Allele-specific copy number profiling by next-generation DNA sequencing

The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by falcon allows us to draw detailed conclusions regarding the clonal history of the individual''s colon cancer.     

Effective DNA/RNA co-extraction for analysis of microRNAs, mRNAs, and genomic DNA from formalin-fixed paraffin-embedded specimens

Background

Retrospective studies of archived human specimens, with known clinical follow-up, are used to identify predictive and prognostic molecular markers of disease. Due to biochemical differences, however, formalin-fixed paraffin-embedded (FFPE) DNA and RNA have generally been extracted separately from either different tissue sections or from the same section by dividing the digested tissue. The former limits accurate correlation whilst the latter is impractical when utilizing rare or limited archived specimens.

Principal Findings

For effective recovery of genomic DNA and total RNA from a single FFPE specimen, without splitting the proteinase-K digested tissue solution, we optimized a co-extraction method by using TRIzol and purifying DNA from the lower aqueous and RNA from the upper organic phases. Using a series of seven different archived specimens, we evaluated the total amounts of genomic DNA and total RNA recovered by our TRIzol-based co-extraction method and compared our results with those from two commercial kits, the Qiagen AllPrep DNA/RNA FFPE kit, for co-extraction, and the Ambion RecoverAll™ Total Nucleic Acid Isolation kit, for separate extraction of FFPE-DNA and -RNA. Then, to accurately assess the quality of DNA and RNA co-extracted from a single FFPE specimen, we used qRT-PCR, gene expression profiling and methylation assays to analyze microRNAs, mRNAs, and genomic DNA recovered from matched fresh and FFPE MCF10A cells. These experiments show that the TRIzol-based co-extraction method provides larger amounts of FFPE-DNA and –RNA than the two other methods, and particularly provides higher quality microRNAs and genomic DNA for subsequent molecular analyses.

Significance

We determined that co-extraction of genomic DNA and total RNA from a single FFPE specimen is an effective recovery approach to obtain high-quality material for parallel molecular and high-throughput analyses. Our optimized approach provides the option of collecting DNA, which would otherwise be discarded or degraded, for additional or subsequent studies.     

A distance-type measure approach to the analysis of copy number variation in DNA sequencing data

Background

The next generation sequencing technology allows us to obtain a large amount of short DNA sequence (DNA-seq) reads at a genome-wide level. DNA-seq data have been increasingly collected during the recent years. Count-type data analysis is a widely used approach for DNA-seq data. However, the related data pre-processing is based on the moving window method, in which a window size need to be defined in order to obtain count-type data. Furthermore, useful information can be reduced after data pre-processing for count-type data.

Results

In this study, we propose to analyze DNA-seq data based on the related distance-type measure. Distances are measured in base pairs (bps) between two adjacent alignments of short reads mapped to a reference genome. Our experimental data based simulation study confirms the advantages of distance-type measure approach in both detection power and detection accuracy. Furthermore, we propose artificial censoring for the distance data so that distances larger than a given value are considered potential outliers. Our purpose is to simplify the pre-processing of DNA-seq data. Statistically, we consider a mixture of right censored geometric distributions to model the distance data. Additionally, to reduce the GC-content bias, we extend the mixture model to a mixture of generalized linear models (GLMs). The estimation of model can be achieved by the Newton-Raphson algorithm as well as the Expectation-Maximization (E-M) algorithm. We have conducted simulations to evaluate the performance of our approach. Based on the rank based inverse normal transformation of distance data, we can obtain the related z-values for a follow-up analysis. For an illustration, an application to the DNA-seq data from a pair of normal and tumor cell lines is presented with a change-point analysis of z-values to detect DNA copy number alterations.

Conclusion

Our distance-type measure approach is novel. It does not require either a fixed or a sliding window procedure for generating count-type data. Its advantages have been demonstrated by our simulation studies and its practical usefulness has been illustrated by an experimental data application.

     

Proteome analysis of microdissected formalin-fixed and paraffin-embedded tissue specimens.

