DNA microarrays, also known as DNA chips, allow simultaneous measurement of gene expression levels for every gene in a genome. They detect mRNA levels by hybridizing cDNA to arrays of gene probes spotted on glass slides or other surfaces. Differences in gene expression between cell types or conditions can be measured and analyzed to answer biological questions.
Dr. Shamalamma S. presented on DNA microarrays. DNA microarrays allow thousands of genes to be compared simultaneously by attaching DNA probes to a chip which fluorescently labeled samples can bind to. The chip is then scanned to analyze gene expression levels. Applications include disease diagnosis, toxicology studies, and pharmacogenomics. While a powerful tool, microarrays have limitations such as lack of knowledge about many genes and lack of standardization.
The document provides an overview of the history and techniques of transcriptome analysis. It discusses how RNA was separated from DNA with the formulation of the central dogma in 1958. Key developments include the discoveries of messenger RNA, transfer RNA, and ribosomal RNA in the 1960s. The document outlines techniques such as serial analysis of gene expression (SAGE) and RNA sequencing (RNA-seq) that allow comprehensive analysis of gene expression patterns. It provides details on the basic steps and advantages of SAGE and describes how next generation sequencing revolutionized transcriptome analysis through massive parallel sequencing.
1. A DNA microarray contains thousands of DNA probes attached to a solid surface in defined locations. Each probe represents a single gene.
2. Sample mRNA is converted to fluorescently labeled cDNA and hybridized to the DNA microarray. The level of fluorescence indicates the expression level of each gene.
3. After washing, the microarray is scanned and analyzed to determine changes in gene expression between control and test samples. This allows high-throughput analysis of gene expression profiles.
This document discusses DNA microarrays, including:
1. DNA microarrays contain many DNA probes attached to a solid surface that allow measurement of gene expression levels or genotyping of many regions simultaneously through hybridization.
2. The core principle is hybridization - complementary nucleic acid sequences pair through hydrogen bonds, and fluorescent labeling allows detection of binding to quantify expression.
3. DNA microarrays have many applications including gene expression profiling, disease diagnosis, drug discovery, and toxicology research.
Gene expression and transcript profiling involves determining the pattern of genes expressed at the transcriptional level under specific circumstances by measuring the expression of thousands of genes simultaneously. This allows one to understand cellular function. Common techniques for profiling include DNA microarrays, RNA sequencing, and EST tags. DNA microarrays involve hybridizing cDNA or cRNA samples to probes on a chip to determine relative abundance of sequences. RNA sequencing uses next-generation sequencing to reveal presence and quantity of RNA in a sample.
This session will follow up from transcript quantification of RNAseq data and discusses statistical means of identifying differentially regulated transcripts, and isoforms and contrasts these against microarray analysis approaches.
Microarrays allow researchers to study gene expression across thousands of genes simultaneously. They work by hybridizing labeled cDNA or cRNA to probes attached to a solid surface, then detecting and quantifying the hybridized genes. The document outlines the history and development of microarray technology. It describes the key steps in a DNA microarray experiment including tissue collection, RNA isolation, cDNA synthesis, hybridization to the array, scanning, and data analysis. Applications include studying gene expression in health and disease, drug development, and pharmacogenomics. Advantages are the ability to study many genes at once, while limitations include expense and complexity of data analysis.
MicroRNAs (miRNAs) are small non-coding RNAs that play important gene regulatory roles in eukaryotic cells. They are approximately 22 nucleotides in length and are transcribed from independent genes or introns, then processed through a biogenesis pathway before targeting mRNAs for silencing or degradation. MiRNAs regulate genes involved in development, metabolism, and diseases like cancer. Their expression and function is tightly controlled through transcriptional and post-transcriptional mechanisms in order to influence protein expression levels. While much progress has been made in understanding miRNAs, further study is still needed to elucidate their complex regulatory networks and roles in development and disease.
DNA microarrays allow scientists to measure gene expression levels across large numbers of genes simultaneously. A DNA microarray consists of microscopic DNA spots attached to a solid surface. There are five main steps to performing a microarray: sample preparation and labeling, hybridization, washing, image acquisition, and data analysis. Microarrays use the principle of hybridization between complementary DNA strands, where fluorescent labeled target sequences bind to probe sequences on the array, generating signals to measure expression levels. Microarrays have applications in gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicological research.
Next generation sequencing (NGS) refers to modern DNA sequencing technologies that allow for high-speed, low-cost sequencing of entire genomes. NGS works by massively parallel sequencing of millions of DNA fragments. The Illumina sequencing by synthesis method is the most commonly used NGS approach. It involves library preparation, cluster generation on a flow cell, sequencing via reversible dye-terminator chemistry, and computational analysis of sequenced reads. Key advantages of NGS include its scalability, unlimited dynamic range, tunable coverage levels, and ability to multiplex many samples simultaneously in a single run.
it will help you to understand how the protein microarrays are made, what are the different types and what all purposes they are used for. its very useful ppt
DNA SEQUENCING METHODS AND STRATEGIES FOR GENOME SEQUENCINGPuneet Kulyana
This presentation will give you a brief idea about the various DNA sequencing methods and various strategies used for genome sequencing and much more vital information related to gene expression and analysis
Microarrays allow researchers to analyze gene expression levels across thousands of genes simultaneously. DNA microarrays work by hybridizing fluorescently-labeled cDNA or cRNA to complementary DNA probes attached to a solid surface. This technology has applications in gene expression profiling, disease diagnosis, drug discovery, and toxicology research. While microarrays provide high-throughput analysis, their limitations include not reflecting true protein levels, complex data analysis, expense, and short shelf life of DNA chips.
