The impact of inversions across 33,924 families with rare disease from a national genome sequencing project.

Detection of structural variants (SVs) is currently biased toward those that alter copy number. The relative contribution of inversions toward genetic disease is unclear. In this study, we analyzed genome sequencing data for 33,924 families with rare disease from the 100,000 Genomes Project. From a database hosting >500 million SVs, we focused on 351 genes where haploinsufficiency is a confirmed disease mechanism and identified 47 ultra-rare rearrangements that included an inversion (24 bp to 36.4 Mb, 20/47 de novo). Validation utilized a number of orthogonal approaches, including retrospective exome analysis. RNA-seq data supported the respective diagnoses for six participants. Phenotypic blending was apparent in four probands. Diagnostic odysseys were a common theme (>50 years for one individual), and targeted analysis for the specific gene had already been performed for 30% of these individuals but with no findings. We provide formal confirmation of a European founder origin for an intragenic MSH2 inversion. For two individuals with complex SVs involving the MECP2 mutational hotspot, ambiguous SV structures were resolved using long-read sequencing, influencing clinical interpretation. A de novo inversion of HOXD11-13 was uncovered in a family with Kantaputra-type mesomelic dysplasia. Lastly, a complex translocation disrupting APC and involving nine rearranged segments confirmed a clinical diagnosis for three family members and resolved a conundrum for a sibling with a single polyp. Overall, inversions play a small but notable role in rare disease, likely explaining the etiology in around 1/750 families across heterogeneous clinical cohorts.

MDSR-NMF: Multiple deconstruction single reconstruction deep neural network model for non-negative matrix factorization.

Dimension reduction is one of the most sought-after strategies to cope with high-dimensional ever-expanding datasets. To address this, a novel deep-learning architecture has been designed with multiple deconstruction and single reconstruction layers for non-negative matrix factorization aimed at low-rank approximation. This design ensures that the reconstructed input matrix has a unique pair of factor matrices. The two-stage approach, namely, pretraining and stacking, aids in the robustness of the architecture. The sigmoid function has been adjusted in such a way that fulfils the non-negativity criteria and also helps to alleviate the data-loss problem. Xavier initialization technique aids in the solution of the exploding or vanishing gradient problem. The objective function involves regularizer that ensures the best possible approximation of the input matrix. The superior performance of MDSR-NMF, over six well-known dimension reduction methods, has been demonstrated extensively using five datasets for classification and clustering. Computational complexity and convergence analysis have also been presented to establish the model.

Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal.

Introduction: Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space. Methods: We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex. Results: We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation. Conclusion: We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers.

Whole genome analysis of water buffalo and global cattle breeds highlights convergent signatures of domestication.

More people globally depend on the water buffalo than any other domesticated species, and as the most closely related domesticated species to cattle they can provide important insights into the shared evolutionary basis of domestication. Here, we sequence the genomes of 79 water buffalo across seven breeds and compare patterns of between breed selective sweeps with those seen for 294 cattle genomes representing 13 global breeds. The genomic regions under selection between cattle breeds significantly overlap regions linked to stature in human genetic studies, with a disproportionate number of these loci also shown to be under selection between water buffalo breeds. Investigation of potential functional variants in the water buffalo genome identifies a rare example of convergent domestication down to the same mutation having independently occurred and been selected for across domesticated species. Cross-species comparisons of recent selective sweeps can consequently help identify and refine important loci linked to domestication.

Genetic and genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep.

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield, and four mastitis-related traits (milk somatic cell count, California Mastitis Test score, total viable bacterial count in milk and clinical mastitis presence) were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism (SNP) array. We performed targeted genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis traits. Environmental factors appeared to favour both milk production and udder health. There were no overlapping of SNPs associated with mastitis resistance and milk yield in Chios sheep. Furthermore, four distinct Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations other than those previously identified to affect mastitis resistance. Five genes (DNAJA1, GHR, LYPLA1, NUP35 and OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of two of these genes (NUP35 and OXCT1) was enriched in immune tissues implying a potentially pleiotropic effect or likely role in milk production during udder infection, which needs to be further elucidated in future studies. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable.

Analysis of the DosR regulon genes to select cytotoxic T lymphocyte epitope specific vaccine candidates using a reverse vaccinology approach.

