A Bayesian approach to copy-number-polymorphism analysis in nuclear pedigrees

Segmental copy-number polymorphisms (CNPs) represent a significant component of human genetic variation and are likely to contribute to disease susceptibility. These potentially multiallelic and highly polymorphic systems present new challenges to family-based genetic-analysis tools that commonly assume codominant markers and allow for no genotyping error. The copy-number quantitation (CNP phenotype) represents the total number of segmental copies present in an individual and provides a means to infer, rather than to observe, the underlying allele segregation. We present an integrated approach to meet these challenges, in the form of a graphical model in which we infer the underlying CNP phenotype from the (single or replicate) quantitative measure within the analysis while assuming an allele-based system segregating through the pedigree. This approach can be readily applied to the study of any form of genetic measure, and the construction permits extension to a wide variety of hypothesis tests. We have implemented the basic model for use with nuclear families, and we illustrate its application through an analysis of the CNP located in gene CCL3L1 in 201 families with asthma.     

Viral Detection: Past,Present, and Future

Viruses are essentially composed of a nucleic acid (segmented or not, DNA, or RNA) and a protein coat. Despite their simplicity, these small pathogens are responsible for significant economic and humanitarian losses that have had dramatic consequences in the course of human history. Since their discovery, scientists have developed different strategies to efficiently detect viruses, using all possible viral features. Viruses shape, proteins, and nucleic acid are used in viral detection. In this review, the development of these techniques, especially for plant and mammalian viruses, their strengths and weaknesses as well as the latest cutting‐edge technologies that may be playing important roles in the years to come are described.     

Growing functional modules from a seed protein via integration of protein interaction and gene expression data

Background  

Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI) networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules) in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules.     

Organoid systems to study the human female reproductive tract and pregnancy

Both the proper functioning of the female reproductive tract (FRT) and normal placental development are essential for women’s health, wellbeing, and pregnancy outcome. The study of the FRT in humans has been challenging due to limitations in the in vitro and in vivo tools available. Recent developments in 3D organoid technology that model the different regions of the FRT include organoids of the ovaries, fallopian tubes, endometrium and cervix, as well as placental trophoblast. These models are opening up new avenues to investigate the normal biology and pathology of the FRT. In this review, we discuss the advances, potential, and limitations of organoid cultures of the human FRT.Subject terms: Cell biology, Physiology, Diseases

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Monitoring aging-associated structural alterations in Caenorhabditis elegans striated muscles via polarization-dependent second-harmonic generation measurements

The in-vivo elucidation of the molecular mechanisms underlying muscles dysfunction due to aging via non-invasive label free imaging techniques is an important issue with high biological significance. In this study, polarization-dependent second-harmonic generation (PSHG) was used to evaluate structural alterations in the striated muscles during Caenorhabditis elegans lifespan. Young and old wild-type animals were irradiated. The obtained results showed that it was not feasible to detect differences in the structure of myosin that could be correlated with the aging of the worms, via the implementation of the classical, widely used, cylindrical symmetry model and the calculation of the SHG anisotropy values. A trigonal symmetry model improved the extracted results; however, the best outcome was originated from the application of a general model. Myosin structural modifications were monitored via the estimation of the difference in spectral phases derived from discrete Fourier transform analysis. Age classification of the nematodes was achieved by employing both models, proving the usefulness of the usage of PSHG microscopy as a potential diagnostic tool for the investigation of muscle diseases.