Adapting ACMG/AMP sequence variant classification guidelines for single-gene copy number variants.

PURPOSE: The ability of a single technology, next-generation sequencing, to provide both sequence and copy number variant (CNV) results has driven the merger of clinical cytogenetics and molecular genetics. Consequently, the distinction between the definition of a sequence variant and a CNV is blurry. As the 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) standards and guidelines for interpretation of sequence variants address CNV classification only sparingly, this study focused on adapting ACMG/AMP criteria for single-gene CNV interpretation. METHODS: CNV-specific modifications of the 2015 ACMG/AMP criteria were developed and their utility was independently tested by three diagnostic laboratories. Each laboratory team interpreted the same 12 single-gene CNVs using three systems: (1) without ACMG/AMP guidance, (2) with ACMG/AMP criteria, and (3) with new modifications. A replication study of 12 different CNVs validated the modified criteria. RESULTS: The adapted criteria system presented here showed improved concordance and usability for single-gene CNVs compared with using the ACMG/AMP interpretation guidelines focused on sequence variants. CONCLUSION: These single-gene CNV criteria modifications could be used as a supplement to the ACMG/AMP guidelines for sequence variants, allowing for a streamlined workflow and a step toward a uniform classification system for both sequence and copy number alterations.

Fast read alignment with incorporation of known genomic variants.

BACKGROUND: Many genetic variants have been reported from sequencing projects due to decreasing experimental costs. Compared to the current typical paradigm, read mapping incorporating existing variants can improve the performance of subsequent analysis. This method is supposed to map sequencing reads efficiently to a graphical index with a reference genome and known variation to increase alignment quality and variant calling accuracy. However, storing and indexing various types of variation require costly RAM space. METHODS: Aligning reads to a graph model-based index including the whole set of variants is ultimately an NP-hard problem in theory. Here, we propose a variation-aware read alignment algorithm (VARA), which generates the alignment between read and multiple genomic sequences simultaneously utilizing the schema of the Landau-Vishkin algorithm. VARA dynamically extracts regional variants to construct a pseudo tree-based structure on-the-fly for seed extension without loading the whole genome variation into memory space. RESULTS: We developed the novel high-throughput sequencing read aligner deBGA-VARA by integrating VARA into deBGA. The deBGA-VARA is benchmarked both on simulated reads and the NA12878 sequencing dataset. The experimental results demonstrate that read alignment incorporating genetic variation knowledge can achieve high sensitivity and accuracy. CONCLUSIONS: Due to its efficiency, VARA provides a promising solution for further improvement of variant calling while maintaining small memory footprints. The deBGA-VARA is available at: https://github.com/hitbc/deBGA-VARA.

Medical Devices; Immunology and Microbiology Devices; Classification of the Next Generation Sequencing Based Tumor Profiling Test. Final order.

The Food and Drug Administration (FDA or we) is classifying the next generation sequencing based tumor profiling test into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the next generation sequencing based tumor profiling test's classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.

Medical Devices; Clinical Chemistry and Clinical Toxicology Devices; Classification of the High Throughput Genomic Sequence Analyzer for Clinical Use. Final order.

The Food and Drug Administration (FDA) is classifying the high throughput genomic sequence analyzer for clinical use into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the classification of the high throughput genomic sequence analyzer for clinical use device. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

Sequence variation in the Toxoplasma gondii ROP20 gene among strains from different hosts and geographical locations.

Toxoplasma gondii, an opportunistic protozoan parasite, infects almost all warm-blooded animals. In this study, we examined the sequence variation in rhoptry protein 20 (ROP20) genes among 18 T. gondii isolates collected from different hosts and geographical regions. Full length ROP20 genes were amplified and sequenced. The results showed that the genes were 1659 bp in length and contained only a single exon, and that the A+T content varied from 46.68 to 47.20% among the 18 strains. The results of sequence alignment indicated that there were 30 variable nucleotide positions (0-1.40%) in the 18 T. gondii strains containing 18 transitions and 11 transversions, representing 1.81% overall sequence variation. Phylogenetic analysis of the ROP20 sequences showed that ROP20 variation could differentiate between the clonal lineage genotypes I and ToxoDB #9, indicating that ROP20 exhibits a relatively marked degree of sequence diversity and might represent a novel genetic marker for intraspecies phylogenetic analyses of T. gondii.

[Resequencing microarrays: a rapid tool for better identification and understanding of viral and bacterial emergence]. / La puce à ADN de reséquençage: un outil rapide pour mieux identifier et comprendre une émergence virale et bactérienne.

