SEARCH · bioRxiv Science

Results for “molecular biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources

bioRxiv2026

Engineering and characterisation of AAVS1 FRT cell lines for inducible and dose-dependent gene expression

Investigating biological function with high reproducibility requires the generation of stable cell lines that offer precise and inducible transgene expression. However, traditional methods often suffer from the limitations of random genomic integration, including unpredictable expression levels, leaky basal activity, and disruption of endogenous loci. To address these challenges, we engineered a versatile RPE1 cell line by integrating a TetOn3G-FRT cassette into the AAVS1 safe-harbour locus using CRISPR/Cas9(D10A) nickase. This platform utilises the Flp-FRT recombination system to facilitate rapid, site-specific "plug-and-play" insertion of transgenes, combined with the Tet-On 3G system for tight, dose-dependent expression control. The resulting RPE1 AAVS1 FRT8 line enables highly consistent transgene induction across independent clones, behaving as a monoclonal population. We highlight the importance of rigorous cell line characterisation through a multi-omics approach. Whole genome sequencing identified precise heterozygous integration at the target locus and de novo genomic duplications on other chromosomes. By integrating WGS with high-resolution proteomics and cell cycle analysis, we confirmed that these alterations did not significantly perturb cellular homeostasis or phenotypic fitness. This work establishes a robust and reliable platform for the efficient generation of inducible AAVS1 FRT stable cell lines, facilitating reproducible research in modern molecular biology.

bioengineering↗

bioRxiv2016

Transcriptomic analysis of diplomonad parasites reveals a trans-spliced intron in a helicase gene in Giardia

Gene expression is the central preoccupation of molecular biology, thus newly discovered facets of gene expression are of great interest. Recently, ourselves and others reported that in the diplomonad protist Giardia lamblia, the coding regions of several mRNAs are produced by ligation of independent RNA species expressed from distinct genomic loci. Such trans-splicing of introns was found to affect nearly as many genes in this organism as does classical cis-splicing of introns. These findings raised questions about the incidence of intron trans-splicing both across the G. lamblia transcriptome and across diplomonad diversity, however a dearth of transcriptomic data at the time prohibited systematic study of these questions. Here, I leverage newly available transcriptomic data from G. lamblia and the related diplomonad Spironucleus salmonicida to search for trans-spliced introns. My computational pipeline recovers all four previously reported trans-spliced introns in G. lamblia, suggesting good sensitivity. Scrutiny of thousands of potential cases revealed only a single additional trans-spliced intron in G. lamblia, in the p68 helicase gene, and no cases in S. salmonicida. The p68 intron differs from the previously reported trans-spliced introns in its high degree of streamlining: the core features of G. lamblia trans-spliced introns closely packed together, revealing striking efficiency in the implementation of a seemingly inherently inefficient molecular mechanism. These results serve to circumscribe the role of trans-splicing both in terms of genes effected and taxonomically. Future work should focus on the molecular mechanisms, evolutionary origins and phenotypic implications of this intriguing phenomenon.

Genomics↗

bioRxiv2024

Bridging biomolecular modalities for knowledge transfer in bio-language models

In biology, messenger RNA (mRNA) plays a crucial role in gene expression and protein synthesis. Accurate predictive modeling of mRNA properties can greatly enhance our understanding and manipulation of biological processes, leading to advancements in medical and biotechnological applications. Utilizing bio-language foundation models allows for leveraging large-scale pretrained knowledge, which can significantly improve the efficiency and accuracy of these predictions. However, mRNA specific foundation models are notably limited posing challenges for efficient predictive modeling in mRNA-focused tasks. In contrast, DNA and protein modalities have numerous general-purpose foundation models trained on billions of sequences. This paper explores the potential for adaptation of existing DNA and protein bio-language models for mRNA-focused tasks. Through experiments using various mRNA datasets curated from both public domain and internal proprietary database, we demonstrate that pre-trained DNA and protein models can be effectively transferred for mRNA-focused tasks using various adaptation techniques such as probing, full-rank, and low-rank finetuning. In addition, we identify key factors that influence successful adaptation, offering guidelines on when general-purpose DNA and protein models are likely to perform well for mRNA-focused tasks. We further assess the impact of model size on adaptation efficacy, finding that medium-scale models often outperform larger ones for cross-modal knowledge transfer. We conclude that by leveraging the interconnectedness of DNA, mRNA, and proteins, as outlined by the central dogma of molecular biology, the knowledge in foundation models can be effectively transferred across modalities, significantly enhancing the repertoire of computational tools available for mRNA analysis.

