Optimization of primer design for the detection of variable genomic lesions in cancer

openPrimeR for multiplex amplification of highly diverse templates

To study the diversity of immune receptors and pathogens, multiplex PCR has become a central approach in research and diagnostics. However, insufficient primer design against highly diverse templates often prevents amplification and therefore limits the correct understanding of biological processes. Here, we present openPrimeR, an R-based tool for evaluating and designing multiplex PCR primers. openPrimeR provides a functional and intuitive interface and uses either a greedy algorithm or an integer linear program to compute the minimal set of primers that performs full target coverage. As proof of concept, we used openPrimeR to find optimal primer sets for the amplification of highly mutated immunoglobulins. Comprehensive analyses on specifically generated immunoglobulin variable gene segment libraries resulted in the composition of highly effective primer sets (oPR-IGHV, oPR-IGKV and oPR-IGLV) that demonstrated to be particularly suitable for the isolation of novel human antibodies.

MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics

Background

Bisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful.

Results

We have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format.

Conclusions

MSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic strands to increase the success rate. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 66 BSP primer pairs, 63 were successfully validated without any further optimization step and using the same qPCR conditions. The MSP-HTPrimer pipeline is freely available from http://sourceforge.net/p/msp-htprimer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0269-3) contains supplementary material, which is available to authorized users.

Combining reverse-transcription multiplex PCR and microfluidic electrophoresis to simultaneously detect seven mosquito-transmitted zoonotic encephalomyelitis viruses

Several mosquito-transmitted viruses are causative agents for zoonotic encephalomyelitis. Rapid identification of these viruses in mosquito populations is an effective method for surveying these diseases. To detect multiple mosquito-transmitted viral agents, including West Nile virus, Saint Louis encephalitis virus, Venezuelan equine encephalomyelitis virus, Western equine encephalomyelitis virus, Eastern equine encephalomyelitis virus, Highlands J virus and Japanese encephalitis virus, an assay using multiplex reverse-transcription PCR combined with microfluidic electrophoresis was developed and evaluated. Tailed nested primers were used in the assay to amplify specific viral genomic segments, and products with specific length were further analyzed by using a microfluidic electrophoresis chip. The assay exhibited good specificity and analytical sensitivity (10(2) copies/µL). This technology can be helpful in the quarantine and surveillance of exotic encephalomyelitis viruses which are transmitted by mosquitoes.

Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation

Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

Influence of immune responses in gene/stem cell therapies for muscular dystrophies

Muscular dystrophies (MDs) are a heterogeneous group of diseases, caused by mutations in different components of sarcolemma, extracellular matrix, or enzymes. Inflammation and innate or adaptive immune response activation are prominent features of MDs. Various therapies under development are directed toward rescuing the dystrophic muscle damage using gene transfer or cell therapy. Here we discussed current knowledge about involvement of immune system responses to experimental therapies in MDs.

Using Genome Query Language to uncover genetic variation

MOTIVATION

With high-throughput DNA sequencing costs dropping <$1000 for human genomes, data storage, retrieval and analysis are the major bottlenecks in biological studies. To address the large-data challenges, we advocate a clean separation between the evidence collection and the inference in variant calling. We define and implement a Genome Query Language (GQL) that allows for the rapid collection of evidence needed for calling variants.

RESULTS

We provide a number of cases to showcase the use of GQL for complex evidence collection, such as the evidence for large structural variations. Specifically, typical GQL queries can be written in 5-10 lines of high-level code and search large datasets (100 GB) in minutes. We also demonstrate its complementarity with other variant calling tools. Popular variant calling tools can achieve one order of magnitude speed-up by using GQL to retrieve evidence. Finally, we show how GQL can be used to query and compare multiple datasets. By separating the evidence and inference for variant calling, it frees all variant detection tools from the data intensive evidence collection and focuses on statistical inference.

AVAILABILITY

GQL can be downloaded from http://cseweb.ucsd.edu/~ckozanit/gql.

