Compressive Sensing DNA Microarrays

Compressive sensing microarrays (CSMs) are DNA-based sensors that operate using group testing and compressive sensing (CS) principles. In contrast to conventional DNA microarrays, in which each genetic sensor is designed to respond to a single target, in a CSM, each sensor responds to a set of targets. We study the problem of designing CSMs that simultaneously account for both the constraints from CS theory and the biochemistry of probe-target DNA hybridization. An appropriate cross-hybridization model is proposed for CSMs, and several methods are developed for probe design and CS signal recovery based on the new model. Lab experiments suggest that in order to achieve accurate hybridization profiling, consensus probe sequences are required to have sequence homology of at least 80% with all targets to be detected. Furthermore, out-of-equilibrium datasets are usually as accurate as those obtained from equilibrium conditions. Consequently, one can use CSMs in applications in which only short hybridization times are allowed

Compressive Inverse Scattering II. SISO Measurements with Born scatterers

Inverse scattering methods capable of compressive imaging are proposed and analyzed. The methods employ randomly and repeatedly (multiple-shot) the single-input-single-output (SISO) measurements in which the probe frequencies, the incident and the sampling directions are related in a precise way and are capable of recovering exactly scatterers of sufficiently low sparsity. For point targets, various sampling techniques are proposed to transform the scattering matrix into the random Fourier matrix. The results for point targets are then extended to the case of localized extended targets by interpolating from grid points. In particular, an explicit error bound is derived for the piece-wise constant interpolation which is shown to be a practical way of discretizing localized extended targets and enabling the compressed sensing techniques. For distributed extended targets, the Littlewood-Paley basis is used in analysis. A specially designed sampling scheme then transforms the scattering matrix into a block-diagonal matrix with each block being the random Fourier matrix corresponding to one of the multiple dyadic scales of the extended target. In other words by the Littlewood-Paley basis and the proposed sampling scheme the different dyadic scales of the target are decoupled and therefore can be reconstructed scale-by-scale by the proposed method. Moreover, with probes of any single frequency \om the coefficients in the Littlewood-Paley expansion for scales up to \om/(2\pi) can be exactly recovered.Comment: Add a new section (Section 3) on localized extended target

Set-Codes with Small Intersections and Small Discrepancies

We are concerned with the problem of designing large families of subsets over a common labeled ground set that have small pairwise intersections and the property that the maximum discrepancy of the label values within each of the sets is less than or equal to one. Our results, based on transversal designs, factorizations of packings and Latin rectangles, show that by jointly constructing the sets and labeling scheme, one can achieve optimal family sizes for many parameter choices. Probabilistic arguments akin to those used for pseudorandom generators lead to significantly suboptimal results when compared to the proposed combinatorial methods. The design problem considered is motivated by applications in molecular data storage and theoretical computer science

Bestrophin1: A Gene that Causes Many Diseases

Bestrophinopathies are a group of clinically distinct inherited retinal dystrophies that lead to the gradual loss of vision in and around the macular area. There are no treatments for patients suffering from bestrophinopathies, and no measures can be taken to prevent visual deterioration in those who have inherited disease-causing mutations. Bestrophinopathies are caused by mutations in the Bestrophin1 gene (BEST1), a protein found exclusively in the retinal pigment epithelial (RPE) cells of the eye. Mutations in BEST1 affect the function of the RPE leading to the death of overlying retinal cells and subsequent vision loss. The pathogenic mechanisms arising from BEST1 mutations are still not fully understood, and it is not clear how mutations in BEST1 lead to diseases with distinct clinical features. This chapter discusses BEST1, the use of model systems to investigate the effects of mutations and the potential to investigate individual bestrophinopathies using induced pluripotent stem cells

A common genetic variant of a mitochondrial RNA processing enzyme predisposes to insulin resistance

Mitochondrial energy metabolism plays an important role in the pathophysiology of insulin resistance. Recently, a missense N437S variant was identified in the MRPP3 gene, which encodes a mitochondrial RNA processing enzyme within the RNase P complex, with predicted impact on metabolism. We used CRISPR-Cas9 genome editing to introduce this variant into the mouse Mrpp3 gene and show that the variant causes insulin resistance on a high-fat diet. The variant did not influence mitochondrial gene expression markedly, but instead, it reduced mitochondrial calcium that lowered insulin release from the pancreatic islet β cells of the Mrpp3 variant mice. Reduced insulin secretion resulted in lower insulin levels that contributed to imbalanced metabolism and liver steatosis in the Mrpp3 variant mice on a high-fat diet. Our findings reveal that the MRPP3 variant may be a predisposing factor to insulin resistance and metabolic disease in the human population

