Multi-Omics Analysis FAQ Summary
• What are the steps for transcriptome sample extraction?
The core of transcriptome sample extraction lies in the extraction and quality control of high-quality total RNA. The entire process must avoid RNA degradation and retain the original transcript expression information as much as possible. The following are standardized steps: 1. Sample Preparation Sample Types: can be cells, tissues, fresh or frozen samples; it is recommended to use liquid nitrogen for rapid freezing and store at -80°C or in RNA preservation solution. Precautions: Avoid RNase contamination throughout the process, using DEPC-treated tools and reagents. 2. RNA Extraction Common methods include: TRIzol method (phenol/chloroform method): suitable for most tissue samples, high extraction efficiency; column-based kits (e.g., Qiagen RNeasy): easy to operate, suitable for high-throughput sample processing, better purity but slightly lower yield. The steps are summarized as follows: 1. Cell/Tissue Lysis: Add TRIzol or lysis buffer and thoroughly homogenize. 2. Phase Separation: Add chloroform, centrifuge to separate layers, and collect the aqueous phase. 3. RNA Precipitation: Add isopropanol and centrifuge to recover RNA. 4. Washing and Resuspension: After washing with 70–75% ethanol, resuspend RNA in nuclease-free water. 5. (Optional) Removal of gDNA contamination: DNase I treatment (strongly recommended). 3. RNA Quality Control 1. Concentration Measurement: NanoDrop or Qubit, requiring A260/280 ≈ 2.0, A260/230 ≥ 1.8. 2. Integrity Assessment: Use Agilent Bioanalyzer or TapeStation to determine the RIN value.......
• How much gram of lychee peel is enough for transcriptome sequencing?
The amount of sample required for transcriptome sequencing mainly depends on the RNA content and extraction efficiency of the sample itself. For plant tissues (such as lychee peel), it is generally recommended to prepare 0.5–1 g of fresh tissue per sample; if the sample has high moisture content or low RNA yield, it can be increased to 1–2 g; if the sample is a powdered form that has been ground in liquid nitrogen, about 0.5 g is usually sufficient, provided it is ground evenly and without degradation. It is recommended to freeze immediately in liquid nitrogen, grind thoroughly, and avoid RNA degradation. Samples can be packaged separately for frozen transport (using dry ice or liquid nitrogen). If multiple replicates or time points are planned, each sample should be weighed and stored independently to avoid mixing.
• How to analyze the results of transcriptome sequencing?
After the results of transcriptome sequencing (RNA-Seq) come back, the analysis steps typically include the following main stages, each with its specific processing methods and software tools: 1. Data Quality Control 1. FastQC Analysis: Use tools like FastQC to perform quality control on the raw data, assessing the quality of sequencing data, such as base quality scores, GC content, and sequence length distribution. 2. Data Trimming: Use tools like Trimmomatic or Cutadapt to remove low-quality sequences, adapter sequences, and overly short reads to ensure the accuracy of subsequent analyses. 2. Sequence Alignment 1. Choose Alignment Software: Common alignment tools include HISAT2 and STAR, which align the processed reads to the reference genome or transcriptome; the choice of alignment depends on the sequencing platform, species, and complexity of the genome. 2. Assess Alignment Rate: By examining the alignment rate, one can determine the quality of the sequencing data and the suitability of the reference genome; typically, a high-quality RNA-Seq experiment should have a high alignment rate (>70%). 3. Transcript Assembly and Quantification 1. StringTie or Cufflinks: If transcript assembly is needed, tools like StringTie or Cufflinks can be used to assemble transcripts from the alignment results, identifying new transcripts or new genes. 2. Gene Expression Quantification: Use HTSeq, FeatureCounts, Salmon, or Kall...
In the joint analysis of proteomics and transcriptomics, the phenomenon of only 3 genes being commonly upregulated and no commonly downregulated genes may be caused by multiple factors: 1. Differences in the regulation of transcription and translation 1.1 Differences between transcription level and translation level Transcriptomic analysis focuses on mRNA levels, while proteomic analysis focuses on protein levels, which are not always consistent. The stability of mRNA, translation efficiency, and protein degradation rates can all affect the final results. 1.2 Post-translational regulation During the mRNA translation process, factors such as miRNA may regulate translation, affecting protein abundance. 2. Differences in technical sensitivity and data analysis methods 2.1 Differences in technical sensitivity Transcriptomics technologies (like RNA-Seq) can detect low-abundance mRNAs, but mass spectrometry faces challenges in detecting low-abundance proteins, leading to situations where certain genes are upregulated at the mRNA level but not significantly at the protein level. 2.2 Differences in data analysis methods When performing joint analyses, different analysis methods (such as normalization, filtering criteria, statistical significance standards) may lead to different results. For example, using different differential expression screening thresholds (like p-values, Fold change) in proteomic and transcriptomic data can affect the number of commonly upregulated or downregulated genes. 3. Temporal differences in biological processes There is a time lag between transcription and translation, with some genes quickly upregulated at the mRNA level, while changes in protein levels may take time, resulting in an inability to observe downregulated genes at specific time points. ...
If some samples fail quality inspection during regular transcriptome sequencing, it is completely acceptable to resend these samples. The resubmitted samples can still be analyzed together with the previously qualified samples in terms of technical process and data analysis, but the following points should be noted to ensure consistency in data quality:
The collection and transport methods for fecal samples must be strictly determined based on the subsequent experimental type. For microbiome studies, it is recommended to use specialized preservation solutions to stabilize microbial DNA; for metabolomics, any preservation solution must be avoided, and samples should be flash-frozen to retain the original state of metabolites; for transcriptomics, RNA protection solution or rapid freezing is necessary to prevent RNA degradation. During transport, it is essential to ensure that the cold chain is intact and that samples are packaged according to standards to guarantee the accuracy and reproducibility of downstream experimental data. Choosing the appropriate preservation strategy is a key step in ensuring high-quality research results.
When analyzing the role of probiotic metabolic products against pathogens, due to the diversity of metabolites including exopolysaccharides, proteins, organic acids, etc., it is necessary to comprehensively utilize metabolomics, glycomics, and proteomics. Metabolomics is suitable for the detection of small molecule metabolites; glycomics specifically studies large molecules such as exopolysaccharides; proteomics analyzes antimicrobial proteins and other functional proteins. Therefore, adopting a multi-omics integrated analysis is the best strategy for obtaining comprehensive results.
De novo Transcriptome Assembly does not have a reference genome, so it cannot directly provide exon position information for genes. However, the availability of gene information depends on subsequent analysis steps. Here are several types of files that may contain information useful for primer design:
• Can RNA be extracted from freeze-dried samples?
RNA can be extracted from freeze-dried samples, but there are some issues to pay attention to during the extraction process. The freeze-drying (lyophilization) process usually removes moisture from the samples, which may have a certain impact on the cellular structure and the integrity of RNA. Therefore, special care must be taken during RNA extraction to ensure that the quality of RNA is not compromised.
In transcriptomics analysis, selecting an appropriate reference genome is crucial for the reliability and biological significance of the results. An alignment rate of only 60% indicates that there may be the following issues:
How to order?
