Electrochemical Genetic Profiling of Single Cancer Cells.

Recent understandings in the development and spread of cancer have led to the realization of novel single cell analysis platforms focused on circulating tumor cells (CTCs). A simple, rapid, and inexpensive analytical platform capable of providing genetic information on these rare cells is highly desirable to support clinicians and researchers alike to either support the selection or adjustment of therapy or provide fundamental insights into cell function and cancer progression mechanisms. We report on the genetic profiling of single cancer cells, exploiting a combination of multiplex ligation-dependent probe amplification (MLPA) and electrochemical detection. Cells were isolated using laser capture and lysed, and the mRNA was extracted and transcribed into DNA. Seven markers were amplified by MLPA, which allows for the simultaneous amplification of multiple targets with a single primer pair, using MLPA probes containing unique barcode sequences. Capture probes complementary to each of these barcode sequences were immobilized on a printed circuit board (PCB) manufactured electrode array and exposed to single-stranded MLPA products and subsequently to a single stranded DNA reporter probe bearing a HRP molecule, followed by substrate addition and fast electrochemical pulse amperometric detection. We present a simple, rapid, flexible, and inexpensive approach for the simultaneous quantification of multiple breast cancer related mRNA markers, with single tumor cell sensitivity.

Interpretation, stratification and evidence for sequence variants affecting mRNA splicing in complete human genome sequences.

Information theory-based methods have been shown to be sensitive and specific for predicting and quantifying the effects of non-coding mutations in Mendelian diseases. We present the Shannon pipeline software for genome-scale mutation analysis and provide evidence that the software predicts variants affecting mRNA splicing. Individual information contents (in bits) of reference and variant splice sites are compared and significant differences are annotated and prioritized. The software has been implemented for CLC-Bio Genomics platform. Annotation indicates the context of novel mutations as well as common and rare SNPs with splicing effects. Potential natural and cryptic mRNA splicing variants are identified, and null mutations are distinguished from leaky mutations. Mutations and rare SNPs were predicted in genomes of three cancer cell lines (U2OS, U251 and A431), which were supported by expression analyses. After filtering, tractable numbers of potentially deleterious variants are predicted by the software, suitable for further laboratory investigation. In these cell lines, novel functional variants comprised 6-17 inactivating mutations, 1-5 leaky mutations and 6-13 cryptic splicing mutations. Predicted effects were validated by RNA-seq analysis of the three aforementioned cancer cell lines, and expression microarray analysis of SNPs in HapMap cell lines.

TagGD: fast and accurate software for DNA Tag generation and demultiplexing.

Multiplexing is of vital importance for utilizing the full potential of next generation sequencing technologies. We here report TagGD (DNA-based Tag Generator and Demultiplexor), a fully-customisable, fast and accurate software package that can generate thousands of barcodes satisfying user-defined constraints and can guarantee full demultiplexing accuracy. The barcodes are designed to minimise their interference with the experiment. Insertion, deletion and substitution events are considered when designing and demultiplexing barcodes. 20,000 barcodes of length 18 were designed in 5 minutes and 2 million barcoded Illumina HiSeq-like reads generated with an error rate of 2% were demultiplexed with full accuracy in 5 minutes. We believe that our software meets a central demand in the current high-throughput biology and can be utilised in any field with ample sample abundance. The software is available on GitHub (https://github.com/pelinakan/UBD.git).

Comparison of total and cytoplasmic mRNA reveals global regulation by nuclear retention and miRNAs.

BACKGROUND: The majority of published gene-expression studies have used RNA isolated from whole cells, overlooking the potential impact of including nuclear transcriptome in the analyses. In this study, mRNA fractions from the cytoplasm and from whole cells (total RNA) were prepared from three human cell lines and sequenced using massive parallel sequencing. RESULTS: For all three cell lines, of about 15000 detected genes approximately 400 to 1400 genes were detected in different amounts in the cytoplasmic and total RNA fractions. Transcripts detected at higher levels in the total RNA fraction had longer coding sequences and higher number of miRNA target sites. Transcripts detected at higher levels in the cytoplasmic fraction were shorter or contained shorter untranslated regions. Nuclear retention of transcripts and mRNA degradation via miRNA pathway might contribute to this differential detection of genes. The consequence of the differential detection was further investigated by comparison to proteomics data. Interestingly, the expression profiles of cytoplasmic and total RNA correlated equally well with protein abundance levels indicating regulation at a higher level. CONCLUSIONS: We conclude that expression levels derived from the total RNA fraction be regarded as an appropriate estimate of the amount of mRNAs present in a given cell population, independent of the coding sequence length or UTRs.

Comprehensive analysis of the genome transcriptome and proteome landscapes of three tumor cell lines.

We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.

Exploration of signals of positive selection derived from genotype-based human genome scans using re-sequencing data.

We have investigated whether regions of the genome showing signs of positive selection in scans based on haplotype structure also show evidence of positive selection when sequence-based tests are applied, whether the target of selection can be localized more precisely, and whether such extra evidence can lead to increased biological insights. We used two tools: simulations under neutrality or selection, and experimental investigation of two regions identified by the HapMap2 project as putatively selected in human populations. Simulations suggested that neutral and selected regions should be readily distinguished and that it should be possible to localize the selected variant to within 40 kb at least half of the time. Re-sequencing of two ~300 kb regions (chr4:158Mb and chr10:22Mb) lacking known targets of selection in HapMap CHB individuals provided strong evidence for positive selection within each and suggested the micro-RNA gene hsa-miR-548c as the best candidate target in one region, and changes in regulation of the sperm protein gene SPAG6 in the other.