bioinformatics↗

bioRxiv2023

Translation in a Box: Orthogonal Evolution in the Saccharomyces cerevisiae Mitochondrion

The ability to re-engineer and creatively evolve the translation system (TS) would allow invention of new coded polymers by altering the amino acid sidechain inventory and by shifting the polypeptide backbone into new chemical spaces. Unfortunately, the TS is difficult to manipulate and is more constrained over evolution than any other biological system. An orthogonal TS, running in parallel to the primary TS within a given host cell, would release constraints and allow TS manipulation. A fully orthogonal TS requires dedicated rRNAs, rProteins, aminoacyl-tRNA synthetases, and initiation and termination factors, none of which interact with the primary TS. The S. cerevisiae mitochondrial TS is fully orthogonal to the cytosolic TS. Mito-rRNAs, mito- rProteins, mito-tRNAs, mito-aminoacyl tRNA synthetases, and mito-translation factors are distinct from, physically separated from, and functionally independent of their cytosolic counterparts. Here, the S. cerevisiae mitochondrial translation system was subjected to various stresses including antibiotics, mutagenesis and truncation of mito-rProteins, or wholesale replacement of mito-rProteins. Directed evolution of these stressed systems was facilitated by controlled transitions between fermentation and respiration, by changing the carbon source in the growth medium; the dependence of S. cerevisiae survival on mitochondrial translation can be toggled on and off. Specific recreation of the resulting mutations recapitulate the evolved phenotypes. The method developed here appears to be a general approach for discovering functional dependencies. Suppressor mutations reveal functional dependencies within the S. cerevisiae mitochondrial TS. For example proteins Rrg9 or Mrx1 interact with the mito-TS and have critical role in its function. The combined results indicate that the S. cerevisiae mitochondrial TS can be engineered and evolved in isolation of the cytosolic TS. SignificanceThe Central Dogma of Molecular Biology rules life on Earth. Information flows from DNA to mRNA to protein. In the last step of the Central Dogma, the translation system decodes mRNA and produces coded proteins by linking amino acids into polymers. Engineering and evolving the translation system could permits full technical control over this process and could lead to the generation of novel polymers. Here, we use the mitochondrial translation system in the budding yeast Saccharomyces cerevisiae for directed evolution of translation. We modify and evolve the translation system both directly and indirectly using antibiotics and gene editing tools and then measure resulting functionality. Our results show this secondary translation system inside S. cerevisiae mitochondria can be used as an approach for translation engineering.

synthetic biology↗

bioRxiv2020

Virus-mediated transient expression techniques enable genetic modification of Alopecurus myosuroides

