Quake: quality-aware detection and correction of sequencing errors

We introduce Quake, a program to detect and correct errors in DNA sequencing reads. Using a maximum likelihood approach incorporating quality values and nucleotide specific miscall rates, Quake achieves the highest accuracy on realistically simulated reads. We further demonstrate substantial improvements in de novo assembly and SNP detection after using Quake. Quake can be used for any size project, including more than one billion human reads, and is freely available as open source software from .     

Molecular detection and correction of ornithine transcarbamylase deficiency

The application of new diagnostic techniques has led to improvement in carrier detection and prenatal diagnosis in ornithine transcarbamylase deficiency. Progress has also been made towards somatic gene therapy.     

Molecular genetic approaches to the cytoskeleton in Dictyostelium.

Recent advances in molecular genetic techniques are being applied in Dictyostelium to test and expand prevailing views on the functioning of the actin-based cytoskeleton. Current research involves the disruption, by homologous recombination, of genes encoding cytoskeletal elements. We suggest combining classical and molecular genetic approaches to supplement these investigations.     

Molecular approaches to nerve regeneration.

Current research into regeneration of the nervous system has focused on defining the molecular events that occur during regeneration. One well-characterized system for studying nerve regeneration is the sciatic nerve of rat. Numerous studies have characterized the sequence of events that occur after a crush injury to the sciatic nerve (Cajal 1928; Hall 1989). These events include axon and myelin breakdown, changes in the permeability of the blood vessels, proliferation of Schwann cells, invasion of macrophages, and the phagocytosis of myelin fragments by Schwann cells and macrophages. The distal segment of the injured sciatic nerve provides a supportive environment for the regeneration of the nerve fibres (Cajal 1928; David & Aguayo 1981). Within a period of weeks, the injured sciatic nerve is able to regrow and successfully reinnervate the appropriate targets. Some of the molecules that provide trophic support for the regrowing nerve fibres have been identified, including nerve growth factor (NGF) (Heumann et al. 1987) and glial maturation factor beta (Bosch et al. 1989). Another class of molecules show changes in their rates of synthesis during regeneration, including both proteins (Skene & Shooter 1983; Muller et al. 1986) and mRNA species (Trapp et al. 1988; Meier et al. 1989). To better understand nerve regeneration, we have taken two, parallel molecular approaches to study the events associated with regeneration. The first of these is to study in detail the mechanism of action of a molecule that has been implicated in the regeneration process, nerve growth factor. The second approach is to identify novel gene sequences which are regulated during regeneration.(ABSTRACT TRUNCATED AT 250 WORDS)     

Proteomics approaches to biomarker detection.

The development of mass spectrometry (MS) technologies has brought the ability to gather massive amounts of data characterising the proteomes of complex mixtures. A major focus in proteomics is to leverage this data-gathering capability to conduct comparative analyses of biofluids from healthy and disease-affected patients for the identification of highly specific biomarkers and/or the development of MS-based diagnostic platforms. Much effort has gone into optimising the biofluid proteome coverage that can be obtained using these technologies, leaving proteomics poised to make an important impact in disease diagnostics in the future.     

Molecular genetic approaches to plant development.

Higher plant morphogenesis has received renewed interest over the past few years. The improvement of molecular genetic approaches to generate tagged developmental mutants, for instance by T-DNA insertion, facilitated the isolation and characterization of the altered genes. Here we present recent progress on flower and root morphogenesis in the small crucifer Arabidopsis thaliana. The current model of Arabidopsis flower development is presented. We report on FLOWER1 (Fl1), which is a T-DNA-tagged ap2 allele. Our observations indicate that this Fl1 mutant has, besides the homeotic Ap2 phenotype, an aberrant seed coat, suggesting that this gene has also a function late in flower development. Furthermore, we present a brief summary about root development and focus on the super root (Sur) mutant, which is an ethyl methanesulfonate-induced mutant that produces excess lateral roots. Root explants of the Sur mutant, that do not develop further than the 4-leaf stage, can be induced to produce normal-looking shoots and flowers by addition of only cytokinin to the medium. The phenotype of Sur and its relation to the action of phytohormones is discussed.     

Molecular genetic approaches to understanding disease.

Molecular genetics has greatly increased the understanding of diseases in which there is a single gene defect such as cystic fibrosis. Discovering the gene responsible and its function not only helps determine the pathogenesis of the disease but also offers a possible treatment-gene therapy. Polygenic disorders such as diabetes may soon yield their secrets to the same approach. Animal models of genetic diseases are proving useful research tools, and transgenesis has made xenografting possible. Furthermore, antisense technology allows specific inhibition of undesirably overexpressed genes such as those driving unwanted vascular cell proliferation and restenosis after angioplasty. The completion of the human genome project should make the search for "disease" gene much quicker and will increase still further the importance of these gene based approaches toward diseases.     

