Differential gene expression in the calvarial and cortical bone of juvenile female mice.

Introduction: Both the calvarial and the cortical bones develop through intramembranous ossification, yet they have very different structures and functions. The calvaria enables the rapid while protected growth of the brain, whereas the cortical bone takes part in locomotion. Both types of bones undergo extensive modeling during embryonic and post-natal growth, while bone remodeling is the most dominant process in adults.

Demographic history and distinct selection signatures of two domestication genes in mungbean.

Domestication is the long and complex process underlying the evolution of crops, in which artificial directional selection transformed wild progenitors into the desired form, affecting genomic variation and leaving traces of selection at targeted loci. However, whether genes controlling important domestication traits follow the same evolutionary pattern expected under the standard selective sweep model remains unclear. With whole-genome resequencing of mungbean (Vigna radiata), we investigated this issue by resolving its global demographic history and targeted dissection of the molecular footprints of genes underlying 2 key traits representing different stages of domestication.

Energy Guided Diffusion for Generating Neurally Exciting Images.

In recent years, most exciting inputs (MEIs) synthesized from encoding models of neuronal activity have become an established method to study tuning properties of biological and artificial visual systems. However, as we move up the visual hierarchy, the complexity of neuronal computations increases. Consequently, it becomes more challenging to model neuronal activity, requiring more complex models.

Protein length distribution is remarkably uniform across the tree of life.

Background: In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species but has so far been scarcely studied.

Results: Here we evaluate this diversity by comparing protein length distribution across 2326 species (1688 bacteria, 153 archaea, and 485 eukaryotes).

networkGWAS: a network-based approach to discover genetic associations.

Motivation: While the search for associations between genetic markers and complex traits has led to the discovery of tens of thousands of trait-related genetic variants, the vast majority of these only explain a small fraction of the observed phenotypic variation. One possible strategy to overcome this while leveraging biological prior is to aggregate the effects of several genetic markers and to test entire genes, pathways or (sub)networks of genes for association to a phenotype. The latter, network-based genome-wide association studies, in particular suffer from a vast search space and an inherent multiple testing problem.

MAIRA: Protein-based Analysis of MinION Reads on a Laptop.

Third-generation sequencing technologies are being increasingly used in microbiome research and this has given rise to new challenges in computational microbiome analysis. Oxford Nanopore's MinION is a portable sequencer that streams data that can be basecalled on-the-fly. Here we give an introduction to the MAIRA software, which is designed to analyze MinION sequencing reads from a microbiome sample, as they are produced in real-time, on a laptop.

DIAMOND + MEGAN Microbiome Analysis.

Metagenomics is the study of microbiomes using DNA sequencing technologies. Basic computational tasks are to determine the taxonomic composition (who is out there?), the functional composition (what can they do?), and also to correlate changes of composition to changes in external parameters (how do they compare?). One approach to address these issues is to first align all sequences against a protein reference database such as NCBI-nr and to then perform taxonomic and functional binning of all sequences based on their alignments.

Inflammation inhibitory activity of green tea, soybean, and guava extracts during Sars-Cov-2 infection through TNF protein in cytokine storm.

Coronavirus disease is caused by the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) known as COVID-19. COVID-19 has caused the deaths of 6,541,936 people worldwide as of September 27th, 2022. SARS-CoV-2 severity is determined by a cytokine storm condition, in which the innate immune system creates an unregulated and excessive production of pro-inflammatory such IL-1, IL-6, NF Kappa B, and TNF alpha signaling molecules known as cytokines.

LFQ-Based Peptide and Protein Intensity Differential Expression Analysis.

Testing for significant differences in quantities at the protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a given proteomics quantification software, many tools and R packages exist to perform the final tasks of imputation, summarization, normalization, and statistical testing. To evaluate the effects of packages and settings in their substeps on the final list of significant proteins, we studied several packages on three public data sets with known expected protein fold changes.

The role of gene presence-absence variations on genetic incompatibility in Asian rice.

Genetic incompatibilities are widespread between species. However, it remains unclear whether they all originated after population divergence as suggested by the Bateson-Dobzhansky-Muller model, and if not, what is their prevalence and distribution within populations. The gene presence-absence variations (PAVs) provide an opportunity for investigating gene-gene incompatibility.

HLA antibody affinity determination: From HLA-specific monoclonal antibodies to donor HLA specific antibodies (DSA) in patient serum.