This document discusses various gene sequencing methods. It begins by introducing DNA and the importance of sequencing the genetic code. It then describes several early sequencing techniques like Sanger sequencing using chain termination or chemical cleavage. It discusses the need for sequencing to understand genetic conditions. The document also covers topics like genome sequencing, genomics, and high-throughput sequencing techniques like dye-terminator sequencing which replaced radioactive labels with fluorescent labels to automate the process.
This document discusses differential gene profiling methods, specifically differential display and subtractive hybridization. It provides details on how differential display and subtractive hybridization work, including that differential display allows comparison of gene expression between two samples and was commonly used in the 1990s before being replaced by microarrays in 2000. Subtractive hybridization identifies differences in nucleic acids between two populations and enriches for sequences not common to both. The document discusses applications and references for further information.
The document discusses Sanger sequencing, a method of DNA sequencing. It provides a brief history of DNA sequencing, noting that Sanger developed an enzymatic DNA sequencing technique in 1977. The document then describes the key steps of Sanger sequencing, including separating the DNA strands, copying one strand with chemically altered bases that cause termination, and analyzing the fragments to reveal the DNA sequence. It also compares Sanger sequencing to the Maxam-Gilbert chemical degradation method.
This document discusses small interfering RNA (siRNA), which are double stranded RNA molecules that play a role in RNA interference (RNAi) pathways by interfering with gene expression of complementary nucleotide sequences. siRNAs are naturally produced by the enzyme Dicer but can also be artificially introduced. The document provides details on siRNA structure, the RNAi mechanism, guidelines for effective siRNA design, methods of siRNA synthesis, delivery methods, and applications in gene silencing research and potential therapies.
Whole genome sequencing is a technique to sequence the entire genome of an organism. It involves breaking the genome into small fragments, copying the fragments, sequencing the fragments, and reassembling the sequence data into the full genome. Key steps include isolating DNA, fragmenting it, ligating fragments into plasmids, amplifying the plasmids, sequencing the fragments using Sanger sequencing, and assembling the sequence reads into the complete genome. Whole genome sequencing allows researchers to discover coding and non-coding regions, predict disease susceptibility, and perform evolutionary studies by comparing species.
Microarrays allow researchers to analyze gene expression and detect mutations across thousands of genes simultaneously. They consist of miniaturized spots containing DNA, proteins, or other biomolecules immobilized on a solid surface. When a fluorescently labeled sample is applied, only matching molecules will hybridize, allowing for quantification. The main types are DNA microarrays for analyzing gene expression, tissue microarrays for pathology studies, and peptide arrays for protein interactions. DNA microarrays use glass slides coated with specific DNA sequences to analyze gene expression profiles in tissues or cells.
This document discusses various molecular marker techniques used in genetics, including their discovery and applications. It covers:
- RFLP (restriction fragment length polymorphism), the first widely used molecular marker technique, which detects variations in DNA fragments after restriction enzyme digestion.
- RAPD (random amplified polymorphic DNA) which uses random primers to amplify variable DNA regions by PCR for genetic mapping.
- AFLP (amplified fragment length polymorphism) which combines restriction enzyme digestion and PCR amplification to generate multiple polymorphic DNA fragments.
- SSR (simple sequence length polymorphism) markers which detect variations in short tandem repeats useful for genetic linkage maps.
- SNPs (single nucleotide polymorphisms)
The DNA microarray is a tool used to determine whether the DNA from a particular individual contains a mutation in genes like BRCA1 and BRCA2. The chip consists of a small glass plate encased in plastic. Some companies manufacture microarrays using methods similar to those used to make computer microchips.
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
Microarrays allow researchers to analyze gene expression across thousands of genes simultaneously. DNA probes are arrayed on a small glass or nylon slide, and labeled mRNA from samples is hybridized to the probes. Fluorescent scanning detects which genes are expressed. Data analysis includes normalization, distance metrics, clustering, and visualization to group genes with similar expression profiles and identify patterns of co-regulated genes. Microarrays enable functional genomics studies of development, disease, response to drugs or environmental factors, and more.
This document provides an overview of DNA microarrays, also known as DNA chips. It discusses the principles and techniques used to prepare DNA microarrays, including photolithography. There are two main types of DNA chips: cDNA-based chips and oligonucleotide-based chips. DNA microarrays have various applications, including gene expression profiling, drug discovery, and diagnostics. They provide the advantage of analyzing thousands of genes simultaneously but also have disadvantages such as high costs and complex data analysis.
