"Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts."
The study of the transcriptome, or the complete set of RNA transcripts produced by a cell or population.
Gene expression: The process by which information from a gene is used to create a functional product such as a protein.
RNA sequencing: The use of high-throughput sequencing technologies to decipher the full complement of RNA molecules present in a biological sample.
Microarray analysis: A technique used to measure gene expression levels across the entire genome using microarray chips that contain thousands of genes.
Assembly and annotation of transcriptomes: The process of reconstructing complete transcripts from RNA sequencing reads and annotating them to identify their source genes and potential functions.
Differential expression analysis: Comparison of gene expression levels between two or more biological samples to identify genes that are differentially expressed under different conditions.
Gene ontology analysis: A method used to assign functional annotations to genes based on their sequence similarity to other known functional genes.
Pathway analysis: A method used to identify the biological pathways that are enriched in a set of differentially expressed genes.
Alternative splicing: The process of generating multiple mRNA isoforms from a single gene by differential exon usage, which can lead to functional diversity of the resulting proteins.
Long non-coding RNAs: Non-coding RNA molecules longer than 200 nucleotides that have been shown to play important roles in regulating gene expression.
Single-cell transcriptomics: The use of RNA sequencing to profile transcriptomes of individual cells, which allows the study of cell-to-cell variation and identification of rare cell types.
RNA editing: The process of modifying RNA molecules after they have been transcribed from DNA, which can affect their stability, structure, and function.
Epigenetics and transcriptomics: Epigenetic modifications such as DNA methylation and histone modifications can regulate gene expression by altering the accessibility of DNA to transcription factors and other regulatory proteins.
Non-coding RNAs and gene regulation: Various types of non-coding RNAs, such as microRNAs and siRNAs, can bind to mRNA molecules and regulate their stability and translation into protein.
Single-nucleotide polymorphism (SNP) analysis: The identification of genetic variations in the DNA sequence that can affect gene expression and transcriptome structure.
Transcription factors and gene regulation: Transcription factors are proteins that bind to DNA and regulate gene expression by either promoting or inhibiting transcription initiation.
RNA sequencing (RNA-Seq): RNA-Seq is a high-throughput technique used to detect and quantify RNA transcripts in a sample. This technique provides information on both the type and abundance of RNA molecules present in a cell or tissue.
Single-cell RNA sequencing (scRNA-Seq): This technique allows scientists to analyze the expression of genes at the single-cell level. It provides unique insights into the heterogeneity of cell populations and cellular decision-making processes.
Differential gene expression (DGE) analysis: DGE analysis is a technique used to compare the expression levels of genes between two or more samples. It is commonly used to identify differentially expressed genes that may be involved in disease, development, or other biological processes.
Microarray analysis: Microarray analysis measures the expression levels of genes on a microarray chip. It is a widely used technology for the simultaneous analysis of thousands of genes in a single experiment.
Reverse transcription polymerase chain reaction (RT-PCR): RT-PCR is a quantitative technique that is used to measure the expression of specific genes. It is a useful tool for validating the results of high-throughput sequencing experiments.
Quantitative real-time PCR (qPCR): This technique is similar to RT-PCR but measures the amount of cDNA in real-time during the amplification process. It is widely used for gene expression analysis and a variety of other applications.
RNA interference (RNAi): RNAi is a technique used to knock down specific genes in cells by introducing small interfering RNA (siRNA) molecules that target mRNA transcripts. It is widely used for functional genomics and drug discovery.
Ribosome profiling (Ribo-Seq): Ribo-Seq is a technique used to identify the specific mRNA molecules that are actively being translated by ribosomes. This technique can provide insight into translation efficiency and the regulation of gene expression.
Single-molecule real-time sequencing (SMRT): SMRT sequencing is a technique used to sequence individual RNA molecules in real-time. It provides highly accurate long-read sequencing data that is useful for genome assembly, transcriptome analysis, and other applications.
Nanopore sequencing: This is a real-time sequencing technology that can detect changes in electrical current as RNA molecules pass through a nanopore. It provides long-read sequencing and has a wide variety of applications in transcriptomics and other fields.
"A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant."
"A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated."
"The first attempts to study whole transcriptomes began in the early 1990s."
"There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA-Seq, which uses high-throughput sequencing to record all transcripts."
"Subsequent technological advances since the late 1990s have repeatedly transformed the field and made transcriptomics a widespread discipline in biological sciences."
"As the technology improved, the volume of data produced by each transcriptome experiment increased. As a result, data analysis methods have steadily been adapted to more accurately and efficiently analyze increasingly large volumes of data."
"Transcriptome databases getting bigger and more useful as transcriptomes continue to be collected and shared by researchers."
"Measuring the expression of an organism's genes in different tissues or conditions, or at different times, gives information on how genes are regulated and reveals details of an organism's biology."
"Transcriptome analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease."
"It can also be used to infer the functions of previously unannotated genes."
"An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays."
"The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions."
"A transcriptome captures a snapshot in time of the total transcripts present in a cell."
"It would be almost impossible to interpret the information contained in a transcriptome without the knowledge of previous experiments."
"A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells."
"Subsequent technological advances since the late 1990s have repeatedly transformed the field and made transcriptomics a widespread discipline in biological sciences."
"There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA-Seq, which uses high-throughput sequencing to record all transcripts."
"Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant."
"As the technology improved, the volume of data produced by each transcriptome experiment increased."