Current Protocols in Molecular Biology最新文献

The auxin-inducible degron (AID) is a powerful tool that is used for depletion of proteins to study their function in vivo. This method can conditionally induce the degradation of any protein by the proteasome simply by the addition of the plant hormone auxin. This approach is particularly valuable to study the function of essential proteins. The protocols provided here describe the steps to construct the necessary strains and to optimize auxin-inducible depletion in Saccharomyces cerevisiae. © 2019 by John Wiley & Sons, Inc.

Basic Protocol 1: Construction of TIR1-expressing strains by transformation

Basic Protocol 2: Tagging a yeast protein of interest with an auxin-inducible degron

Support Protocol: Construction of depletion strains by genetic crosses

Basic Protocol 3: Optimization for depletion of the auxin-inducible-degron-tagged protein

The budding yeast, Saccharomyces cerevisiae, has been widely used for genetic studies of fundamental cellular functions. The isolation and analysis of yeast mutants is a commonly used and powerful technique to identify the genes that are involved in a process of interest. Furthermore, natural genetic variation among wild yeast strains has been studied for analysis of polygenic traits by quantitative trait loci mapping. Whole-genome sequencing, often combined with bulk segregant analysis, is a powerful technique that helps determine the identity of mutations causing a phenotype. Here, we describe protocols for the construction of libraries for S. cerevisiae whole-genome sequencing. We also present a bioinformatic pipeline to determine the genetic variants in a yeast strain using whole-genome sequencing data. This pipeline can also be used for analyzing Schizosaccharomyces pombe mutants. © 2019 by John Wiley & Sons, Inc.

Basic Protocol 1: Generation of haploid spores for bulk segregant analysis

Basic Protocol 2: Extraction of genomic DNA from yeast cells

Basic Protocol 3: Shearing of genomic DNA for library preparation

Basic Protocol 4: Construction and amplification of DNA libraries

Support Protocol 1: Annealing oligonucleotides for forming Y-adapters

Support Protocol 2: Size selection and cleanup using SPRI beads

Basic Protocol 5: Identification of genomic variants from sequencing data

The DMS region extraction and deep sequencing (DREADS) procedure was designed to probe RNA structure in vivo and to link this structural information to specific 3′ isoforms. Growing cells are treated with the alkylating agent dimethyl sulfate (DMS), which enters easily into cells and modifies RNA molecules at solvent-exposed A and C residues. RNA is isolated, and sequencing libraries are constructed in a manner that preserves the identities of individual mRNA isoforms arising from alternative cleavage/polyadenylation sites. During the cDNA synthesis step of library construction, the progress of reverse transcriptase (RT) is blocked when it encounters a DMS modification on the RNA, leading to disproportionate cDNA termination adjacent to DMS-modified positions. After paired-end deep sequencing, the downstream end of each sequenced fragment is mapped to a specific cleavage/poly(A) site representing an individual mRNA 3′ isoform. The upstream mapped end of the sequenced fragment defines where the RT reaction stopped. Over the population of all sequenced fragments derived from a particular isoform, A and C positions that are overrepresented next to the upstream endpoints in the DMS sample (relative to a parallel untreated control) are inferred to have been DMS modified, and hence solvent exposed. This method thus allows in vivo structural information obtained using DMS to be linked to individual mRNA 3′ isoforms. © 2019 by John Wiley & Sons, Inc.

Here we describe CLIP-READS, a technique that combines elements of crosslinking and immunoprecipitation (CLIP) and 3′ region extraction and deep sequencing (READS), to provide a genome-wide map of mRNA 3′ isoform binding by a given messenger ribonucleoprotein (mRNP). In CLIP-READS, cells are grown to logarithmic phase and are irradiated with UV light (254 nm) to form RNA–protein adducts. The protein−mRNA complexes are immunoprecipitated from cell extracts with an antibody specific to the protein of interest, after which the protein component is digested away with Pronase. Messenger RNAs are then subjected to 3′ READS. An input sample processed by 3′ READS in parallel allows for the relative quantification of isoform-specific binding by the mRNP of interest. © 2019 by John Wiley & Sons, Inc.

Cover: In Ji and Sadreyev (https://doi.org/10.1002/cpmb.92), Unsupervised clustering of all single cells in tSNE plot. See e92.

MicroRNAs (miRNAs) are key regulators of cell and tissue development. However, spatial resolution of miRNA heterogeneity and accumulation patterns in vivo remains uncharted. Next-generation sequencing methods assay miRNA abundance in tissues, yet these analyses do not provide spatial resolution. A method to assay miRNA expression at single-cell resolution in vivo should clarify the cell-autonomous functions of miRNAs, their roles in influencing the cellular microenvironment, and their perdurance and turnover rate. We present an in situ hybridization protocol to map miRNA subcellular expression in single cells in vivo in four days. Using this protocol, we mapped distinct miRNAs that accumulate in the cytoplasm of one sibling oocyte but not another, dependent on the oocyte developmental stage. Thus, this method provides spatial and temporal resolution of the heterogeneity in expression of miRNAs during Caenorhabditis elegans oogenesis. This protocol can generally be adapted to any tissue amenable to dissection and fixation. © 2019 by John Wiley & Sons, Inc.

Quantitative analysis of single-cell RNA sequencing (RNA-seq) is crucial for discovering the heterogeneity of cell populations and understanding the molecular mechanisms in different cells. In this unit we present a bioinformatics workflow for analyzing single-cell RNA-seq data with a few current publicly available computational tools. This workflow is focused on the interpretation of the heterogeneity from single-cell transcriptomes as well as the identification of cell clusters and genes that are differentially expressed between clusters. © 2019 by John Wiley & Sons, Inc.

Cell death involves the release of short DNA fragments into blood, termed circulating cell-free DNA (cfDNA). Sequencing of cfDNA in the plasma has recently emerged as a liquid biopsy for detecting fetal chromosomal aberrations, tumor DNA, and graft rejection. However, in cases where cfDNA is derived from tissues with a normal genome, its primary sequence is not informative regarding the tissue of origin. We developed a method of determining the tissue origins of cfDNA, allowing inference of tissue-specific cell death, based on tissue-specific methylation patterns. We have previously described a version of the method that uses next generation sequencing (NGS) to determine methylation patterns in specific marker loci. Here we describe a rapid and simple procedure for cfDNA methylation analysis using droplet digital PCR (ddPCR) on bisulfite treated cfDNA to accurately count the number of molecules carrying a specific methylation signature. Specificity and sensitivity of the assay increases by simultaneously interrogating four to six cytosines in the same molecule using two fluorescent probes. cfDNA methylation analysis using ddPCR can find multiple applications in the non-invasive study of human tissue dynamics in health and disease. © 2019 by John Wiley & Sons, Inc.

An understanding of the dynamic structural properties of chromatin requires techniques that allow the profiling of regions of both open and closed chromatin as well as the assessment of nucleosome occupancy. The recently developed MNase accessibility (MACC) technique allows for the simultaneous measurement of chromatin opening and compaction, as well as nucleosome occupancy, on a genome-wide scale in a single assay. This article presents a low-input MACC procedure that considerably extends the utility of the original MACC assay. Low-input MACC generates high-quality data using very low cell numbers (as few as 50 cells per titration point), making it ideal for samples obtained after fluorescence-activated cell sorting or dissection, or in clinical settings. Moreover, low-input MACC has significantly improved several steps of the initial method, offering a more rapid and robust methodology. © 2019 by John Wiley & Sons, Inc.