This document provides an introduction to genomics and proteomics. It begins with an outline and definitions of genetics and genomics. Genomics is the study of large-scale genetic patterns across genomes, while genetics provides tools to study individual gene function. The document then discusses genes, including differences between prokaryotic and eukaryotic genes. It provides comparisons of genome sizes across species and describes picking genes out of genomes using open reading frames and identifying exons and introns. The document concludes with descriptions of model organisms for genomics studies including humans, and provides statistics on the human genome size, gene number, and characteristics.
This document provides an introduction to genomics and proteomics. It begins with definitions of genetics and genomics, noting that genomics studies large-scale genetic patterns across genomes. Prokaryotes like bacteria have small genomes contained in a single DNA molecule, while eukaryotes have larger, more complex genomes with chromosomes. Model organisms discussed include yeast, nematodes, fruit flies, plants, and humans. The human genome is around 3 billion base pairs distributed across chromosomes, with only around 5% consisting of coding sequences. Gene expression is also examined, along with how regulatory regions control gene expression in response to conditions.
This document provides an introduction to genomics and proteomics. It outlines key topics including the tree of life, genes, and genomics definitions. The tree of life section distinguishes between prokaryotic and eukaryotic genomes, noting that prokaryotes like bacteria contain single circular DNA molecules while eukaryotes have more complex genomes. The document also compares genome sizes across various species and describes genes and exons and introns in eukaryotes. It discusses identifying genes in genomes through similarity to known genes or ab initio methods examining DNA sequence properties.
Genomics is the study of genomes, including sequencing genomes and determining the complete set of proteins and genes in an organism. The first genomes sequenced included Haemophilus influenzae in 1995 and the human genome was completed in 2003, taking 13 years. Genomics provides information on genes, metabolic pathways, and the functioning of organisms through approaches like genome sequencing, structural genomics, functional genomics, comparative genomics, and proteomics.
This document provides an overview of exome sequence analysis. It begins with definitions of key terms like genome, genetic variants, and exome sequencing. It then describes the exome sequencing workflow, which involves fragmentation, hybridization to capture exonic regions, sequencing, mapping reads to reference genome, variant calling, and variant annotation. Challenges of finding causal variants are discussed. The document also compares benefits and challenges of exome sequencing versus whole genome sequencing or traditional methods. Finally, it discusses how exome sequencing has helped identify novel disease genes and expand knowledge of known disease genes.
Genomics is a discipline in genetics that applies recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble and analyze the function and structure of genomes
The document summarizes the sequencing of the yeast Saccharomyces cerevisiae genome. Key points:
1) The yeast genome was sequenced between 1989-1996 by over 35 European laboratories in a collaborative effort. By 1996, the entire 12 megabase genome across 16 chromosomes had been sequenced.
2) The genome contains approximately 6,000 open reading frames that were annotated after sequencing. About 30% of yeast genes have homologs in human genes.
3) Sequencing involved creating ordered cosmid libraries, shotgun sequencing, and assembling overlapping sequences into contigs. Genes were identified and analyzed after full genome assembly.
A retrospective look at the state of many famous modern genome sequences, and a cautionary tale of the dangers in assuming that genome sequence and/or its annotations are finished.
Genomics refers to the study of the entire genome of an organism. It deals with mapping genes on chromosomes and sequencing entire genomes. While work on genomics began with prokaryotes like bacteria, research has now been conducted on crop plants like rice and Arabidopsis thaliana. Genomics is an interdisciplinary field that uses tools from molecular biology, robotics, and computing to study genomes. It provides information on genome size, gene number, gene function, and evolution. Genomics has applications in crop improvement through gene mapping, marker-assisted selection, and transgenic breeding. However, genomic research also faces limitations due to high costs, technical challenges, and complexity of traits.
This document provides an introduction to genomics and proteomics. It begins with definitions of genetics and genomics, noting that genomics studies large-scale genetic patterns across genomes. Prokaryotes like bacteria have small genomes contained in a single DNA molecule, while eukaryotes have larger, more complex genomes with chromosomes. Model organisms discussed include yeast, nematodes, fruit flies, plants, and humans. The human genome is around 3 billion base pairs distributed across chromosomes, with only around 5% consisting of coding sequences. Gene expression is also examined, along with how regulatory regions control gene expression in response to conditions.
This document provides an introduction to genomics and proteomics. It outlines key topics including the tree of life, genes, and genomics definitions. The tree of life section distinguishes between prokaryotic and eukaryotic genomes, noting that prokaryotes like bacteria contain single circular DNA molecules while eukaryotes have more complex genomes. The document also compares genome sizes across various species and describes genes and exons and introns in eukaryotes. It discusses identifying genes in genomes through similarity to known genes or ab initio methods examining DNA sequence properties.
Genomics is the study of genomes, including sequencing genomes and determining the complete set of proteins and genes in an organism. The first genomes sequenced included Haemophilus influenzae in 1995 and the human genome was completed in 2003, taking 13 years. Genomics provides information on genes, metabolic pathways, and the functioning of organisms through approaches like genome sequencing, structural genomics, functional genomics, comparative genomics, and proteomics.
This document provides an overview of exome sequence analysis. It begins with definitions of key terms like genome, genetic variants, and exome sequencing. It then describes the exome sequencing workflow, which involves fragmentation, hybridization to capture exonic regions, sequencing, mapping reads to reference genome, variant calling, and variant annotation. Challenges of finding causal variants are discussed. The document also compares benefits and challenges of exome sequencing versus whole genome sequencing or traditional methods. Finally, it discusses how exome sequencing has helped identify novel disease genes and expand knowledge of known disease genes.
Genomics is a discipline in genetics that applies recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble and analyze the function and structure of genomes
The document summarizes the sequencing of the yeast Saccharomyces cerevisiae genome. Key points:
1) The yeast genome was sequenced between 1989-1996 by over 35 European laboratories in a collaborative effort. By 1996, the entire 12 megabase genome across 16 chromosomes had been sequenced.
2) The genome contains approximately 6,000 open reading frames that were annotated after sequencing. About 30% of yeast genes have homologs in human genes.
3) Sequencing involved creating ordered cosmid libraries, shotgun sequencing, and assembling overlapping sequences into contigs. Genes were identified and analyzed after full genome assembly.
A retrospective look at the state of many famous modern genome sequences, and a cautionary tale of the dangers in assuming that genome sequence and/or its annotations are finished.
