This talk was given at a workshop in Portugal. Here I describe a variety of molecular techniques used for studying the brain as the insight that each can bring and their limitations.
This document presents a flexible architecture for studying plant functional genomics in space environments. The goals are to remotely measure plant responses to space conditions, determine gene function, and optimize plant performance. The basic architecture involves subjecting a test plant to a space environment, analyzing gene expression with microarrays, isolating genes, disrupting genes, and performing functional analysis. Arabidopsis and moss are proposed as model systems. Future work includes generating gene knockouts in moss, introducing additional environmental conditions, and adapting the architecture for space flight.
Introduction to Microarray in Gene Expression studiesSarbesh D. Dangol
The document provides an introduction to microarrays. It describes that microarrays allow for the simultaneous assessment of large numbers of nucleic acids in parallel using molecular hybridization methods. Microarrays involve preparing miniaturized collections of known nucleic acid sequences that are immobilized on a solid surface as targets. Labeled mRNA or DNA samples are used as probes to determine expression levels of thousands of genes at once through detecting which probes hybridize to which targets. The document outlines the basic components and manufacturing of microarrays as well as their applications in gene expression analysis, genome analysis, and drug discovery.
Detecting and Quantifying Low Level Variants in Sanger Sequencing TracesThermo Fisher Scientific
Automated fluorescent dye-terminator DNA Sequencing using capillary electrophoresis (also known as CE or Sanger sequencing) has been instrumental in the detailed characterization of the human genome and is now widely used as gold standard method for verification of mutation findings, notably in tumor samples. The primary information of the DNA sequencing process is the identification of the nucleotides and of possible sequence variants. A largely unexplored feature of fluorescent Sanger sequencing traces is the quantitative information embedded therein. With the growing need for quantifying somatic mutations in tumor tissue it is desirable to exploit the potential of the quantitative information obtained from sequencing traces.
Materials and Methods
To this end, we have developed a software tool that converts a Sanger sequencing trace file into a .comma separated value (.csv) file containing numerical data of peak data characteristics that can be explored and analyzed using conventional spreadsheet software. The web-based tool can be accessed at: http://apps.lifetechnologies.com/ab1peakreporter .
The output file contains the peak height and quality values for each nucleotide and peak height ratios for all 4 bases at any given locus allowing the detection and assessment of subtle changes at any given allele.
Results and Discussion
We demonstrate the utility of this tool by analyzing mixed DNA samples with known amounts of spiked in variant alleles from the human TP53 gene ranging from 2.5%, 5%, 7.5%, 10%, 15% and 25% and show that the minor alleles could be readily detected below the 10% level.
Conclusion
Enabling high sensitivity detection of minor alleles with a widely available and simple to use technology like Sanger sequencing will be useful for verification of results obtained from next generation sequencing (NGS) platforms.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool.
DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Course: Bioinformatics for Biomedical Research (2014).
Session: 3.2- Basic Aspects of Microarray Technology and Data Analysis.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
DNA microarrays allow analysis of gene expression across thousands of genes simultaneously. They consist of DNA probes attached to a solid surface in an organized grid pattern, with each spot representing a single gene. Samples are labeled with fluorescent dyes and hybridized to the chip. Complementary sequences pair via hydrogen bonds, while non-specific sequences are washed away. The signal intensity at each spot indicates the amount of target sequence present and thus gene expression levels. DNA microarrays have applications in clinical diagnosis, drug discovery, and other fields by profiling gene expression patterns.
Centre of innovation, Agricultural College and Research Institute,MaduraiSenthil Natesan
Establishment Central Instrumentation facility with the cost of 6.03 crore to take up multidisciplinary research project at AC&RI,Madurai. The analytical platform includes UP-HPLC for amino acid analysis, XRF for micronutrient analysis and GC-MS for metabolic profiling. The imaging facilities like upright, inverted and Florence microscope established for imaging pathogen & Insects. The molecular biology lab with real time PCR will help for the gene expression studies.
This document presents a flexible architecture for studying plant functional genomics in space environments. The goals are to remotely measure plant responses to space conditions, determine gene function, and optimize plant performance. The basic architecture involves subjecting a test plant to a space environment, analyzing gene expression with microarrays, isolating genes, disrupting genes, and performing functional analysis. Arabidopsis and moss are proposed as model systems. Future work includes generating gene knockouts in moss, introducing additional environmental conditions, and adapting the architecture for space flight.
Introduction to Microarray in Gene Expression studiesSarbesh D. Dangol
The document provides an introduction to microarrays. It describes that microarrays allow for the simultaneous assessment of large numbers of nucleic acids in parallel using molecular hybridization methods. Microarrays involve preparing miniaturized collections of known nucleic acid sequences that are immobilized on a solid surface as targets. Labeled mRNA or DNA samples are used as probes to determine expression levels of thousands of genes at once through detecting which probes hybridize to which targets. The document outlines the basic components and manufacturing of microarrays as well as their applications in gene expression analysis, genome analysis, and drug discovery.
