Construction of correlation networks with explicit time-slices using time-lagged, variable interval standard and partial correlation coefficients

The construction of gene regulatory models from microarray time-series data has received much attention. Here we propose a method that extends standard correlation networks to incorporate explicit time-slices. The method is applied to a time-series dataset of a study on gene expression in the developmental phase of zebrafish. Results show that the method is able to distinguish real relations between genes from the data. These relations are explicitly placed in time, allowing for a better understanding of gene regulation. The method and data normalisation procedure have been implemented using the R statistical language and are available from http://zebrafish.liacs.nl/supplements.html

Constitutive nuclear lamina-genome interactions are highly conserved and associated with A/T-rich sequence

In metazoans, the nuclear lamina is thought to play an important role in the spatial organization of interphase chromosomes, by providing anchoring sites for large genomic segments named lamina-associated domains (LADs). Some of these LADs are cell-type specific, while many others appear constitutively associated with the lamina. Constitutive LADs (cLADs) may contribute to a basal chromosome architecture. By comparison of mouse and human lamina interaction maps, we find that the sizes and genomic positions of cLADs are strongly conserved. Moreover, cLADs are depleted of synteny breakpoints, pointing to evolutionary selective pressure to keep cLADs intact. Paradoxically, the overall sequence conservation is low for cLADs. Instead, cLADs are universally characterized by long stretches of DNA of high A/T content. Cell-type specific LADs also tend to adhere to this “A/T rule” in embryonic stem cells, but not in differentiated cells. This suggests that the A/T rule represents a default positioning mechanism that is locally overruled during lineage commitment. Analysis of paralogs suggests that during evolution changes in A/T content have driven the relocation of genes to and from the nuclear lamina, in tight association with changes in expression level. Taken together, these results reveal that the spatial organization of mammalian genomes is highly conserved and tightly linked to local nucleotide composition

FTO Obesity Variant Circuitry and Adipocyte Browning in Humans

Background Genomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive. Methods We examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR–Cas9 genome editing in samples from patients. Results Our data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR–Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7. Conclusions Our results point to a pathway for adipocyte thermogenesis regulation involving ARID5B, rs1421085, IRX3, and IRX5, which, when manipulated, had pronounced pro-obesity and anti-obesity effects. (Funded by the German Research Center for Environmental Health and others.)National Institutes of Health (U.S.) (R01HG004037)National Institutes of Health (U.S.) (R01GM113708)National Institutes of Health (U.S.) (R01HG008155)National Institutes of Health (U.S.) (RC1HG005334

In situ oligonucleotide synthesis on poly(dimethylsiloxane): a flexible substrate for microarray fabrication

In this paper, we demonstrate in situ synthesis of oligonucleotide probes on poly(dimethylsiloxane) (PDMS) microchannels through use of conventional phosphoramidite chemistry. PDMS polymer was moulded into a series of microchannels using standard soft lithography (micro-moulding), with dimensions <100 μm. The surface of the PDMS was derivatized by exposure to ultraviolet/ozone followed by vapour phase deposition of glycidoxypropyltrimethoxysilane and reaction with poly(ethylene glycol) spacer, resulting in a reactive surface for oligonucleotide coupling. High, reproducible yields were achieved for both 6mer and 21mer probes as assessed by hybridization to fluorescent oligonucleotides. Oligonucleotide surface density was comparable with that obtained on glass substrates. These results suggest PDMS as a stable and flexible alternative to glass as a suitable substrate in the fabrication and synthesis of DNA microarrays