Even though considerable progress has been made in weed ecology, weed molecular biology has been hindered by an inability to genetically manipulate weeds. Genetic manipulation is essential to demonstrate a causative relationship between genotype and phenotype. Herein we demonstrate that virus-mediated transient expression techniques developed for other monocots can be used in black-grass (Alopecurus myosuroides) for loss- and gain-of-function studies. We not only use virus induced gene silencing (VIGS) to create the black-grass exhibiting reduced PHYTOENE DESATURASE expression and virus-mediated overexpression (VOX) to drive GREEN FLUORESCENT PROTEIN, we demonstrate these techniques are applicable to testing hypotheses related to herbicide resistance in black-grass. We use VIGS to demonstrate that AmGSTF1 is necessary for the resistant biotype Peldon to survive fenoxaprop application and show the heterologous expression of the bialaphos resistance gene with VOX is sufficient to confer resistance to an otherwise lethal dose of glufosinate. Black-grass is the most problematic weed for winter-cereal farmers in the UK and Western Europe as it has rapidly evolved adaptions that allow it to effectively avoid current integrated weed management practices. Black-grass also reduces yields and therefore directly threatens food security and productivity. Novel disruptive technologies which mitigate resistance evolution and enable better control over this pernicious weed are therefore required. These virus-mediated protocols offer a step change in our ability to alter genes of interest under controlled laboratory conditions and therefore to gain a molecular-level understanding of how black-grass can survive in the agri-environment. One Sentence SummaryVirus-mediated transient expression techniques create loss- and gain-of-function mutations in black-grass and show causation between specific genotypes and measurable changes in herbicide resistance.

genetics↗

bioRxiv2016

Thanatotranscriptome: genes actively expressed after organismal death

A continuing enigma in the study of biological systems is what happens to highly ordered structures, far from equilibrium, when their regulatory systems suddenly become disabled. In life, genetic and epigenetic networks precisely coordinate the expression of genes -- but in death, it is not known if gene expression diminishes gradually or abruptly stops or if specific genes are involved. We investigated the unwinding of the clock by identifying upregulated genes, assessing their functions, and comparing their transcriptional profiles through postmortem time in two species, mouse and zebrafish. We found transcriptional abundance profiles of 1,063 genes were significantly changed after death of healthy adult animals in a time series spanning from life to 48 or 96 h postmortem. Ordination plots revealed non-random patterns in profiles by time. While most thanatotranscriptome (thanatos-, Greek defn. death) transcript levels increased within 0.5 h postmortem, some increased only at 24 and 48 h. Functional characterization of the most abundant transcripts revealed the following categories: stress, immunity, inflammation, apoptosis, transport, development, epigenetic regulation, and cancer. The increase of transcript abundance was presumably due to thermodynamic and kinetic controls encountered such as the activation of epigenetic modification genes responsible for unraveling the nucleosomes, which enabled transcription of previously silenced genes (e.g., development genes). The fact that new molecules were synthesized at 48 to 96 h postmortem suggests sufficient energy and resources to maintain self-organizing processes. A step-wise shutdown occurs in organismal death that is manifested by the apparent upregulation of genes with various abundance maxima and durations. The results are of significance to transplantology and molecular biology.

Systems Biology↗

bioRxiv2022

Metadata preservation and stewardship for genomic data is possible, but must happen now

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species and population resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies of evolutionary biology, molecular ecology and conservation genetics produce large amounts of genome-scale genetic diversity data for wild populations. While open data policies have ensured an abundance of freely available genomic data stored in the databases of the International Nucleotide Sequence Database Collaboration (INSDC), only about 13% of current accessions have the associated spatial and temporal metadata in INSDC necessary to be reused in monitoring programs, macrogenetic studies, or for acknowledging the sovereignty of nations or Indigenous Peoples. We undertook a "distributed datathon" to quantify the availability of these missing metadata in sources external to the INSDC and to test the hypothesis that these metadata decay with time. We also worked to remediate these missing metadata by extracting them, when present, from associated published papers, online repositories, and/or from direct communication with authors. Starting with 848 programmatically identified candidate datasets (INSDC BioProjects), we manually determined that 561 contained samples from wild populations. We successfully restored spatiotemporal metadata (locality name and/or geospatial coordinates and collection year) for 78% of these 561 datasets (N = 440 BioProjects comprising 45,105 individuals or BioSamples from 762 species in 17 phyla). We also quantified the availability of 33 additional categories of metadata in sources external to the INSDC. Information about associated publications and the type of habitat from which the samples were taken was the most easily found; information about sampling permits was the most challenging to locate. Looking at papers and online repositories was much more fruitful than contacting authors, who only replied to our email requests 45% of the time. Overall, 23% of our email queries to authors discovered useful metadata. Importantly, we found that the probability of retrieving spatiotemporal metadata declines significantly with the age of the dataset, with a 13.5% yearly decrease for metadata located in published papers or online repositories and up to a 22% yearly decrease for metadata that were only available from authors. This observable metadata decay, mirrored in studies of other types of biological data, should motivate swift updates to data sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost forever.