Detecting and Quantifying Low Level Variants in Sanger Sequencing TracesThermo Fisher Scientific
Automated fluorescent dye-terminator DNA Sequencing using capillary electrophoresis (also known as CE or Sanger sequencing) has been instrumental in the detailed characterization of the human genome and is now widely used as gold standard method for verification of mutation findings, notably in tumor samples. The primary information of the DNA sequencing process is the identification of the nucleotides and of possible sequence variants. A largely unexplored feature of fluorescent Sanger sequencing traces is the quantitative information embedded therein. With the growing need for quantifying somatic mutations in tumor tissue it is desirable to exploit the potential of the quantitative information obtained from sequencing traces.
Materials and Methods
To this end, we have developed a software tool that converts a Sanger sequencing trace file into a .comma separated value (.csv) file containing numerical data of peak data characteristics that can be explored and analyzed using conventional spreadsheet software. The web-based tool can be accessed at: http://apps.lifetechnologies.com/ab1peakreporter .
The output file contains the peak height and quality values for each nucleotide and peak height ratios for all 4 bases at any given locus allowing the detection and assessment of subtle changes at any given allele.
Results and Discussion
We demonstrate the utility of this tool by analyzing mixed DNA samples with known amounts of spiked in variant alleles from the human TP53 gene ranging from 2.5%, 5%, 7.5%, 10%, 15% and 25% and show that the minor alleles could be readily detected below the 10% level.
Conclusion
Enabling high sensitivity detection of minor alleles with a widely available and simple to use technology like Sanger sequencing will be useful for verification of results obtained from next generation sequencing (NGS) platforms.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool.
DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Course: Bioinformatics for Biomedical Research (2014).
Session: 3.2- Basic Aspects of Microarray Technology and Data Analysis.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
DNA microarrays allow analysis of gene expression across thousands of genes simultaneously. They consist of DNA probes attached to a solid surface in an organized grid pattern, with each spot representing a single gene. Samples are labeled with fluorescent dyes and hybridized to the chip. Complementary sequences pair via hydrogen bonds, while non-specific sequences are washed away. The signal intensity at each spot indicates the amount of target sequence present and thus gene expression levels. DNA microarrays have applications in clinical diagnosis, drug discovery, and other fields by profiling gene expression patterns.
Centre of innovation, Agricultural College and Research Institute,MaduraiSenthil Natesan
Establishment Central Instrumentation facility with the cost of 6.03 crore to take up multidisciplinary research project at AC&RI,Madurai. The analytical platform includes UP-HPLC for amino acid analysis, XRF for micronutrient analysis and GC-MS for metabolic profiling. The imaging facilities like upright, inverted and Florence microscope established for imaging pathogen & Insects. The molecular biology lab with real time PCR will help for the gene expression studies.
Errors and Limitaions of Next Generation SequencingNixon Mendez
This document discusses some key errors and limitations of next-generation sequencing (NGS). It notes that while NGS has significantly reduced costs and improved throughput, it also has some drawbacks compared to previous sequencing technologies. Specifically, it outlines issues related to low quality bases, PCR errors during amplification, and high error rates that can make rare mutations difficult to detect. Limitations include short read lengths that hamper assembly of repetitive regions, contamination risks, incomplete representation of repeats, difficulties assembling segmental duplications and genes fragmented across scaffolds. The document emphasizes the need for validation of genome assemblies and development of hybrid approaches combining long and short reads to overcome these challenges.
Phylogenomic methods for comparative evolutionary biology - University Colleg...Joe Parker
This document outlines Joe Parker's research interests in phylogenomics and high-throughput comparative genomics at Queen Mary University London. It discusses why phylogenomics is important, provides examples of past studies, and describes the lab's workflow and tools for sequencing, assembly, alignment, phylogeny inference, and phylogenetic analysis. It also presents a case study on detecting genome-wide convergence and discusses future directions including environmental metagenomics, cloud computing models, and real-time phylogenetics.
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.
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 DNA microarrays or DNA chips. It explains that a DNA chip contains many copies of unique DNA sequences attached to a solid surface that are used to measure gene expression levels in cells. The presentation describes how DNA chips can compare gene expression levels between healthy and cancer cells to identify genes that are turned on or off in cancer. It provides examples of extracting RNA from tissue samples, converting it to cDNA, hybridizing it to a DNA chip, and analyzing the results to see differences in gene expression patterns between healthy and cancer cells. In conclusion, it states that DNA chips are a powerful comparative genomics tool for disease diagnosis, drug discovery, and toxicology research.
The document discusses exome sequencing and compares the performance of the xGen Exome Research Panel to other commercial exome sequencing panels. Key points:
1) An independent study directly compared the xGen panel to 3 other commercial exome panels and found that the xGen panel had a higher on-target rate and more uniform coverage than the other panels.
