PLX127660

GSE134785: Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and LDB2-/- skin epidermal lysates

• Organsim mouse
• Type RNASEQ
• Target gene
• Project ARCHS4

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived mouse back skin epidermal transcriptome profiling (RNA-seq) to evaluate protocols for optimal high-throughput data analysis; Methods: Total RNA was isolated using an RNeasy Kit (Qiagen, Germantown, MD, USA). The mRNA sequence libraries were prepared using the TruSeq Stranded mRNA Sample Prep Kit(RS-122; Illumina, San Diego, CA, USA). The protocols followed the TruSeq Stranded mRNA Sample Preparation Guide (Part 15031047 Rev. E). Sequencing was performed using an Illumina Novaseq 6000 sequencer (101 bp paired-end runs), NovaSeq 6000 System User Guide Document (#1000000019358 v02), and TruSeq Stranded mRNA LT Sample Prep Kit. After removing low-quality and adapter sequences, sequence reads were aligned to the University of CaliforniaSanta Cruz(UCSC mm10), mouse genome reference sequence Mus musculus(RefSeq_2017_06_12) using Hierarchical Indexing for Spliced Alignment of Transcripts HISAT2 version 2.1.0, Bowtie2 2.3.4.1; Results: StringTie v.1.3.4d was used to estimate gene abundance. Abundance was measured in fragments per kilobase of exon per million fragments mapped; any values of 0 were discarded. To establish log2 transformation, 1 was added to each abundance value of filtered genes, and quantile normalization was performed.; Conclusions: Our study represents detailed analysis of Skin epidermal lysates transcriptomes, with biologic replicates, generated by mRNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a tissue. We conclude that mRNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. SOURCE: Jonghyo LimVascular Genomics laboratory Yonsei university