bioinformatics↗

bioRxiv2025

The Driving W Hypothesis for Low Within-Population Mitochondrial DNA Diversity and Between-Population Mitochondrial Capture

The fields of evolutionary biology, molecular ecology, genetics, and taxonomy have been profoundly influenced by studies of variation in mitochondrial DNA (mtDNA), yet there are often surprising differences between mtDNA and nuclear DNA in the within- and between-population relationships that they display. Here I articulate and evaluate a hypothesis that may explain many of the cases in which mtDNA shows little within-population variation and recent movement between populations. Many taxonomic groups (e.g., birds, butterflies and moths; most snakes; some amphibians, fish, and plants) have sex chromosome systems in which females are heterogametic (i.e., ZW females and ZZ males). If a W chromosome undergoes a mutation that gives it a transmission advantage in getting into the one egg produced by female meiosis, it will tend to cause a female-biased sex ratio in the offspring of females that carry that driving W chromosome. This sex ratio bias increases the frequency of the driving W in relation to the non-driving W in the next generation. In the great majority of species in which mitochondria are inherited matrilineally, the spread of the driving W through the population will carry along the particular mitochondrial genome that happens to be associated with the driving W. I summarize evidence in support of the seven components of this W-mtDNA Drive Hypothesis and present simulations and mathematical formulae showing that W drivers spread much more rapidly than equivalent-strength Z or autosomal drivers. Suppressors of W drive spread at a vastly lower rate. I conclude that many cases of low within-population mitochondrial diversity and mitochondrial transfer between species might be explained by the spread of driving W chromosomes.

evolutionary biology↗

bioRxiv2015

NCBI BLAST+ integrated into Galaxy

BackgroundThe NCBI BLAST suite has become ubiquitous in modern molecular biology, used for small tasks like checking capillary sequencing results of single PCR products through to genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST was a natural step for sequence comparison workflows.\n\nFindingsThe command line NCBI BLAST+ tool suite was wrapped for use within Galaxy, defining appropriate datatypes as needed, with the goal of making common BLAST tasks easy, and advanced tasks possible.\n\nConclusionsThis effort has been come an informal international collaborative effort, and is deployed and used on Galaxy servers worldwide. Several example use-cases are described herein.

Bioinformatics↗

bioRxiv2015

Tying down loose ends in the Chlamydomonas genome

The Chlamydomonas genome has been sequenced, assembled and annotated to produce a rich resource for genetics and molecular biology in this well-studied model organism. The annotated genome is very rich in open reading frames upstream of the annotated coding sequence ( uORFs): almost three quarters of the assigned transcripts have at least one uORF, and frequently more than one. This is problematic with respect to the standard scanning model for eukaryotic translation initiation. These uORFs can be grouped into three classes: class 1, initiating in-frame with the coding sequence (cds) (thus providing a potential in-frame N-terminal extension); class 2, initiating in the 5UT and terminating out-of-frame in the cds; and class 3, initiating and terminating within the 5UT. Multiple bioinformatics criteria (including analysis of Kozak consensus sequence agreement and BLASTP comparisons to the closely related Volvox genome, and statistical comparison to cds and to random-sequence controls) indicate that of ~4000 class 1 uORFs, approximately half are likely in vivo translation initiation sites. The proposed resulting N-terminal extensions in many cases will sharply alter the predicted biochemical properties of the encoded proteins. These results suggest significant modifications in ~2000 of the ~20,000 transcript models with respect to translation initiation and encoded peptides. In contrast, class 2 uORFs may be subject to purifying selection, and the existent ones (surviving selection) are likely inefficiently translated. Class 3 uORFs are remarkably similar to random sequence expectations with respect to size, number and composition and therefore may be largely selectively neutral; their very high abundance (found in more than half of transcripts, frequently with multiple uORFs per transcript) nevertheless suggests the possibility of translational regulation on a wide scale.