OBJECTIVE/BACKGROUND: There is an urgent need for a more effective vaccine against Mycobacterium tuberculosis (Mtb). Although CD4+ T cells play a central role in host immunity to Mtb, recent evidence suggests a critical role of CD8+ T cells in combating Mtb. In the present study, we have predicted HLA antigen class I binding peptides of DosR operon using an in-silico approach. This method is useful as an initial computational filtration of probable epitopes based on their binding ability and antigenicity. METHODS: CD8+ epitopes were predicted by software NetMHC 3.4 and BIMAS. Self-peptides were found and excluded by indigenously developed Perl script. Antigenicity of promiscuous peptides was predicted using a VaxiJen server. The top VaxiJen scoring antigenic peptides were docked to globally relevant HLA allele using CABS dock and Hex program. RESULTS: A total of 1436 overlapping nonamer peptides were generated which gave 46 promiscuous epitopes, 25 were predicted to be antigenic. Rv2627 epitope "SAFRPPLV" which gave the highest Vaxijen score of 1.9157 and showed binding to all the three HLA loci. The top VaxiJen scoring antigenic peptides were docked and had significant interactions with residues of the HLA class I molecule indicating them to be good cytotoxic T lymphocyte epitopes. CONCLUSION: Our study has generated several promiscuous antigenic peptides capable of binding to major histocompatibility complex class I with high affinity. These epitopes can become part of a postexposure multivalent subunit vaccine upon experimental validation.

Predicting promiscuous antigenic T cell epitopes of Mycobacterium tuberculosis mymA operon proteins binding to MHC Class I and Class II molecules.

Limited efficacy of Bacillus Calmette-Guérin vaccine has raised the need to explore other immunogenic candidates to develop an effective vaccine against Mycobacterium tuberculosis (Mtb). Both CD4+ and CD8+ T cells play a critical role in host immunity to Mtb. Infection of macrophages with Mtb results in upregulation of mymA operon genes thereby suggesting their importance as immune targets. In the present study, after exclusion of self-peptides mymA operon proteins of Mtb were analyzed in silico for the presence of Human Leukocyte Antigen (HLA) Class I and Class II binding peptides using Bioinformatics and molecular analysis section, NetMHC 3.4, ProPred and Immune epitope database software. Out of 56 promiscuous epitopes obtained, 41 epitopes were predicted to be antigenic for MHC Class I. In MHC Class II, out of 336 promiscuous epitopes obtained, 142 epitopes were predicted to be antigenic. The comparative bioinformatics analysis of mymA operon proteins found Rv3083 to be the best vaccine candidate. Molecular docking was performed with the most antigenic peptides of Rv3083 (LASGAASVV with alleles HLA-B51:01, HAATSGTLI with HLA-A02, IVTATGLNI and EKIHYGLKVNTA with HLA-DRB1_01:01) to study the structural basis for recognition of peptides by various HLA molecules. The software binding prediction was validated by the obtained molecular docking score of peptide-HLA complex. These peptides can be further investigated for their immunological relevance in patients of tuberculosis using major histocompatibility complex tetramer approach.

BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts.

BACKGROUND: Tuberculosis (TB) is the second leading cause of death from a single infectious organism, demanding attention towards discovery of novel anti-tubercular compounds. Natural products or their derivatives have provided more than 50% of all existing drugs, offering a chemically diverse space for discovery of novel drugs. DESCRIPTION: BioPhytMol has been designed to systematically curate and analyze the anti-mycobacterial natural product chemical space. BioPhytMol is developed as a drug-discovery community resource with anti-mycobacterial phytomolecules and plant extracts. Currently, it holds 2582 entries including 188 plant families (692 genera and 808 species) from global flora, manually curated from literature. In total, there are 633 phytomolecules (with structures) curated against 25 target mycobacteria. Multiple analysis approaches have been used to prioritize the library for drug-like compounds, for both whole cell screening and target-based approaches. In order to represent the multidimensional data on chemical diversity, physiochemical properties and biological activity data of the compound library, novel approaches such as the use of circular graphs have been employed. CONCLUSION: BioPhytMol has been designed to systematically represent and search for anti-mycobacterial phytochemical information. Extensive compound analyses can also be performed through web-application for prioritizing drug-like compounds. The resource is freely available online at http://ab-openlab.csir.res.in/biophytmol/. Graphical AbstractBioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts generated using Crowdsourcing. The platform comprises of manually curated data on antimycobacterial natural products along with tools to perform structure similarity and visualization. The platform allows for prioritization of drug like natural products for antimycobacterial drug discovery.

Extended C-terminus and length of the linker connecting the G-domains are species-specific variations in the EngA family of GTPases.

EngA is an essential protein involved in ribosome biogenesis. It is an unique GTPase, possessing two consecutive G-domains. Using sequence and phylogenetic analysis, we found two intriguing variants among EngA homologues - one with a shorter linker joining the G-domains and another with a longer linker, which additionally possesses an extended C-terminus. Interestingly, while the former variant is mainly restricted to firmicutes, the latter is found in nonfirmicutes. Chimeric proteins with interchanged linkers and extensions were generated to gauge the importance of these elements. Ribosome interaction experiments employing the chimeric proteins suggest that a precise combination of the linker and C-terminal extension are important features regulating EngA ribosome interactions in a variant-specific manner.