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Currently, the diagnosis of Alzheimer's disease (AD) is based on symptoms and medical imaging, and definitive clinical diagnosis is only possible postmortem. The identification of noninvasive biomarkers such as methylated ccfDNA is crucial for the diagnosis, prognosis and monitoring of AD. However, the analysis of ccfDNA from plasma is a challenge because it is highly fragmented and present in low amounts and originates from various tissues. The authors developed a targeted sequencing protocol using genes previously reported in AD literature (brain, blood and plasma) to identify potential noninvasive biomarkers in plasma. The authors identified positions identical to those in the literature as well as potential novel sites located in the promoter, exon and intron regions of these genes. Although these results must be validated in a large cohort, methylated ccfDNA could be a useful noninvasive biomarker for AD.

Parkinson’s disease (PD) is the second most common neurodegenerative disease clinically characterized by classical motor symptoms and a range of associated non-motor symptoms. Due to the heterogeneity of symptoms and variability in patient prognosis, the discovery of blood biomarkers is of utmost importance to identify the biological mechanisms underlying the different clinical manifestations of PD, monitor its progression and develop personalized treatment strategies. Whereas studies often rely on motor symptoms alone or composite scores, our study focused on finding relevant molecular markers associated with three clinical models describing either motor, cognitive or emotional symptoms. An integrative multiblock approach was performed using regularized generalized canonical correlation analysis to determine specific associations between lipidomics, transcriptomics and clinical data in 48 PD patients. We identified omics signatures confirming that clinical manifestations of PD in our cohort could be classified according to motor, cognition or emotion models. We found that immune-related genes and triglycerides were well-correlated with motor variables, while cognitive variables were linked to triglycerides as well as genes involved in neuronal growth, synaptic plasticity and mitochondrial fatty acid oxidation. Furthermore, emotion variables were associated with phosphatidylcholines, cholesteryl esters and genes related to endoplasmic reticulum stress and cell regulation.

Motivation It is more and more common to perform multi-omics analyses to explore the genome at diverse levels and not only at a single level. Through integrative statistical methods, multi-omics data have the power to reveal new biological processes, potential biomarkers and subgroups in a cohort. Matrix factorization (MF) is an unsupervised statistical method that allows a clustering of individuals, but also reveals relevant omics variables from the various blocks. Results Here, we present PIntMF (Penalized Integrative Matrix Factorization), an MF model with sparsity, positivity and equality constraints. To induce sparsity in the model, we used a classical Lasso penalization on variable and individual matrices. For the matrix of samples, sparsity helps in the clustering, while normalization (matching an equality constraint) of inferred coefficients is added to improve interpretation. Moreover, we added an automatic tuning of the sparsity parameters using the famous glmnet package. We also proposed three criteria to help the user to choose the number of latent variables. PIntMF was compared with other state-of-the-art integrative methods including feature selection techniques in both synthetic and real data. PIntMF succeeds in finding relevant clusters as well as variables in two types of simulated data (correlated and uncorrelated). Next, PIntMF was applied to two real datasets (Diet and cancer), and it revealed interpretable clusters linked to available clinical data. Our method outperforms the existing ones on two criteria (clustering and variable selection). We show that PIntMF is an easy, fast and powerful tool to extract patterns and cluster samples from multi-omics data. Availability and implementation An R package is available at https://github.com/mpierrejean/pintmf. Supplementary information Supplementary data are available at Bioinformatics online.

Recent advances in NGS sequencing, microarrays and mass spectrometry for omics data production have enabled the generation and collection of different modalities of high-dimensional molecular data. The integration of multiple omics datasets is a statistical challenge, due to the limited number of individuals, the high number of variables and the heterogeneity of the datasets to integrate. Recently, a lot of tools have been developed to solve the problem of integrating omics data including canonical correlation analysis, matrix factorization and SM. These commonly used techniques aim to analyze simultaneously two or more types of omics. In this article, we compare a panel of 13 unsupervised methods based on these different approaches to integrate various types of multi-omics datasets: iClusterPlus, regularized generalized canonical correlation analysis, sparse generalized canonical correlation analysis, multiple co-inertia analysis (MCIA), integrative-NMF (intNMF), SNF, MoCluster, mixKernel, CIMLR, LRAcluster, ConsensusClustering, PINSPlus and multi-omics factor analysis (MOFA). We evaluate the ability of the methods to recover the subgroups and the variables that drive the clustering on eight benchmarks of simulation. MOFA does not provide any results on these benchmarks. For clustering, SNF, MoCluster, CIMLR, LRAcluster, ConsensusClustering and intNMF provide the best results. For variable selection, MoCluster outperforms the others. However, the performance of the methods seems to depend on the heterogeneity of the datasets (especially for MCIA, intNMF and iClusterPlus). Finally, we apply the methods on three real studies with heterogeneous data and various phenotypes. We conclude that MoCluster is the best method to analyze these omics data. Availability: An R package named CrIMMix is available on GitHub at https://github.com/CNRGH/crimmix to reproduce all the results of this article.

