Heritability estimates from genomewide relatedness matrices in wild populations: Application to a passerine,using a small sample size

Genomic developments have empowered the investigation of heritability in wild populations directly from genomewide relatedness matrices (GRM). Such GRM‐based approaches can in particular be used to improve or substitute approaches based on social pedigree (PED‐social). However, measuring heritability from GRM in the wild has not been widely applied yet, especially using small samples and in nonmodel species. Here, we estimated heritability for four quantitative traits (tarsus length, wing length, bill length and body mass), using PED‐social, a pedigree corrected by genetic data (PED‐corrected) and a GRM from a small sample (n = 494) of blue tits from natural populations in Corsica genotyped at nearly 50,000 filtered SNPs derived from RAD‐seq. We also measured genetic correlations among traits, and we performed chromosome partitioning. Heritability estimates were slightly higher when using GRM compared to PED‐social, and PED‐corrected yielded intermediate values, suggesting a minor underestimation of heritability in PED‐social due to incorrect pedigree links, including extra‐pair paternity, and to lower information content than the GRM. Genetic correlations among traits were similar between PED‐social and GRM but credible intervals were very large in both cases, suggesting a lack of power for this small data set. Although a positive linear relationship was found between the number of genes per chromosome and the chromosome heritability for tarsus length, chromosome partitioning similarly showed a lack of power for the three other traits. We discuss the usefulness and limitations of the quantitative genetic inferences based on genomic data in small samples from wild populations.     

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q ² value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r ² value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r ² value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis.     

Association mapping of cold‐induced sweetening in potato using historical phenotypic data

In this study, historical phenotypic data from a potato breeding programme were used with an association mapping approach to identify alleles of candidate genes associated with cold‐induced sweetening of potato. Molecular marker analysis was used to determine allelic variation of candidate genes potentially involved in cold‐induced sweetening. Variations in the UDP‐glucose pyrophosphorylase (UGPase, EC 2.7.7.9) and apoplastic invertase genes (EC 3.2.1.26) were significantly associated with cold‐induced sweetening, and a possible interaction of apoplastic invertase and apoplastic invertase inhibitor was identified. This demonstrates that breeding programme phenotypic data collected over multiple years and environments can be used successfully with pedigree information for association mapping. It also confirms that the UGPase and apoplastic invertase markers are transferable across breeding programmes with distinct germplasm.     

A Framework for Development and Communication of Absolute Environmental Sustainability Assessment Methods

An absolute environmental sustainability assessment (AESA) addresses whether a production or consumption activity can be considered environmentally sustainable in an absolute sense. This involves a comparison of its environmental pressure to its allocated environmental carrying capacity. AESA methods have been developed in multiple academic fields, each using their own set of concepts and terms with little communication across the fields. A recent growing interest in using AESA methods for decision support calls for a better common understanding of the constituents of an AESA method and how it can be communicated to scientific peers and to potential users. With this aim, we develop a framework for AESA methods, composed of a succession of four assessment steps and involving six methodological choices that must be made by the method developer or the user. We then use the framework to analyze and compare five selected AESA methods that focus on the release of phosphorus and nitrogen to the environment. In this manner, we show that the framework is able to systematically differentiate AESA methods that initially appear to be similar. Intended users of the framework include (1) method developers communicating new AESA methods to academic peers or potential method users and (2) researchers comparing a group of existing AESA methods and communicating their differences to their peers and to potential users looking for guidance on method selection.     

«Salivaomics» of Different Molecular Biological Subtypes of Breast Cancer

The aim of the study was to determine the metabolic characteristics of saliva depending on the molecular biological subtype of breast cancer, as well as depending on the expression levels of HER2, estrogen receptors (ER), and progesterone receptors (PR). The study included 487 patients with morphologically verified breast cancer and 298 volunteers without breast pathologies. Saliva samples were obtained from all patients strictly before the start of treatment and the values of 42 biochemical indicators were determined. It has been established that the saliva of healthy volunteers and patients with various molecular biological subtypes of breast cancer differs in 12 biochemical indicators: concentrations of protein, urea, nitric oxide, malondialdehyde, total amino acid content, and activity of lactate dehydrogenase, alkaline phosphatase, gamma-glutamyltransferase, catalase, amylase, superoxide dismutase, and peroxidases. The saliva composition of patients with basal-like breast cancer differs from other subtypes in terms of the maximum number of indicators. Changes in biochemical indicators indicated an increase in the processes of lipid peroxidation and endogenous intoxication and a weakening of antioxidant protection, which correlates with the severity of the disease and the least favorable prognosis for this subtype of breast cancer. An analysis was made of the individual contribution of the expression level of HER2, estrogen, and progesterone receptors to changes in the biochemical composition of saliva. The HER2 (−)/HER2 (+) group, which should be considered as a single group, as well as ER-positive breast cancer, differ statistically significantly from the control group. For ER/PR-positive breast cancer, a more favorable ratio of saliva biochemical indicators was also noted compared to ER/PR-negative breast cancer.     