Analysis of mass spectrometry data using sub-spectra

BACKGROUND: Spectra resulting from Surface-Enhanced Laser Desorption/Ionisation (SELDI) mass spectrometry measurements are constructed by combining sub-spectra, each of which are the result of a single firing of the laser responsible for the process of desorption/ionisation. These firings are performed at different locations of the spot on which the sample is analysed. The final spectrum is then constructed by summing over all these sub-spectra. This process is sub-optimal in that it can average out peaks from peptides that are present in low abundance or are unevenly distributed across the spot, particularly because the amount of noise varies considerably between sub-spectra. This argues for analysing sub-spectra separately and combining results afterwards. RESULTS: Here, we propose to analyse these sub-spectra one-by-one and combine the results using a framework which includes a significance test. This allows one to, for the first time, attach a confidence measure to detected peaks, based on the signal strength of a peak across sub-spectra. In a comparison with three other approaches the sub-spectral approach achieves a higher sensitivity and a low FDR. We further introduce the notion of peak-bags, which provide rich information about the sub-spectral contributions to a given peak. CONCLUSION: The proposed procedure offers better control over the process of distinguishing signal from noise, resulting in an improved performance over other available methods. Moreover, our method provides an implicit deconvolution of peaks, yielding insight in the actual shape of a peak, potentially aiding in a deeper understanding of peak distribution. AVAILABILITY: Implementations of the algorithm in R are available upon request

Detection of Colorectal Cancer by Serum and Tissue Protein Profiling: A Prospective Study in a Population at Risk

Colorectal cancer (CRC) is the second most common cause of cancer-related death in Europe and its prognosis is largely dependent on stage at diagnosis. Currently, there are no suitable tumour markers for early detection of CRC. In a retrospective study we previously found discriminative CRC serum protein profiles with surface enhanced laser desorption ionisation—time of flight mass spectrometry (SELDI-TOF MS). We now aimed at prospective validation of these profiles. Additionally, we assessed their applicability for follow-up after surgery and investigated tissue protein profiles of patients with CRC and adenomatous polyps (AP). Serum and tissue samples were collected from patients without known malignancy with an indication for colonoscopy and patients with AP and CRC during colonoscopy. Serum samples of controls (CON; n = 359), patients with AP (n = 177) and CRC (n = 73), as well as tissue samples from AP (n = 52) and CRC (n = 47) were analysed as described previously. Peak intensities were compared by non-parametric testing. Discriminative power of differentially expressed proteins was assessed with support vector machines (SVM). We confirmed the decreased serum levels of apolipoprotein C-1 in CRC in the current population. No differences were observed between CON and AP. Apolipoprotein C-I levels did not change significantly within 1 month post-surgery, although a gradual return to normal levels was observed. Several proteins differed between AP and CRC tissue, among which a peak with similar mass as apolipoprotein C-1. This peak was increased in CRC compared to AP. Although we prospectively validated the serum decrease of apolipoprotein C-1 in CRC, serum protein profiles did not yield SVM classifiers with suitable sensitivity and specificity for classification of our patient groups

Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.</p> <p>Results</p> <p>In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package.</p> <p>Conclusion</p> <p>In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.</p

Small chromosomal regions position themselves autonomously according to their chromatin class

The spatial arrangement of chromatin is linked to the regulation of nuclear processes. One striking aspect of nuclear organization is the spatial segregation of heterochromatic and euchromatic domains. The mechanisms of this chromatin segregation are still poorly understood. In this work, we investigated the link between the primary genomic sequence and chromatin domains. We analyzed the spatial intranuclear arrangement of a human artificial chromosome (HAC) in a xenospecific mouse background in comparison to an orthologous region of native mouse chromosome. The two orthologous regions include segments that can be assigned to three major chromatin classes according to their gene abundance and repeat repertoire: (1) gene-rich and SINE-rich euchromatin; (2) gene-poor and LINE/LTR-rich heterochromatin; and (3) genedepleted and satellite DNA-containing constitutive heterochromatin. We show, using fluorescence in situ hybridization (FISH) and 4C-seq technologies, that chromatin segments ranging from 0.6 to 3 Mb cluster with segments of the same chromatin class. As a consequence, the chromatin segments acquire corresponding positions in the nucleus irrespective of their chromosomal context, thereby strongly suggesting that this is their autonomous property. Interactions with the nuclear lamina, although largely retained in the HAC, reveal less autonomy. Taken together, our results suggest that building of a functional nucleus is largely a self-organizing process based on mutual recognition of chromosome segments belonging to the major chromatin classes