In the era of precision medicine, the identification of novel prognostic biomarkers such as epigenetic modifications is crucial. Advanced methods need to be developed in order to analyze epigenetic biomarkers in clinical samples such as fresh frozen, formalin-fixed paraffin-embedded tissue, single-cell samples, or from liquid biopsies, that allow the identification and quantitative analysis of these novel biomarkers. Complementary methods have been developed to specifically analyze DNA methylation, DNA hydroxymethylation, posttranslational histone modifications, nucleosome occupancy, chromatin, noncoding RNA such as microRNA or long noncoding RNA, and interactions between nucleic acids and proteins. They have taken advantage in technological improvement including PCR, sequencing, microarrays, and quantitative proteomic mass spectrometry. The combination of these technologies with reverse transcription, bisulfite conversion, affinity antibody, binding protein, hybridization probe, or restriction enzyme, allowed the identification of novel epigenetic biomarkers, validation of biomarkers, global-level analysis, and quantitative analysis of prognostic epigenetic biomarkers in clinical samples.

To the Editor: Enhanced- ice -COLD-PCR allows the detection of mutations in a single mutation hotspot down to 0.05% of mutant alleles without prior knowledge of the mutated base, and their identification by subsequent (pyro)sequencing experiments (1). This approach is useful for diagnosis, choice of a personalized treatment, prediction, or the monitoring of treatment response, and has been successfully performed on fresh frozen and formalin-fixed, paraffin-embedded tissue, and circulating cell-free DNA (1, 2). The method is a further development of ice -COLD-PCR (3) and based on the incorporation of locked–nucleic acid nucleotides in the blocker probe complementary to the wild-type (WT)1 sequence (1). During each PCR cycle, denaturation is followed by hybridization at 70 °C, where WT-blocker and mutant-blocker heteroduplexes are formed, mutant-blocker heteroduplexes are denatured at a critical temperature (Tc) higher than 75 °C, and primers are hybridized at the annealing temperature and elongated at 72 °C, leading to the enrichment of mutations underlying the blocker sequence (1). Enhanced- ice -COLD-PCR can enrich all types of mutations, allows stronger mutation enrichment, and is less sensitive to variations of the Tc (±5 °C) compared to full -, fast -, or ice -COLD-PCR, for which a slight variation (0.2 °C) can abolish mutation enrichment (1, 3, 4). Therefore, different full -, fast …

International audience; The REvolutionary Approaches and Devices for Nucleic Acid analysis (READNA) project received 12 million s funding under the European Union Framework Programme 7 from 1st June 2008 to 30th November 2012. The 19 project partners from both academia and industry from in total 7 countries had a project budget of 16 Ms with which they have discovered, created and developed a huge body of insights into nucleic acid analysis. Results have been presented widely in publications and in innumerous public presentations. Results have been moved to spin-offs such as the Olink enrichment kits (now sold by Agilent as Haloplex) and are findingtheir way to the market, such as the Oxford Nanopore MinIon sequencer that was first released to early-access user sites in 2014.

The mitogen-activated protein kinase (MAPK) pathway is constantly activated in Langerhans cell histiocytosis (LCH). Mutations of the downstream kinasesBRAFandMAP2K1mediate this activation in a subset of LCH lesions. In this study, we attempted to identify other mutations which may explain the MAPK activation in nonmutatedBRAFandMAP2K1LCH lesions.We analysed 26 pulmonary and 37 nonpulmonary LCH lesions for the presence ofBRAF,MAP2K1,NRASandKRASmutations. Grossly normal lung tissue from 10 smoker patients was used as control. Patient spontaneous outcomes were concurrently assessed.BRAFV600Emutations were observed in 50% and 38% of the pulmonary and nonpulmonary LCH lesions, respectively. 40% of pulmonary LCH lesions harbouredNRASQ61K/Rmutations, whereas noNRASmutations were identified in nonpulmonary LCH biopsies or in lung tissue control. In seven out of 11NRASQ61K/R-mutated pulmonary LCH lesions,BRAFV600Emutations were also present. Separately genotyping each CD1a-positive area from the same pulmonary LCH lesion demonstrated that these concurrentBRAFandNRASmutations were carried by different cell clones.NRASQ61K/Rmutations activated both the MAPK and AKT (protein kinase B) pathways. In the univariate analysis, the presence of concurrentBRAFV600EandNRASQ61K/Rmutations was significantly associated with patient outcome.These findings highlight the importance ofNRASgenotyping of pulmonary LCH lesions because the use of BRAF inhibitors in this context may lead to paradoxical disease progression. These patients might benefit from MAPK kinase inhibitor-based treatments.