2) When deeply sequenced, the xGen panel was able to achieve greater than 20x coverage of over 94% of bases in the RefSeq database with only 40 million reads, which is 2.5-4 times fewer reads than the other panels tested.
3) The coverage profile produced by the xGen panel more closely resembled whole genome sequencing
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.
This document discusses the history and technologies of DNA microarrays. It begins with the early techniques of DNA hybridization from the 1960s-1970s that led to the development of microarrays. The key aspects of microarrays are that they allow analysis of hundreds or thousands of DNA probes simultaneously attached to a solid surface using robotics and informatics. Major technologies include cDNA probes on nylon or glass and oligonucleotides synthesized on glass slides. Principal uses are for genome-scale analysis of gene expression, genetic variations, and mutations.
This document discusses DNA microarray technology, which allows researchers to study thousands of genes simultaneously using a chip that contains DNA probes. It describes how DNA microarray works by hybridizing labeled DNA or RNA samples to the probes on the chip to detect gene expression patterns. Different types of microarrays like expression analysis, mutation analysis, and comparative genomic hybridization are used for various applications such as gene discovery, disease diagnosis, drug discovery, and toxicological research.
Understanding and controlling for sample and platform biases in NGS assaysCandy Smellie
What is the impact of assay failure in your laboratory and how do you monitor for it?
The advancement of next-generation sequencing has provided invaluable resources to researchers in multiple industries and disciplines, and will be a major driver during the personalized medicine revolution that is upon us. However, while the cost of generating sequencing data continues to decrease this does not take into account the significant costs associated with the infrastructure and expertise that are required to develop a robust, routine NGS pipeline.
Specifically, as predicted by Sboner, et al in 2011, the cost of the sequencing portion of the experiment continues to decrease and the costs associated with upfront experimental design and downstream analysis dominate the cost of each assay. This is true whether you are performing a pre-clinical R&D project, and perhaps even more so for clinical assays. In the paper, the authors note the unpredictable and considerable ‘human time’ spent on the upstream design and downstream analysis. Here at Horizon, we aim to develop tools that help researchers and clinicians optimize these workflows to make NGS more reliable and ultimately, more affordable by streamlining these resource intensive areas.
DNA microarray technology allows researchers to analyze gene expression patterns across thousands of genes simultaneously. It involves affixing DNA probes to a solid surface in an orderly array and then measuring which genes are expressed by the level of hybridization with fluorescently labeled cDNA or cRNA from samples. The document discusses the history and principles of microarray techniques, including types such as cDNA and oligonucleotide microarrays. It also covers applications in genomics research and analysis of microarray data.
DNA microarray is a technique that allows high-throughput analysis of gene expression. It involves depositing DNA fragments onto a glass slide and using fluorescent probes made from sample RNA to detect expression levels of thousands of genes simultaneously. The document discusses the basic principles and steps of DNA microarray, including sample preparation, hybridization, image analysis and data normalization. It also compares different microarray fabrication technologies and platforms, and discusses quality control considerations and limitations of the technique.
The document summarizes new services offered by the Genomics and Epigenomics Shared Resource (GESR) at Georgetown, including quantitative DNA methylation analysis, custom SNP genotyping, microarray analysis of SNPs, copy number variation and gene expression, and microRNA profiling. It provides contact information for directors and staff of GESR.
This document provides an overview of DNA microarrays (DNA chips). It discusses that DNA chips allow scientists to simultaneously measure gene expression levels or genotype multiple genomic regions. It describes the principle technologies used in DNA chips, including attaching cDNA or oligonucleotide probes to glass or silicon surfaces. The document also provides background on DNA and microarrays, their history, applications in gene expression analysis and disease research, and principle of hybridization. It discusses alternative bead-based array technologies and how microarrays enabled large-scale genomic experiments.
Meren's pirate presentation at the STAMPS course to talk about the basic concepts most binning algorithms use to bin contigs into genome bins: sequence composition, and differential coverage.
Next Generation Sequencing Informatics - Challenges and OpportunitiesChung-Tsai Su
Genetic data is the foundation of precision medicine. Next Generation Sequencing(NGS) enable us to get our whole genome data in affordable cost. How to process huge amount of NGS data effectively ?
Microarray technology allows scientists to study thousands of genes simultaneously. It works by breaking open cells, isolating genetic contents, and identifying which genes are turned on or off in a particular cell. Probes for each gene are attached to a chip, and a fluorescently labeled target sample is hybridized. A scanner then detects the fluorescent signal from each spot on the chip to determine the relative abundance of nucleic acid sequences and expression levels of genes. Microarray analysis provides a fast way to obtain gene expression profiling results but it is an expensive technique that produces large datasets requiring complex analysis.
Genotyping by Sequencing is a robust,fast and cheap approach for high throughput marker discovery.It has applications in crop improvement programs by enhancing identification of superior genotypes.
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.