Amplification and thrifty single-molecule sequencing of recurrent somatic structural variations

Deletion of tumor-suppressor genes as well as other genomic rearrangements pervade cancer genomes across numerous types of solid tumor and hematologic malignancies. However, even for a specific rearrangement, the breakpoints may vary between individuals, such as the recurrent CDKN2A deletion. Characterizing the exact breakpoints for structural variants (SVs) is useful for designating patient-specific tumor biomarkers. We propose AmBre (Amplification of Breakpoints), a method to target SV breakpoints occurring in samples composed of heterogeneous tumor and germline DNA. Additionally, AmBre validates SVs called by whole-exome/genome sequencing and hybridization arrays. AmBre involves a PCR-based approach to amplify the DNA segment containing an SV's breakpoint and then confirms breakpoints using sequencing by Pacific Biosciences RS. To amplify breakpoints with PCR, primers tiling specified target regions are carefully selected with a simulated annealing algorithm to minimize off-target amplification and maximize efficiency at capturing all possible breakpoints within the target regions. To confirm correct amplification and obtain breakpoints, PCR amplicons are combined without barcoding and simultaneously long-read sequenced using a single SMRT cell. Our algorithm efficiently separates reads based on breakpoints. Each read group supporting the same breakpoint corresponds with an amplicon and a consensus amplicon sequence is called. AmBre was used to discover CDKN2A deletion breakpoints in cancer cell lines: A549, CEM, Detroit562, MOLT4, MCF7, and T98G. Also, we successfully assayed RUNX1–RUNX1T1 reciprocal translocations by finding both breakpoints in the Kasumi-1 cell line. AmBre successfully targets SVs where DNA harboring the breakpoints are present in 1:1000 mixtures.

Full-length dysferlin expression driven by engineered human dystrophic blood derived CD133+ stem cells

The protein dysferlin is abundantly expressed in skeletal and cardiac muscles, where its main function is membrane repair. Mutations in the dysferlin gene are involved in two autosomal recessive muscular dystrophies: Miyoshi myopathy and limb-girdle muscular dystrophy type 2B. Development of effective therapies remains a great challenge. Strategies to repair the dysferlin gene by skipping mutated exons, using antisense oligonucleotides (AONs), may be suitable only for a subset of mutations, while cell and gene therapy can be extended to all mutations. AON-treated blood-derived CD133+ stem cells isolated from patients with Miyoshi myopathy led to partial dysferlin reconstitution in vitro but failed to express dysferlin after intramuscular transplantation into scid/blAJ dysferlin null mice. We thus extended these experiments producing the full-length dysferlin mediated by a lentiviral vector in blood-derived CD133+ stem cells isolated from the same patients. Transplantation of engineered blood-derived CD133+ stem cells into scid/blAJ mice resulted in sufficient dysferlin expression to correct functional deficits in skeletal muscle membrane repair. Our data suggest for the first time that lentivirus-mediated delivery of full-length dysferlin in stem cells isolated from Miyoshi myopathy patients could represent an alternative therapeutic approach for treatment of dysferlinopathies.

Absence of T and B lymphocytes modulates dystrophic features in dysferlin deficient animal model

Dysferlin mutations cause muscular dystrophy (dysferlinopathy) characterized by adult onset muscle weakness, high serum creatine kinase levels, attenuation of muscle regeneration and a prominent inflammatory infiltrate. In order to verify the role of lymphocytes and immune cells on this disease, we generated the Scid/A/J transgenic mice and compared these animals with the age-matched A/J mice. The absence of T and B lymphocytes in this animal model of dysferlinopathy resulted in an improvement of the muscle regeneration. Scid/A/J mice showed increased specific force in the myosin heavy chain 2A-expressing fibers of the diaphragm and abdominal muscles. Moreover, a partial reduction in complement deposition was observed together with a diminution in pro-inflammatory M1 macrophages. Consistent with this model, T and B lymphocytes seem to have a role in the muscle damaging immune response. The knowledge of the involvement of immune system in the development of dysferlinopathies could represent an important tool for their rescuing. By studying Scid/blAJ mice, we showed that it could be possible to modulate the pathological symptoms of these diseases by interfering with different components of the immune system.

