Current protocols最新文献

Genetic ancestry inference has become essential in population and medical genetics, especially for studies of admixed populations. Accurate determination of both global ancestry (GA) proportions and local ancestry (LA) segmental origins requires careful selection of computational methods and reference panels. Here, we present a practical, protocol-oriented guide that (i) clarifies key concepts (GA vs. LA, reference panel selection, phasing requirements), (ii) organizes methods into model-based clustering and dimensionality-reduction approaches for GA and hidden Markov model–based, window-based machine learning, and deep learning frameworks for LA and (iii) provides concise guidance on tool selection for GA and LA. Step-by-step protocols are provided for a typical ADMIXTURE-based GA analysis and for a SHAPEIT5 + RFMix LA inference pipeline, with practical considerations for genotype array and whole-genome sequencing data. We also discuss quality control, method validation, and downstream applications of ancestry inference. Finally, we address current challenges and highlight recent advances, including fast algorithms, deep learning models, improved phasing, and integrative tools. This guide aims to help researchers select and implement appropriate ancestry inference methods for diverse study designs and datasets. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Global ancestry analysis (ADMIXTURE pipeline)

Basic Protocol 2: Local ancestry analysis (phasing + RFMix pipeline)

Differential abundance or expression analyses are routinely performed on metagenomic, metatranscriptomic, and amplicon sequencing data. In such datasets, analysts usually have no information regarding the true scale (i.e., size) of the microbial community or sample under study, with inter-sample differences in sequencing depth instead being driven by technical variation rather than biological factors. Recent work has demonstrated that normalizations used in all analysis tools make incorrect assumptions about the biological scale of the system in question, leading to unacceptably high false-discovery rates in the output. To mitigate this, analysts can acknowledge and account for the uncertainty of the overall system scale during normalization by building scale models of the data—a feature that has been integrated into the ALDEx2 R package. Here, we provide reproducible examples that demonstrate how to incorporate scale models into differential expression analyses of RNA-seq data using bulk transcriptome and metatranscriptomic datasets, as well as the consequences of not doing so. We also show how to use the output of ALDEx2 to create high-level exploratory visualizations of their data through principal component analysis. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Using a simple scale model for differential expression analysis to avoid dual-cutoff P value/significance thresholds

Basic Protocol 2: Implementing a full informed scale model to correct scale-related data asymmetry in differential expression analyses

Basic Protocol 3: Visualizing ALDEx2 outputs using a compositional approach: Principal component analysis

Next-generation RNA sequencing (RNA-seq) allows researchers to study gene expression across the whole genome. However, its analysis often needs powerful computers and advanced command-line skills, which can be challenging when resources are limited. This protocol provides a simple, start-to-finish RNA-seq data analysis method that is easy to follow, reproducible, and requires minimal local hardware. It uses free tools such as SRA Toolkit, FastQC, Trimmomatic, BWA/HISAT2, Samtools, and Subread, along with Python and R for further analysis using Google Colab. The process includes downloading raw data from NCBI GEO/SRA, checking data quality, trimming adapters and low-quality reads, aligning sequences to reference genomes, converting file formats, counting reads, normalizing to TPM, and creating visualizations such as heatmaps, bar plots, and volcano plots. Differential gene expression is analyzed with pyDESeq2, and functional enrichment is done using g:Profiler. Troubleshooting in RNA-seq generally involves configuring essential tools, resolving path and dependency issues, and ensuring proper handling of paired-end reads during analysis. By running the heavy computational steps on cloud platforms, this workflow makes RNA-seq analysis affordable and accessible to more researchers. © 2026 Wiley Periodicals LLC.

Basic Protocol 1: Extracting and processing a high-throughput RNA-seq dataset with the command prompt and Windows Subsystem for Linux

Basic Protocol 2: Normalization and visualization of processed RNA-seq dataset with Google Colab and Python 3