Targeted proteomics research, based on the enrichment of disease-relevant proteins from isolated cell populations selected from high-quality tissue specimens, offers great potential for the identification of diagnostic, prognostic, and predictive biological markers for use in the clinical setting and during preclinical testing and clinical trials, as well as for the discovery and validation of new protein drug targets. Formalin-fixed and paraffin-embedded (FFPE) tissue collections, with attached clinical and outcome information, are invaluable resources for conducting retrospective protein biomarker investigations and performing translational studies of cancer and other diseases. Combined capillary isoelectric focusing/nano-reversed-phase liquid chromatography separations equipped with nano-electrospray ionization-tandem mass spectrometry are employed for the studies of proteins extracted from microdissected FFPE glioblastoma tissues using a heat-induced antigen retrieval (AR) technique. A total of 14,478 distinct peptides are identified, leading to the identification of 2733 non-redundant SwissProt protein entries. Eighty-three percent of identified FFPE tissue proteins overlap with those obtained from the pellet fraction of fresh-frozen tissue of the same patient. This large degree of protein overlapping is attributed to the application of detergent-based protein extraction in both the cell pellet preparation protocol and the AR technique.     

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.     

Evaluation of a transposase protocol for rapid generation of shotgun high-throughput sequencing libraries from nanogram quantities of DNA

Construction of DNA fragment libraries for next-generation sequencing can prove challenging, especially for samples with low DNA yield. Protocols devised to circumvent the problems associated with low starting quantities of DNA can result in amplification biases that skew the distribution of genomes in metagenomic data. Moreover, sample throughput can be slow, as current library construction techniques are time-consuming. This study evaluated Nextera, a new transposon-based method that is designed for quick production of DNA fragment libraries from a small quantity of DNA. The sequence read distribution across nine phage genomes in a mock viral assemblage met predictions for six of the least-abundant phages; however, the rank order of the most abundant phages differed slightly from predictions. De novo genome assemblies from Nextera libraries provided long contigs spanning over half of the phage genome; in four cases where full-length genome sequences were available for comparison, consensus sequences were found to match over 99% of the genome with near-perfect identity. Analysis of areas of low and high sequence coverage within phage genomes indicated that GC content may influence coverage of sequences from Nextera libraries. Comparisons of phage genomes prepared using both Nextera and a standard 454 FLX Titanium library preparation protocol suggested that the coverage biases according to GC content observed within the Nextera libraries were largely attributable to bias in the Nextera protocol rather than to the 454 sequencing technology. Nevertheless, given suitable sequence coverage, the Nextera protocol produced high-quality data for genomic studies. For metagenomics analyses, effects of GC amplification bias would need to be considered; however, the library preparation standardization that Nextera provides should benefit comparative metagenomic analyses.     

Application of multiplex PCR with histopathologic features for detection of familial breast cancer in formalin-fixed, paraffin-embedded histologic specimens

Breast cancer is the most common malignancy among females in the world. Age and familial history are the major risk factors for the development of this disease in Iran. Mutations of BRCA1 and BRCA2 genes are associated with a greatly increased risk for development of familial breast cancer. Frequency of BRCA mutations was identified in familial breast cancers (FBC) and non-familial breast cancers (NFBC) by molecular genetics, morphological and Immunohistochemical methods. Thirty forth formalin-fixed, paraffin-embedded breast tissue tumors were analyzed from 16 patients with FBC and 18 patients with NFBC. Three 5382insC mutations detected by multiplex PCR in 16 familial breast cancers. Immunohistochemical method was used to detect estrogen receptor (ER) and progesterona receptor (PR) and TP53. Comparison of ER, PR and TP53 exhibited high difference (P < 0.0001) in familial breast cancers and non-familial breast cancers. Our results demonstrated that 5382insC mutation, ER, PR, TP53, mitotic activity, polymorphism, necrosis and tubules can serve as the major risk factors for the development of FBC.     

seqCNA: an R package for DNA copy number analysis in cancer using high-throughput sequencing

Background

Deviations in the amount of genomic content that arise during tumorigenesis, called copy number alterations, are structural rearrangements that can critically affect gene expression patterns. Additionally, copy number alteration profiles allow insight into cancer discrimination, progression and complexity. On data obtained from high-throughput sequencing, improving quality through GC bias correction and keeping false positives to a minimum help build reliable copy number alteration profiles.