The introduction of microarray technologies in microbiology has transformed the detection and characterization of microbial pathogens. Microarray-based platforms can be classified into different families according to their characteristics and applications. Resequencing microarrays have several advantages over other technologies for pathogen detection and characterization.

TWARIT: an extremely rapid and efficient approach for phylogenetic classification of metagenomic sequences.

Phylogenetic assignment of individual sequence reads to their respective taxa, referred to as 'taxonomic binning', constitutes a key step of metagenomic analysis. Existing binning methods have limitations either with respect to time or accuracy/specificity of binning. Given these limitations, development of a method that can bin vast amounts of metagenomic sequence data in a rapid, efficient and computationally inexpensive manner can profoundly influence metagenomic analysis in computational resource poor settings. We introduce TWARIT, a hybrid binning algorithm, that employs a combination of short-read alignment and composition-based signature sorting approaches to achieve rapid binning rates without compromising on binning accuracy and specificity. TWARIT is validated with simulated and real-world metagenomes and the results demonstrate significantly lower overall binning times compared to that of existing methods. Furthermore, the binning accuracy and specificity of TWARIT are observed to be comparable/superior to them. A web server implementing TWARIT algorithm is available at http://metagenomics.atc.tcs.com/Twarit/

Gene tree parsimony of multilocus snake venom protein families reveals species tree conflict as a result of multiple parallel gene loss.

The proliferation of gene data from multiple loci of large multigene families has been greatly facilitated by considerable recent advances in sequence generation. The evolution of such gene families, which often undergo complex histories and different rates of change, combined with increases in sequence data, pose complex problems for traditional phylogenetic analyses, and in particular, those that aim to successfully recover species relationships from gene trees. Here, we implement gene tree parsimony analyses on multicopy gene family data sets of snake venom proteins for two separate groups of taxa, incorporating Bayesian posterior distributions as a rigorous strategy to account for the uncertainty present in gene trees. Gene tree parsimony largely failed to infer species trees congruent with each other or with species phylogenies derived from mitochondrial and single-copy nuclear sequences. Analysis of four toxin gene families from a large expressed sequence tag data set from the viper genus Echis failed to produce a consistent topology, and reanalysis of a previously published gene tree parsimony data set, from the family Elapidae, suggested that species tree topologies were predominantly unsupported. We suggest that gene tree parsimony failure in the family Elapidae is likely the result of unequal and/or incomplete sampling of paralogous genes and demonstrate that multiple parallel gene losses are likely responsible for the significant species tree conflict observed in the genus Echis. These results highlight the potential for gene tree parsimony analyses to be undermined by rapidly evolving multilocus gene families under strong natural selection.

Medical devices: immunology and microbiology devices: classification of in vitro human immunodeficiency virus drug resistance genotype assay. Final rule.

The Food and Drug Administration (FDA) is classifying an in vitro human immunodeficiency virus (HIV) drug resistance genotype assay into class II (special controls). The special control that will apply to this device is the guidance document entitled "Class II Special Controls Guidance Document: In Vitro HIV Drug Resistance Genotype Assay." FDA is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of this device. Elsewhere in this issue of the Federal Register, FDA is announcing the availability of the guidance document that will serve as the special control for this device.

Classifying genomic sequences by sequence feature analysis.

Traditional sequence analysis depends on sequence alignment. In this study, we analyzed various functional regions of the human genome based on sequence features, including word frequency, dinucleotide relative abundance, and base-base correlation. We analyzed the human chromosome 22 and classified the upstream, exon, intron, downstream, and intergenic regions by principal component analysis and discriminant analysis of these features. The results show that we could classify the functional regions of genome based on sequence feature and discriminant analysis.

GapCoder automates the use of indel characters in phylogenetic analysis.

BACKGROUND: Several ways of incorporating indels into phylogenetic analysis have been suggested. Simple indel coding has two strengths: (1) biological realism and (2) efficiency of analysis. In the method, each indel with different start and/or end positions is considered to be a separate character. The presence/absence of these indel characters is then added to the data set. ALGORITHM: We have written a program, GapCoder to automate this procedure. The program can input PIR format aligned datasets, find the indels and add the indel-based characters. The output is a NEXUS format file, which includes a table showing what region each indel characters is based on. If regions are excluded from analysis, this table makes it easy to identify the corresponding indel characters for exclusion. DISCUSSION: Manual implementation of the simple indel coding method can be very time-consuming, especially in data sets where indels are numerous and/or overlapping. GapCoder automates this method and is therefore particularly useful during procedures where phylogenetic analyses need to be repeated many times, such as when different alignments are being explored or when various taxon or character sets are being explored. GapCoder is currently available for Windows from http://www.home.duq.edu/~youngnd/GapCoder.