Microarray technology allows researchers to analyze the expression levels of thousands of genes simultaneously using DNA probes attached to a solid surface. There are two main types of microarrays: glass cDNA microarrays which involve spotting pre-fabricated cDNA fragments on glass slides; and high-density oligonucleotide arrays which involve the in situ synthesis of oligonucleotides on a chip. The key steps in a microarray experiment are sample preparation and labeling, hybridization of labeled cDNA to the probes, washing, and image analysis to quantify gene expression levels. Microarrays have numerous applications including gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicology research.
RNASeq - Analysis Pipeline for Differential ExpressionJatinder Singh
RNA-Seq is a technique that uses next generation sequencing to sequence RNA transcripts and quantify gene expression levels. It can be used to estimate transcript abundance, detect alternative splicing, and compare gene expression profiles between healthy and diseased tissue. Computational challenges include read mapping due to exon-exon junctions and normalization of read counts. Key steps in RNA-Seq analysis include read mapping, transcript assembly, counting and normalizing reads, and detecting differentially expressed genes.
MicroRNAs (miRNAs) are small non-coding RNAs that play important gene regulatory roles in eukaryotic cells. They are approximately 22 nucleotides in length and are transcribed from independent genes or introns, then processed through a biogenesis pathway before targeting mRNAs for silencing or degradation. MiRNAs regulate genes involved in development, metabolism, and diseases like cancer. Their expression and function is tightly controlled through transcriptional and post-transcriptional mechanisms in order to influence protein expression levels. While much progress has been made in understanding miRNAs, further study is still needed to elucidate their complex regulatory networks and roles in development and disease.
DNA microarrays allow scientists to measure gene expression levels across large numbers of genes simultaneously. A DNA microarray consists of microscopic DNA spots attached to a solid surface. There are five main steps to performing a microarray: sample preparation and labeling, hybridization, washing, image acquisition, and data analysis. Microarrays use the principle of hybridization between complementary DNA strands, where fluorescent labeled target sequences bind to probe sequences on the array, generating signals to measure expression levels. Microarrays have applications in gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicological research.
Next generation sequencing (NGS) refers to modern DNA sequencing technologies that allow for high-speed, low-cost sequencing of entire genomes. NGS works by massively parallel sequencing of millions of DNA fragments. The Illumina sequencing by synthesis method is the most commonly used NGS approach. It involves library preparation, cluster generation on a flow cell, sequencing via reversible dye-terminator chemistry, and computational analysis of sequenced reads. Key advantages of NGS include its scalability, unlimited dynamic range, tunable coverage levels, and ability to multiplex many samples simultaneously in a single run.
it will help you to understand how the protein microarrays are made, what are the different types and what all purposes they are used for. its very useful ppt
DNA SEQUENCING METHODS AND STRATEGIES FOR GENOME SEQUENCINGPuneet Kulyana
This presentation will give you a brief idea about the various DNA sequencing methods and various strategies used for genome sequencing and much more vital information related to gene expression and analysis
Microarrays allow researchers to analyze gene expression levels across thousands of genes simultaneously. DNA microarrays work by hybridizing fluorescently-labeled cDNA or cRNA to complementary DNA probes attached to a solid surface. This technology has applications in gene expression profiling, disease diagnosis, drug discovery, and toxicology research. While microarrays provide high-throughput analysis, their limitations include not reflecting true protein levels, complex data analysis, expense, and short shelf life of DNA chips.
This document discusses various gene sequencing methods. It begins by introducing DNA and the importance of sequencing the genetic code. It then describes several early sequencing techniques like Sanger sequencing using chain termination or chemical cleavage. It discusses the need for sequencing to understand genetic conditions. The document also covers topics like genome sequencing, genomics, and high-throughput sequencing techniques like dye-terminator sequencing which replaced radioactive labels with fluorescent labels to automate the process.
This document discusses differential gene profiling methods, specifically differential display and subtractive hybridization. It provides details on how differential display and subtractive hybridization work, including that differential display allows comparison of gene expression between two samples and was commonly used in the 1990s before being replaced by microarrays in 2000. Subtractive hybridization identifies differences in nucleic acids between two populations and enriches for sequences not common to both. The document discusses applications and references for further information.
The document discusses Sanger sequencing, a method of DNA sequencing. It provides a brief history of DNA sequencing, noting that Sanger developed an enzymatic DNA sequencing technique in 1977. The document then describes the key steps of Sanger sequencing, including separating the DNA strands, copying one strand with chemically altered bases that cause termination, and analyzing the fragments to reveal the DNA sequence. It also compares Sanger sequencing to the Maxam-Gilbert chemical degradation method.
This document discusses small interfering RNA (siRNA), which are double stranded RNA molecules that play a role in RNA interference (RNAi) pathways by interfering with gene expression of complementary nucleotide sequences. siRNAs are naturally produced by the enzyme Dicer but can also be artificially introduced. The document provides details on siRNA structure, the RNAi mechanism, guidelines for effective siRNA design, methods of siRNA synthesis, delivery methods, and applications in gene silencing research and potential therapies.
