PeakSeeker: a program for interpreting genotypes of mononucleotide repeats

<p>Abstract</p> <p>Background</p> <p>Mononucleotide repeat microsatellites are abundant, highly polymorphic DNA sequences, having the potential to serve as valuable genetic markers. Use of mononucleotide microsatellites has been limited by their tendency to produce "stutter", confounding signals from insertions and deletions within the mononucleotide tract that occur during PCR, which complicates interpretation of genotypes by masking the true position of alleles. Consequently, microsatellites with larger repeating subunits (dinucleotide and trinucleotide motifs) are used, which produce less stutter but are less genetically heterogeneous and less informative. A method to interpret the genotypes of mononucleotide repeats would permit the widespread use of those highly informative microsatellites in genetic research.</p> <p>Findings</p> <p>We have developed an approach to interpret genotypes of mononucleotide repeats using a software program, named PeakSeeker. PeakSeeker interprets experimental electropherograms as the most likely product of signals from individual alleles. Because mononucleotide tracts demonstrate locus-specific patterns of stutter peaks, this approach requires that the genotype pattern from a single allele is defined for each marker, which can be approximated by genotyping single DNA molecules or homozygotes. We have evaluated the program's ability to discriminate various types of homozygous and heterozygous mononucleotide loci using simulated and experimental data.</p> <p>Conclusion</p> <p>Mononucleotide tracts offer significant advantages over di- and tri-nucleotide microsatellite markers traditionally employed in genetic research. The PeakSeeker algorithm provides a high-throughput means to type mononucleotide tracts using conventional and widely implemented fragment length polymorphism genotyping. Furthermore, the PeakSeeker algorithm could potentially be adapted to improve, and perhaps to standardize, the analysis of conventional microsatellite genotypes.</p

16S rRNA deep sequencing identifies Actinotignum schaalii as the major component of a polymicrobial intra-abdominal infection and implicates a urinary source

Introduction. It can be difficult to catalogue the individual organisms comprising polymicrobial patient infections, both because conventional clinical microbiological culture does not facilitate the isolation and enumeration of all members of a complex microbial community, and because fastidious organisms may be mixed with organisms that grow rapidly in vitro. Empiric antimicrobial treatment is frequently employed based on the anatomical site and the suspected source of the infection, especially when an appropriately collected surgical specimen is not obtained., Case presentation. We present a case of an intra-abdominal infection in a patient with complex anatomy and recurrent urinary tract infections. Imaging did not reveal a clear source of infection, no growth was obtained from urine cultures and initial abdominal fluid cultures were also negative. In contrast, 16S rRNA deep sequencing of abdominal fluid samples revealed mixed bacterial populations with abundant anaerobes, including Actinotignum schaalii (Actinobaculum schaalii). Ultimately, only Enterobacter cloacae complex and meticillin-resistant Staphylococcus aureus, both of which were identified by sequencing, were recovered by culture., Conclusion. The clinical application of 16S rRNA deep sequencing can more comprehensively and accurately define the organisms present in an individual patient's polymicrobial infection than conventional microbiological culture, detecting species that are not recovered under standard culture conditions or that are otherwise unexpected. These results can facilitate effective antimicrobial stewardship and help elucidate the possible origins of infections

Ultrasensitive detection of acute myeloid leukemia minimal residual disease using single molecule molecular inversion probes

The identification of minimal residual disease is the primary diagnostic finding which predicts relapse in patients treated for acute myeloid leukemia. Ultrasensitive detection of minimal residual disease would enable better patient risk stratification and could open opportunities for early therapeutic intervention. Herein we apply single molecule molecular inversion probe capture, a technology combining multiplexed targeted sequencing with error correction schemes based on molecular barcoding, in order to detect mutations identifying minimal residual disease with ultrasensitive and quantitative precision. We designed a single molecule molecular inversion probe capture panel spanning >50 kb and targeting 32 factors relevant to acute myeloid leukemia pathogenesis. We demonstrate linearity and quantitative precision over 100-fold relative abundance of mutant cells (1 in 100 to 1 in 1,500), with estimated error rates approaching 1 in 1,200 base pairs sequenced and maximum theoretical limits of detection exceeding 1 in 60,000 mutant alleles. In 3 of 4 longitudinally collected specimens from patients with acute myeloid leukemia, we find that single molecule molecular inversion probe capture detects somatic mutations identifying minimal residual disease at substantially earlier time points and with greater sensitivity than clinical diagnostic approaches used as current standard of care (flow cytometry and conventional molecular diagnosis), and identifies persisting neoplastic cells during clinical remission. In 2 patients, single molecule molecular inversion probe capture detected heterogeneous, subclonal acute myeloid leukemia populations carrying distinct mutational signatures. Single molecule molecular inversion probe technology uniquely couples scalable target enrichment with sequence read error correction, providing an integrated, ultrasensitive approach for detecting minimal residual disease identifying mutations