Wolf Kahn is a painter known for using vibrant, unexpected colors in his landscape paintings of nature. Rather than depicting nature with realistic colors, Kahn experiments with bold hues that transform familiar scenes into something surreal. His unconventional color choices have become a signature style that challenge viewers' perceptions of the natural world.
Robert Motherwell was an American artist and scholar who was influenced by Surrealism and was a pioneer of Abstract Expressionism. He is known for his series of abstract paintings called the Elegies to the Spanish Republic from the late 1940s addressing the Spanish Civil War. Motherwell had a broad-ranging intellect and played a key role in introducing European avant-garde ideas to the US. He married the painter Helen Frankenthaler and their work explored spontaneous gestures and unconscious expression through abstract color fields.
Errors and Limitaions of Next Generation SequencingNixon Mendez
This document discusses some key errors and limitations of next-generation sequencing (NGS). It notes that while NGS has significantly reduced costs and improved throughput, it also has some drawbacks compared to previous sequencing technologies. Specifically, it outlines issues related to low quality bases, PCR errors during amplification, and high error rates that can make rare mutations difficult to detect. Limitations include short read lengths that hamper assembly of repetitive regions, contamination risks, incomplete representation of repeats, difficulties assembling segmental duplications and genes fragmented across scaffolds. The document emphasizes the need for validation of genome assemblies and development of hybrid approaches combining long and short reads to overcome these challenges.
Phylogenomic methods for comparative evolutionary biology - University Colleg...Joe Parker
This document outlines Joe Parker's research interests in phylogenomics and high-throughput comparative genomics at Queen Mary University London. It discusses why phylogenomics is important, provides examples of past studies, and describes the lab's workflow and tools for sequencing, assembly, alignment, phylogeny inference, and phylogenetic analysis. It also presents a case study on detecting genome-wide convergence and discusses future directions including environmental metagenomics, cloud computing models, and real-time phylogenetics.
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.
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 DNA microarrays or DNA chips. It explains that a DNA chip contains many copies of unique DNA sequences attached to a solid surface that are used to measure gene expression levels in cells. The presentation describes how DNA chips can compare gene expression levels between healthy and cancer cells to identify genes that are turned on or off in cancer. It provides examples of extracting RNA from tissue samples, converting it to cDNA, hybridizing it to a DNA chip, and analyzing the results to see differences in gene expression patterns between healthy and cancer cells. In conclusion, it states that DNA chips are a powerful comparative genomics tool for disease diagnosis, drug discovery, and toxicology research.
The document discusses exome sequencing and compares the performance of the xGen Exome Research Panel to other commercial exome sequencing panels. Key points:
1) An independent study directly compared the xGen panel to 3 other commercial exome panels and found that the xGen panel had a higher on-target rate and more uniform coverage than the other panels.
2) When deeply sequenced, the xGen panel was able to achieve greater than 20x coverage of over 94% of bases in the RefSeq database with only 40 million reads, which is 2.5-4 times fewer reads than the other panels tested.
3) The coverage profile produced by the xGen panel more closely resembled whole genome sequencing
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.
This document discusses the history and technologies of DNA microarrays. It begins with the early techniques of DNA hybridization from the 1960s-1970s that led to the development of microarrays. The key aspects of microarrays are that they allow analysis of hundreds or thousands of DNA probes simultaneously attached to a solid surface using robotics and informatics. Major technologies include cDNA probes on nylon or glass and oligonucleotides synthesized on glass slides. Principal uses are for genome-scale analysis of gene expression, genetic variations, and mutations.
This document discusses DNA microarray technology, which allows researchers to study thousands of genes simultaneously using a chip that contains DNA probes. It describes how DNA microarray works by hybridizing labeled DNA or RNA samples to the probes on the chip to detect gene expression patterns. Different types of microarrays like expression analysis, mutation analysis, and comparative genomic hybridization are used for various applications such as gene discovery, disease diagnosis, drug discovery, and toxicological research.
Understanding and controlling for sample and platform biases in NGS assaysCandy Smellie
What is the impact of assay failure in your laboratory and how do you monitor for it?
The advancement of next-generation sequencing has provided invaluable resources to researchers in multiple industries and disciplines, and will be a major driver during the personalized medicine revolution that is upon us. However, while the cost of generating sequencing data continues to decrease this does not take into account the significant costs associated with the infrastructure and expertise that are required to develop a robust, routine NGS pipeline.
Specifically, as predicted by Sboner, et al in 2011, the cost of the sequencing portion of the experiment continues to decrease and the costs associated with upfront experimental design and downstream analysis dominate the cost of each assay. This is true whether you are performing a pre-clinical R&D project, and perhaps even more so for clinical assays. In the paper, the authors note the unpredictable and considerable ‘human time’ spent on the upstream design and downstream analysis. Here at Horizon, we aim to develop tools that help researchers and clinicians optimize these workflows to make NGS more reliable and ultimately, more affordable by streamlining these resource intensive areas.