Genomics refers to the study of the entire genome of an organism. It deals with mapping genes on chromosomes and sequencing entire genomes. While work on genomics began with prokaryotes like bacteria, research has now been conducted on crop plants like rice and Arabidopsis thaliana. Genomics is an interdisciplinary field that uses tools from molecular biology, robotics, and computing to study genomes. It provides information on genome size, gene number, gene function, and evolution. Genomics has applications in crop improvement through gene mapping, marker-assisted selection, and transgenic breeding. However, genomic research also faces limitations due to high costs, technical challenges, and complexity of traits.
The document discusses genomics and provides an overview of key topics including the importance of studying genomes, the human genome project, applications of genomics such as genetic testing and pharmacogenomics, and legal and ethical issues. It notes that while humans share 99.9% identical genetic makeup, the remaining 0.1% difference provides information about disease susceptibility and responses to drugs and environmental factors. The human genome project mapped the entire human genome to further the understanding of health and disease. Genomics has applications in medicine such as improved diagnosis, drug development through pharmacogenomics, and precision medicine approaches tailored to individuals' genomes. However, genomics also raises ethical issues regarding use and privacy of genetic information.
A complete set of chromosomes/genes inherited as a unit from one parent called genome. The entire genetic complement of a living organism.
The total amount of genetic information in the chromosomes of an organism, including its genes and DNA sequences. The genome of eukaryotes is made up of a single, haploid set of chromosomes that is contained in the nucleus of every cell and exists in two copies in the chromosomes of all cells except reproductive and red blood cells. The human genome is made up of about 35,000 genes.
Aim1: To study the method of genome identification through ENSEMBL browser.
Aim2: To study the method of genome identification through VISTA.
Aim3: To study the method of genome identification through UCSC Genome Browser.
Aim4: To study the method of genome and amino acid sequences through UCSC Genome Browser.
The document discusses genome sequencing projects and their history. It describes how Frederic Sanger invented the shotgun sequencing method and how it works. The first bacterial genome completed was Haemophilus influenzae in 1995. Early animal genome projects included sequencing the genome of C. elegans, Drosophila melanogaster, mouse, and human. Genome assembly and annotation are also discussed, along with some early plant, animal, and marine genome sequencing projects. Issues with human genome sequencing are also mentioned.
Whole genome sequencing of arabidopsis thalianaBhavya Sree
This document summarizes the genome sequencing of Arabidopsis thaliana. It discusses that genome sequencing approaches began being discussed in 1984 and the Human Genome Project officially began in 1990. The Arabidopsis genome project was initiated in 1990 and was completed in 2000, sequencing approximately 115.4 Mb and predicting 25,498 genes. The outcomes of the sequencing project included characterization of coding regions, comparative analysis between accessions and other plant genera, and integration of the three plant genomes.
The genome is the complete set of genetic material within an organism. It is made up of DNA organized into chromosomes, which contain genes that specify traits. Sequencing the genome involves determining the order of nitrogenous bases that make up the DNA. While genome sequencing was previously very expensive, cost reductions have allowed researchers to study DNA variations within families to link genes to diseases.
Genomic sequencing allows researchers to determine the order of DNA nucleotides in whole genomes. There are two main approaches - hierarchical shotgun sequencing and whole genome shotgun sequencing. Hierarchical shotgun sequencing was used for the Human Genome Project. It involves first creating a physical map using markers like RFLPs, VNTRs, and STSs. The genome is then broken into large clones which are sequenced and assembled based on the physical map. Advances in genomic sequencing have led to sequencing of many important genomes like yeast, nematode, rice, fruit fly, and human. Genomic sequencing provides valuable information about gene structure and organization and aids in understanding genome function and evolution.
Genomics is the study of genomes and includes determining entire DNA sequences, genetic mapping, and studying intragenomic phenomena. It allows determining an ideal genotype. Genomics and bioinformatics provide benefits like improved crop productivity, stress tolerance, and nutritional quality. Proteomics studies proteins in cells. Bioinformatics handles large genomic and proteomic data using algorithms. Structural genomics constructs sequence data and maps genes. Functional genomics studies gene function. Comparative genomics compares sequences to find relationships.
Comparative proteogenomics using mass spectrometry data from multiple genomes can address problems that a single genome approach cannot. It helps identify rare post-translational modifications, resolve "one-hit wonders" by looking for correlated peptides in orthologous proteins across species, and identify programmed frameshifts and sequencing errors. The approach is demonstrated through an analysis of mass spectrometry data from three Shewanella bacteria genomes, improving gene predictions and annotations compared to existing tools.
The document outlines lectures on the human genome that will take place from October 12-16, 2014. It discusses the structure and content of the lectures. The lectures will cover: (1) an introduction and analogy comparing the genome to a book, (2) the human genome project and sequencing technologies, and (3) outcomes of the genomic era. It also provides background on the genome, including that humans are diploid and have 23 chromosome pairs, as well as an overview of polymerase chain reaction as a method for amplifying DNA sequences.
"Phylogenomics: Combining Evolutionary Reconstructions and Genome Analysis in...Jonathan Eisen
Talk by Jonathan Eisen given in December 2000 as guest seminar at the University of Maryland. Title; "Phylogenomics: Combining Evolutionary Reconstructions and Genome Analysis into a Single Composite Approach"
Phylogenomics talk in 2000 at University of Maryland by J. EisenJonathan Eisen
This document discusses phylogenomics, which combines evolutionary reconstructions and genome analysis into a single approach. It provides examples of how phylogenomic analysis can be used for functional predictions by examining the MutS family of proteins. A BLAST search of the H. pylori "MutS" protein initially suggested it was most similar to MutS2 from Syn. sp. A phylogenetic tree of the MutS family revealed that H. pylori MutS fell into a distinct subfamily, suggesting it may have a divergent function compared to other known MutS proteins.
Nadia Pisanti - With the recent New Genome Sequencing Technologies, Medicine and Biology are witnessing a revolution where Computer Science and Data Analysis play a crucial role. In this talk, I will give an overview of perspectives and challenges in this field.
Lecture1 1 Perl for bioinformatics Davide Pisani & James Cottonnathanlawless
Bioinformatics uses computers to store, organize, and interpret biological data, especially from high-throughput technologies that generate large datasets. These technologies include genomics, proteomics, interactomics, transcriptomics, and metabolomics. The amount of biological sequence data is enormous and growing rapidly, with over 7,000 ongoing genome projects currently and the human genome alone containing over 3 billion base pairs. Protein structure data is also extensively collected in databases like the Protein Data Bank.