The detection of specific DNA methylation patterns bears great promise as biomarker for personalized management of cancer patients. Co-amplification at lower denaturation temperature-PCR (COLD-PCR) assays are sensitive methods, but have previously only been able to analyze loss of DNA methylation.Enhanced (E)-ice-COLD-PCR reactions starting from 2 ng of bisulfite-converted DNA were developed to analyze methylation patterns in two promoters with locked nucleic acid (LNA) probes blocking amplification of unmethylated CpGs. The enrichment of methylated molecules was compared to quantitative (q)PCR and quantified using serial dilutions.E-ice-COLD-PCR allowed the multiplexed enrichment and quantification of methylated DNA. Assays were validated in primary breast cancer specimens and circulating cell-free DNA from cancer patients.E-ice-COLD-PCR could prove a useful tool in the context of DNA methylation analysis for personalized medicine.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and disease-associated investigations. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered as the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here we provide two detailed protocols based on commercial kits for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. If only DNA methylation is of interest, sequencing libraries can be constructed from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For samples with significant levels of hydroxymethylation such as stem cells or brain tissue, we describe the protocol of oxidative bisulfite sequencing (OxBs-seq), which in its current version uses a post-bisulfite adaptor tagging (PBAT) approach. Two methylomes need to be generated: a classic methylome following bisulfite conversion and analyzing both methylated and hydroxymethylated cytosines and a methylome analyzing only methylated cytosines, respectively. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocols have been successfully applied to different human samples and yield robust and reproducible results.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and disease-associated investigations. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered as the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here we provide two detailed protocols based on commercial kits for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. If only DNA methylation is of interest, sequencing libraries can be constructed from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For samples with significant levels of hydroxymethylation such as stem cells or brain tissue, we describe the protocol of oxidative bisulfite sequencing (OxBs-seq), which in its current version uses a post-bisulfite adaptor tagging (PBAT) approach. Two methylomes need to be generated: a classic methylome following bisulfite conversion and analyzing both methylated and hydroxymethylated cytosines and a methylome analyzing only methylated cytosines, respectively. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocols have been successfully applied to different human samples and yield robust and reproducible results.

The analysis of genome-wide epigenomic alterations including DNA methylation has become a subject of intensive research for many complex diseases. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies can be considered the gold standard for a comprehensive and quantitative analysis of cytosine methylation throughout the genome. Several approaches including tagmentation- and post bisulfite adaptor tagging (PBAT)-based WGBS have been devised. Here, we provide a detailed protocol based on a commercial kit for the preparation of libraries for WGBS from limited amounts of input DNA (50-100 ng) using the classical approach of WGBS by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. The converted library is then amplified with an optimal number of PCR cycles to ensure high sequence diversity and low duplicate rates. Spike-in of unmethylated DNA allows for the precise estimation of bisulfite conversion rates. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human samples as well as DNA extracted from plant tissues and yields robust and reproducible results.

The analysis of genome-wide epigenomic alterations including DNA methylation has become a subject of intensive research for many complex diseases. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies can be considered the gold standard for a comprehensive and quantitative analysis of cytosine methylation throughout the genome. Several approaches including tagmentation- and post bisulfite adaptor tagging (PBAT)-based WGBS have been devised. Here, we provide a detailed protocol based on a commercial kit for the preparation of libraries for WGBS from limited amounts of input DNA (50-100 ng) using the classical approach of WGBS by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. The converted library is then amplified with an optimal number of PCR cycles to ensure high sequence diversity and low duplicate rates. Spike-in of unmethylated DNA allows for the precise estimation of bisulfite conversion rates. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human samples as well as DNA extracted from plant tissues and yields robust and reproducible results.