DNA microarray technology allows researchers to analyze gene expression patterns across thousands of genes simultaneously. It involves affixing DNA probes to a solid surface in an orderly array and then measuring which genes are expressed by the level of hybridization with fluorescently labeled cDNA or cRNA from samples. The document discusses the history and principles of microarray techniques, including types such as cDNA and oligonucleotide microarrays. It also covers applications in genomics research and analysis of microarray data.
DNA microarray is a technique that allows high-throughput analysis of gene expression. It involves depositing DNA fragments onto a glass slide and using fluorescent probes made from sample RNA to detect expression levels of thousands of genes simultaneously. The document discusses the basic principles and steps of DNA microarray, including sample preparation, hybridization, image analysis and data normalization. It also compares different microarray fabrication technologies and platforms, and discusses quality control considerations and limitations of the technique.
The document summarizes new services offered by the Genomics and Epigenomics Shared Resource (GESR) at Georgetown, including quantitative DNA methylation analysis, custom SNP genotyping, microarray analysis of SNPs, copy number variation and gene expression, and microRNA profiling. It provides contact information for directors and staff of GESR.
This document provides an overview of DNA microarrays (DNA chips). It discusses that DNA chips allow scientists to simultaneously measure gene expression levels or genotype multiple genomic regions. It describes the principle technologies used in DNA chips, including attaching cDNA or oligonucleotide probes to glass or silicon surfaces. The document also provides background on DNA and microarrays, their history, applications in gene expression analysis and disease research, and principle of hybridization. It discusses alternative bead-based array technologies and how microarrays enabled large-scale genomic experiments.
Meren's pirate presentation at the STAMPS course to talk about the basic concepts most binning algorithms use to bin contigs into genome bins: sequence composition, and differential coverage.
Next Generation Sequencing Informatics - Challenges and OpportunitiesChung-Tsai Su
Genetic data is the foundation of precision medicine. Next Generation Sequencing(NGS) enable us to get our whole genome data in affordable cost. How to process huge amount of NGS data effectively ?
Microarray technology allows scientists to study thousands of genes simultaneously. It works by breaking open cells, isolating genetic contents, and identifying which genes are turned on or off in a particular cell. Probes for each gene are attached to a chip, and a fluorescently labeled target sample is hybridized. A scanner then detects the fluorescent signal from each spot on the chip to determine the relative abundance of nucleic acid sequences and expression levels of genes. Microarray analysis provides a fast way to obtain gene expression profiling results but it is an expensive technique that produces large datasets requiring complex analysis.
Genotyping by Sequencing is a robust,fast and cheap approach for high throughput marker discovery.It has applications in crop improvement programs by enhancing identification of superior genotypes.
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.
Wolf Kahn is a painter known for using vibrant, unexpected colors in his landscape paintings of nature. Rather than depicting nature with realistic colors, Kahn experiments with bold hues that transform familiar scenes into something surreal. His unconventional color choices have become a signature style that challenge viewers' perceptions of the natural world.
Robert Motherwell was an American artist and scholar who was influenced by Surrealism and was a pioneer of Abstract Expressionism. He is known for his series of abstract paintings called the Elegies to the Spanish Republic from the late 1940s addressing the Spanish Civil War. Motherwell had a broad-ranging intellect and played a key role in introducing European avant-garde ideas to the US. He married the painter Helen Frankenthaler and their work explored spontaneous gestures and unconscious expression through abstract color fields.
Central Problem of Pattern Recognition: Supervised and Unsupervised Learning. Machine Learning addresses challenging inference problems in pattern recognition that span statistical modeling to efficient algorithms. These include:
1) Representing objects through data representation.
2) Defining and modeling patterns and structure in the data.
3) Optimizing structures through searching for preferred structures.
4) Validating structures by determining if they are actually present in the data or are due to fluctuations.
Hans Hofmann was a German-born American abstract expressionist painter who was born in 1880. He was influenced by Matisse, Gorky, Still, and others and taught the "push and pull" theory of abstract painting. Hofmann moved to the US in the 1930s to escape Nazi Germany and became a highly influential teacher known for his abstract, expressionist works using vibrant colors and geometric shapes based on structure rather than appearance.
Wolf Kahn is an American painter born in Germany in 1927 who is still living today. He fled Germany at age 12 to escape the Nazis and came to America in 1940. Kahn was educated at the Hans Hofmann School of Art and influenced by Hofmann's teachings on using nature as inspiration. Known for his landscape paintings, Kahn works primarily in pastels and paints, blending colors together to create low-contrast scenes of nature. He lives in New York but spends summers on a farm in Vermont, drawing inspiration from nature for his influential paintings.