The document discusses several types of genomics: structural genomics aims to determine the 3D structure of every protein encoded in a genome. Functional genomics determines the biological functions of genes and their products. Mutational genomics characterizes mutation-associated genes and links genotypes to transcriptional states. Comparative genomics compares genomic features between species to study evolution and identify conserved and unique genes.
This document provides an introduction to genomics and proteomics. It discusses key definitions and concepts related to genetics and genomics. It compares genome sizes across different species, from bacteria to humans. Key points include that the human genome is around 3 billion base pairs distributed across 23 chromosome pairs, and contains around 32,000 genes. The document outlines methods for identifying genes within genomes and discusses characteristics of prokaryotic and eukaryotic genomes.
Sk microfluidics and lab on-a-chip-ch3stanislas547
This document provides an overview of molecular biology concepts and analytical tools relevant to lab-on-a-chip applications in medical diagnostics. It describes the basic biological units of cells and DNA, as well as DNA analysis techniques like genome projects, DNA sequencing, and measuring gene expression using microarrays. Specific concepts covered include the central dogma of biology, DNA/RNA structure, genes and chromosomes, and how proteomics and single molecule DNA manipulation can be used for medical analysis.
The document discusses genomics and provides an overview of key topics including the importance of studying genomes, the human genome project, applications of genomics such as genetic testing and pharmacogenomics, and legal and ethical issues. It notes that while humans share 99.9% identical genetic makeup, the remaining 0.1% difference provides information about disease susceptibility and responses to drugs and environmental factors. The human genome project mapped the entire human genome to further the understanding of health and disease. Genomics has applications in medicine such as improved diagnosis, drug development through pharmacogenomics, and precision medicine approaches tailored to individuals' genomes. However, genomics also raises ethical issues regarding use and privacy of genetic information.
A complete set of chromosomes/genes inherited as a unit from one parent called genome. The entire genetic complement of a living organism.
The total amount of genetic information in the chromosomes of an organism, including its genes and DNA sequences. The genome of eukaryotes is made up of a single, haploid set of chromosomes that is contained in the nucleus of every cell and exists in two copies in the chromosomes of all cells except reproductive and red blood cells. The human genome is made up of about 35,000 genes.
Aim1: To study the method of genome identification through ENSEMBL browser.
Aim2: To study the method of genome identification through VISTA.
Aim3: To study the method of genome identification through UCSC Genome Browser.
Aim4: To study the method of genome and amino acid sequences through UCSC Genome Browser.
The document discusses genome sequencing projects and their history. It describes how Frederic Sanger invented the shotgun sequencing method and how it works. The first bacterial genome completed was Haemophilus influenzae in 1995. Early animal genome projects included sequencing the genome of C. elegans, Drosophila melanogaster, mouse, and human. Genome assembly and annotation are also discussed, along with some early plant, animal, and marine genome sequencing projects. Issues with human genome sequencing are also mentioned.
Whole genome sequencing of arabidopsis thalianaBhavya Sree
This document summarizes the genome sequencing of Arabidopsis thaliana. It discusses that genome sequencing approaches began being discussed in 1984 and the Human Genome Project officially began in 1990. The Arabidopsis genome project was initiated in 1990 and was completed in 2000, sequencing approximately 115.4 Mb and predicting 25,498 genes. The outcomes of the sequencing project included characterization of coding regions, comparative analysis between accessions and other plant genera, and integration of the three plant genomes.
The genome is the complete set of genetic material within an organism. It is made up of DNA organized into chromosomes, which contain genes that specify traits. Sequencing the genome involves determining the order of nitrogenous bases that make up the DNA. While genome sequencing was previously very expensive, cost reductions have allowed researchers to study DNA variations within families to link genes to diseases.
Genomic sequencing allows researchers to determine the order of DNA nucleotides in whole genomes. There are two main approaches - hierarchical shotgun sequencing and whole genome shotgun sequencing. Hierarchical shotgun sequencing was used for the Human Genome Project. It involves first creating a physical map using markers like RFLPs, VNTRs, and STSs. The genome is then broken into large clones which are sequenced and assembled based on the physical map. Advances in genomic sequencing have led to sequencing of many important genomes like yeast, nematode, rice, fruit fly, and human. Genomic sequencing provides valuable information about gene structure and organization and aids in understanding genome function and evolution.
Genomics is the study of genomes and includes determining entire DNA sequences, genetic mapping, and studying intragenomic phenomena. It allows determining an ideal genotype. Genomics and bioinformatics provide benefits like improved crop productivity, stress tolerance, and nutritional quality. Proteomics studies proteins in cells. Bioinformatics handles large genomic and proteomic data using algorithms. Structural genomics constructs sequence data and maps genes. Functional genomics studies gene function. Comparative genomics compares sequences to find relationships.
Comparative proteogenomics using mass spectrometry data from multiple genomes can address problems that a single genome approach cannot. It helps identify rare post-translational modifications, resolve "one-hit wonders" by looking for correlated peptides in orthologous proteins across species, and identify programmed frameshifts and sequencing errors. The approach is demonstrated through an analysis of mass spectrometry data from three Shewanella bacteria genomes, improving gene predictions and annotations compared to existing tools.
The document outlines lectures on the human genome that will take place from October 12-16, 2014. It discusses the structure and content of the lectures. The lectures will cover: (1) an introduction and analogy comparing the genome to a book, (2) the human genome project and sequencing technologies, and (3) outcomes of the genomic era. It also provides background on the genome, including that humans are diploid and have 23 chromosome pairs, as well as an overview of polymerase chain reaction as a method for amplifying DNA sequences.
"Phylogenomics: Combining Evolutionary Reconstructions and Genome Analysis in...Jonathan Eisen
Talk by Jonathan Eisen given in December 2000 as guest seminar at the University of Maryland. Title; "Phylogenomics: Combining Evolutionary Reconstructions and Genome Analysis into a Single Composite Approach"
Phylogenomics talk in 2000 at University of Maryland by J. EisenJonathan Eisen
This document discusses phylogenomics, which combines evolutionary reconstructions and genome analysis into a single approach. It provides examples of how phylogenomic analysis can be used for functional predictions by examining the MutS family of proteins. A BLAST search of the H. pylori "MutS" protein initially suggested it was most similar to MutS2 from Syn. sp. A phylogenetic tree of the MutS family revealed that H. pylori MutS fell into a distinct subfamily, suggesting it may have a divergent function compared to other known MutS proteins.