Whole genome sequencing is a technique to sequence the entire genome of an organism. It involves breaking the genome into small fragments, copying the fragments, sequencing the fragments, and reassembling the sequence data into the full genome. Key steps include isolating DNA, fragmenting it, ligating fragments into plasmids, amplifying the plasmids, sequencing the fragments using Sanger sequencing, and assembling the sequence reads into the complete genome. Whole genome sequencing allows researchers to discover coding and non-coding regions, predict disease susceptibility, and perform evolutionary studies by comparing species.
Microarrays allow researchers to analyze gene expression and detect mutations across thousands of genes simultaneously. They consist of miniaturized spots containing DNA, proteins, or other biomolecules immobilized on a solid surface. When a fluorescently labeled sample is applied, only matching molecules will hybridize, allowing for quantification. The main types are DNA microarrays for analyzing gene expression, tissue microarrays for pathology studies, and peptide arrays for protein interactions. DNA microarrays use glass slides coated with specific DNA sequences to analyze gene expression profiles in tissues or cells.
This document discusses various molecular marker techniques used in genetics, including their discovery and applications. It covers:
- RFLP (restriction fragment length polymorphism), the first widely used molecular marker technique, which detects variations in DNA fragments after restriction enzyme digestion.
- RAPD (random amplified polymorphic DNA) which uses random primers to amplify variable DNA regions by PCR for genetic mapping.
- AFLP (amplified fragment length polymorphism) which combines restriction enzyme digestion and PCR amplification to generate multiple polymorphic DNA fragments.
- SSR (simple sequence length polymorphism) markers which detect variations in short tandem repeats useful for genetic linkage maps.
- SNPs (single nucleotide polymorphisms)
The DNA microarray is a tool used to determine whether the DNA from a particular individual contains a mutation in genes like BRCA1 and BRCA2. The chip consists of a small glass plate encased in plastic. Some companies manufacture microarrays using methods similar to those used to make computer microchips.
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
Microarrays allow researchers to analyze gene expression across thousands of genes simultaneously. DNA probes are arrayed on a small glass or nylon slide, and labeled mRNA from samples is hybridized to the probes. Fluorescent scanning detects which genes are expressed. Data analysis includes normalization, distance metrics, clustering, and visualization to group genes with similar expression profiles and identify patterns of co-regulated genes. Microarrays enable functional genomics studies of development, disease, response to drugs or environmental factors, and more.
This document provides an overview of DNA microarrays, also known as DNA chips. It discusses the principles and techniques used to prepare DNA microarrays, including photolithography. There are two main types of DNA chips: cDNA-based chips and oligonucleotide-based chips. DNA microarrays have various applications, including gene expression profiling, drug discovery, and diagnostics. They provide the advantage of analyzing thousands of genes simultaneously but also have disadvantages such as high costs and complex data analysis.
Microarray technology allows researchers to analyze the expression levels of thousands of genes simultaneously using DNA probes attached to a solid surface. There are two main types of microarrays: glass cDNA microarrays which involve spotting pre-fabricated cDNA fragments on glass slides; and high-density oligonucleotide arrays which involve the in situ synthesis of oligonucleotides on a chip. The key steps in a microarray experiment are sample preparation and labeling, hybridization of labeled cDNA to the probes, washing, and image analysis to quantify gene expression levels. Microarrays have numerous applications including gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicology research.
RNASeq - Analysis Pipeline for Differential ExpressionJatinder Singh
RNA-Seq is a technique that uses next generation sequencing to sequence RNA transcripts and quantify gene expression levels. It can be used to estimate transcript abundance, detect alternative splicing, and compare gene expression profiles between healthy and diseased tissue. Computational challenges include read mapping due to exon-exon junctions and normalization of read counts. Key steps in RNA-Seq analysis include read mapping, transcript assembly, counting and normalizing reads, and detecting differentially expressed genes.
This document provides an introduction to RNA sequencing (RNA-Seq) applications using next-generation sequencing technologies. It discusses how RNA-Seq can be used to identify which genes are expressed, detect differential gene expression between samples, identify splicing isoforms, and detect genetic variants and structural variations. The document reviews Illumina sequencing by synthesis, the most common platform, outlining the work flow from sample acquisition, RNA extraction and library preparation to sequencing. It also discusses considerations for different sample types and extraction methods.
If a microbiologist is studying bacteria that premeditate, or break down, toxic wastes and wants to know which specific genes are active when that bacterium is degrading, say, PCBs, he would likely use a tool called the DNA microarray.
Microarrays enable scientists to monitor the activities of hundreds or thousands of genes at once. All microarrays (also called DNA chips or gene chips) work on the basic principle that complementary nucleotide sequences in DNA (and RNA) match up like the two halves of a piece of Velcro coming together.
Pattern of gene activity on a microarray chip.
A microarray consists of an orderly arrangement of bits of genetic material in super-tiny spots laid down in a grid on a suitable surface, often a glass slide with a specially chemically treated surface.