Mark Rothko and Barnett Newman were influential 20th century abstract expressionist painters known for their use of color and exploration of spiritual themes. Rothko began experimenting with color field paintings in the 1940s-50s, focusing on large areas of color and eliminating figurative elements. Newman began creating minimalist works featuring blocks of intense color separated by thin lines in the 1950s, seeking to express profound emotions and create a quasi-religious experience for viewers. Both artists saw their abstract works as conveying philosophical and spiritual truths beyond mere visual aesthetics.
The document provides information about German Expressionism, including:
- It was a reaction against conservative academies and embraced distorted forms and exaggerated colors.
- Artists wanted to startle viewers with direct, frank works in various media.
- Many artists served in WWI and returned disillusioned by the war and economic/political turmoil in Germany.
- The movement reflected humanistic concerns and ambivalence about modernity through the early 1920s.
The document summarizes the Encyclopedia of DNA Elements (ENCODE) project. It describes ENCODE as a follow-up to the Human Genome Project that aims to identify all functional elements in the human genome, including regions that regulate genes. The document outlines the phases of the project and some of the high-throughput techniques used, such as ChIP-seq, DNase-seq, and MNase-seq. It also discusses how the data from ENCODE is being utilized and the future plans to expand the project.
Course: Bioinformatics for Biomedical Research (2014).
Session: 2.1.2- Next Generation Sequencing. Technologies and Applications. Part II: NGS Applications I.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
Time and Money: Techniques for Neural Gene Expression ProfilingRayna Harris
This was the very first talk I gave in front of a classroom based heavily on my research own personal research. It was 2013, and my audience was a group of students at the Marine Biological Lab in Woods Hole, MA and a group of students who Skyped in from Uruguay. The goal of this talk is to help students better understand when candidate gene approaches are preferred of whole genome approaches and vice versa.
You can watch this talk here: http://videocenter.mbl.edu/videos/video/630/in/channel/21/
Microarrays (DNA chips) allow large numbers of DNA probes to be immobilized on a solid surface like nylon or glass. They have various applications including identifying genes responsible for development, diseases, and single nucleotide polymorphisms. Restriction fragment length polymorphism (RFLP) detects length variations in DNA fragments after restriction enzyme digestion, revealing polymorphisms. DNA fingerprinting analyzes variable numbers of tandem repeats in satellite DNA, producing unique patterns that can identify individuals in forensic investigations.
1) The document discusses a study analyzing the impact of gene length on detecting differentially expressed genes using RNA-seq technology.
2) The study will first test the reproducibility of RNA-seq and the effect of normalization. It will then compare different statistical tests for identifying differentially expressed genes.
3) Finally, the study will specifically test how gene length impacts the likelihood of a gene being identified as differentially expressed, as longer genes are easier to map with short reads.
Molecular Markers and Their Application in Animal Breed.pptxTrilokMandal2
Molecular markers have had a significant impact on breed development and conservation efforts, transforming genetics and offering vital insights into genetic diversity, lineage tracing, and genotype characterization. The importance of molecular markers in improving genetic gains, facilitating breeding programs, and preserving genetic diversity for the long-term sustainability of the animal population has been underlined in this review paper. Emerging advancements in molecular marker technology show enormous potential for improving and conserving breeds. Deeper insights into the genetic basis of complex traits will be provided through GWAS, CRISPR/Cas9, gene editing technologies, and sequencing technologies, resulting in faster genetic gains. Breeders and conservationists will be able to make more informed judgments thanks to these technologies. In conclusion, molecular markers have had a significant impact on breed conservation and enhancement. Their innovations have changed the industry and given both conservationists and breeders vital knowledge. We can pave the road for more effective and sustainable genetic improvement and the preservation of biodiversity for future generations by combining the power of molecular markers with conventional breeding and conservation techniques.
This document provides an overview of genomics and proteomics tools and techniques. It discusses genomics and the study of genomes, including structural and functional genomics. It also covers proteomics and the study of the proteome. The document then describes several key techniques in more detail, including DNA gel electrophoresis, polymerase chain reaction (PCR), reverse transcription PCR (RT-PCR), DNA sequencing, microarrays, enzyme-linked immunosorbent assay (ELISA), blotting techniques like Western blotting, and SDS-PAGE gel electrophoresis. It provides information on the principles, applications, and procedures for each technique.
As increasing numbers of people choose to have their genomes sequenced and made available for research, more genomic data is available for analysis by machine learning approaches. Single Nucleotide Polymorphisms (SNPs) are known to be a major factor influencing many physical traits, diseases and other phenotypes. Using publicly available data and tools we predict phenotype from genotype using SNP data (1 to 2 million SNPs). We utilize data analysis and machine learning approaches only, no domain knowledge, so that our automated approach may be generally used to predict different phenotypes from genotype. In the first application of our method we predicted eye color with 87% accuracy.
