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Single nucleotide polymorphism (SNP)-heritability estimation is an important topic in several research fields, including animal, plant and human genetics, as well as in ecology. Linear mixed model estimation of SNP-heritability uses the structures of genomic relationships between individuals, which is constructed from genome-wide sets of SNP-markers that are generally weighted equally in their contributions. Proposed methods to handle dependence between SNPs include, “thinning” the marker set by linkage disequilibrium (LD)-pruning, the use of haplotype-tagging of SNPs, and LD-weighting of the SNP-contributions. For improved estimation, we propose a new conceptual framework for genomic relationship matrix, in which Mahalanobis distance-based LD-correction is used in a linear mixed model estimation of SNP-heritability. The superiority of the presented method is illustrated and compared to mixed-model analyses using a VanRaden genomic relationship matrix, a matrix used by GCTA and a matrix employing LD-weighting (as implemented in the LDAK software) in simulated (using real human, rice and cattle genotypes) and real (maize, rice and mice) datasets. Despite of the computational difficulties, our results suggest that by using the proposed method one can improve the accuracy of SNP-heritability estimates in datasets with high LD.

Flowering time is a well-known complex trait in crops and is influenced by many interacting genes. In this study, Mathew et al. identify two-way and....Gene-by-gene interactions, also known as epistasis, regulate many complex traits in different species. With the availability of low-cost genotyping it is now possible to study epistasis on a genome-wide scale. However, identifying genome-wide epistasis is a high-dimensional multiple regression problem and needs the application of dimensionality reduction techniques. Flowering Time (FT) in crops is a complex trait that is known to be influenced by many interacting genes and pathways in various crops. In this study, we successfully apply Sure Independence Screening (SIS) for dimensionality reduction to identify two-way and three-way epistasis for the FT trait in a Multiparent Advanced Generation Inter-Cross (MAGIC) barley population using the Bayesian multilocus model. The MAGIC barley population was generated from intercrossing among eight parental lines and thus, offered greater genetic diversity to detect higher-order epistatic interactions. Our results suggest that SIS is an efficient dimensionality reduction approach to detect high-order interactions in a Bayesian multilocus model. We also observe that many of our findings (genomic regions with main or higher-order epistatic effects) overlap with known candidate genes that have been already reported in barley and closely related species for the FT trait.

Cellular biomolecular complexes including protein–protein, protein–RNA, and protein–DNA interactions regulate and execute most biological functions. In particular in brain, protein–protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell–cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte–neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.

This paper extends the concept of topology on a point set to a topology of an arbitrary rough universe. The concept of I- rough topology on an arbitrary rough universe is introduced and some topological properties of the resultant I-rough topological spaces are studied. Also a comparison study is carried out between topological spaces and I-rough topological spaces.

Unambiguous analysis of hemoglobin variants is critical in the diagnosis of hemoglobinopathies. In diagnostic laboratories, alkaline gel electrophoresis and automated HPLC are used in identifying variants. In specific instances, comigration of hemoglobin variant bands in gel and coelution of different variants or elution of variants with unmatched library information in HPLC can result in ambiguities in interpretation. Hemoglobin variants mostly arise from point mutations leading to very high sequence homology between normal and variant hemoglobin. In addition, unavailability of a variant database compatible with proteomics data analysis software makes mass spectrometry based variant analysis very challenging. In the present study, we standardized a nanoLC–MS based method for variant analysis to achieve substantially high sequence coverage. We developed three hemoglobin variant databases, specific to three different proteolytic enzymes, compatible with proteomics search engine software. The above nanoLC–MS method and the compatibility of the customized databases were validated by analysis of a sickle hemoglobin variant. Six other hemoglobin variants were characterized wherein diagnosis reports based on conventional tools were ambiguous. The novelty of our method lies in its simplicity and accuracy of the analysis with minimal manual intervention. The presently described method may be used in the future for the routine hemoglobin variant diagnosis.

The scintillation has been monitored at Rajkot using the VHF (250 MHz) signals from geostationary satellite FLEETSAT at 73°E since 1986. The paper describes the observed characteristics of scintillation such as its noctural occurrence pattern, seasonal, geomagnetic and solar activity dependence. Employing digital data acquisition and power spectral analysis techniques, quantitative parameters such as the scintillation index S4, upper roll of frequency and spectral slope are derived and discussed in terms of the parameters of causative plasma irregularities. Spaced receiver technique and cross correlation analysis is employed to determined the characteristic scale size and velocity of the irregularities. A comprehensive study of the above parameters throws some light on the possible plasma instability mechanism responsible for the generation of those irregularities. The effects of the irregularities in terms of signal statistics such as cumulative amplitude distribution functions, fade rate, message reliability and bit error on a typical modern communication system are computed and presented.

Using simultaneous long-term observations of ionospheric scintillation at equator and anomaly crest region in the same longitude (Indian) zone comparative features of scintillation occurrence are brought out. The salient features are: (a) predominantly pre-midnight occurrence of scintillation at equator during winter and equinox seasons, (b) increase of pre-midnight scintillation occurrence with solar activity (c) shifting of occurrence peak during summer from post-midnight in low to pre-midnight in high solar activity periods (d) similarity of scintillation behaviour at these locations during winter and equinoxes but dissimilarity during summer. The solar activity response and magnetic effects indicate that the scintillations at the anomaly crest region in winter and equinox, particularly during high solar activity periods, are of equatorial origin while the summer events may be of local or mid-latitude origin.