The document discusses allele mining, which aims to identify allelic variations in genetic resources collections that are relevant for traits of interest. It describes how allele mining works to unlock hidden genetic variation by identifying single nucleotide polymorphisms and new haplotypes. The document then provides details on a case study of allele mining focused on three genes - calmodulin, LEA3, and SalT - important for abiotic stress tolerance in rice and related species. Primers were developed to amplify regions of these three genes from 64 accessions representing rice and other grasses.
DNA microarrays allow simultaneous measurement of gene expression levels across an entire genome. They work by hybridizing fluorescently labeled cDNA or cRNA from a sample to complementary DNA probes affixed to a solid surface in a high-density array. After hybridization, the array is scanned and expression levels are quantified by fluorescence intensity. Microarrays can be used to compare gene expression between cell types, disease states, drug treatments, and developmental stages to better understand gene regulation and biological processes.
DNA microarrays allow scientists to analyze thousands of genes simultaneously. They work by attaching DNA probes to a plate to measure gene expression levels in different samples. The process involves isolating mRNA from samples, converting it to labeled cDNA, hybridizing it to the microarray plate, and scanning the plate to analyze gene expression differences between samples. Microarrays have benefits like speed and analyzing many genes at once, though they also produce large amounts of data to analyze. Future uses include disease diagnosis, pharmacogenomics, and toxicogenomics research.
The document discusses DNA microarrays, including their applications, history, major steps, methods of construction, and technical issues. DNA microarrays allow analysis of gene expression across thousands of genes simultaneously. They have been used since the 1990s and are constructed by attaching DNA probes to a solid surface in a high-density array. Two main types are cDNA-based microarrays using amplified cDNA and oligonucleotide-based arrays like Affymetrix GeneChips containing short DNA sequences.
Gene Expression - Microarrays discusses analyzing gene expression data from microarray experiments. It describes the basic workflow including experimental design, sample preparation, hybridization, image analysis, preprocessing, normalization, and statistical analysis. Key points are that microarrays allow measuring expression of thousands of genes simultaneously, and proper experimental design and data analysis are important to draw meaningful biological conclusions from microarray data.
Molecular Biology research evolves through the development of the technologies used for carrying them out. It is not possible to research on a large number of genes using traditional methods
This document provides an overview of the course BIONF/BENG 203: Functional Genomics. It discusses the grading breakdown, course outline, sources of functional genomic data including expression data from microarrays and RNA-Seq, proteomic data from mass spectrometry, protein-protein interaction data, and systematic phenotyping data. High-throughput methods for measuring these various types of omics data are also summarized.
Bio-chips, also known as lab-on-a-chip devices, can provide portable, low-cost, and low-power platforms for integrating sensors and other components. DNA microarrays allow high-throughput screening by placing probes for thousands of genes on a single chip. mRNA is extracted from experimental and control samples, converted to fluorescent cDNA, and hybridized on the chip. The resulting colors indicate gene expression levels. Protein microarrays similarly attach thousands of proteins to a chip and use probes to study protein interactions, expression profiles, and biochemical functions through detection of reaction products. Technical challenges include maintaining protein activity and structure during immobilization and detection.
Bio-chips, also known as lab-on-a-chip devices, can provide portable, low-cost, and low-power platforms for integrating sensors and other components. DNA microarrays allow high-throughput screening by placing probes for thousands of genes on a single chip. mRNA is extracted from experimental and control samples, converted to fluorescent cDNA, and hybridized on the chip. The fluorescent intensities indicate gene expression levels. Protein microarrays similarly attach thousands of proteins to a chip and detect binding with probes to study protein interactions, expression levels, and functions.
SAGE (Serial analysis of Gene Expression)talhakhat
SAGE (Serial Analysis of Gene Expression) is a technique that allows for the rapid and comprehensive analysis of gene expression patterns in a given cell population. It works by isolating mRNA, synthesizing cDNA, ligating short sequence tags to the cDNA, and then counting the number of times each tag is observed to quantify gene expression levels. The tags are concatenated and sequenced to generate vast amounts of data that must be analyzed computationally to identify which genes particular tags correspond to and to compare expression profiles between cell types. SAGE provides an overview of a cell's complete transcriptional activity and has been applied to study differences in cancer vs normal cells and to identify targets of oncogenes and tumor suppressor genes.
The document discusses various applications and techniques of DNA microarrays, including summarizing key points about Affymetrix GeneChips, spotted microarrays, experimental design, data analysis, and several case studies on various topics like ovarian cancer, Sjogren's syndrome, wine yeast genomics, and norovirus genotyping. Microarrays allow analysis of gene expression patterns and copy number variations across genomes through comparative hybridization experiments. The document provides an overview of microarray technology and applications in genomic and biomedical research.
DNA microarrays allow researchers to study gene expression patterns across thousands of genes simultaneously. Microarrays work by hybridizing fluorescently-labeled cDNA or cRNA to complementary DNA probes affixed to a solid surface, such as a glass slide. There are two main types of microarrays: cDNA microarrays where cDNA fragments are spotted onto glass slides, and in situ synthesized oligonucleotide arrays with short DNA sequences directly built onto chips. Microarrays have numerous applications including gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicology research.
