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1. FlyBase: updates to the Drosophila melanogaster knowledge base

   https://doi.org/10.1093/nar/gkaa1026  

   Larkin, Aoife ; Marygold, Steven J ; Antonazzo, Giulia ; Attrill, Helen ; dos Santos, Gilberto ; Garapati, Phani V ; Goodman, Joshua L ; Gramates, L Sian ; Millburn, Gillian ; Strelets, Victor B ; et al ( November 2020 , Nucleic Acids Research)

   null (Ed.)

   Abstract FlyBase (flybase.org) is an essential online database for researchers using Drosophila melanogaster as a model organism, facilitating access to a diverse array of information that includes genetic, molecular, genomic and reagent resources. Here, we describe the introduction of several new features at FlyBase, including Pathway Reports, paralog information, disease models based on orthology, customizable tables within reports and overview displays (‘ribbons’) of expression and disease data. We also describe a variety of recent important updates, including incorporation of a developmental proteome, upgrades to the GAL4 search tab, additional Experimental Tool Reports, migration to JBrowse for genome browsing and improvements to batch queries/downloads and the Fast-Track Your Paper tool. 

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2. Histone Acid Extraction and High Throughput Mass Spectrometry to Profile Histone Modifications in Arabidopsis thaliana

   https://doi.org/10.1002/cpz1.527  

   Scheid, Ray ; Dowell, James A. ; Sanders, Dean ; Jiang, Jianjun ; Denu, John M. ; Zhong, Xuehua ( August 2022 , Current Protocols)

   Histone post‐translational modifications (PTMs) play important roles in many biological processes, including gene regulation and chromatin dynamics, and are thus of high interest across many fields of biological research. Chromatin immunoprecipitation coupled with sequencing (ChIP‐seq) is a powerful tool to profile histone PTMsin vivo. This method, however, is largely dependent on the specificity and availability of suitable commercial antibodies. While mass spectrometry (MS)–based proteomic approaches to quantitatively measure histone PTMs have been developed in mammals and several other model organisms, such methods are currently not readily available in plants. One major challenge for the implementation of such methods in plants has been the difficulty in isolating sufficient amounts of pure, high‐quality histones, a step rendered difficult by the presence of the cell wall. Here, we developed a high‐yielding histone extraction and purification method optimized forArabidopsis thalianathat can be used to obtain high‐quality histones for MS. In contrast to other methods used in plants, this approach is relatively simple, and does not require membranes or additional specialized steps, such as gel excision or chromatography, to extract highly purified histones. We also describe methods for producing MS‐ready histone peptides through chemical labeling and digestion. Finally, we describe an optimized method to quantify and analyze the resulting histone PTM data using a modified version of EpiProfile 2.0 for Arabidopsis. In all, the workflow described here can be used to measure changes to histone PTMs resulting from various treatments, stresses, and time courses, as well as in different mutant lines. © 2022 Wiley Periodicals LLC.

   Basic Protocol 1: Nuclear isolation and histone acid extraction

   Basic Protocol 2: Peptide labeling, digestion, and desalting

   Basic Protocol 3: Histone HPLC‐MS/MS and data analysis

    

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3. CUT&RUN for Chromatin Profiling in Caenorhabditis elegans

   https://doi.org/10.1002/cpz1.445  

   Emerson, Felicity J. ; Lee, Siu Sylvia ( June 2022 , Current Protocols)

   Cleavage under targets and release using nuclease (CUT&RUN) is a recently developed chromatin profiling technique that uses a targeted micrococcal nuclease cleavage strategy to obtain high‐resolution binding profiles of protein factors or to map histones with specific post‐translational modifications. Due to its high sensitivity, CUT&RUN allows quality binding profiles to be obtained with only a fraction of the starting material and sequencing depth typically required for other chromatin profiling techniques such as chromatin immunoprecipitation. Although CUT&RUN has been widely adopted in multiple model systems, it has rarely been utilized inCaenorhabditis elegans, a model system of great importance to genomic research. Cell dissociation techniques, which are required for this approach, can be challenging inC. elegansdue to the toughness of the worm's cuticle and the sensitivity of the cells themselves. Here, we describe a robust CUT&RUN protocol for use inC. elegansto determine the genome‐wide localization of protein factors and specific histone marks. With a simple protocol utilizing live, uncrosslinked tissue as the starting material, performing CUT&RUN in worms has the potential to produce physiologically relevant data at a higher resolution than chromatin immunoprecipitation. This protocol involves a simple dissociation step to uniformly permeabilize worms while avoiding sample loss or cell damage, resulting in high‐quality CUT&RUN profiles with as few as 100 worms and detectable signal with as few as 10 worms. This represents a significant advancement over chromatin immunoprecipitation, which typically uses thousands or hundreds of thousands of worms for a single experiment. The protocols presented here provide a detailed description of worm growth, sample preparation, CUT&RUN workflow, library preparation for high‐throughput sequencing, and a basic overview of data analysis, making CUT&RUN simple and accessible for any worm lab. © 2022 Wiley Periodicals LLC.

