Genetic adaptation despite high gene flow in a range-expanding population.

Signals of natural selection can be quickly eroded in high gene flow systems, curtailing efforts to understand how and when genetic adaptation occurs in the ocean. This long-standing, unresolved topic in ecology and evolution has renewed importance because changing environmental conditions are driving range expansions that may necessitate rapid evolutionary responses. One example occurs in Kellet's whelk (Kelletia kelletii), a common subtidal gastropod with an ~40- to 60-day pelagic larval duration that expanded their biogeographic range northwards in the 1970s by over 300 km.

The relationship between sarcopenic obesity and changes in quadriceps muscle thickness and echo intensity in patients with stroke.

Background: Research findings on skeletal muscle degeneration in post-stroke sarcopenic obesity are limited. Thus, this study aimed to investigate the association between post-stroke sarcopenic obesity and quantitative and qualitative changes in skeletal muscles.

Methods: This was a cross-sectional study conducted on patients with stroke admitted to the convalescent rehabilitation ward.

The Validity of Quadriceps Muscle Thickness as a Nutritional Risk Indicator in Patients with Stroke.

This study aimed to investigate whether quadriceps muscle thickness (QMT) is useful for nutritional assessment in patients with stroke. This was a retrospective cohort study. Nutritional risk was assessed using the Geriatric Nutritional Risk Index (GNRI), with GNRI < 92 indicating a risk of malnutrition and GNRI ≥ 92 indicating normal conditions.

Distance-AF: Modifying Predicted Protein Structure Models by Alphafold2 with User-Specified Distance Constraints.

The three-dimensional structure of a protein plays a fundamental role in determining its function and has an essential impact on understanding biological processes. Despite significant progress in protein structure prediction, such as AlphaFold2, challenges remain on those hard targets that Alphafold2 does not often perform well due to the complex folding of protein and a large number of possible conformations. Here we present a modified version of the AlphaFold2, called Distance-AF, which aims to improve the performance of AlphaFold2 by including distance constraints as input information.

Improved Peptide Docking with Privileged Knowledge Distillation using Deep Learning.

Protein-peptide interactions play a key role in biological processes. Understanding the interactions that occur within a receptor-peptide complex can help in discovering and altering their biological functions. Various computational methods for modeling the structures of receptor-peptide complexes have been developed.

Domain-PFP allows protein function prediction using function-aware domain embedding representations.

Domains are functional and structural units of proteins that govern various biological functions performed by the proteins. Therefore, the characterization of domains in a protein can serve as a proper functional representation of proteins. Here, we employ a self-supervised protocol to derive functionally consistent representations for domains by learning domain-Gene Ontology (GO) co-occurrences and associations.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target.

NuFold: A Novel Tertiary RNA Structure Prediction Method Using Deep Learning with Flexible Nucleobase Center Representation.

RNA is not only playing a core role in the central dogma as mRNA between DNA and protein, but also many non-coding RNAs have been discovered to have unique and diverse biological functions. As genome sequences become increasingly available and our knowledge of RNA sequences grows, the study of RNA's structure and function has become more demanding. However, experimental determination of three-dimensional RNA structures is both costly and time-consuming, resulting in a substantial disparity between RNA sequence data and structural insights.

Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations.

Domains are functional and structural units of proteins that govern various biological functions performed by the proteins. Therefore, the characterization of domains in a protein can serve as a proper functional representation of proteins. Here, we employ a self-supervised protocol to derive functionally consistent representations for domains by learning domain-Gene Ontology (GO) co-occurrences and associations.

COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations.

Gene coexpression is synchronization of gene expression across many cellular and environmental conditions and is widely used to infer the biological function of genes. Gene coexpression information is complex, comprising a complete graph of all genes in the genome, and requires appropriate visualization and analysis tools. Since its initial release in 2007, the animal gene expression database COXPRESdb (https://coxpresdb.

ContactPFP: Protein function prediction using predicted contact information.