Long-range massively parallel mate pair sequencing detects distinct mutations and similar patterns of structural mutability in two breast cancer cell lines

Cancer genomes frequently undergo genomic instability resulting in accumulation of chromosomal rearrangement. To date, one of the main challenges has been to confidently and accurately identify these rearrangements by using short-read massively parallel sequencing. We were able to improve cancer rearrangement detection by combining two distinct massively parallel sequencing strategies: fosmid-sized (36 kb on average) and standard 5 kb mate pair libraries. We applied this combined strategy to map rearrangements in two breast cancer cell lines, MCF7 and HCC1954. We detected and validated a total of 91 somatic rearrangements in MCF7 and 25 in HCC1954, including genomic alterations corresponding to previously reported transcript aberrations in these two cell lines. Each of the genomes contains two types of breakpoints: clustered and dispersed. In both cell lines, the dispersed breakpoints show enrichment for low copy repeats, while the clustered breakpoints associate with high copy number amplifications. Comparing the two genomes, we observed highly similar structural mutational spectra affecting different sets of genes, pointing to similar histories of genomic instability against the background of very different gene network perturbations.

Optimizing PCR assays for DNA-based cancer diagnostics

Somatically acquired DNA rearrangements are characteristic of many cancers. The use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal DNA. Detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. Here, we present an algorithm for designing polymerase chain reaction (PCR) primers and oligonucleotide probes to assay for these variant rearrangements. Specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant DNA over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. Our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. Simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. Additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection. We applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the CDKN2A locus. The CDKN2A deletion has highly variable boundaries across many cancers. We successfully detect the breakpoint in all cell-lines, even when the region has undergone multiple rearrangements. These results point to the development of a successful protocol for early diagnosis and monitoring of cancer. For online Supplementary Material, see www.liebertonline.com.

Evaluation of paired-end sequencing strategies for detection of genome rearrangements in cancer

Paired-end sequencing is emerging as a key technique for assessing genome rearrangements and structural variation on a genome-wide scale. This technique is particularly useful for detecting copy-neutral rearrangements, such as inversions and translocations, which are common in cancer and can produce novel fusion genes. We address the question of how much sequencing is required to detect rearrangement breakpoints and to localize them precisely using both theoretical models and simulation. We derive a formula for the probability that a fusion gene exists in a cancer genome given a collection of paired-end sequences from this genome. We use this formula to compute fusion gene probabilities in several breast cancer samples, and we find that we are able to accurately predict fusion genes in these samples with a relatively small number of fragments of large size. We further demonstrate how the ability to detect fusion genes depends on the distribution of gene lengths, and we evaluate how different parameters of a sequencing strategy impact breakpoint detection, breakpoint localization, and fusion gene detection, even in the presence of errors that suggest false rearrangements. These results will be useful in calibrating future cancer sequencing efforts, particularly large-scale studies of many cancer genomes that are enabled by next-generation sequencing technologies.

Cancer is driven by genomic mutations that can range from single nucleotide changes to chromosomal aberrations that rearrange large pieces of DNA. Often, these chromosomal aberrations disrupt a gene sequence, and even fuse the sequences of two genes, producing a “fusion gene.” Fusion genes have been identified as key participants in the development of several types of cancer. Using genome-sequencing technology it is now possible to identify chromosomal aberrations genome-wide and at high resolution. In this paper, we address the question of how much sequencing is required to detect a chromosomal aberration and to determine the location of the aberration precisely enough to identify if a fusion gene is created by this aberration. We derive a mathematical formula that accurately predicts a number of fusion genes in a breast cancer sequencing study. We also demonstrate how the ability to detect chromosomal aberrations and fusion genes depends on both the size of the fusion gene and the parameters of the genome sequencing strategy that is used. These results will be useful in calibrating future cancer sequencing efforts, especially those using next-generation sequencing technologies.