scholarly journals Efficient enrichment of synchronized mouse spermatocytes suitable for genome-wide analysis.

2022 ◽  
Author(s):  
Agustin Carbajal ◽  
Irma Gryniuk ◽  
Rodrigo de Castro ◽  
Roberto Pezza
Keyword(s):  
Binding Sites ◽  
Quality Data ◽  
Chromatin Binding ◽  
High Quality Data ◽  
Developmental Transitions ◽  
Male Gametogenesis ◽  
Genome Wide ◽  
Chromosome Associations ◽  
Specific Proteins ◽  
Reliable Isolation

Chromatin-based mechanisms regulating developmental transitions during meiosis are fundamental but understudied aspects of male gametogenesis. Indeed, chromatin undergoes extensive remodeling dur-ing meiosis, leading to specific patterns of gene expression and chromosome organization, which ulti-mately controls fundamental meiotic processes such as recombination and homologous chromosome associations. Recent game-changing advances have been made by analysis of chromatin binding sites of meiotic specific proteins genome-wide in mouse spermatocytes. However, further progress is still highly dependent on the reliable isolation of sufficient quantities of spermatocytes at specific stages of prophase I. Here, we describe a combination of methodologies adapted for rapid and reliable isolation of synchronized fixed mouse spermatocytes. We show that chromatin isolated from these cells can be used to study chromatin binding sites by ChIP-seq. High quality data we obtained from INO80 ChIP-seq in zygotene cells was used for functional analysis of chromatin binding sites.

scholarly journals CUT&RUN: Targeted in situ genome-wide profiling with high efficiency for low cell numbers

2017 ◽  
Author(s):  
Peter J. Skene ◽  
Steven Henikoff
Keyword(s):  
Chromatin Immunoprecipitation ◽  
High Efficiency ◽  
Specific Protein ◽  
Micrococcal Nuclease ◽  
Quality Data ◽  
High Quality Data ◽  
Left Behind ◽  
Dna Accessibility ◽  
Genome Wide

SUMMARYCleavage Under Targets and Release Using Nuclease (CUT&RUN) is an epigenomic profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing. As only the targeted fragments enter into solution, and the vast majority of DNA is left behind, CUT&RUN has exceptionally low background levels. CUT&RUN outperforms the most widely-used Chromatin Immunoprecipitation (ChIP) protocols in resolution, signal-to-noise, and depth of sequencing required. In contrast to ChIP, CUT&RUN is free of solubility and DNA accessibility artifacts and can be used to profile insoluble chromatin and to detect long-range 3D contacts without cross-linking. Here we present an improved CUT&RUN protocol that does not require isolation of nuclei and provides high-quality data starting with only 100 cells for a histone modification and 1000 cells for a transcription factor. From cells to purified DNA CUT&RUN requires less than a day at the lab bench.

scholarly journals HiCBricks: building blocks for efficient handling of large Hi-C datasets

2019 ◽  
Author(s):  
Koustav Pal ◽  
Ilario Tagliaferri ◽  
Carmen Maria Livi ◽  
Francesco Ferrari
Keyword(s):  
High Throughput Sequencing ◽  
Building Blocks ◽  
Efficient Solutions ◽  
Quality Data ◽  
Supplementary Information ◽  
Complex Data ◽  
High Quality Data ◽  
Chromosome Conformation ◽  
Genome Wide ◽  
User Friendly

Abstract Summary Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high-quality data visualization. Availability and implementation http://bioconductor.org/packages/devel/bioc/html/HiCBricks.html. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Genome-wide detection and quantitation of RNA distribution by ChIRC13a-seq

2021 ◽  
Author(s):  
Fan Yang ◽  
Bogdan Tanasa ◽  
Rudi Micheletti ◽  
Kenneth A. Ohgi ◽  
Aneel K. Aggarwal ◽  
...  
Keyword(s):  
Molecular Biology ◽  
Binding Sites ◽  
Eukaryotic Genome ◽  
Chromatin Binding ◽  
Library Preparation ◽  
Guide Rnas ◽  
Genome Wide ◽  
Target Rna ◽  
Detailed Protocol ◽  
Standard Molecular Biology