Nadia Pisanti - With the recent New Genome Sequencing Technologies, Medicine and Biology are witnessing a revolution where Computer Science and Data Analysis play a crucial role. In this talk, I will give an overview of perspectives and challenges in this field.
Lecture1 1 Perl for bioinformatics Davide Pisani & James Cottonnathanlawless
Bioinformatics uses computers to store, organize, and interpret biological data, especially from high-throughput technologies that generate large datasets. These technologies include genomics, proteomics, interactomics, transcriptomics, and metabolomics. The amount of biological sequence data is enormous and growing rapidly, with over 7,000 ongoing genome projects currently and the human genome alone containing over 3 billion base pairs. Protein structure data is also extensively collected in databases like the Protein Data Bank.
The document discusses several types of genomics: structural genomics aims to determine the 3D structure of every protein encoded in a genome. Functional genomics determines the biological functions of genes and their products. Mutational genomics characterizes mutation-associated genes and links genotypes to transcriptional states. Comparative genomics compares genomic features between species to study evolution and identify conserved and unique genes.
This document provides an introduction to genomics and proteomics. It discusses key definitions and concepts related to genetics and genomics. It compares genome sizes across different species, from bacteria to humans. Key points include that the human genome is around 3 billion base pairs distributed across 23 chromosome pairs, and contains around 32,000 genes. The document outlines methods for identifying genes within genomes and discusses characteristics of prokaryotic and eukaryotic genomes.
Sk microfluidics and lab on-a-chip-ch3stanislas547
This document provides an overview of molecular biology concepts and analytical tools relevant to lab-on-a-chip applications in medical diagnostics. It describes the basic biological units of cells and DNA, as well as DNA analysis techniques like genome projects, DNA sequencing, and measuring gene expression using microarrays. Specific concepts covered include the central dogma of biology, DNA/RNA structure, genes and chromosomes, and how proteomics and single molecule DNA manipulation can be used for medical analysis.
The document provides an introduction to proteomics and genomics. It discusses that proteomics is the large-scale study of proteins, which is more complex than genomics due to constant changes in the proteome through biochemical interactions. Key points covered include an overview of proteomics technologies like electrophoresis, mass spectrometry and chromatography. It also discusses maps of hereditary information like linkage maps, chromosome banding patterns, contig maps and single nucleotide polymorphisms (SNPs). The document aims to give an overview of important concepts and technologies in proteomics and genomics.
This document provides an introduction to proteomics. It begins by defining proteomics as the large-scale study of proteins, their structures and functions. Unlike genomics, the proteome is constantly changing through biochemical interactions. Key points made include: proteomics aims to describe the deployment of proteins in an organism over time and space; post-translational modifications mean proteins differ from what is suggested by genes; and mass spectrometry, electrophoresis and chromatography are important technologies used to identify and characterize proteins and their interactions.
Chapter 7 genome structure, chromatin, and the nucleosome (1)Roger Mendez
This document provides an overview of genome structure and organization. It discusses the components of chromosomes, including DNA and histone and non-histone proteins. It describes differences in genome size and organization between prokaryotes and eukaryotes. In humans, it notes the 22 pairs of autosomes and sex chromosomes. It also discusses repetitive and unique sequences in genomes, including pseudogenes, transposons, gene duplications, and the roles of introns and intergenic DNA.
contains descriptive and other studies on genetics and epigenetics and whole gene concepts from central dogma to future concepts . Dr Harshavardhan Patwal
this is done by me and my team mates of Wayamba University Sri Lanka for our project.From now we decided to allow download this file.I would be greatful if you could send your comments..
And I'm willing to help you in similar works.I'm in final year of my degree(.BSc Biotechnology)..
pubudu_gokarella@yahoo.com
The human PRNP gene is located on chromosome 20 and encodes the prion protein (PrP). Mutations in this gene can cause neurodegenerative diseases like Creutzfeldt-Jakob disease. The protein's exact function is unknown but it may be involved in copper transport, neuroprotection, and communication between neurons. Alternatively spliced variants have been identified for this gene and the mouse protein shares high sequence identity with the human protein. Clinically relevant genetic variants in PRNP have been associated with prion diseases.
Model organisms are non-human species that are widely studied in laboratories to help scientists understand biological processes. They are usually easy to maintain and breed in a lab setting. The document discusses several important model organisms including mice, fruit flies, yeast, and bacteria. It provides details on their genomes, uses for research, and similarities to humans that make them valuable models. Key model organisms like mice and fruit flies have been widely used to study genetics, development, and disease due to their small genomes and short lifecycles.
The document summarizes the history and key aspects of the Human Genome Project. It began in the 1980s with the sequencing of important genes. In the 1990s, the first whole bacterial genome was sequenced. The project, carried out from 1990-2003, was a large international collaboration that sequenced the entire human genome. It involved mapping the genome using markers and then determining the base sequence using shotgun sequencing and Sanger sequencing. The outcomes included discovering that most of the genome is non-coding junk DNA, and identifying around 25,000 human genes located across 23 chromosome pairs.
This document discusses DNA sequencing and bioinformatics. It explains that DNA sequencing has become much cheaper and faster, allowing entire genomes to be sequenced. Sequencing the human genome originally cost billions and took years, but can now be done for under $100,000. Understanding DNA sequences allows for preventing and curing diseases. The document goes on to describe what genes look like, where they are found, how they encode proteins, and how bioinformaticians can identify genes by finding open reading frames in DNA sequences.
This document discusses DNA sampling and analysis techniques. It begins by outlining the aims and objectives, which are to understand the basic structure of DNA, various DNA sampling methods, extraction techniques, profiling methods, applications, limitations and case studies. It then provides detailed information on the structure of human DNA, genetic markers like SNPs, satellites, minisatellites and microsatellites. The document also discusses methods of collecting biological samples for DNA analysis from various sources like blood, saliva, teeth etc and sending them for authentication and testing.
This document discusses chromosomes and their structure and function. It begins with the historical discovery of chromosomes in 1875 and defines them as stainable nuclear components that duplicate and are passed from parents to offspring. It describes the main types of chromosomes, including autosomes and sex chromosomes. It details the structure of chromosomes and their compaction into nucleosomes and higher order packaging. Key parts like the centromere and kinetochores are explained. The functions of chromosomes in heredity, growth, and determining sex are summarized. Special giant chromosome types like polytene and lampbrush chromosomes found in insect salivary glands and amphibian oocytes respectively are also outlined.