Integrated genetic and epigenetic analysis identifies haplotype-specific methylation in the FTO type 2 diabetes and obesity susceptibility locus.

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10(-4), permutation p = 1.0×10(-3)). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10(-7)). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.

Linkage disequilibrium mapping of the replicated type 2 diabetes linkage signal on chromosome 1q.

OBJECTIVE: Linkage of the chromosome 1q21-25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23-Mb interval in a multiethnic sample to search for variants responsible for this linkage signal. RESEARCH DESIGN AND METHODS: In all, 5,290 single nucleotide polymorphisms (SNPs) were successfully genotyped in 3,179 type 2 diabetes case and control subjects from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q linkage. After imputation, we estimate approximately 80% coverage of common variation across the region (r (2) > 0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in approximately 8,500 case subjects and 12,400 control subjects. RESULTS: Association mapping of the 23-Mb region identified two strong signals, both of which were restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, odds ratio 1.38 [95% CI 1.21-1.57], P = 1.4 x 10(-6), in 999 case subjects and 1,190 control subjects); the second mapped within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, odds ratio 1.48 [1.18-1.76], P = 1.0 x 10(-5), under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), there was no indication that these variants were causally related to type 2 diabetes status. CONCLUSIONS: Detailed fine-mapping of the 23-Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.

A histone map of human chromosome 20q13.12.

BACKGROUND: We present a systematic search for regulatory elements in a 3.5 Mb region on human chromosome 20q13.12, a region associated with a number of medical conditions such as type II diabetes and obesity. METHODOLOGY/PRINCIPAL FINDINGS: We profiled six histone modifications alongside RNA polymerase II (PolII) and CTCF in two cell lines, HeLa S3 and NTERA-2 clone D1 (NT2/D1), by chromatin immunoprecipitation using an in-house spotted DNA array, constructed with 1.8 kb overlapping plasmid clones. In both cells, more than 90% of transcription start sites (TSSs) of expressed genes showed enrichments with PolII, di-methylated lysine 4 of histone H3 (H3K4me2), tri-methylated lysine 4 of histone H3 (H3K4me3) or acetylated H3 (H3Ac), whereas mono-methylated lysine 4 of histone H3 (H3K4me1) signals did not correlate with expression. No TSSs were enriched with tri-methylated lysine 27 of histone H3 (H3K27me3) in HeLa S3, while eight TSSs (4 expressed) showed enrichments in NT2/D1. We have also located several CTCF binding sites that are potential insulator elements. CONCLUSIONS/SIGNIFICANCE: In summary, we annotated a number of putative regulatory elements in 20q13.12 and went on to verify experimentally a subset of them using dual luciferase reporter assays. Correlating this data to sequence variation can aid identification of disease causing variants.

DNA sequence and structural properties as predictors of human and mouse promoters.

Promoters play a central role in gene regulation, yet our power to discriminate them from non-promoter sequences in higher eukaryotes is mainly restricted to those associated with CpG islands. Here, we examined in silico the promoters of 30,954 human and 18,083 mouse transcripts in the DBTSS database, to assess the impact of particular sequence and structural features (propeller twist, bendability and nucleosome positioning preference) on promoter classification and prediction. Our analysis showed that a stricter-than-traditional definition of CpG islands captures low and high CpG count promoter classes more accurately than the traditional one. We observed that both human and mouse promoter sequences are flexible with the exception of the TATA box and TSS, which are rigid regions irrespective of association with a CpG island. Therefore varying levels of structural flexibility in promoters may affect their accessibility to proteins, and hence their specificity. For all features investigated, averaged values across core promoters discriminated CpG island associated promoters from background, whereas the same did not hold for promoters without a CpG island. However, local changes around - 34 to - 23 (expected position of TATA box) and the TSS were informative in discriminating promoters (both classes) from non-promoter sequences. Additionally, we investigated ATG deserts and observed that they occur in all promoter sets except those with a TATA-box and without a CpG island in human. Interestingly, all mouse promoter sets showed ATG codon depletion irrespective of the presence of a TATA-box, possibly reflecting a weaker contribution to TSS specificity in mouse.

SNP allele frequency estimation in DNA pools and variance components analysis.

The estimation of single nucleotide polymorphism (SNP) allele frequency in pooled DNA samples has been proposed as a cost-effective approach to whole genome association studies. However, the key issue is the allele frequency window in which a genotyping method operates and provides a statistically reliable answer. We assessed the homogeneous mass extend assay and estimated the variance associated with each experimental stage. We report that a relationship between estimated allele frequency and variance might exist, suggesting that high statistical power can be retained at low, as well as high, allele frequencies. Assuming this relationship, the formation of subpools consisting of 100 samples retains an effective sample size greater than 70% of the true sample size, with a savings of 11-fold the cost of an individual genotyping study, regardless of allele frequency.

Small-world communication of residues and significance for protein dynamics.

It is not merely the position of residues that is critically important for a protein's function and stability, but also their interactions. We illustrate, by using a network construction on a set of 595 nonhomologous proteins, that regular packing is preserved in short-range interactions, but short average path lengths are achieved through some long-range contacts. Thus, lying between the two extremes of regularity and randomness, residues in folded proteins are distributed according to a "small-world" topology. Using this topology, we show that the core residues have the same local packing arrangements irrespective of protein size. Furthermore, we find that the average shortest path lengths are highly correlated with residue fluctuations, providing a link between the spatial arrangement of the residues and protein dynamics.