Genomics↗

bioRxiv2015

Patching holes in the Chlamydomonas genome

The Chlamydomonas genome has been sequenced, assembled and annotated to produce a rich resource for genetics and molecular biology in this well-studied model organism. However, the current reference genome contains ~1000 blocks of unknown sequence ( N-islands), which are frequently placed in introns of annotated gene models. We developed a strategy, using careful bioinformatics analysis of short-sequence cDNA and genomic DNA reads, to search for previously unknown exons hidden within such blocks, and determine the sequence and exon/intron boundaries of such exons. These methods are based on assembly and alignment completely independent of prior reference assembly or reference annotation. Our evidence indicates that ~one-quarter of the annotated intronic N-islands actually contain hidden exons. For most of these our algorithm recovers full exonic sequence with associated splice junctions and exon-adjacent intron sequence, that can be joined to the reference genome assembly and annotated transcript models. These new exons represent de novo sequence generally present nowhere in the assembled genome, and the added sequence can be shown in many cases to greatly improve evolutionary conservation of the predicted encoded peptides. At the same time, our results confirm the purely intronic status for a substantial majority of N-islands annotated as intronic in the reference annotated genome, increasing confidence in this valuable resource.

Genomics↗

bioRxiv2016

Expanding perspectives on cognition in humans, animals, and machines

Over the past decade neuroscience has been attacking the problem of cognition with increasing vigor. Yet, what exactly is cognition, beyond a general signifier of anything seemingly complex the brain does? Here, we briefly review attempts to define, describe, explain, build, enhance and experience cognition. We highlight perspectives including psychology, molecular biology, computation, dynamical systems, machine learning, behavior and phenomenology. This survey of the landscape reveals not a clear target for explanation but a pluralistic and evolving scene with diverse opportunities for grounding future research. We argue that rather than getting to the bottom of it, over the next century, by deconstructing and redefining cognition, neuroscience will and should expand rather than merely reduce our concept of the mind.

Animal Behavior and Cognition↗

bioRxiv2016

Statistical inference of protein structural alignments using information and compression

Structural molecular biology depends crucially on computational techniques that compare protein three-dimensional structures and generate structural alignments (the assignment of one-to-one correspondences between subsets of amino acids based on atomic coordinates.) Despite its importance, the structural alignment problem has not been formulated, much less solved, in a consistent and reliable way. To overcome these difficulties, we present here a framework for precise inference of structural alignments, built on the Bayesian and information-theoretic principle of Minimum Message Length (MML). The quality of any alignment is measured by its explanatory power - the amount of lossless compression achieved to explain the protein coordinates using that alignment. We have implemented this approach in the program MMLigner http://lcb.infotech.monash.edu.au/mmligner to distinguish statistically significant alignments, not available elsewhere. We also demonstrate the reliability of MMLigners alignment results compared with the state of the art. Importantly, MMLigner can also discover different structural alignments of comparable quality, a challenging problem for oligomers and protein complexes.

Bioinformatics↗

bioRxiv2016

Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease

Genetic association studies have identified 210 risk loci for inflammatory bowel disease, which have revealed fundamental aspects of the molecular biology of the disease, including the roles of autophagy and Th17 cell signaling and development. We performed a genome-wide association study of 25,305 individuals, and meta-analyzed with published summary statistics, yielding a total sample size of 59,957 subjects. We identified 26 new genome-wide significant loci, three of which contain integrin genes that encode molecules in pathways identified as important therapeutic targets in inflammatory bowel disease. The associated variants are also correlated with expression changes in response to immune stimulus at two of these genes (ITGA4, ITGB8) and at two previously implicated integrin loci (ITGAL, ICAM1). In all four cases, the stimulus-dependent expression increasing allele also increases disease risk. We applied summary statistic fine-mapping and identified likely causal missense variants in the primary immune deficiency gene PLCG2 and the negative regulator of inflammation, SLAMF8. Our results demonstrate that new common variant associations continue to identify genes and pathways of relevance to therapeutic target identification and prioritization.