The document discusses the Human Genome Project, which had goals of identifying all 30,000 human genes, determining the sequence of the 3 billion base pairs that make up human DNA, storing this information in databases, and improving data analysis tools. By sequencing factories generating 1000 nucleotides per second, the project was completed ahead of schedule. The project revealed that humans have fewer genes than expected, 99.9% of bases are identical between humans, and 50% or more of the genome consists of "junk DNA" with unknown functions.
Organellar genomes, such as those found in mitochondria and chloroplasts, can be manipulated. The mitochondria genome is maternally inherited and contains genes that code for proteins involved in respiration. The chloroplast genome is also maternally inherited and contains genes for photosynthesis-related proteins. Methods to transform these genomes include particle bombardment, PEG-mediated transformation, and Agrobacterium-mediated transformation. Manipulating organellar genomes has applications for crop improvement like developing cytoplasmic male sterility.
The document discusses genome sequencing and related topics. It begins by defining what a genome is - the complete set of DNA in an organism. It then discusses the different types of genomes, such as prokaryotic and eukaryotic, including nuclear, mitochondrial, and chloroplast genomes. The document also defines genomics as the comprehensive study of whole genomes and all gene interactions, distinguishing it from traditional genetics which focuses on single genes. It outlines some key milestones in genomic sequencing and the technical foundations that enabled sequencing whole genomes. Finally, it describes the main approaches used for genome sequencing projects, including hierarchical shotgun sequencing and whole genome shotgun sequencing.
The Human Genome Project was an international scientific research project with the goal of determining the sequence of nucleotide base pairs that make up human DNA. It originally aimed to map the over three billion nucleotides contained in the human genome. The finished human genome is a mosaic assembled from sequencing a small number of individuals. The project has provided insights into human genetics and disease research.
The document discusses the human genome project, which aimed to sequence the entire human genome and identify all human genes. It provides background on the human genome, describing its size, number of genes, and chromosomes. It details the goals and milestones of the human genome project from 1986 to 2003. Vectors like yeast artificial chromosomes and bacterial artificial chromosomes were used to clone large fragments of DNA for sequencing.
1. Mutations are changes in the nucleotide sequence of DNA that can arise spontaneously during DNA replication or due to damage from mutagens.
2. DNA repair enzymes work to minimize mutations by correcting errors during replication or reacting to damaged DNA.
3. If a mismatch introduced during replication is not repaired, it will become a permanent mutation when that region is replicated again.
The document discusses key concepts in biochemistry including cells, chromosomes, DNA, and genes. It describes cells as the basic structural and functional units of living organisms and explains the differences between prokaryotic and eukaryotic cells. The role of chromosomes, DNA, and genes in heredity and controlling the metabolism of organisms is also summarized.
The document discusses genome assembly and finishing processes. It begins by outlining typical project goals of completely restoring the genome and producing a high-quality consensus sequence. It then describes the evolution of sequencing technologies from Sanger to newer platforms and their impact on draft assemblies. Key steps in the assembly and finishing process include library preparation, assembly, identifying gaps, and improving consensus quality.
The cell membrane separates the intracellular components of the cell from the external environment. It is composed of a lipid bilayer with embedded proteins and acts as a selective barrier. The cytoplasm contains organelles that carry out specialized functions like the mitochondria, which generates energy, and the endoplasmic reticulum and Golgi apparatus, which modify and transport proteins. Lysosomes contain enzymes that break down materials inside and outside the cell. Together, these organelles and their membranes comprise the endomembrane system, which manufactures components and transports materials within the cell.
The document discusses gene expression and regulation in eukaryotes. It covers several key points in 3 sentences:
Eukaryotic genes require complex regulatory systems involving chromatin remodeling and transcription factors to initiate expression, unlike bacterial genes which can be transcribed without regulatory proteins. Development in multicellular organisms is controlled by signaling between cells using hormones and diffusible receptors which act as transcriptional regulators. Gene expression patterns in fruit flies establish polarity, segment the body, and determine segment identities through maternal, segmentation, and homeotic genes, providing insights into human developmental gene regulation.
Proteins are composed of amino acids linked together by peptide bonds to form polypeptide chains. There are 20 standard amino acids that make up proteins. Proteins have four levels of structure - primary, secondary, tertiary, and quaternary. The primary structure is the linear sequence of amino acids. Secondary structures form due to hydrogen bonding between amino acids and include alpha helices and beta sheets. Tertiary structure involves folding of secondary structures into a compact 3D structure. Hydrogen bonds, disulfide bridges, and hydrophobic interactions stabilize tertiary structure.
The document discusses several DNA repair mechanisms including mismatch repair, base excision repair, nucleotide excision repair, direct repair, and recombinational repair. It also describes different types of recombination including homologous recombination, site-specific recombination, and transposition. Finally, it discusses mechanisms of meiotic recombination including gene conversion and resolution of Holliday structures.
The document discusses chromosomes, mitosis, meiosis, and apoptosis. It explains that chromosomes contain DNA and genes, and replicate during cell division. Mitosis produces genetically identical cells while meiosis creates gametes with half the number of chromosomes. Apoptosis is programmed cell death that occurs through caspase activation and DNA fragmentation, while necrosis results from external damage.
The document discusses metabolism and metabolic pathways. It summarizes that catabolism provides energy and building blocks for anabolism through metabolic pathways. Metabolic pathways involve enzymatically catalyzed reactions, with enzymes determining the pathways. Reaction rates are influenced by factors like temperature, pH, substrate concentration, and inhibitors. The document then discusses specific metabolic pathways like glycolysis, the Krebs cycle, and the electron transport chain which are involved in breaking down carbohydrates to release energy through cellular respiration.
The document discusses the main types of biological macromolecules - proteins, carbohydrates, lipids, and nucleic acids. It provides details on their structures, functions and examples of each type of macromolecule. The key macromolecules discussed are proteins, which are composed of amino acids, and nucleic acids like DNA and RNA, which provide genetic instructions and are made of nucleotides containing nitrogen bases. Energy production in cells is also summarized, with ATP being generated through substrate-level phosphorylation or chemiosmosis using electron transport chains.
