Multiomics Analysis FAQ

• • What Software Should Be Used to Analyze Third-Generation Full-Length 16S

  After obtaining full-length 16S rRNA sequences using third-generation sequencing technologies, the following software tools can be employed for downstream data analysis: 1. QIIME 2 A widely adopted platform for microbiome data analysis, offering a comprehensive pipeline from quality control to operational taxonomic unit (OTU) clustering and diversity assessment. 2. Mothur Another robust toolset for analyzing 16S rRNA sequence data, providing an integrated suite of functions for sequence processing and......

• • What Are the Steps and Principles of Transcriptome Sequencing

  Steps of Transcriptome Sequencing 1. RNA Extraction Total RNA, including messenger RNA (mRNA) and various types of non-coding RNA, is extracted from biological samples using specialized reagent kits, such as TRIzol or Qiagen RNeasy. 2. RNA Quality and Quantity Assessment (1) Quality Control: The integrity of the extracted RNA is evaluated using a microfluidic-based bioanalyzer system (e.g., Agilent Bioanalyzer) or agarose gel electrophoresis. (2) Quantification: RNA concentration is determined using........

• • What Are the Sample Submission Requirements for Regular Transcriptome Sequencing

  Sample Submission Requirements for Standard Transcriptome Sequencing: 1. Sample Type: The samples should consist of either total RNA or enriched mRNA. 2. Quantity and Quality: A minimum quantity of 1-5 µg of RNA is required. The RNA should be of high quality, with an RNA Integrity Number (RIN) of 7.0 or higher, as assessed by standard integrity evaluation methods. 3. Purity: The purity of the RNA should be confirmed by an OD260/280 ratio between 1.8 and 2.0, indicating minimal contamination by proteins or..

• • What Is the Appropriate Amount of Sequencing Data for Transcriptome Sequencing

  The sequencing data requirements for RNA-seq are contingent on the specific objectives and nature of your research. Below is a guideline for reference: 1. Gene Expression Quantification: To accurately quantify gene expression levels, it is generally necessary to obtain at least 30-50 million paired-end sequencing reads per sample. 2. Differential Expression Analysis: For the purpose of differential expression analysis, it is advised to acquire a minimum of 20-30 million paired-end sequencing reads per......

• • What Is the Difference Between Transcriptome Sequencing and RNA-Seq

  Transcriptome sequencing is a technique that employs high-throughput sequencing technologies to study the transcriptome. This approach enables the profiling of all RNA molecules present in a given organism or cell type. RNA sequencing (RNA-seq) is a specialized form of transcriptome sequencing, focused specifically on measuring the levels of mRNA (messenger RNA) within the transcriptome using advanced deep sequencing methods.

• • How Can Gene Expression Levels of Specific Genes Be Quantified Across Different Species in Transcriptome Sequencing?

  To quantify the expression levels of specific genes across different species, the following approach can be applied:   1. Quality Control and Data Cleaning Begin by assessing the raw sequencing data (FASTQ files) using quality control tools such as FastQC to evaluate sequencing quality, duplication levels, adaptor contamination, and other technical artifacts.   Based on the quality reports, employ sequence trimming tools like Trimmomatic or cutadapt to remove low-quality sequences, adaptors, and other......

• • Can Saccharomyces cerevisiae S288C Be Used as the Reference Genome for Transcriptome Sequencing of the BY4741 Strain?

  BY4741 and S288C are both commonly used laboratory strains of Saccharomyces cerevisiae. S288C is the reference strain of yeast, with its genome being the first to be fully sequenced, and it is widely used as a reference in various genomic tools and databases. BY4741, on the other hand, is a haploid strain derived from S288C and is frequently employed in genomic studies, including gene knockout experiments.   If you are conducting transcriptome sequencing (RNA-Seq) and require a reference genome for al......

• • What Are the Major Applications of RNA Sequencing (RNA-seq) in Biological and Medical Research?

  RNA sequencing (RNA-seq) is a powerful and widely adopted technique with broad applications across various domains of biological and medical research. Below are several key application areas of RNA-seq:   Gene Expression Profiling RNA-seq enables the quantification of gene expression across different biological samples or experimental conditions, facilitating the investigation of transcriptional regulation and the identification of genes with condition-specific expression changes.   Differential Gene ......

• • What Distinguishes Unigene from CDS in Eukaryotic De Novo Transcriptome Assembly?

  In eukaryotic de novo transcriptome assembly, the terms “Unigene” and “CDS” refer to distinct biological concepts and data entities, each serving different analytical purposes.   Unigene A Unigene typically represents a non-redundant set of assembled transcripts derived from RNA sequencing data. It is often constructed by clustering expressed sequence tags (ESTs) or mRNA sequences originating from the same gene locus. The Unigene concept is also associated with databases that integrate and classify su......

• • How Can Genomic, Transcriptomic, Proteomic, and Metabolomic Data Be Effectively Integrated?

  Integrating multi-omics datasets—including genomic, transcriptomic, proteomic, and metabolomic data—is a complex but increasingly essential task in systems biology. The following outlines a systematic approach and key steps for effective integration:   Define the Research Objective and Biological Question The first step in multi-omics integration is to clearly identify the research goal, which directly influences the integration strategy:   1. Disease Mechanism Elucidation Focuses on analyzing cross-t......