerophila

The relationship between numerical advantage and competitive ability is a fundamental component in contests between groups of social animals. An individual's ability to correctly assess the numerical state of its group is of vital importance. In addition to numerical dominance, the group's fighting ability also plays an important role in competitive interactions. By staging experimental fights between two Formica ant species, I show that Formica xerophila are able to assess their own group's strength prior to any competitive encounter. Ants that perceive themselves as part of a large group act more aggressively toward a competitor than ants that perceive themselves as isolated individuals. This increase in aggression improves F. xerophila's competitive ability. Furthermore, the number of individuals in a contest was found to affect competitive ability. In contests with equal number of competitors, groups of F. xerophila were more successful than individual F. xerophila. Contrary to previous predictions using Lanchester's laws of fighting, F. xerophila's ability to kill competitors increased nonlinearly with group size. This nonlinearity was due to the collective fighting strategy of an F. xerophila group isolating and engaging a single Formica integroides competitors.     

Assay of lactogenic hormones using receptors isolated from rabbit liver.

Using 125-I-labelled ovine prolactin and receptors isolated from the livers of rabbits, a sensitive method has been developed suitable for the assay of ovine, bovine, porcine, human and rat prolactins. These hormones showed competitive displacement of 125-I-ovine prolactin which was in general agreement with their respective activities in the pigeon crop sac bioassay. Human and monkey growth hormones and human placental lactogen, which have marked prolactin-like actions on mammary tissue were also effective competitors. Non-primate growth hormones (ovine, bovine, equine and canine) which do not have prolactin-like activity gave little if any displacement as did human FSH, LH, TSH, ACTH and bovine insulin. Preparations of equine and canine prolactin of varying purity gave dose-response curves although their activity as competitors relative to ovine prolactin was poor and not related to their pigeon crop stimulating activity. This indicates species differences between prolactins in hormone-receptor interaction. Experiments with antiserum to human growth hormone have suggested an effective method of making the assay specific in species such as man in which prolactin is not the sole hormone with lactogenic activity.     

Functional interaction between Ku and the werner syndrome protein in DNA end processing

Werner syndrome (WS) is an autosomal recessive disease characterized by premature aging. The gene responsible for the syndrome was recently cloned and shown to encode a protein with strong homology to DNA/RNA helicases. In addition, the Werner syndrome protein (WRN) possesses an exonuclease activity. Based on the homology to helicases it has been proposed that WRN functions in some aspects of DNA replication, recombination, or repair. However, there is currently no evidence of a role of WRN in any of these processes; therefore, its biological function remains unknown. Using a biochemical approach, we have identified two polypeptides that bind to the WRN protein. Peptide sequence analysis indicates that the two proteins are identical to Ku70 and Ku80, a heterodimer involved in double strand DNA break repair by non-homologous DNA end joining. Protein-protein interaction studies reveal that WRN binds directly to Ku80 and that this interaction is mediated by the amino terminus of WRN. In addition, we show that the binding of Ku alters the specificity of the WRN exonuclease. These results suggest a potential involvement of WRN in the repair of double strand DNA breaks.     

Protein beta-turn prediction using nearest-neighbor method

MOTIVATION: With the emerging success of protein secondary structure prediction through the applications of various statistical and machine learning techniques, similar techniques have been applied to protein beta-turn prediction. In this study, we perform protein beta-turn prediction using a k-nearest neighbor method, which is combined with a filter that uses predicted protein secondary structure information. Traditional beta-turn prediction from k-nearest neighbor method is modified to account for the unbalanced ratio of the natural occurrence of beta-turns and non-beta-turns. RESULTS: Our prediction scheme is tested on a set of 426 non-homologous protein sequences. The prediction scheme consists of two stages: k-nearest neighbor method stage and filtering stage. Variations of the k-nearest neighbor method were used to take property of beta-turns into consideration. Our filtering method uses beta-turn/non-beta-turn estimates from the k-nearest neighbor method stage and predicted protein secondary structure information from PSI-PRED in order to get new beta-turn/non-beta-turn estimate. Our result is compared with the previously best known beta-turn prediction method on the dataset of 426 non-homologous protein sequences and is shown to give slightly superior performance at significantly lower computational complexity. AVAILABILITY: Contact the author for information on the source code of the programs used.     

Radioimmunochemical evidence for a role of carbohydrate in antigenic determinant(s) on human liver alpha-L-fucosidase.

