RNA sequencing Overview

 We started the week inoculating 3 plates and 3 flasks from freeze back, then later in the week did a pre-desiccation procedure and discussed more about what the RNA sequencing would look like. 

For pre desiccation we did the usual procedure, let it dehydrate for two days then placed it in the Egg, which is our new desiccator. Unlike the old glass one, this one is sealed and vacuumed making it true desiccation. Dehydration is a process of removing water or moisture from a substance, typically through heat, air circulation, or other drying methods. In dehydration, some water remains within the material, and the substance typically retains some degree of moisture. True desiccation, on the other hand, is a more extreme form of water removal that aims to completely eliminate all moisture from a substance. 

A vacuum is not absolutely necessary for true desiccation, but it can be an extremely effective method for removing moisture. In the desiccation process, a vacuum proves valuable by comprehensively addressing moisture removal through several key mechanisms. By lowering atmospheric pressure, a vacuum reduces the boiling point of water, which means moisture can be extracted more easily and at lower temperatures. This creates optimal conditions for facilitating more complete moisture removal, essentially allowing water molecules to transition to vapor more readily. Additionally, the vacuum environment prevents moisture reabsorption from the surrounding atmosphere, ensuring a more thorough and stable desiccation process.


Pre-desiccation cell packing 

1. Normalize 3ml of culture to an OD between 0.95-1.00

2. Spin down 1ml of media, remove supernatant and resuspend pellet in nuclease free water

3. Resuspend pellet, then centrifuge and remove supernatant

4. Add the second ml of culture, repeat washing steps

5. Add the third ml of culture, repeat washing steps

6. Plate 100ul dots into 1 inch kapton squares in a 6 well plate in triplicate



The process of RNA sequencing begins with sample preparation and careful RNA isolation, ensuring high-quality RNA extraction while minimizing degradation. Subsequent purification focuses on isolating messenger RNA through methods like poly-A selection or rRNA depletion. Library preparation transforms RNA into sequencing-compatible fragments by fragmenting RNA, synthesizing complementary DNA (cDNA), adding sequencing adapters, and performing PCR amplification. High-throughput sequencing platforms generate millions of short DNA sequence reads, which are then subjected to rigorous computational analysis. This computational stage involves quality control of sequencing reads, alignment to reference genomes or transcriptomes, read count quantification, data normalization, and statistical analysis to identify differentially expressed genes. The final stage encompasses data interpretation, including biological pathway analysis, gene ontology enrichment, functional annotation, and validation of key findings through alternative methodological approaches.

Library Preparation Once high-quality RNA is isolated, the next step is library preparation, which transforms RNA into sequencing-compatible DNA fragments. This involves several key processes:

  • Reverse transcription of RNA to complementary DNA (cDNA)
  • Adding sequencing adapters to the cDNA fragments
  • Selecting specific RNA types (often mRNA via poly-A selection or rRNA depletion)
  • Fragmenting the cDNA to create a suitable size range for sequencing
  • Amplifying the library through PCR to generate sufficient material

Sequencing Modern RNA sequencing typically employs high-throughput platforms like Illumina's next-generation sequencing technologies. These platforms generate millions of short DNA sequence reads that will later be computationally mapped back to a reference genome or transcriptome. The depth of sequencing (number of reads) is crucial - deeper sequencing provides more comprehensive coverage and increased sensitivity for detecting low-abundance transcripts.

Bioinformatics Analysis The computational analysis of RNA sequencing data is complex and involves multiple sophisticated steps:

  1. Quality filtering of sequencing reads
  2. Alignment of reads to a reference genome or transcriptome
  3. Quantification of gene expression levels
  4. Normalization to account for technical variations
  5. Statistical analysis to identify differentially expressed genes

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