La Genetica Toxicologica: Una ciencia en constante desarrollo / The genetica Toxicologica: A science in constant development

La Genética toxicológica es una ciencia que como resultado del descubrimiento de que la interacción entre tóxicos y DNA, traducidos en varios procesos nocivos como: la mutagénesis, carcinogénesis y teratogénesis entre otros. El reconocimiento de la mutagénesis, como paso previo para la carcinogenicidad y los peligros potenciales de los agentes mutagénicos para la población humana y la biosfera, despertó el interés por desarrollar la Genética Toxicológica como ciencia, de ahí que desde los años 80 los organismos de salud pública en varios países industrializados se preocuparon de implementar tecnologías para evaluar las propiedades genotóxicas de agentes químicos, fisicos, y biológicos, en aditivos alimenticios y medicamentos, entre otros. La Genética Toxicológica evalúa los efectos genotóxicos potenciales en las células somáticas y estuclia la inducción de mutaciones en células germinales que pueden aumentar las frecuencias de enfermedades genéticas. Para tales cometidos son utilizadas diferentes herramientas y técnicas validadas mejoradas día a día con el empleo de equipos computarizados, técnicas en Biología Molecular, modelos en animales extrapolables a humanos, etc. Así, la Genética toxicológica abre un campo de investigación en el mundo y en nuestro país, permitiendo crear nuevas líneas de observación, proporcionando importantes aportes desde 1990 con la evaluación de la genotoxicidad de extractos vegetales y biomonitorización de poblaciones expuestos a diferentes agentes como metales pesados y plaguicidas. El presente articulo pretende mostrar la importancia, aplicabilidad y los últimos avances de esta ciencia en el mundo y particularmente en nuestro país

Relacion de la replicacion con la reparacion por recombinacion de daños en el DNA de Escherichia coli / Relation of the replication with the repair by recombination of damages in the DNA of Escherichia coli

Aunque los fenómenos de recombinación y reparación del DNA inicialmente fueron estudiados sin relacionarlos entre sí, ahora se observan que están muy relacionados con la replicación del DNA. En E. cok, el DNAdc dafiado se generan principalmente en la replícación cuando el molde contiene una hebra dañada, esta molécula es reparada por recombinación con un duplex homologo intacto, usualmente el cromosoma hermano. Se presentan dos tipos principales de lesiones del DNAdc que son reparados por recombinación en dos. formas diferentes. Los vacíos de DNAdc son rellenados por vía RecF, y la horquilla de replicación desintegrada es reestablecida por vía RecBCD. El progreso en el entendimiento de los mecanismos de reparación por recombinación en E. cok en la última década se deben a la caracterización in vitro de las actividades de proteínas individuales de recombinación

[Genetic diversity of Borrelia burgdorferi sensu lato in Ixodes ricinus ticks collected in north-west Poland]. / Genetyczna zmiennosc Borrelia burgdorferi s. l. u kleszczy Ixodes ricinus zebranych w pólnocnozachodniej Polsce.

Borrelia burgdorferi sensu lato (s. l.), the etiological agent of Lyme diesease, is transmitted by the bite of Ixodes ricinus. During May and September 1999, field surveys on Lyme disease spirochetes were conducted in three locations of a region of north-west Poland, known as recreational districts visited by many people. The ticks Ixodes ricinus were collected in natural habitats by dragging a flanel cloth over the vegetation. Sex and developmental stage of each tick were determined. Based on a polymerase chain reaction test with primers that recognize a chromosomal gene of all strains, out of the total 1414 specimens collected, 126 (8.9%) were found to be infected. The species B. burgdorferi s. l. comprises at least three pathogenic genomospecies, B. burgdorferi sensu stricto (s. s.), Borrelia garinii, and Borerelia afzelii, witch could be distinguished in nested-PCR tests with species-specific primers. B. burgdorferi s. s. was most prevalent (96% of infected ticks), followed by B. garinii (1.3%), and B. afzelii. was not found. Of the infected ticks, over the 99% were infected with a single species, one specimens was infected with two species. For 4 ticks, the infecting species could not be identied. The difference in rates of prevalence was observed among the tree locations (17%--5.3%--3.2%).