Organs transplanted across donor-specific HLA antibodies (DSA) are associated with a variety of clinical outcomes, including a high risk of acute kidney graft rejection. Unfortunately, the currently available assays to determine DSA characteristics are insufficient to clearly discriminate between potentially harmless and harmful DSA. To further explore the hazard potential of DSA, their concentration and binding strength to their natural target, using soluble HLA, may be informative.

UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis.

Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions, and an integration to the GNPS workflows Feature-Based Molecular Networking and Ion Identity Molecular Networking for downstream analysis.

Synthesis of Amino Acids Bearing Halodifluoromethyl Moieties and Their Application to p53-Derived Peptides Binding to Mdm2/Mdm4.

Introduction: Therapeutic peptides are a significant class of drugs in the treatment of a wide range of diseases. To enhance their properties, such as stability or binding affinity, they are usually chemically modified. This includes, among other techniques, cyclization of the peptide chain by bridging, modifications to the backbone, and incorporation of unnatural amino acids.

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning.

The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging to detect for taxonomically novel genomic data. Assembly errors can affect all downstream analyses of the assemblies.

Positive feedback induces switch between distributive and processive phosphorylation of Hog1.

Cellular decision making often builds on ultrasensitive MAPK pathways. The phosphorylation mechanism of MAP kinase has so far been described as either distributive or processive, with distributive mechanisms generating ultrasensitivity in theoretical analyses. However, the in vivo mechanism of MAP kinase phosphorylation and its activation dynamics remain unclear.

A Mixture Method for Robust Detection HCV Early Diagnosis Biomarker with ML Approach and Molecular Docking.

Given the substantial correlation between early diagnosis and prolonged patient survival in HCV patients, it is vital to identify a reliable and accessible biomarker. The purpose of this research was to identify accurate miRNA biomarkers to aid in the early diagnosis of HCV and to identify key target genes for anti-hepatic fibrosis therapeutics. The expression of 188 miRNAs in 42 HCV liver patients with different functional states and 23 normal livers were determined using RT-qPCR.

Tackling the Pangenome Dilemma Requires the Concerted Analysis of Multiple Population Genetic Processes.

The pangenome is the set of all genes present in a prokaryotic population. Most pangenomes contain many accessory genes of low and intermediate frequencies. Different population genetics processes contribute to the shape of these pangenomes, namely selection and fitness-independent processes such as gene transfer, gene loss, and migration.

Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory, and Metabolic Pathways.

Alteration of the status of the metabolic enzymes could be a probable way to regulate metabolic reprogramming, which is a critical cellular adaptation mechanism especially for cancer cells. Coordination among biological pathways, such as gene-regulatory, signaling, and metabolic pathways is crucial for regulating metabolic adaptation. Also, incorporation of resident microbial metabolic potential in human body can influence the interplay between the microbiome and the systemic or tissue metabolic environments.

Co-expression and clinical utility of AR-FL and AR splice variants AR-V3, AR-V7 and AR-V9 in prostate cancer.

Background: Androgen receptor (AR) splice variants (AR-Vs) have been discussed as a biomarker in prostate cancer (PC). However, some reports question the predictive property of AR-Vs. From a mechanistic perspective, the connection between AR full length (AR-FL) and AR-Vs is not fully understood.

Bursts in biosynthetic gene cluster transcription are accompanied by surges of natural compound production in the myxobacterium Sorangium sp.

A better understanding of the genetic regulation of the biosynthesis of microbial compounds could accelerate the discovery of new biologically active molecules and facilitate their production. To this end, we have investigated the time course of genome-wide transcription in the myxobacterium Sorangium sp. So ce836 in relation to its production of natural compounds.

Foundation model of neural activity predicts response to new stimulus types and anatomy.

The complexity of neural circuits makes it challenging to decipher the brain's algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain's computational objectives and neural coding. However, these models struggle to generalize beyond their training distribution, limiting their utility.

Bipartite invariance in mouse primary visual cortex.

A defining characteristic of intelligent systems, whether natural or artificial, is the ability to generalize and infer behaviorally relevant latent causes from high-dimensional sensory input, despite significant variations in the environment. To understand how brains achieve generalization, it is crucial to identify the features to which neurons respond selectively and invariantly. However, the high-dimensional nature of visual inputs, the non-linearity of information processing in the brain, and limited experimental time make it challenging to systematically characterize neuronal tuning and invariances, especially for natural stimuli.