Open-Sourced CIViC Annotation Pipeline to identify and annotate clinically relevant variants using single-molecule molecular inversion probes

PURPOSE: Clinical targeted sequencing panels are important for identifying actionable variants for patients with cancer; however, existing approaches do not provide transparent and rationally designed clinical panels to accommodate the rapidly growing knowledge within oncology. MATERIALS AND METHODS: We used the Clinical Interpretations of Variants in Cancer (CIViC) database to develop an Open-Sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP provides methods to identify variants within the CIViC database, build probes for variant capture, use probes on prospective samples, and link somatic variants to CIViC clinical relevance statements. OpenCAP was tested using a single-molecule molecular inversion probe (smMIP) capture design on 27 cancer samples from 5 tumor types. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants (61.5 kb of genomic space). RESULTS: When compared with orthogonal sequencing, CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61 of 64 variants). Variant allele frequencies for variants identified on both sequencing platforms were highly concordant (Pearson\u27s CONCLUSION: The OpenCAP design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant interpretation provides a transparent approach to build dynamic next-generation sequencing-based oncology panels

Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.BACKGROUND: There are multiple existing and emerging therapeutic avenues for metastatic prostate cancer, with a common denominator, which is the need for predictive biomarkers. Circulating tumor DNA (ctDNA) has the potential to cost-efficiently accelerate precision medicine trials to improve clinical efficacy and diminish costs and toxicity. However, comprehensive ctDNA profiling in metastatic prostate cancer to date has been limited. METHODS: A combination of targeted and low-pass whole genome sequencing was performed on plasma cell-free DNA and matched white blood cell germline DNA in 364 blood samples from 217 metastatic prostate cancer patients. RESULTS: ctDNA was detected in 85.9% of baseline samples, correlated to line of therapy and was mirrored by circulating tumor cell enumeration of synchronous blood samples. Comprehensive profiling of the androgen receptor (AR) revealed a continuous increase in the fraction of patients with intra-AR structural variation, from 15.4% during first-line metastatic castration-resistant prostate cancer therapy to 45.2% in fourth line, indicating a continuous evolution of AR during the course of the disease. Patients displayed frequent alterations in DNA repair deficiency genes (18.0%). Additionally, the microsatellite instability phenotype was identified in 3.81% of eligible samples (≥ 0.1 ctDNA fraction). Sequencing of non-repetitive intronic and exonic regions of PTEN, RB1, and TP53 detected biallelic inactivation in 47.5%, 20.3%, and 44.1% of samples with ≥ 0.2 ctDNA fraction, respectively. Only one patient carried a clonal high-impact variant without a detectable second hit. Intronic high-impact structural variation was twice as common as exonic mutations in PTEN and RB1. Finally, 14.6% of patients presented false positive variants due to clonal hematopoiesis, commonly ignored in commercially available assays. CONCLUSIONS: ctDNA profiles appear to mirror the genomic landscape of metastatic prostate cancer tissue and may cost-efficiently provide somatic information in clinical trials designed to identify predictive biomarkers. However, intronic sequencing of the interrogated tumor suppressors challenges the ubiquitous focus on coding regions and is vital, together with profiling of synchronous white blood cells, to minimize erroneous assignments which in turn may confound results and impede true associations in clinical trials.The Belgian Foundation Against Cancer (grant number C/2014/227); Kom op tegen Kanker (Stand up to Cancer), the Flemish Cancer Society (grant number 00000000116000000206); Royal College of Surgeons/Cancer Research UK (C19198/A1533); The Cancer Research Funds of Radiumhemmet, through the PCM program at KI (grant number 163012); The Erling-Persson family foundation (grant number 4-2689-2016); the Swedish Research Council (grant number K2010-70X-20430-04-3), and the Swedish Cancer Foundation (grant number 09-0677)

Retraction: Measures of Clade Confidence Do Not Correlate with Accuracy of Phylogenetic Trees