DNA Microarray introdution and applicationNeeraj Sharma
DNA microarrays allow researchers to analyze gene expression levels across thousands of genes simultaneously. A DNA microarray contains many DNA probes attached to a solid surface in a regular pattern. Researchers isolate mRNA from samples, convert it to cDNA, and label the cDNA with fluorescent dyes. They then hybridize the labeled cDNA to the probes on the microarray. A scanner detects the fluorescence at each probe location, allowing researchers to compare gene expression levels between samples by the intensity and color of fluorescence. Microarrays have applications in medicine, agriculture, forensics and toxicology by enabling the comparison of gene expression in different tissues or in response to different conditions.
This document provides an overview of DNA microarrays (DNA chips), including:
1. It describes how DNA microarrays work, the basic components and steps involved including manufacturing probes, sample preparation, hybridization, scanning, and data analysis.
2. It discusses the two main types of microarrays - cDNA microarrays produced by robotic spotting and oligonucleotide arrays produced by in situ synthesis.
3. It outlines some of the applications of DNA microarrays including analyzing gene expression, disease classification, toxicogenomics, and more.
The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2−ΔΔCT method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2−ΔΔCT method. In addition, we present the derivation and applications of two variations of the 2−ΔΔCT method that may be useful in the analysis of real-time, quantitative PCR data.
Microarrays allow researchers to examine gene expression patterns across thousands of genes simultaneously. A microarray contains probes for known genes that are used to detect complementary mRNA in a biological sample. Microarrays can be used to study gene expression differences between normal and diseased tissues, classify tumor subtypes, and diagnose cancers. They also show promise for personalized cancer treatment by predicting patient prognosis and response to therapy.
“MS-Extractor: An Innovative Approach to Extract Microsatellites on „Y‟ Chrom...IJERD Editor
Simple Sequence Repeats (SSR), also known as Microsatellites, have been extensively used as
molecular markers due to their abundance and high degree of polymorphism. The nucleotide sequences of
polymorphic forms of the same gene should be 99.9% identical. So, Microsatellites extraction from the Gene is
crucial. However, Microsatellites repeat count is compared, if they differ largely, he has some disorder. The Y
chromosome likely contains 50 to 60 genes that provide instructions for making proteins. Because only males
have the Y chromosome, the genes on this chromosome tend to be involved in male sex determination and
development. Several Microsatellite Extractors exist and they fail to extract microsatellites on large data sets of
giga bytes and tera bytes in size. The proposed tool “MS-Extractor: An Innovative Approach to extract
Microsatellites on „Y‟ Chromosome” can extract both Perfect as well as Imperfect Microsatellites from large
data sets of human genome „Y‟. The proposed system uses string matching with sliding window approach to
locate Microsatellites and extracts them.
DNA microarrays contain thousands of DNA probes attached to a solid surface that allow for the simultaneous analysis of gene expression across many genes. The core principle is based on DNA hybridization, where fluorescently labeled cDNA or RNA samples are hybridized to complementary probes on the array. By detecting which probes light up after hybridization and washing, researchers can determine which genes are expressed or detect genetic variations in the sample. Microarrays have numerous applications, including gene expression analysis, disease diagnosis, drug discovery, and toxicology research. They provide a fast way to study thousands of genes but results require further validation and correlations do not necessarily indicate causation.
This document provides an overview of Serial Analysis of Gene Expression (SAGE). SAGE allows for the digital analysis of overall gene expression patterns in a sample by producing a snapshot of the mRNA population. It provides a quantitative and comprehensive expression profile. The document outlines the key principles and steps of the SAGE methodology, including isolating mRNA, synthesizing cDNA, ligating linkers, releasing tags, concatenating tags, and sequencing. It also discusses various applications and advances of SAGE, such as LongSAGE, CAGE, and SuperSAGE. SAGE is a powerful tool for studying gene expression, but it has some limitations regarding transcript identification and quantitation bias.
The document discusses various sequence comparison techniques including pairwise alignment, local alignment, global alignment, and multiple alignment. It describes heuristic methods like FASTA and BLAST that are faster than dynamic programming but may miss optimal alignments. It provides details on the FASTA algorithm including finding identical words, re-scoring, joining segments, and dynamic programming. It also explains the BLAST algorithm and steps including query preprocessing, database scanning, and hit extension. Specialized BLAST databases and tools are also listed.
This document discusses RNA interference (RNAi) and its mechanisms. It can be summarized as follows:
1. RNAi is a process where double-stranded RNA causes degradation of homologous mRNA sequences. It was discovered in 1998 and is found across many organisms.
2. The RNAi pathway involves conversion of dsRNA to siRNAs by the enzyme Dicer. siRNAs are incorporated into the RISC complex containing Argonaute proteins. RISC then cleaves and destroys homologous mRNA targets.