Circulating cell-free DNA (ccfDNA) has great potential for non-invasive diagnostics, and prediction and monitoring of treatment response, but its amount is usually limited. Therefore, the choice of methods to extract and characterize ccfDNA is crucial. In the current study, we performed the most comprehensive comparison of methods for ccfDNA extraction (11 methods), quantification (3 methods), and estimation of the integrity index (2 methods) from small quantities of different kinds of plasma. The QIAamp® Circulating Nucleic Acid Kit and the Norgen Plasma/Serum Circulating DNA Purification Mini Kit showed the best accuracy and reproducibility, but the Norgen kit allowed to extract a higher amount of ccfDNA. This workflow provides a reliable protocol for the multiple applications of ccfDNA in biomedicine.

International audience; Circulating cell-free DNA (ccfDNA) bears great promise as biomarker for personalized medicine, but ccfDNA ispresent only at low levels in the plasma or serum of cancer patients. E-ice-COLD-PCR is a recently developed enrichmentmethod to detect and identify mutations present at low-abundance in clinical samples. However, recentstudies have shown the importance to accurately quantify low-abundance mutations as clinicallyimportant decisions will depend on certainmutation thresholds. The possibility for an enrichmentmethod to accuratelyquantify the mutation levels remains a point of concern and might limit its clinical applicability.In the present study, we compared the quantification of KRAS mutations in ccfDNA from metastatic colorectalcancer patients by E-ice-COLD-PCR with two digital PCR approaches. For the quantification of mutations by Eice-COLD-PCR, cell lines with known mutations diluted into WT genomic DNA were used for calibration. E-ice-COLD-PCR and the two digital PCR approaches showed the same range of the mutation level and were concordantfor mutation levels below the clinical relevant threshold.E-ice-COLD-PCR can accurately detect and quantify low-abundantmutations in ccfDNA and has a shorter time toresults making it compatible with the requirements of analyses in a clinical setting without the loss of quantitativeaccuracy.

Somatic mutations bear great promise for use as biomarkers for personalized medicine, but are often present only in low abundance in biological material and are therefore difficult to detect. Many assays for mutation analysis in cancer-related genes (hotspots) have been developed to improve diagnosis, prognosis, prediction of drug resistance, and monitoring of the response to treatment. Two major approaches have been developed: mutation-specific amplification methods and methods that enrich and detect mutations without prior knowledge on the exact location and identity of the mutation. CO-amplification at Lower Denaturation temperature Polymerase Chain Reaction (COLD-PCR) methods such as full-, fast-, ice- (improved and complete enrichment), enhanced-ice, and temperature-tolerant COLD-PCR make use of a critical temperature in the polymerase chain reaction to selectively denature wild-type-mutant heteroduplexes, allowing the enrichment of rare mutations. Mutations can subsequently be identified using a variety of laboratory technologies such as high-resolution melting, digital polymerase chain reaction, pyrosequencing, Sanger sequencing, or next-generation sequencing. COLD-PCR methods are sensitive, specific, and accurate if appropriately optimized and have a short time to results. A large variety of clinical samples (tumor DNA, circulating cell-free DNA, circulating cell-free fetal DNA, and circulating tumor cells) have been studied using COLD-PCR in many different applications including the detection of genetic changes in cancer and infectious diseases, non-invasive prenatal diagnosis, detection of microorganisms, or DNA methylation analysis. In this review, we describe in detail the different COLD-PCR approaches, highlighting their specificities, advantages, and inconveniences and demonstrating their use in different fields of biological and biomedical research.

RATIONALE High-energy collision-induced dissociation (CID) spectra of isomeric RNA/DNA chimeras using matrix-assisted laser desorption/ionization time-of-flight LIFT mass spectrometry (MALDI-LIFT-TOF/TOF) can potentially be applied for an exhaustive fragment characterization in a nucleic acid sequencing scheme. These chimeras contain deoxynucleotides and at the 3'-end a ribonucleotide with a 3'-phosphate group. METHODS Deprotonated RNA/DNA chimeras of 4-, 5-, 7- and 10-mers are analyzed by CID. This enhances consecutive dissociations from both the precursor and prompt product anions generated by MALDI and metastable fragmentations prior to entering the LIFT cell. RESULTS Gas-phase fragmentations of 4- and 5-mers produced many fragment ions, from base release prior to consecutive cleavage of the nucleotide phosphate bond linkage phosphate. The unusual a4− product ion is a specific and diagnostic dissociation of the 4-mer if the ribonucleotide contains cytosine. As the size of RNA/DNA chimeras increase, several abundant product ions are generated mainly from zwitterionic forms (deprotonated phosphate ester and protonated base sites): [(M-H)–BiH]−, [ai–BiH]−, wj−, [wj, (ai-BiH)]− (if Bi ≠ T) as internal product ion, and more rarely [wj–BiH]−. The absence of the majority of the [ai–BiH]− series although the wj− series suggested that the higher critical energy processes with a loose transition state are favored yielding the wj− series. A large number of abundant fragment ions are detected which enable each isomer to be sequenced. CONCLUSIONS This sequencing method is high-throughput, accurate and could be used to sequence isomers of up to 10-mers and also oligonucleotides of unknown sequence. However, RNA/DNA chimeras without thymine must be sufficiently concentrated to reach desorption of deprotonated molecular species to be selected in LIFT to produce all fragment ions within measurable abundances. Copyright © 2014 John Wiley & Sons, Ltd.