Maryann Martone
Making Sense of Biological Systems: Using Knowledge Mining to Improve and Validate Models of Living Systems; NIH COBRE Center for the Analysis of Cellular Mechanisms and Systems Biology, Montana State University, Bozeman, MT
August 24, 2012
This document provides an overview of DNA microarray technology. It discusses that a DNA microarray contains DNA spots attached to a solid surface with specific DNA sequences known as probes. Each probe occupies a spot on the chip and fluorescent activity from labeled target sequences binding to probes allows measurement of gene expression levels. The document outlines the historical development of microarrays and describes the basic principles and process, including sample preparation, hybridization of labeled targets to probes, washing, and image analysis. It distinguishes between cDNA and oligonucleotide microarrays and lists requirements for a microarray system.
Microhaplotype, A Powerful New Type of Genetic MarkerMojgan Talebian
This document discusses microhaplotypes as a new type of genetic marker for forensic analysis. Microhaplotypes are loci containing 2 or more SNPs within 200 base pairs, making them multi-allelic. This increases their statistical power over individual SNPs. The study aims to validate microhaplotypes for familial searching, mixture analysis, and other forensic applications. It presents materials and methods for evaluating over 50 candidate microhaplotype loci on over 2500 individuals from 54 populations. 31 highly informative loci were selected as a pilot microhaplotype panel.
Bio-chips, also known as lab-on-a-chip devices, are portable, low cost, low power microfluidic chips that can integrate multiple components. They contain arrays of nanoscale sensors and devices to analyze biological and chemical samples. Microarrays are a type of bio-chip that contain thousands of microscopic spots of DNA, proteins, or other biological molecules in a defined area to perform high-throughput screening of biological material. DNA microarrays allow analysis of gene expression by detecting fluorescence-labeled cDNA that hybridizes to DNA probes on the chip.
This presentation explains the meaning of curation and includes an introduction to the Apollo genome annotation editing tool and its curation environment.
Functional Genomics Journal Club presentation on the following publication:
Kuzawa, C. W., Chugani, H. T., Grossman, L. I., Lipovich, L., Muzik, O., Hof, P. R., … Lange, N. (2014). Metabolic costs and evolutionary implications of human brain development. Proceedings of the National Academy of Sciences, 111(36), 13010–13015. https://doi.org/10.1073/pnas.1323099111
In Search of Better Tools and Capabilities
"We need to do more with less." This is a common theme we hear in our conversations and follow up with Researchers in early phase drug discovery.
To us this translates into better identification and more intense screening of potential therapeutic compounds and targets. Failure is success if it is determined before animal testing.
The foundation being potent, pure and easy to culture primary cells. Then building on the platform with the required media/growth factors, markers, transfection reagents and apoptosis detection kits.
The document discusses various topics related to molecular profiling and personalized medicine. It describes first generation molecular profiling techniques like gene sequencing, microarrays, and PCR. It then covers next generation sequencing technologies like Roche 454, Illumina, and ABI SOLID. It also discusses second generation techniques for DNA and RNA profiling including exome sequencing, ChIP-seq, and RNA-seq. Finally, it briefly mentions third generation sequencing and epigenetic profiling.
What is Genome,Genome mapping,types of Genome mapping,linkage or genetic mapping,Physical mapping,Somatic cell hybridization
Radiation hybridization ,Fish( =fluorescence in - situ hybridization),Types of probes for FISH,applications,Molecular markers,Rflp(= Restriction fragment length polymorphism),RFLPs may have the following Applications;Advantages of rflp,disAdvantages of rflp, Rapd(=Random amplification of polymorphic DNA),Process of rapd, Difference between rflp &rapd
1) The document discusses an autism exome sequencing study that aims to sequence 1000 autism cases and 1000 controls to identify genetic variants associated with autism.
2) It describes the exome production process at two sequencing centers, the Broad Institute and Baylor, including data processing, variant calling, and quality control measures to generate a high quality set of variants and samples.
3) Challenges of exome sequencing include managing large amounts of sequencing data, interpreting millions of variants per individual, and generalizing findings beyond rare Mendelian disorders. The study aims to address these through robust data analysis and matching cases and controls.
This document summarizes trends in DNA sequencing methods and applications. It discusses the purpose and historical methods of DNA sequencing, including the Maxam-Gilbert and Sanger methods. Next generation sequencing methods like Roche 454, Illumina, SOLiD, Ion Torrent, and PacBio are described. Applications of sequencing include analyzing gene structure, detecting mutations, microbial identification, and whole genome sequencing. The document provides details on sequencing techniques, platforms, yields, and error rates.