   Basic Protocol 1: Growth and synchronization ofC. elegans

   Basic Protocol 2: Worm dissociation, sample preparation, and optimization

   Basic Protocol 3: CUT&RUN chromatin profiling

   Alternate Protocol: Improving CUT&RUN signal using a secondary antibody

   Basic Protocol 4: CUT&RUN library preparation for Illumina high‐throughput sequencing

   Basic Protocol 5: Basic data analysis using Linux

    

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4. Base Editing in Human Cells to Produce Single‐Nucleotide‐Variant Clonal Cell Lines

   https://doi.org/10.1002/cpmb.129  

   Vasquez, Carlos A. ; Cowan, Quinn T. ; Komor, Alexis C. ( November 2020 , Current Protocols in Molecular Biology)

   Base‐editing technologies enable the introduction of point mutations at targeted genomic sites in mammalian cells, with higher efficiency and precision than traditional genome‐editing methods that use DNA double‐strand breaks, such as zinc finger nucleases (ZFNs), transcription‐activator‐like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR‐associated protein 9 (CRISPR‐Cas9) system. This allows the generation of single‐nucleotide‐variant isogenic cell lines (i.e., cell lines whose genomic sequences differ from each other only at a single, edited nucleotide) in a more time‐ and resource‐effective manner. These single‐nucleotide‐variant clonal cell lines represent a powerful tool with which to assess the functional role of genetic variants in a native cellular context. Base editing can therefore facilitate genotype‐to‐phenotype studies in a controlled laboratory setting, with applications in both basic research and clinical applications. Here, we provide optimized protocols (including experimental design, methods, and analyses) to design base‐editing constructs, transfect adherent cells, quantify base‐editing efficiencies in bulk, and generate single‐nucleotide‐variant clonal cell lines. © 2020 Wiley Periodicals LLC.

   Basic Protocol 1: Design and production of plasmids for base‐editing experiments

   Basic Protocol 2: Transfection of adherent cells and harvesting of genomic DNA

   Basic Protocol 3: Genotyping of harvested cells using Sanger sequencing

   Alternate Protocol 1: Next‐generation sequencing to quantify base editing

   Basic Protocol 4: Single‐cell isolation of base‐edited cells using FACS

   Alternate Protocol 2: Single‐cell isolation of base‐edited cells using dilution plating

   Basic Protocol 5: Clonal expansion to generate isogenic cell lines and genotyping of clones

    

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5. WISTFUL: Whole‐Rock Interpretative Seismic Toolbox for Ultramafic Lithologies

   https://doi.org/10.1029/2022GC010329  

   Shinevar, William J. ; Jagoutz, Oliver ; Behn, Mark D. ( August 2022 , Geochemistry, Geophysics, Geosystems)

   To quantitatively convert upper mantle seismic wave speeds measured into temperature, density, composition, and corresponding and uncertainty, we introduce theWhole‐rockInterpretativeSeismicToolboxForUltramaficLithologies (WISTFUL). WISTFUL is underpinned by a database of 4,485 ultramafic whole‐rock compositions, their calculated mineral modes, elastic moduli, and seismic wave speeds over a range of pressure (P) and temperature (T) (P = 0.5–6 GPa,T = 200–1,600°C) using the Gibbs free energy minimization routine Perple_X. These data are interpreted with a toolbox of MATLAB® functions, scripts, and three general user interfaces:WISTFUL_relations, which plots relationships between calculated parameters and/or composition;WISTFUL_geotherms, which calculates seismic wave speeds along geotherms; andWISTFUL_inversion, which inverts seismic wave speeds for best‐fit temperature, composition, and density. To evaluate our methodology and quantify the forward calculation error, we estimate two dominant sources of uncertainty: (a) the predicted mineral modes and compositions, and (b) the elastic properties and mixing equations. To constrain the first source of uncertainty, we compiled 122 well‐studied ultramafic xenoliths with known whole‐rock compositions, mineral modes, and estimatedP‐Tconditions. We compared the observed mineral modes with modes predicted using five different thermodynamic solid solution models. The Holland et al. (2018,https://doi.org/10.1093/petrology/egy048) solution models best reproduce phase assemblages (∼12 vol. % phase root‐mean‐square error [RMSE]) and estimated wave speeds. To assess the second source of uncertainty, we compared wave speed measurements of 40 ultramafic rocks with calculated wave speeds, finding excellent agreement (V_pRMSE = 0.11 km/s). WISTFUL easily analyzes seismic datasets, integrates into modeling, and acts as an educational tool.

    

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