Here, we describe a high-throughput, single-tube, allele-specific ribonucleotide analog pyrophosphorolysis-activated polymerization (ribo-PAP) PCR multiplex genotyping and resequencing method. An RNA/DNA chimeric PCR product is generated using genomic DNA as starting template, a panel of allele-selective 5′-tagged primers, a reverse primer, one nucleotide in the ribo-form (90–100%), the other nucleotides in the deoxy-form, a DNA polymerase capable of incorporating ribonucleotides, a suitable buffer and thermal cycling. The RNA/DNA chimeric PCR products are fragmented by treatment with alkali and analyzed by mass spectrometry. All allele-selective primers have a 5′ repetitive motif where each repeat unit has a unique, distinct mass upon reverse copying and alkali fragmentation. The mass of the complement repeat fragment or flag identifies the primer or primers that were recruited in the ribo-PAP PCR. The method readily identifies homozygous and heterozygous positions in simplex or duplex ribo-PAP PCR. Many different tags can be analyzed simultaneously. The assay can genotype several SNPs in a single tube. It thus constitutes the simplest genotyping protocol with multiplex analysis. This novel genotyping and resequencing protocol was applied to different genomic loci: NOS1 and H19 in 30 individuals in simplex ribo-PAP PCR and at two SLCO1B1 loci in 95 individuals in duplex ribo-PAP PCR.

Approaches developed for sequencing DNA with detection by mass spectrometry use strategies that deviate from the Sanger-type methods. Procedures demonstrated so far used the sequence specificity of RNA endonucleases, as unfortunately equivalent enzymes for DNA do not exist and therefore require transcription of DNA into RNA prior to fragmentation. We have developed a novel, rapid and accurate concept for DNA sequencing using mass spectrometry and RNA/DNA chimeras and applied it to sequence mitochondrial DNA. Our method is based on the preparation of a chimeric RNA/DNA with a DNA polymerase that also incorporates ribonucleotides. Sequencing is carried out with one ribonucleotide (ATP, CTP or GTP) and the other three nucleotides in their deoxyribo-form. The product is treated with alkali, which cleaves 3' of all ribonucleotides to form a terminal 3' phosphate. Conditions have been streamlined so that molecular, biological and alkali cleavage conditions are compatible with matrix-assisted laser desorption/ionization time-of-flight (MALDI) mass spectrometric analysis. Fragment analysis by MALDI MS provides a sequence-specific fingerprint, which allows the identification of differences between a reference and another sequence. Due to the mass profile, the position and kind of the mutation can be assigned. These differences between signatures are indicative of known, unidentified, rare and private mutations. This novel DNA sequencing protocol was applied to sequence the hypervariable region 1 (HV1) of mitochondrial DNA in 22 individuals.

Single nucleotide polymorphisms (SNPs) are now widely used for many DNA analysis applications such as linkage disequilibrium mapping, pharmacogenomics and traceability. Many methods for SNP genotyping exist with diverse strategies for allele-distinction. Mass spectrometers are used most commonly in conjunction with primer extension procedures with allele-specific termination. Here we present a novel concept for allele-preparation for SNP genotyping. Primer extension is carried out with an extension primer positioned immediately upstream of the SNP that is to be genotyped, a complete set of four ribonucleotides and a ribonucleotide incorporating DNA polymerase. The allele-extension products are then treated with alkali, which results in the cleavage immediately after the first added ribonucleotide. In addition, to obtain fragments easily detectable by mass spectrometry, we have included a ribonucleotide in the primer usually at the fourth nucleotide from the 3' terminus. The method was tested on four SNPs each with a different combination of nucleotides. The advantage over other mass spectrometry-based SNP genotyping assays is that this one only requires a PCR, a primer extension reaction with a universal extension mix and an inexpensive facile cleavage reaction, which makes it overall very cost effective and easy in handling.