Results

We introduce seqCNA, a parallelized R package for an integral copy number analysis of high-throughput sequencing cancer data. The package includes novel methodology on (i) filtering, reducing false positives, and (ii) GC content correction, improving copy number profile quality, especially under great read coverage and high correlation between GC content and copy number. Adequate analysis steps are automatically chosen based on availability of paired-end mapping, matched normal samples and genome annotation.

Conclusions

seqCNA, available through Bioconductor, provides accurate copy number predictions in tumoural data, thanks to the extensive filtering and better GC bias correction, while providing an integrated and parallelized workflow.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-178) contains supplementary material, which is available to authorized users.     

A multiplex endpoint RT-PCR assay for quality assessment of RNA extracted from formalin-fixed paraffin-embedded tissues

Background

mRNAs are highly versatile, non-toxic molecules that are easy to produce and store, which can allow transient protein expression in all cell types. The safety aspects of mRNA-based treatments in gene therapy make this molecule one of the most promising active components of therapeutic or prophylactic methods. The use of mRNA as strategy for the stimulation of the immune system has been used mainly in current strategies for the cancer treatment but until now no one tested this molecule as vaccine for infectious disease.

Results

We produce messenger RNA of Hsp65 protein from Mycobacterium leprae and show that vaccination of mice with a single dose of 10 μg of naked mRNA-Hsp65 through intranasal route was able to induce protection against subsequent challenge with virulent strain of Mycobacterium tuberculosis. Moreover it was shown that this immunization was associated with specific production of IL-10 and TNF-alpha in spleen. In order to determine if antigen presenting cells (APCs) present in the lung are capable of capture the mRNA, labeled mRNA-Hsp65 was administered by intranasal route and lung APCs were analyzed by flow cytometry. These experiments showed that after 30 minutes until 8 hours the populations of CD11c⁺, CD11b⁺ and CD19⁺ cells were able to capture the mRNA. We also demonstrated in vitro that mRNA-Hsp65 leads nitric oxide (NO) production through Toll-like receptor 7 (TLR7).

Conclusions

Taken together, our results showed a novel and efficient strategy to control experimental tuberculosis, besides opening novel perspectives for the use of mRNA in vaccines against infectious diseases and clarifying the mechanisms involved in the disease protection we noticed as well.     

Assay for nanogram quantities of DNA in cellular homogenates.

The DNA concentration of a crude cellular homogenate can be measured accurately in the nanogram range using the fluorescence enhancement of 4′,6-diamidino-2-phenylindole (DAPI) or bisbenzimidazole (Hoechst H 33258) complexed with DNA. A simple assay has been devised including an internal standard, which allows reliable measurement and compensates for any quenching due to cellular components or buffer. The fluorescence enhancement is highly specific for DNA; no other cell component produces significant fluorescence. The response is linear over a broad dynamic range making the measurement of unknown DNA concentrations convenient.     

Southern and dot blot analysis of DNA from formalin-fixed, paraffin-embedded tissue samples from colonic carcinomas

Two extraction methods for the isolation of DNA from formalin-fixed, paraffin-embedded tissue samples from colonic carcinomas were compared. The processed DNAs were compared with DNAs from fresh specimens of the same tumors. The two extraction methods gave similar results. Formalin-fixation and paraffin-embedding irreversibly denatured DNA and consequently decreased the extraction yield and interfered with the quantitative measurement of DNA. Southern blot and dot blot analysis of processed and native DNA was performed using a c-myc and an actin probe. The results show that for Southern analysis processed DNA can be used but, due to the generation of random breaks, the restriction fragments have to be small. Furthermore, the fixation-induced crosslinking of DNA appears to hamper hybridization. For these reasons processed DNA can be analyzed better by dot blot rather than Southern blot hybridization.     

