Phenotypic Variability of LGMD 2C/R5 in a Genetically Homogenous Group of Bulgarian Muslim Roma.

Sarcoglycanopathies are among the most frequent and severe forms of autosomal recessive forms of limb-girdle muscular dystrophies (LGMDs) with childhood onset. Four subtypes are known: LGMDR3, LGMDR4, LGMDR5 and LGMDR6, which are caused, respectively, by mutations in the , SGCB, and genes. We present the clinical variability of LGMD 2C/R5 among a genetically homogeneous group of 57 patients, belonging to 35 pedigrees.

Prokaryote communities along a source-to-estuary river continuum in the Brazilian Atlantic Forest.

The activities of microbiomes in river sediments play an important role in sustaining ecosystem functions by driving many biogeochemical cycles. However, river ecosystems are frequently affected by anthropogenic activities, which may lead to microbial biodiversity loss and/or changes in ecosystem functions and related services. While parts of the Atlantic Forest biome stretching along much of the eastern coast of South America are protected by governmental conservation efforts, an estimated 89% of these areas in Brazil are under threat.

Patient subtyping analysis of baseline multi-omic data reveals distinct pre-immune states associated with antibody response to seasonal influenza vaccination.

Understanding the molecular mechanisms underpinning diverse vaccination responses is critical for developing efficient vaccines. Molecular subtyping can offer insights into heterogeneous nature of responses and aid in vaccine design. We analyzed multi-omic data from 62 haemagglutinin seasonal influenza vaccine recipients (2019-2020), including transcriptomics, proteomics, glycomics, and metabolomics data collected pre-vaccination.

Polysome collapse and RNA condensation fluidize the cytoplasm.

The cell interior is packed with macromolecules of mesoscale size, and this crowded milieu significantly influences cellular physiology. Cellular stress responses almost universally lead to inhibition of translation, resulting in polysome collapse and release of mRNA. The released mRNA molecules condense with RNA-binding proteins to form ribonucleoprotein (RNP) condensates known as processing bodies and stress granules.

Chemical genomic analysis reveals the interplay between iron chelation, zinc homeostasis, and retromer function in the bioactivity of an ethanol adduct of the feijoa fruit-derived ellagitannin vescalagin.

Nature has been a rich source of pharmaceutical compounds, producing 80% of our currently prescribed drugs. The feijoa plant, Acca sellowiana, is classified in the family Myrtaceae, native to South America, and currently grown worldwide to produce feijoa fruit. Feijoa is a rich source of bioactive compounds with anticancer, anti-inflammatory, antibacterial, and antifungal activities; however, the mechanism of action of these compounds is largely not known.

Host obesity impacts genetic variation in influenza A viral populations.

Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. Here, we investigated the impact of host obesity on influenza A virus (IAV) genetic variation using a diet-induced obesity ferret model and the A/Hong Kong/1073/1999 (H9N2) strain. Using a co-caging study design, we investigated the maintenance, generation, and transmission of intrahost IAV genetic variation by sequencing viral genomic RNA obtained from nasal wash samples over multiple days of infection.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses.

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination.

Structure-primed embedding on the transcription factor manifold enables transparent model architectures for gene regulatory network and latent activity inference.

Background: Modeling of gene regulatory networks (GRNs) is limited due to a lack of direct measurements of genome-wide transcription factor activity (TFA) making it difficult to separate covariance and regulatory interactions. Inference of regulatory interactions and TFA requires aggregation of complementary evidence. Estimating TFA explicitly is problematic as it disconnects GRN inference and TFA estimation and is unable to account for, for example, contextual transcription factor-transcription factor interactions, and other higher order features.

Multilevel gene expression changes in lineages containing adaptive copy number variants.

Copy-number variants (CNVs) are an important class of recurrent variants that mediate adaptive evolution. While CNVs can increase the relative fitness of the organism, they can also incur a cost. We previously evolved populations of over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the locus.

Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression.

Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms.

Copy number variation alters local and global mutational tolerance.