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources

Interaction of Bestrophin-1 and Ca2+ Channel β-Subunits: Identification of New Binding Domains on the Bestrophin-1 C-Terminus

Bestrophin-1 modulates currents through voltage-dependent L-type Ca2+ channels by physically interacting with the β-subunits of Ca2+ channels. The main function of β-subunits is to regulate the number of pore-forming CaV-subunits in the cell membrane and modulate Ca2+ channel currents. To understand the influence of full-length bestrophin-1 on β-subunit function, we studied binding and localization of bestrophin-1 and Ca2+ channel subunits, together with modulation of CaV1.3 Ca2+ channels currents. In heterologeous expression, bestrophin-1 showed co-immunoprecipitation with either, β3-, or β4-subunits. We identified a new highly conserved cluster of proline-rich motifs on the bestrophin-1 C-terminus between amino acid position 468 and 486, which enables possible binding to SH3-domains of β-subunits. A bestrophin-1 that lacks these proline-rich motifs (ΔCT-PxxP bestrophin-1) showed reduced efficiency to co-immunoprecipitate with β3 and β4-subunits. In the presence of ΔCT-PxxP bestrophin-1, β4-subunits and CaV1.3 subunits partly lost membrane localization. Currents from CaV1.3 subunits were modified in the presence of β4-subunit and wild-type bestrophin-1: accelerated time-dependent activation and reduced current density. With ΔCTPxxP bestrophin-1, currents showed the same time-dependent activation as with wild-type bestrophin-1, but the current density was further reduced due to decreased number of Ca2+ channels proteins in the cell membrane. In summary, we described new proline-rich motifs on bestrophin-1 C-terminus, which help to maintain the ability of β-subunits to regulate surface expression of pore-forming CaV Ca2+-channel subunits

TMEM16B, a novel protein with calcium-dependent chloride channel activity, associates with a presynaptic protein complex in photoreceptor terminals

Photoreceptor ribbon synapses release glutamate in response to graded changes in membrane potential evoked by vast, logarithmically scalable light intensities. Neurotransmitter release is modulated by intracellular calcium levels. Large Ca2+-dependent chloride currents are important regulators of synaptic transmission from photoreceptors to second-order neurons; the molecular basis underlying these currents is unclear. We cloned human and mouse TMEM16B, a member of the TMEM16 family of transmembrane proteins, and show that it is abundantly present in the photoreceptor synaptic terminals in mouse retina. TMEM16B colocalizes with adaptor proteins PSD95, VELI3, and MPP4 at the ribbon synapses and contains a consensus PDZ class I binding motif capable of interacting with PDZ domains of PSD95. Furthermore, TMEM16B is lost from photoreceptor membranes of MPP4-deficient mice. This suggests that TMEM16B is a novel component of a presynaptic protein complex recruited to specialized plasma membrane domains of photoreceptors. TMEM16B confers Ca2+-dependent chloride currents when overexpressed in mammalian cells as measured by halide sensitive fluorescent protein assays and whole-cell patch-clamp recordings. The compartmentalized localization and the electrophysiological properties suggest TMEM16B to be a strong candidate for the long sought-after Ca2+-dependent chloride channel in the photoreceptor synapse

Low dispersal and ploidy differences in a grass maintain photosynthetic diversity despite gene flow and habitat overlap

Geographical isolation facilitates the emergence of distinct phenotypes within a single species, but reproductive barriers or selection is needed to maintain the polymorphism after secondary contact. Here, we explore the processes that maintain intraspecific variation of C4 photosynthesis, a complex trait that results from the combined action of multiple genes. The grass Alloteropsis semialata includes C4 and non‐C4 populations, which have co‐existed as a polyploid series for more than one million years in the miombo woodlands of Africa. Using population genomics, we show that there is genome‐wide divergence for the photosynthetic types, but the current distribution does not reflect a simple habitat displacement scenario as the genetic clusters overlap, being occasionally mixed within a given habitat. Despite evidence of recurrent introgression between non‐C4 and C4, in both diploids and polyploids, the distinct genetic lineages retain their identity, potentially because of selection against hybrids. Coupled with strong isolation by distance within each genetic group, this selection created a geographical mosaic of photosynthetic types. Diploid C4 and non‐C4 types never grew together, and the C4 type from mixed populations constantly belonged to the hexaploid lineage. By limiting reproductive interactions between photosynthetic types, the ploidy difference likely allows their co‐occurrence, reinforcing the functional diversity within this species. Together, these factors enabled the persistence of divergent physiological traits of ecological importance within a single species despite gene flow and habitat overlap