Globular proteins are spherical proteins that contain heme as a prosthetic group. Globular heme proteins function as electron carriers, parts of enzyme active sites, and carriers of oxygen and carbon dioxide like hemoglobin and myoglobin. Myoglobin stores oxygen in muscle cells and facilitates oxygen transport between hemoglobin and cells. Hemoglobin transports oxygen in red blood cells through a cooperative binding mechanism between its four heme groups that allows for high oxygen affinity when oxygen levels are high. Both proteins bind oxygen reversibly to their heme groups through interactions with proximal and distal histidine residues.
Cloning involves inserting foreign DNA into a vector, which is then taken up by host cells. The host cells replicate, producing multiple copies of the recombinant DNA. Libraries contain fragments of DNA from a source inserted randomly into vectors. Genomic libraries contain chromosomal DNA fragments, while cDNA libraries contain mRNA sequences converted to DNA. Expression libraries contain cDNAs in vectors allowing protein expression. Cloning allows isolation and expression of genes, enabling study and production of proteins.
The document summarizes various genetic techniques including PCR, restriction mapping, the human genome project, in situ hybridization, and cloning the gene responsible for alkaptonuria. It provides an example of how PCR, genomic libraries, DNA sequencing, and other methods were used to clone the HGO gene involved in alkaptonuria. Ethical considerations are discussed around using genetic testing to predict late-onset genetic disorders in fetuses.
This lecture discusses genome organization and structure. It covers topics like genome size, DNA hybridization, Cot curves, repeated sequences, introns and exons. Cot curves show that apparently large genomes are filled with repetitive sequences, resolving the C-value paradox. There are two types of repeated sequences - tandem repeats like satellites and interspersed repeats like retrotransposons and SINEs. Genome structure includes features like linear/circular chromosomes, centromeres, telomeres, GC content distributions. Genes contain exons and introns, and detecting open reading frames is a way to predict genes, though it works better in prokaryotes than eukaryotes due to intron sizes.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Presentation of the OECD Artificial Intelligence Review of Germany
Biotech 2011-01-intro
1. Ulf Schmitz, Introduction to genomics and proteomics I 1
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BioinformaticsBioinformatics
Introduction to genomics and proteomics IIntroduction to genomics and proteomics I
Ulf Schmitz
ulf.schmitz@informatik.uni-rostock.de
Bioinformatics and Systems Biology Group
www.sbi.informatik.uni-rostock.de
2. Ulf Schmitz, Introduction to genomics and proteomics I 2
www. .uni-rostock.de
Outline
Genomics/Genetics
1. The tree of life
• Prokaryotic Genomes
– Bacteria
– Archaea
• Eukaryotic Genomes
– Homo sapiens
2. Genes
• Expression Data
3. Ulf Schmitz, Introduction to genomics and proteomics I 3
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Genomics - Definitions
Genetics: is the science of genes, heredity, and the variation of organisms.
Humans began applying knowledge of genetics in prehistory with
the domestication and breeding of plants and animals.
In modern research, genetics provides tools in the investigation
of the function of a particular gene, e.g. analysis of genetic
interactions.
Genomics: attempts the study of large-scale genetic patterns across the
genome for a given species. It deals with the systematic use of
genome information to provide answers in biology, medicine, and
industry.
Genomics has the potential of offering new therapeutic methods
for the treatment of some diseases, as well as new diagnostic
methods.
Major tools and methods related to genomics are bioinformatics,
genetic analysis, measurement of gene expression, and
determination of gene function.
4. Ulf Schmitz, Introduction to genomics and proteomics I 4
www. .uni-rostock.deGenes
• a gene coding for a protein corresponds to a sequence of
nucleotides along one or more regions of a molecule of DNA
• in species with double stranded DNA (dsDNA), genes may appear
on either strand
• bacterial genes are continuous regions of DNA
bacterium:
• a string of 3N nucleotides encodes a string of N amino acids
• or a string of N nucleotides encodes a structural RNA molecule of N
residues
eukaryote:
• a gene may appear split into separated segments in the DNA
• an exon is a stretch of DNA retained in mRNA that the ribosomes translate
into protein
5. Ulf Schmitz, Introduction to genomics and proteomics I 5
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Genomics
Genome size comparison
4.1 million5,0001Bacterium
(E. coli)
19,000
14,000
14,000
31,000
22.5-30,000
28-35,000
Genes
97 million12Roundworm
(C. elegans)
137 million8Fruit Fly
(Drosophila melanogaster)
289 million6Malaria mosquito
(Anopheles gambiae)
365 million44Puffer fish
(Fugu rubripes)
2.7 billion40Mouse
(Mus musculus)
3.1 billion46
(23 pairs)
Human
(Homo sapiens)
Base pairsChrom.Species
6. Ulf Schmitz, Introduction to genomics and proteomics I 6
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Genes
exon:
A section of DNA which carries the coding
sequence for a protein or part of it. Exons
are separated by intervening, non-coding
sequences (called introns). In eukaryotes
most genes consist of a number of exons.
exon:
A section of DNA which carries the coding
sequence for a protein or part of it. Exons
are separated by intervening, non-coding
sequences (called introns). In eukaryotes
most genes consist of a number of exons.
intron:
An intervening section of DNA which occurs
almost exclusively within a eukaryotic gene, but
which is not translated to amino-acid sequences in
the gene product.
The introns are removed from the pre-mature
mRNA through a process called splicing, which
leaves the exons untouched, to form an active
mRNA.
intron:
An intervening section of DNA which occurs
almost exclusively within a eukaryotic gene, but
which is not translated to amino-acid sequences in
the gene product.
The introns are removed from the pre-mature
mRNA through a process called splicing, which
leaves the exons untouched, to form an active
mRNA.