Copy number variants (CNVs), duplications and deletions of genomic sequences, contribute to evolutionary adaptation but can also confer deleterious effects and cause disease. Whereas the effects of amplifying individual genes or whole chromosomes (i.e.

Parallel proteomics and phosphoproteomics defines starvation signal specific processes in cell quiescence.

Cells arrest growth and enter a quiescent state upon nutrient deprivation. However, the molecular processes by which cells respond to different starvation signals to regulate exit from the cell division cycle and initiation of quiescence remains poorly understood. To study the role of protein expression and signaling in quiescence we combined temporal profiling of the proteome and phosphoproteome using stable isotope labeling with amino acids in cell culture (SILAC) in (budding yeast).

Host obesity impacts genetic variation in influenza A viral populations.

Obesity is a chronic health condition characterized by excess adiposity leading to a systemic increase in inflammation and dysregulation of metabolic hormones and immune cell populations. Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. Influenza A virus (IAV) is a highly infectious pathogen responsible for seasonal and pandemic influenza.

mRNA condensation fluidizes the cytoplasm.

The intracellular environment is packed with macromolecules of mesoscale size, and this crowded milieu significantly influences cell physiology. When exposed to stress, mRNAs released after translational arrest condense with RNA binding proteins, resulting in the formation of membraneless RNA protein (RNP) condensates known as processing bodies (P-bodies) and stress granules (SGs). However, the impact of the assembly of these condensates on the biophysical properties of the crowded cytoplasmic environment remains unclear.

Best Practices in Microbial Experimental Evolution: Using Reporters and Long-Read Sequencing to Identify Copy Number Variation in Experimental Evolution.

Copy number variants (CNVs), comprising gene amplifications and deletions, are a pervasive class of heritable variation. CNVs play a key role in rapid adaptation in both natural, and experimental, evolution. However, despite the advent of new DNA sequencing technologies, detection and quantification of CNVs in heterogeneous populations has remained challenging.

Increased mesoscale diffusivity in response to acute glucose starvation.

Macromolecular crowding is an important property of cells that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) and mRNPs ( -PP7) in response to acute glucose starvation.

Influenza A virus reassortment is strain dependent.

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange can occur when genome segments from distinct strains reassort in coinfected cells. Predicting potential genomic reassortment between influenza strains has been a long-standing goal.

Metagenomes from Soils along an Agricultural Transect in Ulster County, New York.

Many modern farming practices negatively impact ecosystems on the local and global scales. Here, we assessed the taxonomic structures of 48 soil microbial communities along an agricultural transect using 16S rRNA and internal transcribed spacer (ITS) amplicon sequencing. We further characterized the functional structures of a subsample of 12 microbiomes using whole-genome sequencing.

Structure primed embedding on the transcription factor manifold enables transparent model architectures for gene regulatory network and latent activity inference.

The modeling of gene regulatory networks (GRNs) is limited due to a lack of direct measurements of regulatory features in genome-wide screens. Most GRN inference methods are therefore forced to model relationships between regulatory genes and their targets with expression as a proxy for the upstream independent features, complicating validation and predictions produced by modeling frameworks. Separating covariance and regulatory influence requires aggregation of independent and complementary sets of evidence, such as transcription factor (TF) binding and target gene expression.

Increased mesoscale diffusivity in response to acute glucose starvation.

Macromolecular crowding is an important parameter that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) in response to acute glucose starvation.

Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes.

Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals.

Complex Genomic Rearrangements following Selection in a Glutamine-Limited Medium over Hundreds of Generations.

Large-scale genomic changes, including copy number variations (CNVs), are frequently observed in long-term evolution experiments (LTEEs). We have previously reported the detection of recurrent CNVs in Saccharomyces cerevisiae populations adapting to glutamine-limited conditions over hundreds of generations. Here, we present the whole-genome sequencing (WGS) assemblies of 7 LTEE strains and their ancestor.

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics.

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values.

High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0.

Motivation: Gene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.