Methods in molecular biology
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The discovery of the CRISPR-Cas9 system raises hope for the treatment of many genetic disorders. We describe here an approach based on the use of a pair of single guide RNAs to form a hybrid exon that does not only restore the dystrophin gene reading frame but also results in the production of a dystrophin protein with an adequate structure of the central rod-domain, with a correct spectrin-like repeat. The therapeutic approach described here involved DMD patient cells having a deletion of exons 51-53 of the DMD gene.
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The diversity and huge omics data take biology and biomedicine research and application into a big data era, just like that popular in human society a decade ago. They are opening a new challenge from horizontal data ensemble (e.g., the similar types of data collected from different labs or companies) to vertical data ensemble (e.g., the different types of data collected for a group of person with match information), which requires the integrative analysis in biology and biomedicine and also asks for emergent development of data integration to address the great changes from previous population-guided to newly individual-guided investigations. Data integration is an effective concept to solve the complex problem or understand the complicate system. ⋯ Current integration approaches on biological data have two modes: one is "bottom-up integration" mode with follow-up manual integration, and the other one is "top-down integration" mode with follow-up in silico integration. This paper will firstly summarize the combinatory analysis approaches to give candidate protocol on biological experiment design for effectively integrative study on genomics and then survey the data fusion approaches to give helpful instruction on computational model development for biological significance detection, which have also provided newly data resources and analysis tools to support the precision medicine dependent on the big biomedical data. Finally, the problems and future directions are highlighted for integrative analysis of omics big data.
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DNA cytosine methylation is one of the most abundant epigenetic marks found in the plant nuclear genome. Bisulfite sequencing (BS-Seq) is the method of choice for profiling DNA cytosine methylation genome-wide at a single nucleotide resolution. ⋯ By deep sequencing of the bisulfite converted genomic DNA, the methylation level of each mappable cytosine position in the genome could be measured. In this chapter, we present a detailed 2-day protocol for performing a BS-Seq experiment and a simple bioinformatic workflow for wet lab biologists to visualize the methylation data.
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Whole genome bisulfite sequencing (WGBS) enables the detection of DNA methylation at single base-pair resolution. The treatment of DNA with sodium bisulfite allows the discrimination of methylated and unmethylated cytosines, but the power of this technology can be limited by the input amounts of DNA and the length of DNA fragments due to DNA damage caused by the desulfonation process. ⋯ Briefly, genomic DNA is sheared, end-repaired, 3'-adenylated, and ligated to adaptors with fewer cleanup steps in between, minimizing DNA loss. The adapter-ligated DNA is then treated with sodium bisulfite and amplified with few PCR cycles to reach the yield needed for sequencing.
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Single-cell transcriptome sequencing, often referred to as single-cell RNA sequencing (scRNA-seq), is used to measure gene expression at the single-cell level and provides a higher resolution of cellular differences than bulk RNA-seq. With more detailed and accurate information, scRNA-seq will greatly promote the understanding of cell functions, disease progression, and treatment response. ⋯ Particularly, we present a protocol to discover and validate cancer stem cells (CSCs) using scRNA-seq. Suggestions have also been made to help researchers rationally design their scRNA-seq experiments and data analysis in their future studies.