3. miRNAs are endogenous single-stranded RNAs that regulate gene expression at the translation level by preventing ribosome binding. They are processed from hairpin precursors by the enzymes Dro
The document discusses the field of proteomics, which is the large-scale study of proteins, including their functions and structures. It defines proteomics and describes several areas within it, such as functional proteomics, expressional proteomics, and structural proteomics. It outlines typical proteomics experiments and some key methods used, including two-dimensional electrophoresis, mass spectrometry, and protein-protein interaction prediction methods like phylogenetic profiling.
Genetic mapping uses genetic techniques like cross-breeding experiments to construct maps showing gene positions. Physical mapping uses molecular techniques to examine DNA directly and construct maps showing sequence features. Different DNA markers like RFLPs, SSLPs, SNPs can be used for genetic mapping. Techniques for physical mapping include restriction mapping, fluorescent in situ hybridization (FISH), and sequence tagged site (STS) mapping. Integrating genetic and physical maps provides high resolution mapping needed for genome sequencing.
The document summarizes the Human Genome Project (HGP), which had the goals of identifying all human genes, determining the sequences of DNA base pairs that make up human DNA, storing this information in databases, and addressing ethical issues. Key milestones included completing a working draft in 2000 and fully sequencing the genome in 2003, two years ahead of schedule. The HGP and a private company collaborated to obtain the DNA sequence.
The document discusses several topics related to genome evolution, including:
1. Genome evolution involves the acquisition of new genes through gene duplication within genomes or lateral gene transfer between species. Gene duplication can occur at the whole genome level or for individual or groups of genes.
2. Genome evolution also involves rearrangement of existing genes through domain shuffling, where gene segments are joined to form new proteins, or domain duplication where repetitive domains evolve new functions.
3. Introns may have evolved early in ancestral genes and are gradually being lost from genomes ("introns early" hypothesis) or evolved more recently and are accumulating ("introns late"). Early evidence supported "introns early" with conserved intron positions in homologous genes.
The document discusses genome expression and evolution. It begins by defining the transcriptome as the collection of RNA molecules derived from protein-coding genes expressed by a cell at a given time. It then discusses two views of genome expression - observing the transcriptome which is high-throughput and context dependent/dynamic, and how it predicts biology and regulatory networks. The remainder discusses various mechanisms of genome evolution, including duplication of entire chromosome sets, alterations of chromosome structure through fusions/inversions, duplication and divergence of gene-sized DNA regions, evolution of related gene functions through duplication and divergence like human globin genes, and evolution of novel gene functions through duplication and divergence.
Odoo 18 Accounting Access Rights - Odoo 18 SlidesCeline George
In this slide, we’ll discuss on accounting access rights in odoo 18. To ensure data security and maintain confidentiality, Odoo provides a robust access rights system that allows administrators to control who can access and modify accounting data.
One Click RFQ Cancellation in Odoo 18 - Odoo SlidesCeline George
In this slide, we’ll discuss the one click RFQ Cancellation in odoo 18. One-Click RFQ Cancellation in Odoo 18 is a feature that allows users to quickly and easily cancel Request for Quotations (RFQs) with a single click.
Hannah Borhan and Pietro Gagliardi OECD present 'From classroom to community ...EduSkills OECD
Hannah Borhan, Research Assistant, OECD Education and Skills Directorate and Pietro Gagliardi, Policy Analyst, OECD Public Governance Directorate present at the OECD webinar 'From classroom to community engagement: Promoting active citizenship among young people" on 25 February 2025. You can find the recording of the webinar on the website https://oecdedutoday.com/webinars/
Dr. Ansari Khurshid Ahmed- Factors affecting Validity of a Test.pptxKhurshid Ahmed Ansari
Validity is an important characteristic of a test. A test having low validity is of little use. Validity is the accuracy with which a test measures whatever it is supposed to measure. Validity can be low, moderate or high. There are many factors which affect the validity of a test. If these factors are controlled, then the validity of the test can be maintained to a high level. In the power point presentation, factors affecting validity are discussed with the help of concrete examples.
Research Publication & Ethics contains a chapter on Intellectual Honesty and Research Integrity.
Different case studies of intellectual dishonesty and integrity were discussed.
Effective Product Variant Management in Odoo 18Celine George
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RRB ALP CBT 2 Mechanic Motor Vehicle Question Paper (MMV Exam MCQ)SONU HEETSON
Microarray
1. DNA Microarrays Ms.ruchi yadav lecturer amity institute of biotechnology amity university lucknow(up)
2. Gene expression A human organism has over 250 different cell types (e.g., muscle, skin, bone, neuron), most of which have identical genomes, yet they look different and do different jobs It is believed that less than 20% of the genes are‘expressed’ (i.e., making RNA) in a typical cell type Apparently the differences in gene expression is what makes the cells different
9. Some questions for the golden age of genomics How gene expression differs in different cell types? How gene expression differs in a normal and diseased (e.g., cancerous) cell? How gene expression changes when a cell is treated by a drug? How gene expression changes when the organism develops and cells are differentiating? How gene expression is regulated – which genes regulate which and how?