Similar to Toward Single Neuron Gene Expression Analysis for Studying Behavior (20)
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Toward Single Neuron Gene Expression Analysis for Studying Behavior
1. TOWARD SINGLE NEURON GENE
EXPRESSION ANALYSIS FOR STUDYING
BEHAVIOR
(AND OTHER TECHNIQUES)
RAYNA M. HARRIS
HANS HOFMANN LAB, THE UNIVERSITY OF TEXAS AT
AUSTIN
http://raynamharris.github.io/
1
2. qRT-PCR Microarrays &
RNA-seq
immunohistochemistryin situ
hybridization
Common approaches for neural gene
expression profiling
2
• How you process the brain for each technique is different
• Each technique has its own challenges and opportunities
• Each tells you something different
3. Tradeoffs between spatial resolution and
fraction of the genome surveyed
3
0.0001
0.001
0.01
0.1
1
1 10 100 1000 10000
FractionoftheBrain
Surveyed
Number of Genes Measured
in situ
Hybridization
&
Immuno-
histochemistry
qPCR
RNA-seq
Nanostring
Microarray
4. Candidate genes vs genomic approaches
• Histological approaches allow for co-localization
• Histological approaches are low throughput
• You may choose the wrong candidate genes
• Candidate genes act in networks that are poorly
understood
• Genomics allows systems-level view of brain and
behavior
• Genomic approaches lack spatial resolution
4
5. 5
Mapping gene and protein expression with in
situ hybridization and immunohistochemistry
Androgen receptors
Muchrath & Hofmann 2010
Estrogen receptors
Muchrath & Hofmann 2010
Blue: in situ hybridization (RNA)
Brown: immunohistochemistry (protein)
Shading Left: RNA, paralog a
Shading right: RNA, paralog b
Dots: protein
9. 9
Maruska et al. (2013)
J Neuroendocrinol 25, 145–157
Tissue punches: brain region specific gene expression
10. 10
Chemical Cue
DOM urine
SUB urine
Pre-ovulatory urine
Post-ovulatory urin
Simões et al. 2015
10 2 3 4
Hierarchical Clustering: Gene Expression
Patterns Across Phenotypes
11. Laser microdissection for increased spatial
resolution
11
O’Connell & Hofmann 2012
1. Does this variation map onto behavior?
2. The POA has multiple cell groups, maybe
we should look at individual neurons…
No significant difference in candidate gene expression in the
POA
13. Using IEG-driven GFP-expressing transgenics
13
Denny et al. 2014
I’m doing this in mouse (Arc-GFP)
But, researchers have been using this to study zebrafish
development for over a decade
Delporte et al. 2008
15. Nanostring
1. Hybridize – 2. Purify – 3. Count
• Step 0: Select 200-800 of your
favorite genes from any species
with a transcriptome/genome
• Step 1. Hybridize probes to
target RNA in your sample.
• Step 2. Purify the sample and
immobilize target-probe complex
in special cartidge
• Step 3. Count the number of
unique reporter probes to infer
number of transcripts
http://www.nanostring.com/ 15
16. Singe cell gene expression (and physiology) in
learning-recruited neurons
16
Learning-
recruited
Not
recruited
Future studies will integrative variation in learning & memory to
variation in gene expression
18. Identifying similar patterns of gene expression
across datasets, experiments, or contexts
18
Ghazalpour et al. 2006
Preservation of female mouse liver modules in male data
I’m using this approach to identify
unique and preserved gene expression
patterns
that are important for hippocampal-dependent
spatial (CA1) and social (CA2) learning
19. 19
Single cell analysis of teleost Dl might to
examine homology with mammalian CA1,
CA2, CA3, & DG
O’Connell & Hofmann 2012 Hawrylycz et al., 2012; Lein et al., 2004
20. Each technique provides unique but limited
insight into the neuromolecular basis of
behavior
20
Kelly & Goodson 2005;
O’Connell et al. 2013; Hilliard et al. 2012
Denny et al. 2014
C-fos Immunohistochemistry Arc-driven expression of GFP
21. A comprehensive research program uses
each of these techniques to inform future
experiments
21
0.0001
0.001
0.01
0.1
1
1 10 100 1000 10000
FractionoftheBrain
Surveyed
Number of Genes Measured
in situ
Hybridization
&
Immuno-
histochemistry
qPCR
RNA-seq
Nanostring
Microarray
22. 22
So, now you have a transcriptome…
Harris & Hofmann
2014
23. A few questions that may help you choose most
appropriate technique
• What are your molecules of interest?
– Candidate mRNA or protein, transcriptomic patterns?
– How soon after the stimulus will its activity be altered?
• How big is your experiment?
– How many groups, animals, brain regions, genes?
• What resources do you have at your fingertips?
– Core facilities and equipment
– Validated PCR primers, riboprobes, antibodies?
– A mentor who can help you collect & analyze the data?
– Bioinformatic and statistical consulting?
23
24. Bioinformatics: An Essential Part of Every Biologist’s
Toolkit
24
“The ability to harvest the
wealth of information
contained in biomedical Big
Data will advance our
understanding of human
health and disease.
However, lack of appropriate
tools, poor data accessibility,
and insufficient training, are
major impediments to rapid
translational impact”.
— NIH Big Data to Knowledge
(BD2K) Initiative
25. Many Thanks!
NS&B Students & FacultyLars & Rui for the invitation
Hofmann Lab
Neuroscience FolksThe CCBB
EEB, IB, CMB & MBS Folks
25