Genomics↗

bioRxiv2016

Vibrio natriegens, a new genomic powerhouse

Recombinant DNA technology has revolutionized biomedical research with continual innovations advancing the speed and throughput of molecular biology. Nearly all these tools, however, are reliant on Escherichia coli as a host organism, and its lengthy growth rate increasingly dominates experimental time. Here we report the development of Vibrio natriegens, a free-living bacteria with the fastest generation time known, into a genetically tractable host organism. We systematically characterize its growth properties to establish basic laboratory culturing conditions. We provide the first complete Vibrio natriegens genome, consisting of two chromosomes of 3,248,023 bp and 1,927,310 bp that together encode 4,578 open reading frames. We reveal genetic tools and techniques for working with Vibrio natriegens. These foundational resources will usher in an era of advanced genomics to accelerate biological, biotechnological, and medical discoveries.

Genomics↗

bioRxiv2016

Measurements of translation initiation from all 64 codons in E. coli

Our understanding of translation is one cornerstone of molecular biology that underpins our capacity to engineer living matter. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are typically considered as the \"start codons\" for translation initiation in Escherichia coli (E. coli). Translation is typically not thought to initiate from the 61 remaining codons. Here, we systematically quantified translation initiation in E. coli from all 64 triplet codons. We detected protein synthesis above background initiating from at least 46 codons. Translation initiated from these non-canonical start codons at levels ranging from 0.01% to 2% relative to AUG. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems

Synthetic Biology↗

bioRxiv2016

Morphological plant modeling: Unleashing geometric and topologic potential within the plant sciences

Plant morphology is inherently mathematical in that morphology describes plant form and architecture with geometrical and topological descriptors. The geometries and topologies of leaves, flowers, roots, shoots and their spatial arrangements have fascinated plant biologists and mathematicians alike. Beyond providing aesthetic inspiration, quantifying plant morphology has become pressing in an era of climate change and a growing human population. Modifying plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems with fewer natural resources. In this white paper, we begin with an overview of the mathematical models applied to quantify patterning in plants. We then explore fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leafs in air streams. We end with a discussion concerning the incorporation of plant morphology into educational programs. This strategy focuses on synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. This white paper arose from bringing mathematicians and biologists together at the National Institute for Mathematical and Biological Synthesis (NIMBioS) workshop titled \"Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences\" held at the University of Tennessee, Knoxville in September, 2015. Never has the need to quantify plant morphology been more imperative. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.

Plant Biology↗

bioRxiv2016

CASTOR: A machine learning platform for reproducible viral genome classification

MotivationAdvances in cloning and sequencing technology yielded a massive number of genome of virus strains. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for a well-studied virus. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families.\n\nResultsHere, we introduce a fast, accurate and generic virus classification platform, CASTOR, based on a machine learning approach. CASTOR is inspired by a well-known technique in molecular biology: Restriction Fragment Length Polymorphism (RFLP). It simulates the restriction digestion of genomic material by different enzymes into fragments in-silico. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of Human Papillomaviruses (HPV), Hepatitis B Viruses (HBV) and Human Immunodeficiency viruses (HIV). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV M group subtyping respectively. Furthermore, CASTOR shows a competitive performance compare to well-known HIV-specific classifier REGA and COMET on whole genome and pol fragments. With such prediction rates, genericity and robustness, as well as rapidity, such approach could constitute a reference in large-scale virus studies. Finally, we developed the CASTOR web platform for open access and reproducible viral machine learning classifiers.\n\nAvailabilityhttp://castor.bioinfo.uqam.ca\n\nContactdiallo.abdoulaye@uqam.ca

bioinformatics↗