10. What is a DNA Microarray? (cont.) Biological Samples in 2D Arrays on Membranes or Glass Slides Cheung et al. 1999
11. What is a DNA Microarray? Also known as DNA Chip Allows simultaneous measurement of the level of transcription for every gene in a genome (gene expression) Microarray detects mRNA, or rather the more stable cDNA
13. The Colours of a Microarray GREEN represents Control DNA , where either DNA or cDNA derived from normal tissue is hybridized to the target DNA. RED represents Sample DNA , where either DNA or cDNA is derived from diseased tissue hybridized to the target DNA. YELLOW represents a combination of Control and Sample DNA , where both hybridized equally to the target DNA. BLACK represents areas where neither the Control nor Sample DNA hybridized to the target DNA.
14. Microarray Steps Experiment and Data Acquisition Sample preparation and labelling Hybridisation Washing Image acquisition Data normalization Data analysis Biological interpretation
16. There are many ways to obtain a labeled target sample. ...GGCUUAAUGAGCCUUAAAAAA...A mRNA TTTTTT...T viral enzyme reverse transcriptase recognizes poly-T bound to poly-A and begins to add complementary DNA nucleotides. The C nucleotides are dyed. A A A G G C T C T T A A G C C ... poly-A tail cDNA target poly-T primer
20. How do we manufacture a microarray? Start with individual genes, e.g. the ~6,200 genes of the yeast genome Amplify all of them using polymerase chain reaction (PCR) “ Spot” them on a medium, e.g. an ordinary glass microscope slide Each spot is about 100 µm in diameter Spotting is done by a robot Complex and potentially expensive task
24. The PixSys 5500 Arraying Robot (Cartesian Technologies) Vacuum wash station The print head holds up to 32 pins in a 8x4 format Vacuum hold-down platform (50 slide capacity) Robotic arm
28. Spotting the Probes on the Microarray 8 X 4 Print Head microarray slide plate with wells holding probes in solution All spots of the same color are made at the same time. All spots in the same sector are made by the same pin.
40. Oligonucleotide Microarray Gene chip (DNA chip, Affymetrix chip): Oligonucleotide (20~80-mer oligos) is synthesized either in situ (on-chip) Developed at Affymetrix, Inc. , under the GeneChip® trademark
41. Affymetrix Chip Each gene has 16 – 20 pairs of probes synthesized on the chip Each pairs of probes have two oligonucleotide – Perfect match (PM, reference seq) ATG…C…TGC (20-25 bases) – Mismatch (MM, one base change) ATG… T …TGC A MM oligo is identical to a PM oligo except that the middle nucleotide (13 th of 25) is intentionally replaced by its complementary nucleotide . The scanned result for a given gene is the average differences between PM and MM signals, over probes
42. Different Probe Pairs Represent Different Parts of the Same Gene gene sequence Probes are selected to be specific to the target gene and have good hybridization characteristics.
43. A Probe Set for Measuring Expression Level of a Particular Gene probe pair gene sequence ...TGCAATGGGTCAGAA G GACTCCTATGTGCCT... AATGGGTCAGAA G GACTCCTATGTG AATGGGTCAGAA C GACTCCTATGTG perfect match sequence mismatch sequence probe set probe cell
51. Affymetrix GeneChips The black features represent no intensity (no RNA hybridized to the respective probe in the feature). The intensity level from lowest to highest by color is: Dark blue -> Blue -> Light Blue -> Green -> Yellow -> Orange -> Red - > White . More intensity means more RNA bound to a specific feature, which basically means the gene was expressed at a higher level.
53. Affymetrix GeneChip experiment labeled cRNA randomly fragmented in to pieces anywhere from 30 to 400 base pairs in length The fragmented, Biotin-labeled cRNA is added to the array Anywhere on the array where a RNA fragment and a probe are complimentary, the RNA hybridizes to the probes in the feature. The array is then washed to remove any RNA that is not stuck to an array then stained with the fluorescent molecule that sticks to Biotin (Cy5 conjugated to streptavidin) Lastly, the entire array is scanned with a laser and the information is kept in a computer for quantitative analysis of what genes were expressed and at what approximate level
54. in-situ synthesised arrays The different methods for deprotection lead to the three main technologies for making in-situ synthesised arrays: Photodeprotection using masks: this is the basis of the Affymetrix® technology. Photodeprotection without masks : this is the method used by Nimblegen and Febit. Chemical deprotection with synthesis via inkjet technology: this is the method used by Rosetta, Agilent and Oxford Gene Technology.
60. * Measuring levels of gene expression * Creating diagnostic tests to predict whether a patient has a genetic predisposition to obesity * Designing Drugs Gene expression and obesity
62. Color Coding Tables are difficult to read Data is presented with a color scale Coding scheme: Green = repressed (less mRNA) gene in experiment Red = induced (more mRNA) gene in experiment Black = no change (1:1 ratio) Or Green = control condition (e.g. aerobic) Red = experimental condition (e.g. anaerobic) We only use ratio Campbell & Heyer, 2003