A competitive-binding radioimmunoassay method was employed to investigate the role of carbohydrate in antigenic determinant(s) of human liver alpha-L-fucosidase. Competition curves were used to quantify the concentrations of competitors needed to cause 30% inhibition of the precipitation of 125I-labelled alpha-L-fucosidase. The isoelectric forms of alpha-L-fucosidase, which are related by sialic acid residues, were separated preparatively and used as competitors in the radioimmunoassay. A pattern of increasing effectiveness as competitors with increasing acidity of the forms was found, suggesting that sialic acid may be involved in the antigenic determinant(s) of alpha-L-fucosidase. Specificity was exhibited when sugar and sugar derivatives were used as competitors in the radioimmunoassay: a 51-fold range of competitive ability was found, and sialic acids (N-acetylneuraminic acid and N-glycollylneuraminic acid) and colominic acid (a polymer of N-acetylneuraminic acid) were the best competitors. The results of our studies suggest that carbohydrate contributes to antigenic determinant(s) of alpha-L-fucosidase and that sialic acid is probably the major sugar involved.     

Non-homologous chromosome pairing and crossover formation in haploid rice meiosis

While many studies have provided significant insight into homolog pairing during meiosis, information on non-homologous pairing is much less abundant. In the present study, fluorescence in situ hybridization (FISH) was used to investigate non-homologous pairing in haploid rice during meiosis. At pachytene, non-homologous chromosomes paired and formed synaptonemal complexes. FISH analysis data indicated that chromosome pairing could be grouped into three major types: (1) single chromosome paired fold-back as the univalent structure, (2) two non-homologous chromosomes paired as the bivalent structure, and (3) three or more non-homologous chromosomes paired as the multivalent structure. In the survey of 70 cells, 65 contained univalents, 45 contained bivalents, and 49 contained multivalent. Moreover, chromosomes 9 and 10 as well as chromosomes 11 and 12 formed non-homologous bivalents at a higher frequency than the other chromosomes. However, chiasma was always detected in the bivalent only between chromosomes 11 and 12 at diakinesis or metaphase I, indicating the pairing between these two chromosomes leads non-homologous recombination during meiosis. The synaptonemal complex formation between non-homologs was further proved by immunodetection of RCE8, PAIR2, and ZEP1. Especially, ZEP1 only loaded onto the paired chromosomes other than the un-paired chromosomes at pachytene in haploid.     

Successes and prospects for genetic engineering]

The review of literature (1970-1976) on problems of gene engineering is given. Gene engineering is pointed out to be a new method of modern biology and a new page of modern molecular genetics. Gene engineering detected a real possibility of artificial creating living hybrid organisms, i.e. constructing functional recombinant DNA molecules according to a project of investigator, but not to possibilities of crossing. The determination of gene engineering (in contrast with genetical engineering) is given in the first division of the article. Genetical engineering is a construction of hybrid organisms on the basis of recombination between non-homologous chromosomes cy crossing. Genetical engineering is based on sex crossing, thus the application of this method is restricted by crossability (i.e. experiments in vivo), which possibilities are determined by taxonomical limits. Gene engineering is a new method of operating directly with genes. It permits constructing in vitro any hybrid genomes desirable. There is no limits of combining ability for gene engineering. Three main stages of constructing hybrid genomes should be taken into account for the proper determination of gene engineering as a method of genome constructing: 1) the gene isolation; 2) their cross-linking in vitro; 3) the transfer of hybrid DNA into recipient cell or its genome. The cardinal stage of gene engineering is the construction of hybrid DNA, cross-linking any initial DNAs from any remote animals, plants and bacteria. All the methods known of gene isolation are described. The chemical method of gene isolation is based on that case, when DNA of some gene differs in its physico-chemical characteristics from total DNA, for example, DNAs of genes coding ribosomal RNAs or sea urchine histone DNA. Isolation of promotors and operators using DNA dependent RNA polymerase, which recognizes promotors, repressor and operator DNA, should also be considered as the chemical method of gene isolation. Restrictase method, which is also well known, is convenuent because the restricts have long enough sticky ends, which is important for the following gene cross-linking. The method of total restriction, reported by Lederberg et al. and Debabov et al., is described. The phage method (in particular, Shimada method) is given, permitting the direct integration of lambda phage into a number of sites of Escherichia coli chromosome. Gene engineering method of gene isolation is mentioned, in particular, the data of Kameron et al. on hybrid phages carrying DNA ligase gene, and Clark a. Carbon on hybrid plasmids carrying triptophane and arabinose operons genes. These methods are called "shot gun". Methods of gene isolation from higher organisms are less developed. A method of gene isolation using so called colony hybridization (according to Grünstein and Hognes) is also given...