Profiling of T-cell receptor signaling complex assembly in human CD4 T-lymphocytes using RP protein arrays.

The RP protein (RPP) array approach immobilizes minute amounts of cell lysates or tissue protein extracts as distinct microspots on NC-coated slide. Subsequent detection with specific antibodies allows multiplexed quantification of proteins and their modifications at a scale that is beyond what traditional techniques can achieve. Cellular functions are the result of the coordinated action of signaling proteins assembled in macromolecular complexes. These signaling complexes are highly dynamic structures that change their composition with time and space to adapt to cell environment. Their comprehensive analysis requires until now relatively large amounts of cells (>5 x 10(7)) due to their low abundance and breakdown during isolation procedure. In this study, we combined small scale affinity capture of the T-cell receptor (TCR) and RPP arrays to follow TCR signaling complex assembly in human ex vivo isolated CD4 T-cells. Using this strategy, we report specific recruitment of signaling components to the TCR complex upon T-cell activation in as few as 0.5 million of cells. Second- to fourth-order TCR interacting proteins were accurately quantified, making this strategy specially well-suited to the analysis of membrane-associated signaling complexes in limited amounts of cells or tissues, e.g., ex vivo isolated cells or clinical specimens.

Does Semantic Context Benefit Speech Understanding through "Top-Down" Processes? Evidence from Time-resolved Sparse fMRI.

When speech is degraded, word report is higher for semantically coherent sentences (e.g., her new skirt was made of denim) than for anomalous sentences (e.g., her good slope was done in carrot). Such increased intelligibility is often described as resulting from "top-down" processes, reflecting an assumption that higher-level (semantic) neural processes support lower-level (perceptual) mechanisms. We used time-resolved sparse fMRI to test for top-down neural mechanisms, measuring activity while participants heard coherent and anomalous sentences presented in speech envelope/spectrum noise at varying signal-to-noise ratios (SNR). The timing of BOLD responses to more intelligible speech provides evidence of hierarchical organization, with earlier responses in peri-auditory regions of the posterior superior temporal gyrus than in more distant temporal and frontal regions. Despite Sentence content × SNR interactions in the superior temporal gyrus, prefrontal regions respond after auditory/perceptual regions. Although we cannot rule out top-down effects, this pattern is more compatible with a purely feedforward or bottom-up account, in which the results of lower-level perceptual processing are passed to inferior frontal regions. Behavioral and neural evidence that sentence content influences perception of degraded speech does not necessarily imply "top-down" neural processes.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Affymetrix Whole-Transcript Human Gene 1.0 ST array is highly concordant with standard 3' expression arrays.

The recently released Affymetrix Human Gene 1.0 ST array has two major differences compared with standard 3' based arrays: (i) it interrogates the entire mRNA transcript, and (ii) it uses DNA targets. To assess the impact of these differences on array performance, we performed a series of comparative hybridizations between the Human Gene 1.0 ST and the Affymetrix HG-U133 Plus 2.0 and the Illumina HumanRef-8 BeadChip arrays. Additionally, both RNA and DNA targets were hybridized on HG-U133 Plus 2.0 arrays. The results show that the overall reproducibility of the Gene 1.0 ST array is best. When looking only at the high intensity probes, the reproducibility of the Gene 1.0 ST array and the Illumina BeadChip array is equally good. Concordance of array results was assessed using different inter-platform mappings. Agreements are best between the two labeling protocols using HG-U133 Plus 2.0 array. The Gene 1.0 ST array is most concordant with the HG-U133 array hybridized with cDNA targets. This may reflect the impact of the target type. Overall, the high degree of correspondence provides strong evidence for the reliability of the Gene 1.0 ST array.

Substantial deletion overlap among divergent Arabidopsis genomes revealed by intersection of short reads and tiling arrays.

ABSTRACT: Identification of small polymorphisms from next generation sequencing short read data is relatively easy, but detection of larger deletions is less straightforward. Here, we analyzed four divergent Arabidopsis accessions and found that intersection of absent short read coverage with weak tiling array hybridization signal reliably flags deletions. Interestingly, individual deletions were frequently observed in two or more of the accessions examined, suggesting that variation in gene content partly reflects a common history of deletion events.