Comparison of eight commercially available kits for DNA extraction from formalin-fixed paraffin-embedded tissues

A proper extraction method from formalin-fixed paraffin-embedded (FFPE) blocks is essential to obtain DNA of satisfactory quality/quantity. We compared the effectiveness of eight commercially available kits for DNA extraction based on 10 FFPE tissues. Kits differed significantly in terms of DNA yield, purity, and quality. Using the QIAamp DNA FFPE Tissue Kit (Qiagen) and the ReliaPrep FFPE gDNA Miniprep System (Promega), we obtained DNA of the highest quality and acceptable quantity. We also demonstrated that overnight digestion of samples usually improved DNA yield and/or purity. For precious or limited material, double elution is recommended for obtaining up to 42% higher amount of DNA.     

CODEX: a normalization and copy number variation detection method for whole exome sequencing

High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.     

Microarray analysis of copy number variation in single cells

We present a protocol for reliably detecting DNA copy number aberrations in a single human cell. Multiple displacement-amplified DNAs of a cell are hybridized to a 3,000-bacterial artificial chromosome (BAC) array and to an Affymetrix 250,000 (250K)-SNP array. Subsequent copy number calling is based on the integration of BAC probe-specific copy number probabilities that are estimated by comparing probe intensities with a single-cell whole-genome amplification (WGA) reference model for diploid chromosomes, as well as SNP copy number and loss-of-heterozygosity states estimated by hidden Markov models (HMM). All methods for detecting DNA copy number aberrations in single human cells have difficulty in confidently discriminating WGA artifacts from true genetic variants. Furthermore, some methods lack thorough validation for segmental DNA imbalance detection. Our protocol minimizes false-positive variant calling and enables uniparental isodisomy detection in single cells. Additionally, it provides quality assessment, allowing the exclusion of uninterpretable single-cell WGA samples. The protocol takes 5-7 d.     

Detecting single DNA copy number variations in complex genomes using one nanogram of starting DNA and BAC-array CGH

Comparative genomic hybridization to bacterial artificial chromosome (BAC)-arrays (array-CGH) is a highly efficient technique, allowing the simultaneous measurement of genomic DNA copy number at hundreds or thousands of loci, and the reliable detection of local one-copy-level variations. We report a genome-wide amplification method allowing the same measurement sensitivity, using 1 ng of starting genomic DNA, instead of the classical 1 microg usually necessary. Using a discrete series of DNA fragments, we defined the parameters adapted to the most faithful ligation-mediated PCR amplification and the limits of the technique. The optimized protocol allows a 3000-fold DNA amplification, retaining the quantitative characteristics of the initial genome. Validation of the amplification procedure, using DNA from 10 tumour cell lines hybridized to BAC-arrays of 1500 spots, showed almost perfectly superimposed ratios for the non-amplified and amplified DNAs. Correlation coefficients of 0.96 and 0.99 were observed for regions of low-copy-level variations and all regions, respectively (including in vivo amplified oncogenes). Finally, labelling DNA using two nucleotides bearing the same fluorophore led to a significant increase in reproducibility and to the correct detection of one-copy gain or loss in >90% of the analysed data, even for pseudotriploid tumour genomes.     

CONAN: copy number variation analysis software for genome-wide association studies

Background  

Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.     

Rapid quantification of DNA libraries for next-generation sequencing

The next-generation DNA sequencing workflows require an accurate quantification of the DNA molecules to be sequenced which assures optimal performance of the instrument. Here, we demonstrate the use of qPCR for quantification of DNA libraries used in next-generation sequencing. In addition, we find that qPCR quantification may allow improvements to current NGS workflows, including reducing the amount of library DNA required, increasing the accuracy in quantifying amplifiable DNA, and avoiding amplification bias by reducing or eliminating the need to amplify DNA before sequencing.