This article describes a chemically defined stepwise protocol to differentiate human induced pluripotent stem cells (hiPSCs) into mature oligodendrocytes via harvestable developmental intermediates. The workflow recapitulates in vitro neural lineage specification through embryoid body formation, neuroectoderm induction, the generation of glial-restricted progenitors, and the transition through oligodendrocyte progenitor cells (OPCs) to terminally differentiated, myelinating oligodendrocytes. Lineage progression is driven exclusively by small molecules and growth factors selected based on developmental and pharmacological evidence, without the use of exogenous transcription factor overexpression. The protocol enables isolation and expansion of physiologically relevant intermediate populations, making it suitable for mechanistic studies, disease modeling, and drug screening. Differentiation efficiency and purity can be validated by immunocytochemistry, flow cytometry, and co-culture-based myelination assays. The method reliably yields high-purity oligodendroglial cultures within approximately 90 days and is readily adaptable across hiPSC lines. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Thawing and plating of human iPSCs on Geltrex-coated plates Support Protocol 1: Passaging of human iPSCs using ReLeSR Basic Protocol 2: Dissociation of iPSC colonies into clusters for suspension embryoid body formation and early basal differentiation Basic Protocol 3: Embryoid body differentiation for enhancing ectoderm by suppressing mesoderm and endoderm using specific growth factor cocktail Basic Protocol 4: Selection of embryoid bodies and plating for neuroectoderm differentiation Basic Protocol 5: Differentiation of neuroectodermal cells to glial-restricted progenitors Basic Protocol 6: Magnetic-activated cell sorting of A2B5⁺ cells for differentiation to oligodendrocyte progenitor cells Basic Protocol 7: Optimization of culture protocol for differentiation of oligodendrocyte progenitor cells to pre-oligodendrocytes Basic Protocol 8: Optimization of culture protocol for differentiation of pre-oligodendrocytes to immature oligodendrocytes Basic Protocol 9: Optimization of culture protocol for differentiation of immature oligodendrocytes to mature oligodendrocytes Basic Protocol 10: Co-culture of iPSC-derived neurons with iPSC-derived oligodendrocytes for myelination assay Support Protocol 2: Differentiation of iPSCs to neurons Support Protocol 3: Immunocytochemistry analysis Support Protocol 4: Flow cytometry analysis.

Drosophila melanogaster has been an indispensable model for dissecting out innate immune pathways in a controlled and genetically tractable system. Two modes of infection, oral and systemic, in flies reveal distinct facets of host defense. Oral infection captures how the gut senses and responds to ingested microbes, whereas systemic challenges expose the mechanisms that act once pathogens breach external barriers and multiply systemically. Here, we provide a set of protocols that together offer a framework for studying infection biology in flies. They comprise a step-by-step guide to studying infection biology in adult flies using the two routes of infection-systemic infection via needle pricking/injection into the hemolymph and oral infection via pathogen-contaminated food or filter disks. We also outline assays to track infection outcomes, both oral and systemic, including survival rates, bacterial load assessments, gut function evaluations, and wound-repair responses. All experiments in this article are described for wild-type flies, but the workflow can be readily applied to different genetic backgrounds or mutant strains as a means to compare post-infection phenotypes and probe shifts in underlying immune signaling. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Preparation of fly food vials Basic Protocol 2: Starvation of adult Drosophila melanogaster flies Basic Protocol 3: Preparation of pathogenic pellets Basic Protocol 4: Systemic infection of adult Drosophila melanogaster flies Basic Protocol 5: Oral infection of adult Drosophila melanogaster flies Basic Protocol 6: Assessment of survival in infected adult Drosophila melanogaster flies Basic Protocol 7: Scoring of melanization in adult Drosophila melanogaster flies Basic Protocol 8: Tracking bacterial load and pathogen clearance in adult Drosophila melanogaster flies Basic Protocol 9: Monitoring defecation patterns in adult Drosophila melanogaster flies.

The mouse is currently the most widely used animal model for scientific research worldwide. In Europe, statistical data show that half of all mice used in research are genetically modified, and that 60% of the transgenic mice produced are ultimately not used. Optimizing production strategies is therefore essential to minimize the production of animals that will not be included in research. In this article, we examine the key components required for the rigorous management of genetically modified lines, organized under the acronym DOPPUME: Define, Obtain, Protect, Produce, Use, Manage, and Exchange. The first step is to clearly define the model in accordance with the scientific objective and strictly control its genetic characteristics, including both the genetic background and the engineered modification. Ensuring the stability of these parameters is crucial for maintaining continuity between studies and preventing genetic drift. The article also provides tools to support the clear definition of production goals based on planned experiments and to estimate production needs as accurately as possible, accounting for the types of crosses and breeding schemes involved. Emphasis is placed on producing only what is necessary and on implementing proactive, rather than reactive, colony management. This framework is fully aligned with the 3Rs principles (Replace, Reduce, Refine) by promoting a responsible, rational, and optimized use of mouse models in research. © 2026 Wiley Periodicals LLC.