Computational function prediction is one of the most important problems in bioinformatics as elucidating the function of genes is a central task in molecular biology and genomics. Most of the existing function prediction methods use protein sequences as the primary source of input information because the sequence is the most available information for query proteins. There are attempts to consider other attributes of query proteins.

Real-time structure search and structure classification for AlphaFold protein models.

Last year saw a breakthrough in protein structure prediction, where the AlphaFold2 method showed a substantial improvement in the modeling accuracy. Following the software release of AlphaFold2, predicted structures by AlphaFold2 for proteins in 21 species were made publicly available via the AlphaFold Database. Here, to facilitate structural analysis and application of AlphaFold2 models, we provide the infrastructure, 3D-AF-Surfer, which allows real-time structure-based search for the AlphaFold2 models.

ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components.

ATTED-II (https://atted.jp) is a gene coexpression database for nine plant species based on publicly available RNAseq and microarray data. One of the challenges in constructing condition-independent coexpression data based on publicly available gene expression data is managing the inherent sampling bias.

Analyzing effect of quadruple multiple sequence alignments on deep learning based protein inter-residue distance prediction.

Protein 3D structure prediction has advanced significantly in recent years due to improving contact prediction accuracy. This improvement has been largely due to deep learning approaches that predict inter-residue contacts and, more recently, distances using multiple sequence alignments (MSAs). In this work we present AttentiveDist, a novel approach that uses different MSAs generated with different E-values in a single model to increase the co-evolutionary information provided to the model.

Protein contact map refinement for improving structure prediction using generative adversarial networks.

Motivation: Protein structure prediction remains as one of the most important problems in computational biology and biophysics. In the past few years, protein residue-residue contact prediction has undergone substantial improvement, which has made it a critical driving force for successful protein structure prediction. Boosting the accuracy of contact predictions has, therefore, become the forefront of protein structure prediction.

A novel circular ssDNA virus of the phylum Cressdnaviricota discovered in metagenomic data from otter clams (Lutraria rhynchaena).

In this study, we present an analysis of metagenome sequences obtained from a filtrate of a siphon tissue homogenate of otter clams (Lutraria rhynchaena) with swollen-siphon disease. The viral signal was mined from the metagenomic data, and a novel circular ssDNA virus was identified. Genomic features and phylogenetic analysis showed that the virus belongs to the phylum Cressdnaviricota, which consists of viruses with circular, single-stranded DNA (ssDNA) genomes.

MAINMASTseg: Automated Map Segmentation Method for Cryo-EM Density Maps with Symmetry.

For structural interpretation of cryo-electron microscopy (cryo-EM) density maps that contain multiple chains, map segmentation is an important step. If a map is segmented accurately into regions of individual protein components, the structure of each protein can be separately modeled using an existing modeling tool. Here, we developed new software, MAINMASTseg, for segmenting maps with symmetry.

Metagenome Sequences from the Environment of Diseased Otter Clams, Lutraria rhynchaena, from a Farm in Vietnam.

Otter clam farming in Vietnam has recently encountered difficulties due to swollen-siphon disease. Here, we report the metagenome sequences of microorganisms extracted from the siphon tissue of infected otter clams. The data comprised bacterial and viral sequences which likely include those derived from the disease-causing agent.

COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference.

The advent of RNA-sequencing and microarray technologies has led to rapid growth of transcriptome data generated for a wide range of organisms, under various cellular, organ and individual conditions. Since the number of possible combinations of intercellular and extracellular conditions is almost unlimited, cataloging all transcriptome conditions would be an immeasurable challenge. Gene coexpression refers to the similarity of gene expression patterns under various conditions, such as disease states, tissue types, and developmental stages.

ATTED-II in 2018: A Plant Coexpression Database Based on Investigation of the Statistical Property of the Mutual Rank Index.

ATTED-II (http://atted.jp) is a coexpression database for plant species to aid in the discovery of relationships of unknown genes within a species. As an advanced coexpression analysis method, multispecies comparisons have the potential to detect alterations in gene relationships within an evolutionary context.