Integrated computational approaches to screen gene expression data to determine key genes and therapeutic targets for type-2 diabetes mellitus

There is a rapid rise in cases of Type-2-diabetes mellitus (T2DM) globally, irrespective of the geography, ethnicity or any other variable factors. The molecular mechanisms that could cause the condition of T2DM need to be more thoroughly analysed to understand the clinical manifestations and to derive better therapeutic regimes. Tools in bioinformatics are used to trace out key gene elements and to identify the key causative gene elements and their possible therapeutic agents. Microarray datasets were retrieved from the Gene expression omnibus database and studied using R to derive different expressed gene (DEG) elements. With the comparison of the expressed genes with disease specific genes in DisGeNET, the final annotated genes were taken for analysis. Gene Ontology studies, Protein–protein interaction (PPI), Co-expression analysis, Gene-drug interactions were performed to scale down the hub genes and to identify the novelty across the genes analysed so far. In vivo and invitro analysis of key genes and the trace of interaction pathway is crucial to better understand the unique outcomes from the novel genes, forming the basis to understand the pathway that ends up causing T2DM. Afterwards, docking was executed enabling recognition of interacting residues involved in inhibition. The complex CCL5-265 and CD8A-40585 thus docked showed best results as is evident from its PCA analysis and MMGBSA calculation. There is now scope for deriving candidate drugs that could possibly detect personalized therapies for T2DM.     

Probing the interaction between p53 and the bacterial protein azurin by single molecule force spectroscopy

p53 is a human tumour suppressor which regulates multiple cellular processes, including cell growth, genomic stability and cell death. Recent works have demonstrated the bacterial redox protein azurin to enter cancer cells and induce apoptosis through p53 stabilization, resulting in a tumour growth regression. Azurin has been shown to bind p53 although many details of the complex formed by these two proteins are still poorly characterized. Here, we get insight into the kinetics of this complex formation, by exploring the interaction between p53 and azurin in their environment by single molecule force spectroscopy. To this aim, azurin has been linked to the atomic force microscope tip, whereas p53 has been immobilized onto a gold substrate. Therefore, by performing force-distance cycles we have detected specific recognition events between p53 and azurin, displaying unbinding forces of around 70 pN for an applied loading rate of 3 nN s(-1). The specificity of these events has been assessed by the significant reduction of their frequency observed after blocking the p53 sample by an azurin solution. Moreover, by measuring the rupture force as a function of the loading rate we have determined the dissociation rate constant of this complex to be approximately 0.1 s(-1). Our findings are here discussed in connection with results obtained in bulk experiments, with the aim of clarifying some molecular details of the p53-azurin complex that may help designing new anticancer strategy.     

Sequence and structure space of RNA-binding peptides

Studies of RNA-binding peptides, and recent combinatorial library experiments in particular, have demonstrated that diverse peptide sequences and structures can be used to recognize specific RNA sites. The identification of large numbers of sequences capable of binding to a particular site has provided extensive phylogenetic information used to deduce basic principles of recognition. The high frequency at which RNA-binding peptides are found in large sequence libraries suggests plausible routes to evolve sequence-specific binders, facilitating the design of new binding molecules and perhaps reflecting characteristics of natural evolution.     

Modulation of immunogenicity of poly(sarcosine) displayed on various nanoparticle surfaces due to different physical properties

Poly(sarcosine) displayed on polymeric micelle is reported to trigger a T cell‐independent type2 reaction with B1a cells in the mice to produce IgM and IgG3 antibodies. In addition to polymeric micelle, three kinds of vesicles displaying poly(sarcosine) on surface were prepared here to evaluate the amounts and avidities of IgM and IgG3, which were produced in mice, to correlate them with physical properties of the molecular assemblies. The largest amount of IgM was produced after twice administrations of a polymeric micelle of 35 nm diameter ( G1 ). On the other hand, the production amount of IgG3 became the largest after twice administrations of G3 (vesicle of 229 nm diameter) or G4 (vesicle of 85 nm diameter). The augmented avidity of IgG3 after the twice administrations compared with that at the single administration was the highest with G3 . These differences in immune responses are discussed in terms of surface density of poly(sarcosine) chains, nanoparticle size, hydrophobic component of poly(L‐lactic acid) or (Leu‐ or Val‐Aib)_n, and membrane elasticity of the nanoparticles. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.