7. Ulf Schmitz, Introduction to genomics and proteomics I 7
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Genes
exon intron
Globin gene – 1525 bp: 622 in exons, 893 in introns
Ovalbumin gene - ~ 7500 bp: 8 short exons comprising 1859 bp
Conalbumin gene - ~ 10,000 bp: 17 short exons comprising ~ 2,200 bp
Examples of the exon:intron mosaic of genes
8. Ulf Schmitz, Introduction to genomics and proteomics I 8
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Picking out genes in genomes
• Computer programs for genome analysis identify ORFs
(open reading frames)
• An ORF begins with an initiation codon ATG (AUG)
• An ORF is a potential protein-coding region
• There are two approaches to identify protein coding
regions…
9. Ulf Schmitz, Introduction to genomics and proteomics I 9
www. .uni-rostock.de
Picking out genes in genomes
• Regions may encode amino acid sequences similar to known proteins
• Or may be similar to ESTs (correspond to genes known to be
expressed)
• Few hundred initial bases of cDNA are sequenced to identify a gene
1. Detection of regions similar to known coding regions from other organisms
2. Ab initio methods, seek to identify genes from the properties of the
DNA sequence itself
• Bacterial genes are easy to identify, because they are contiguous
• They have no introns and the space between genes is small
• Identification of exons in higher organisms is a problem, assembling
them another…
10. Ulf Schmitz, Introduction to genomics and proteomics I 10
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Picking out genes in genomes
• The initial (5´) exon starts with a transcription start
point, preceded by a core promoter site such as the
TATA box (~30bp upstream)
– Free of stop codons
– End immediately before a GT splice-signal
Ab initio gene identification in eukaryotic genomes
binds and directs RNA polymerase
to the correct transcriptional start site
11. Ulf Schmitz, Introduction to genomics and proteomics I 11
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Picking out genes in genomes
5' splice signal
3' splice signal
12. Ulf Schmitz, Introduction to genomics and proteomics I 12
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Picking out genes in genomes
• Internal exons are free of stop codons too
– Begin after an AG splice signal
– End before a GT splice signal
Ab initio gene identification in eukaryotic genomes
13. Ulf Schmitz, Introduction to genomics and proteomics I 13
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Picking out genes in genomes
• The final (3´) exon starts after a an AG splice signal
– Ends with a stop codon (TAA,TAG,TGA)
– Followed by a polyadenylation signal sequence
Ab initio gene identification in eukaryotic genomes
14. Ulf Schmitz, Introduction to genomics and proteomics I 14
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Humans have
spliced genes…
15. Ulf Schmitz, Introduction to genomics and proteomics I 15
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DNA makes RNA makes Protein
16. Ulf Schmitz, Introduction to genomics and proteomics I 16
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Tree of life
Prokaryotes
17. Ulf Schmitz, Introduction to genomics and proteomics I 17
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Genomics – Prokaryotes
• the genome of a prokaryote comes
as a single double-stranded DNA
molecule in ring-form
– in average 2mm long
– whereas the cells diameter is only
0.001mm
– < 5 Mb
• prokaryotic cells can have plasmids
as well (see next slide)
• protein coding regions have no
introns
• little non-coding DNA compared to
eukaryotes
– in E.coli only 11%
18. Ulf Schmitz, Introduction to genomics and proteomics I 18
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Genomics - Plasmids
• Plasmids are circular double stranded DNA molecules that are separate
from the chromosomal DNA.
• They usually occur in bacteria, sometimes in eukaryotic organisms
• Their size varies from 1 to 250 kilo base pairs (kbp). There are from one
copy, for large plasmids, to hundreds of copies of the same plasmid
present in a single cell.
19. Ulf Schmitz, Introduction to genomics and proteomics I 19
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Prokaryotic model organisms
E.coli (Escherichia coli)
Methanococcus jannaschii (archaeon)
Mycoplasma genitalium
(simplest organism known)
20. Ulf Schmitz, Introduction to genomics and proteomics I 20
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Genomics
• DNA of higher organisms is organized into chromosomes
(human – 23 chromosome pairs)
• not all DNA codes for proteins
• on the other hand some genes exist in multiple copies
• that’s why from the genome size you can’t easily estimate
the amount of protein sequence information
21. Ulf Schmitz, Introduction to genomics and proteomics I 21
www. .uni-rostock.de
Genomes of eukaryotes
• majority of the DNA is in the nucleus, separated into
bundles (chromosomes)
– small amounts of DNA appear in organelles (mitochondria and
chloroplasts)
• within single chromosomes gene families are common
– some family members are paralogues (related)
• they have duplicated within the same genome
• often diverged to provide separate functions in descendants
(Nachkommen)
• e.g. human α and β globin
– orthologues genes
• are homologues in different species
• often perform the same function
• e.g. human and horse myoglobin
– pseudogenes
• lost their function
• e.g. human globin gene cluster
pseudogene
22. Ulf Schmitz, Introduction to genomics and proteomics I 22
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Eukaryotic model organisms
• Saccharomyces cerevisiae (baker’s yeast)
• Caenorhabditis elegans (C.elegans)
• Drosophila melanogaster (fruit fly)
• Arabidopsis thaliana (flower)
• Homo sapiens (human)
23. Ulf Schmitz, Introduction to genomics and proteomics I 23
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The human genome
• ~3.2 x 109 bp (thirty time larger than C.elegans or D.melongaster)
• coding sequences form only 5% of the human genome
• Repeat sequences over 50%
• Only ~32.000 genes
• Human genome is distributed over 22 chromosome pairs plus X and
Y chromosomes
• Exons of protein-coding genes are relatively small compared to
other known eukaryotic genomes
• Introns are relatively long
• Protein-coding genes span long stretches of DNA (dystrophin,
coding a 3.685 amino acid protein, is >2.4Mbp long)
• Average gene length: ~ 8,000 bp
• Average of 5-6 exons/gene
• Average exon length: ~200 bp
• Average intron length: ~2,000 bp
• ~8% genes have a single exon
• Some exons can be as small as 1 or 3 bp.
24. Ulf Schmitz, Introduction to genomics and proteomics I 24
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0.03Enzyme activator
20.6
2.9
2.5
5.3
1.8
3242
457
403
839
295
Enzyme
Peptidase
Endopeptidase
Protein kinase
Protein phosphatase
3.8603Defense/immunity protein
0.8129Actin binding
0.585Motor
0.9154Chaperone
0.475Cell Cycle regulator
0.06Transcription factor binding
14.0
10.5
0.2
0.0
6.2
2.4
0.8
0.2
2207
1656
45
7
986
380
137
44
Nucleic acid binding
DNA binding
DNA repair protein
DNA replication factor
Transcription factor
RNA binding
Structural protein of ribosome
Translation factor
%NumberFunction
100.015683Total
30.64813Unclassified
0.05Tumor suppressor
9.7
0.2
0.3
1536
33
50
Ligand binding or carrier
Electron transfer
Cytochrome P450
4.3
1.7
0.1
682
269
19
Transporter
Ion channel
Neurotransmitter transporter
4.5
0.9
714
145
Structural protein
Cytoskeletal structural protein
1.2189Cell adhesion
0.07Storage protein
11.4
8.4
7.6
3.1
0.0
1790
1318
1202
489
71
Signal transduction
Receptor
Transmembrane receptor
G-protein link receptor
Olfactory receptor
0.8132Apoptosis inhibitor
%NumberFunction
The human genomeThe human genome
Top categories in a function classification:
25. Ulf Schmitz, Introduction to genomics and proteomics I 25
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The human genome
• Repeated sequences comprise over 50% of the genome:
– Transposable elements, or interspersed repeats include LINEs and
SINEs (almost 50%)
– Retroposed pseudogenes
– Simple ‘stutters’ - repeats of short oligomers (minisatellites and
microsatellites)
– Segment duplication, of blocks of ~10 - 300kb
– Blocks of tandem repeats, including gene families
3300.00080-3000DNA Transposon fossils
8450.00015.000 -110.000Long Terminal Repeats
21850.0006000-8000Long Interspersed Nuclear
Elements (LINEs)
131.500.000100-300Short Interspersed Nuclear
Elements (SINEs)
Fraction of
genome %
Copy
number
Size (bp)Element
26. Ulf Schmitz, Introduction to genomics and proteomics I 26
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The human genome
• All people are different, but the DNA of different
people only varies for 0.2% or less.