Abstract Eukaryotic genome are transcribed extensively, but a majority of transcripts remain functionally uncharacterized. This is most ascribed to lacking of a potent RNA-centric technology that is capable of accurately quantitating putative genomic binding sites for endogenous RNAs. We describe here a detailed protocol for Chromatin Isolation by RNA-Cas13a Complex sequencing (ChIRC13a-seq), based on recently discovered CRISPR-Cas13a from Leptotrichia wadei (LwaCas13a), for profiling of RNA associated chromatin binding cites. ChIRC13a-seq employs biotinylated, enzymatically-dead Cas13a (dCas13a) that is still capable of binding target RNA and guide RNAs (gRNAs) specific for the RNA target of interest to enrich RNA and its chromatin binding sites. This assay can be performed in standard molecular biology laboratories with 2 d taken for ChIRC13a-seq library preparation.

What Can Digitization Do For Formulated Product Innovation and Development

2020 ◽  
Author(s):  
James McDonagh ◽  
William Swope ◽  
Richard L. Anderson ◽  
Michael Johnston ◽  
David J. Bray
Keyword(s):  
High Performance ◽  
Quality Data ◽  
High Quality Data ◽  
Base Level ◽  
Hybrid Approaches ◽  
Digital Ecosystem ◽  
Recent Developments ◽  
Chemical Simulation ◽  
High Level ◽  
Physical And Chemical

Digitization offers significant opportunities for the formulated product industry to transform the way it works and develop new methods of business. R&D is one area of operation that is challenging to take advantage of these technologies due to its high level of domain specialisation and creativity but the benefits could be significant. Recent developments of base level technologies such as artificial intelligence (AI)/machine learning (ML), robotics and high performance computing (HPC), to name a few, present disruptive and transformative technologies which could offer new insights, discovery methods and enhanced chemical control when combined in a digital ecosystem of connectivity, distributive services and decentralisation. At the fundamental level, research in these technologies has shown that new physical and chemical insights can be gained, which in turn can augment experimental R&D approaches through physics-based chemical simulation, data driven models and hybrid approaches. In all of these cases, high quality data is required to build and validate models in addition to the skills and expertise to exploit such methods. In this article we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. We discuss the challenges in building and deploying these demonstrators.<br>

Collecting High-Quality Data

2018 ◽  
Author(s):  
Mary Kay Gugerty ◽  
Dean Karlan
Keyword(s):  
Data Collection ◽  
Social Desirability ◽  
Measurement Errors ◽  
Monitoring And Evaluation ◽  
Quality Data ◽  
Social Desirability Bias ◽  
High Quality ◽  
High Quality Data ◽  
Evaluation Systems ◽  
Demand Effect

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

scholarly journals Velocity Analysis Using Separated Diffractions for Lunar Penetrating Radar Obtained by Yutu-2 Rover

2021 ◽  
Vol 13 (7) ◽  
pp. 1387
Author(s):  
Chao Li ◽  
Jinhai Zhang
Keyword(s):  
Dielectric Permittivity ◽  
Lunar Regolith ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Quality Data ◽  
High Quality Data ◽  
Shallow Subsurface ◽  
Subsurface Structures ◽  
Ground Penetrating ◽  
Permittivity Model

The high-frequency channel of lunar penetrating radar (LPR) onboard Yutu-2 rover successfully collected high quality data on the far side of the Moon, which provide a chance for us to detect the shallow subsurface structures and thickness of lunar regolith. However, traditional methods cannot obtain reliable dielectric permittivity model, especially in the presence of high mix between diffractions and reflections, which is essential for understanding and interpreting the composition of lunar subsurface materials. In this paper, we introduce an effective method to construct a reliable velocity model by separating diffractions from reflections and perform focusing analysis using separated diffractions. We first used the plane-wave destruction method to extract weak-energy diffractions interfered by strong reflections, and the LPR data are separated into two parts: diffractions and reflections. Then, we construct a macro-velocity model of lunar subsurface by focusing analysis on separated diffractions. Both the synthetic ground penetrating radar (GPR) and LPR data shows that the migration results of separated reflections have much clearer subsurface structures, compared with the migration results of un-separated data. Our results produce accurate velocity estimation, which is vital for high-precision migration; additionally, the accurate velocity estimation directly provides solid constraints on the dielectric permittivity at different depth.

Sign in / Sign up

Export Citation Format

Share Document