Metrics of phylogenetic tree reliability, such as parametric bootstrap percentages or Bayesian posterior probabilities, represent internal measures of the topological reproducibility of a phylogenetic tree, while the recently introduced aLRT (approximate likelihood ratio test) assesses the likelihood that a branch exists on a maximum-likelihood tree. Although those values are often equated with phylogenetic tree accuracy, they do not necessarily estimate how well a reconstructed phylogeny represents cladistic relationships that actually exist in nature. The authors have therefore attempted to quantify how well bootstrap percentages, posterior probabilities, and aLRT measures reflect the probability that a deduced phylogenetic clade is present in a known phylogeny. The authors simulated the evolution of bacterial genes of varying lengths under biologically realistic conditions, and reconstructed those known phylogenies using both maximum likelihood and Bayesian methods. Then, they measured how frequently clades in the reconstructed trees exhibiting particular bootstrap percentages, aLRT values, or posterior probabilities were found in the true trees. The authors have observed that none of these values correlate with the probability that a given clade is present in the known phylogeny. The major conclusion is that none of the measures provide any information about the likelihood that an individual clade actually exists. It is also found that the mean of all clade support values on a tree closely reflects the average proportion of all clades that have been assigned correctly, and is thus a good representation of the overall accuracy of a phylogenetic tree

Molecular Epidemiology of Mycobacterium leprae as Determined by Structure-Neighbor Clustering ▿ †

It has proven challenging to investigate the molecular epidemiology of Mycobacterium leprae, the causative agent of leprosy, due to difficulties with culturing of the organism and a lack of genetic heterogeneity between strains. Recently, a cost-effective panel of variable-number tandem-repeat (VNTR) markers has been developed. Use of this panel allows some of those limitations to be overcome and has allowed the genotyping of 475 M. leprae strains from six different countries. In the present report, we provide a comprehensive analysis of the relationships among the strains in order to investigate the patterns of transmission and migration of M. leprae. We find phylogenetic analysis to be inadequate and have developed an alternative method, structure-neighbor clustering, which assigns isolates with the most similar genotypes to the same groups and, subsequently, subgroups, without inferring how the strains descended from a common ancestor. We validate the approach by using simulated data and detecting expected epidemiological relationships from experimental data. Our results suggest that most M. leprae strains from a given country cluster together and that the occasional isolates assigned to different clusters are a consequence of migration. We found three genetically distinguishable populations among isolates from the Philippines, as well as evidence for the significant influx of strains to that nation from India. We also report that reference strain TN originated from the Philippines and not from India, as was previously believed. Lastly, analysis of isolates from the same families and villages suggests that most community infections originate from a common source or person-to-person transmission but that infection from independent sources does occur with measurable frequency

GeneHunter, a Transposon Tool for Identification and Isolation of Cryptic Antibiotic Resistance Genes

GeneHunter is a transposon tool designed for the experimental activation and identification of silent antibiotic resistance genes. The method permits the identification of novel resistance genes that lack previously identified homologues. Using Salmonella enterica serovar Typhimurium strain LT2 as a test organism for the in vivo version of the GeneHunter method, we were able to activate, clone, and identify two cryptic antibiotic resistance genes, the aminoglycoside acetyltransferase aac(6′)-Iaa and the probable Mar-A regulon activator rma. Because the method requires being able to electroporate the host with an efficiency of at least 10(10) transformants per microgram, the in vivo method is not applicable to most microorganisms. We therefore developed an in vitro transposition method, showed that it can also recover the cryptic rma gene from S. enterica serovar Typhimurium strain LT2, and showed that it is generally applicable to a variety of microorganisms by using it to recover a cryptic metallo-β-lactamase gene from the gram-positive organism Bacillus cereus. It is anticipated that the GeneHunter method will be used to identify potential resistance genes during the development and testing of novel antibiotics, new variants of existing antibiotics, and drug inhibitor combinations

Typical Phylogenetic Trees

<div><p>(A) True 64-taxon tree initiated with <i>nuoK</i> sequences. The arrow indicates a near trichotomy.</p><p>(B) Bayesian tree estimated from the same data as in (A). Numbers are posterior probabilities of clades whose posterior probabilities are <90%. Arrows indicate the clades that do not exist in the true tree.</p></div

Topology of a Typical Unbalanced Tree of 16 Taxa

<p>Topology of a Typical Unbalanced Tree of 16 Taxa</p