Direct detection of a BRAF mutation in total RNA from melanoma cells using cantilever arrays.

Malignant melanoma, the deadliest form of skin cancer, is characterized by a predominant mutation in the BRAF gene. Drugs that target tumours carrying this mutation have recently entered the clinic. Accordingly, patients are routinely screened for mutations in this gene to determine whether they can benefit from this type of treatment. The current gold standard for mutation screening uses real-time polymerase chain reaction and sequencing methods. Here we show that an assay based on microcantilever arrays can detect the mutation nanomechanically without amplification in total RNA samples isolated from melanoma cells. The assay is based on a BRAF-specific oligonucleotide probe. We detected mutant BRAF at a concentration of 500 pM in a 50-fold excess of the wild-type sequence. The method was able to distinguish melanoma cells carrying the mutation from wild-type cells using as little as 20 ng µl(-1) of RNA material, without prior PCR amplification and use of labels.

Genome-wide arrays in routine diagnostics of hematological malignancies.

Over the last three decades, cytogenetic analysis of malignancies has become an integral part of disease evaluation and prediction of prognosis or responsiveness to therapy. In most diagnostic laboratories, conventional karyotyping, in conjunction with targeted fluorescence in situ hybridization analysis, is routinely performed to detect recurrent aberrations with prognostic implications. However, the genetic complexity of cancer cells requires a sensitive genome-wide analysis, enabling the detection of small genomic changes in a mixed cell population, as well as of regions of homozygosity. The advent of comprehensive high-resolution genomic tools, such as molecular karyotyping using comparative genomic hybridization or single-nucleotide polymorphism microarrays, has overcome many of the limitations of traditional cytogenetic techniques and has been used to study complex genomic lesions in, for example, leukemia. The clinical impact of the genomic copy-number and copy-neutral alterations identified by microarray technologies is growing rapidly and genome-wide array analysis is evolving into a diagnostic tool, to better identify high-risk patients and predict patients' outcomes from their genomic profiles. Here, we review the added clinical value of an array-based genome-wide screen in leukemia, and discuss the technical challenges and an interpretation workflow in applying arrays in the acquired cytogenetic diagnostic setting.

Mixed mating in androdioecious Mercurialis annua inferred using progeny arrays and diploid-acting microsatellite loci in a hexaploid background.

Background and Aims The frequency at which males can be maintained with hermaphrodites in androdioecious populations is predicted to depend on the selfing rate, because self-fertilization by hermaphrodites reduces prospective siring opportunities for males. In particular, high selfing rates by hermaphrodites are expected to exclude males from a population. Here, the first estimates are provided of the mating system from two wild hexaploid populations of the androdioecious European wind-pollinated plant M. annua with contrasting male frequencies.Methods Four diploid microsatellite loci were used to genotype 19-20 progeny arrays from two populations of M. annua, one with males and one without. Mating-system parameters were estimated using the program MLTR.Key Results Both populations had similar, intermediate outcrossing rates (t(m) = 0.64 and 0.52 for the population with and without males, respectively). The population without males showed a lower level of correlated paternity and biparental inbreeding and higher allelic richness and gene diversity than the population with males.Conclusions The results demonstrate the utility of new diploid microsatellite loci for mating system analysis in a hexaploid plant. It would appear that androdioecious M. annua has a mixed-mating system in the wild, an uncommon finding for wind-pollinated species. This study sets a foundation for future research to assess the relative importance of the sexual system, plant-density variation and stochastic processes for the regulation of male frequencies in M. annua over space and time.

Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.

Sparse image reconstruction on the sphere: implications of a new sampling theorem.

We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to improve the fidelity of sparse image reconstruction, through both the dimensionality and sparsity of signals. To demonstrate this result, we consider a simple inpainting problem on the sphere and consider images sparse in the magnitude of their gradient. We develop a framework for total variation inpainting on the sphere, including fast methods to render the inpainting problem computationally feasible at high resolution. Recently a new sampling theorem on the sphere was developed, reducing the required number of samples by a factor of two for equiangular sampling schemes. Through numerical simulations, we verify the enhanced fidelity of sparse image reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.