Pedigree and genotype errors in the Framingham Heart Study

The pedigree and genotype data from the Framingham Heart Study were examined for errors. Errors in 21 of 329 pedigrees were detected with the program PREST, and of these the errors in 16 pedigrees were resolved. Genotyping errors were then detected with SIMWALK2. Five Mendelian errors were found following the pedigree corrections. Double-recombinant errors were more common, with 142 being detected at mistyping probabilities of 0.25 or greater.     

Molecular genetic approaches to the study of cellular senescence.

Normal cells in culture exhibit limited division potential, which is used as a model for cellular aging. In contrast, tumor-derived, carcinogen- or virus-transformed cells are capable of dividing indefinitely (immortal). Fusion of normal with immortal human cells yielded hybrids having limited life span, indicating that cellular senescence is a dominant phenotype and that immortality is recessive. Fusions of various immortal human cell lines with each other led to the identification of four complementation groups for indefinite division. In order to identify the chromosomes and genes involved in growth regulation, that had been modified in immortal cells, we used the technique of microcell fusion to introduce either a normal human chromosome 11 or 4 into cell lines representative of the different complementation groups. Chromosome 11 had no effect on the in vitro life span of the different immortal human tumor lines. However, when a normal human chromosome 4 was introduced into cell lines assigned to complementation group B, the cells lost the immortal phenotype. No effect on the proliferation potential of cell lines representative of the other complementation groups was observed. These results suggest that a gene(s) on human chromosome 4 has been modified in immortal cell lines assigned to complementation group B, to allow escape from senescence. They also provide evidence for a genetic basis for cellular aging.     

Switching off the estrogen effect and approaches to its correction

Data are summarized on experimental means of induction of PSEE and its modification/prevention with the aim to achieve optimal ratio of estrogenic effects (as low as possible genotoxicity in combination with satisfactory and excessive hormonal action). Among studied agents were ethanol, tobacco smoke, irradiation, aging (as PSEE inductors) and carnosine, N-acetylcystein, vit. E and C, melatonin, swimming and antiestrogen ICI 182780 (as PSEE modificators).     

Molecular approaches in pig breeding to improve meat quality.

This article reviews the advances in molecular genetics that have led to the identification of genes and markers associated with meat quality in pig. The development of a considerable number of annotated livestock genome sequences represents an incredibly rich source of information that can be used to identify candidate genes responsible for complex traits and quantitative trait loci effects. In pig, the huge amount of information emerging from the study of the genome has helped in the acquisition of new knowledge concerning biological systems and it is opening new opportunities for the genetic selection of this specie. Among the new fields of genomics recently developed, functional genomics and proteomics that allow considering many genes and proteins at the same time are very useful tools for a better understanding of the function and regulation of genes, and how these participate in complex networks controlling the phenotypic characteristics of a trait. In particular, global gene expression profiling at the mRNA and protein level can provide a better understanding of gene regulation that underlies biological functions and physiology related to the delivery of a better pig meat quality. Moreover, the possibility to realize an integrated approach of genomics and proteomics with bioinformatics tools is essential to obtain a complete exploitation of the available molecular genetics information. The development of this knowledge will benefit scientists, industry and breeders considering that the efficiency and accuracy of the traditional pig selection schemes will be improved by the implementation of molecular data into breeding programs.     

Molecular approaches for the detection and identification of bifidobacteria and lactobacilli in the human gastrointestinal tract

In this review an overview of various molecular techniques and their application for the detection and identification of bifidobacteria and lactobacilli in the gastrointestinal (GI) tract is presented. The techniques include molecular typing techniques such as amplified ribosomal DNA restriction analysis (ARDRA), randomly amplified polymorphic DNA (RAPD), pulsed field gel electrophoresis (PFGE), ribotyping and community profiling techniques such as PCR coupled to temperature and denaturing gradient gel electrophoresis (PCR-TGGE and PCR-DGGE, respectively). Special attention is given to oligonucleotide probes and primers that target the ribosomal RNA (rRNA) sequences and their use in PCR and different hybridisation techniques such as DNA microarrays and fluorescent in situ hybridisation (FISH). In addition, recent findings based on the molecular studies of bifidobacteria and lactobacilli in the GI-tract are reviewed.     

Common scientific and statistical errors in obesity research

This review identifies 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “P‐value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. It is hoped that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician.     

Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications

Statistical analysis reveals that the set of differences between the secondary shifts of the α- and β-carbons for residues i of a protein (Δδ¹³C^α_i- Δδ¹³C^β_i) provides the means to detect and correct referencing errors for ¹H and ¹³C nuclei within a given dataset. In a correctly referenced protein dataset, linear regression plots of Δδ¹³C^α_i,Δδ¹³C^β_i, or Δδ¹H^α_i vs. (Δδ¹³C^α_i- Δδ¹³C^β_i) pass through the origin from two directions, the helix-to-coil and strand-to-coil directions. Thus, linear analysis of chemical shifts (LACS) can be used to detect referencing errors and to recalibrate the ¹H and ¹³C chemical shift scales if needed. The analysis requires only that the signals be identified with distinct residue types (intra-residue spin systems). LACS allows errors in calibration to be detected and corrected in advance of sequence-specific assignments and secondary structure determinations. Signals that do not fit the linear model (outliers) deserve scrutiny since they could represent errors in identifying signals with a particular residue, or interesting features such as a cis-peptide bond. LACS provides the basis for the automated detection of such features and for testing reassignment hypotheses. Early detection and correction of errors in referencing and spin system identifications can improve the speed and accuracy of chemical shift assignments and secondary structure determinations. We have used LACS to create a database of offset-corrected chemical shifts corresponding to nearly 1800 BMRB entries: 300 with and 1500 without corresponding three-dimensional (3D) structures. This database can serve as a resource for future analysis of the effects of amino acid sequence and protein secondary and tertiary structure on NMR chemical shifts.Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1007/s10858-005-1717-0     

Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion

Microsatellite genotyping errors will be present in all but the smallest data sets and have the potential to undermine the conclusions of most downstream analyses. Despite this, little rigorous effort has been made to quantify the size of the problem and to identify the commonest sources of error. Here, we use a large data set comprising almost 2000 Antarctic fur seals Arctocephalus gazella genotyped at nine hypervariable microsatellite loci to explore error detection methods, common sources of error and the consequences of errors on paternal exclusion. We found good concordance among a range of contrasting approaches to error-rate estimation, our range being 0.0013 to 0.0074 per single locus PCR (polymerase chain reaction). The best approach probably involves blind repeat-genotyping, but this is also the most labour-intensive. We show that several other approaches are also effective at detecting errors, although the most convenient alternative, namely mother-offspring comparisons, yielded the lowest estimate of the error rate. In total, we found 75 errors, emphasizing their ubiquitous presence. The most common errors involved the misinterpretation of allele banding patterns (n = 60, 80%) and of these, over a third (n = 22, 36.7%) were due to confusion between homozygote and adjacent allele heterozygote genotypes. A specific test for whether a data set contains the expected number of adjacent allele heterozygotes could provide a useful tool with which workers can assess the likely size of the problem. Error rates are also positively correlated with both locus polymorphism and product size, again indicating aspects where extra effort at error reduction should be directed. Finally, we conducted simulations to explore the potential impact of genotyping errors on paternity exclusion. Error rates as low as 0.01 per allele resulted in a rate of false paternity exclusion exceeding 20%. Errors also led to reduced estimates of male reproductive skew and increases in the numbers of pups that matched more than one candidate male. Because even modest error rates can be strongly influential, we recommend that error rates should be routinely published and that researchers make an attempt to calculate how robust their analyses are to errors.     

Molecular approaches to the study of myiasis-causing larvae

Among arthropod diseases affecting animals, larval infections - myiases - of domestic and wild animals have been considered important since ancient times. Besides the significant economic losses to livestock worldwide, myiasis-causing larvae have attracted the attention of scientists because some parasitise humans and are of interest in forensic entomology. In the past two decades, the biology, epidemiology, immunology, immunodiagnosis and control methods of myiasis-causing larvae have been focused on and more recently the number of molecular studies have also begun to increase. The 'new technologies' (i.e. molecular biology) are being used to study taxonomy, phylogenesis, molecular identification, diagnosis (recombinant antigens) and vaccination strategies. In particular, more in depth molecular studies have now been performed on Sarcophagidae, Calliphoridae and flies of the Oestridae sister group. This review discusses the most topical issues and recent studies on myiasis-causing larvae using molecular approaches. In the first part, PCR-based techniques and the genes that have already been analysed, or are potentially useful for the molecular phylogenesis and identification of myiasis-causing larvae, are described. The second section deals with the more recent advances concerning taxonomy, phylogenetics, population studies, molecular identification, diagnosis and vaccination.