Oligonucleotide-based therapeutics are now widely used in clinical settings. From the late 1980s to the mid-1990s, efforts to improve therapeutic efficacy focused on imparting drug-like properties to oligonucleotides, emphasizing nuclease stability and target sequence affinity. These efforts resulted in the standard gapmer design for RNase H–mediated antisense and the prevalent use of chemical modification such as phosphorothioate and 2′-substituted oligoribonucleotides in oligonucleotide therapeutics. Progress made in the antisense field also enabled the development of splice-modulating oligonucleotide therapeutics and later siRNA therapies. All three modes of action are now widely employed in >25 approved drugs. Since then, we have learned that oligonucleotides and their chemical modifications can interact with pattern recognition receptors as well as various other proteins. This can have both positive and negative effects, such as aiding in oligonucleotide delivery or activating the intracellular innate immune system. My current work aims to optimize the drug-like properties of oligonucleotides by combining the early chemical advances with the more recent insights into off-target protein binding. The present article describes how this resulted in several different cyclic structured oligonucleotide designs, in which 3′ and 5′ ends are transiently held together via Watson-Crick base pairing. The transient nature of these cyclic structures protects the functional parts of the structure against nucleases during delivery and cell entry while allowing effective release of the oligonucleotide drug into the intracellular environment. These cyclic designs demonstrate significant improvements in potency and specificity over gapmer antisense and are broadly applicable to potentially all types of RNA therapeutics, irrespective of their mechanism of action. © 2026 Wiley Periodicals LLC.

The IntelliCage is a home-cage-based radiofrequency identification (RFID) test system for studying learning behavior of group-housed mice. Specifically, the mice must learn where and how to get water within the IntelliCage. The protocol describes how to set up the IntelliCage, how to set up and start a learning experiment, what to consider before starting an experiment, and how to clean the system. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: General instructions for using the IntelliCage with mice

Basic Protocol 2: IntelliCage cleaning

A major, serendipitous psychiatric discovery is monoamine-transporter reuptake inhibition as an antidepressant mechanism of action. Chronic treatment with such antidepressants is efficacious, with onset requiring 1-2 weeks, in many but by no means all patients with major depressive or another stress-related neuropsychiatric disorder. The forced swim test (FST) in rats and mice involves the acute, moderate stressor of placement in a container of water: at test onset, the predominant reaction is swimming, interpreted cautiously as active “struggling”; over minutes, this is replaced by floating, described objectively as immobility. Acute administration of monoamine transporter inhibitors immediately prolongs “struggling.” Although this readout is of behavioral pharmacological interest, the FST has no (back-)translational relevance to the neurobiological and neuropsychological symptoms/states of stress-related psychiatric disorders. The persistent adoption of the FST to measure “depression-like state,” based on interpretation of immobility as “despair,” “helplessness,” or “passive coping,” is a major weakness in applied behavioral neuroscience. Rodents do have a concept of learned uncontrollability, such that tests showing this depict an adaptive, not a “depression-like,” state. Recent psychiatry-neuroscience initiatives, such as the Research Domain Criteria framework, increase the accessibility of specific, transdiagnostic symptoms/states to behavioral neuroscience methods, thereby facilitating the establishment of animal models. Such animal models must incorporate clinically valid (1) etiological factors, such as prolonged psychosocial stress, and (2) neurobehavioral readouts with face and construct validity for specific symptoms/states. Increased reactivity to an acute threat, measured as increased Pavlovian aversion learning-memory (PALM), is a neurobehavioral state common in major depression and other disorders. Mice that have undergone chronic social stress exhibit generalized excessive PALM. Therefore, although stating that the FST measures “depression-like state” is erroneous, mouse models of specific symptoms/states can be achieved by back-translating etiology and neurobehavioral readouts. Though complex and moderately severe, such models have the potential to provide much-needed benefits in terms of preclinical neuropharmacological target discovery and validation. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Multiple myeloma is a bone marrow–derived neoplastic proliferation of plasma cells with low levels of circulating tumor cells. Cytogenetic abnormalities are present in >90% of patients, when assessed by fluorescence in situ hybridization (FISH) on bone marrow, and the specific abnormalities provide vital prognostic information. Provided is a protocol for assessing the high-risk abnormalities del(17p) and amp(1q21) in the circulating plasma cells of myeloma patients by flow cytometry. This utilizes positive plasma cell identification by standard immunophenotyping and then chromosomal analysis by FISH using an imaging flow cytometer. Integrating cell phenotype and FISH in one test, a method called “immuno-flowFISH” allows for the detection of cytogenetic abnormalities in plasma cells identified by their antigenic profile. This method can be applied to both bone marrow and blood samples to detect primary abnormalities [i.e., hyperdiploidy; immunoglobulin heavy locus (IGH) translocation] and secondary abnormalities [i.e., del(17p) found in 10% of patients, and gain(1q) present in ∼40% of patients with myeloma]. Here we describe the protocol for the simultaneous detection of these secondary abnormalities in blood and bone marrow samples from myeloma patients that enables detection of single or “double hit” abnormalities, with the latter classified as ultra high–risk disease. The protocol includes the data analysis strategy, as well as the statistics used to confirm the presence of these abnormalities. Applying this method will facilitate blood-based monitoring for the presence and evolution of these critical cytogenetic abnormalities. © 2026 Wiley Periodicals LLC.

Basic Protocol: Immuno-flowFISH assessment of del(17p) and amp(1q21) in multiple myeloma

Support Protocol: Validation of single fluorophore for positive markers in multiple myeloma