• So, only up to 2 letters in 1000 are expected to be
different.
• Evidence in current genomics studies (Single
Nucleotide Polymorphisms or SNPs) imply that on
average only 1 letter out of 1400 is different
between individuals.
• means that 2 to 3 million letters would differ
between individuals.
27. Ulf Schmitz, Introduction to genomics and proteomics I 27
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TERTIARY STRUCTURE (fold)
TERTIARY STRUCTURE (fold)
Genome
Expressome
Proteome
Metabolome
Functional Genomics
From gene to functionFrom gene to function
28. Ulf Schmitz, Introduction to genomics and proteomics I 28
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DNA makes RNA makes Protein:
Expression data
• More copies of mRNA for a gene leads to more
protein
• mRNA can now be measured for all the genes in a
cell at ones through microarray technology
• Can have 60,000 spots (genes) on a single gene
chip
• Color change gives intensity of gene expression
(over- or under-expression)
30. Ulf Schmitz, Introduction to genomics and proteomics I 30
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Genes and regulatory regions
regulatory mechanisms organize the
expression of genes
– genes may be turned on or off in response to
concentrations of nutrients or to stress
– control regions often lie near the segments
coding for proteins
– they can serve as binding sites for molecules
that transcribe the DNA
– or they bind regulatory molecules that can
block transcription
32. Ulf Schmitz, Introduction to genomics and proteomics I 32
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Outlook – coming lecture
Proteomics
– Proteins
– post-translational modification
– Key technologies
• Maps of hereditary information
• SNPs (Single nucleotide polymorphisms)
• Genetic diseases
33. Ulf Schmitz, Introduction to genomics and proteomics I 33
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Thanks for your
attention!
34. Ulf Schmitz, Introduction to genomics and proteomics II 1
www. .uni-rostock.de
BioinformaticsBioinformatics
Introduction to genomics and proteomics IIIntroduction to genomics and proteomics II
ulf.schmitz@informatik.uni-rostock.de
Bioinformatics and Systems Biology Group
www.sbi.informatik.uni-rostock.de
35. Ulf Schmitz, Introduction to genomics and proteomics II 2
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Outline
1. Proteomics
• Motivation
• Post -Translational Modifications
• Key technologies
• Data explosion
2. Maps of hereditary information
3. Single nucleotide polymorphisms
36. Ulf Schmitz, Introduction to genomics and proteomics II 3
www. .uni-rostock.de
Protomics
Proteomics:
• is the large-scale study of proteins, particularly their structures
and functions
• This term was coined to make an analogy with genomics, and
is often viewed as the "next step",
• but proteomics is much more complicated than genomics.
• Most importantly, while the genome is a rather constant entity,
the proteome is constantly changing through its biochemical
interactions with the genome.
• One organism will have radically different protein expression in
different parts of its body and in different stages of its life cycle.
Proteome:
The entirety of proteins in existence in an organism are
referred to as the proteome.
37. Ulf Schmitz, Introduction to genomics and proteomics II 4
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Proteomics
If the genome is a list of the instruments in an orchestra, the
proteome is the orchestra playing a symphony.
R.Simpson
38. Ulf Schmitz, Introduction to genomics and proteomics II 5
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Proteomics
• Describing all 3D structures of proteins in the cell is called Structural
Genomics
• Finding out what these proteins do is called Functional Genomics
GENOME
PROTEOME
DNA Microarray Genetic Screens
Protein – Ligand
Interactions
Protein – Protein
Interactions
Structure
39. Ulf Schmitz, Introduction to genomics and proteomics II 6
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Proteomics
• What kind of data would we like to measure?
• What mature experimental techniques exist to
determine them?
• The basic goal is a spatio-temporal description of
the deployment of proteins in the organism.
Motivation:
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Proteomics
• the rates of synthesis of different proteins vary among
different tissues and different cell types and states of activity
• methods are available for efficient analysis of transcription
patterns of multiple genes
• because proteins ‘turn over’ at different rates, it is also
necessary to measure proteins directly
• the distribution of expressed protein levels is a kinetic
balance between rates of protein synthesis and degradation
Things to consider:
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Why do Proteomics?
• are there differences between amino acid sequences determined
directly from proteins and those determined by translation from
DNA?
– pattern recognition programs addressing this questions have following
errors:
• a genuine protein sequence may be missed entirely
• an incomplete protein may be reported
• a gene may be incorrectly spliced
• genes for different proteins may overlap
• genes may be assembled from exons in different ways in different tissues
– often, molecules must be modified to make a mature protein that differs
significantly from the one suggested by translation
• in many cases the missing post-translational- modifications are quite
important and have functional significance
• post-transitional modifications include addition of ligands, glycosylation,
methylation, excision of peptides, etc.
– in some cases mRNA is edited before translation, creating changes in
the amino acid sequence that are not inferrable from the genes
• a protein inferred from a genome sequence is a hypothetical object
until an experiment verifies its existence
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Post-translational modification
• a protein is a polypeptide chain composed of 20 possible amino acids
• there are far fewer genes that code for proteins in the human genome than there
are proteins in the human proteome (~33,000 genes vs ~200,000 proteins).
• each gene encodes as many as six to eight different proteins
– due to post-translational modifications such as phosphorylation, glycosylation or cleavage
(Spaltung)
• posttranslational modification extends the range of possible functions a protein can
have
– changes may alter the hydrophobicity of a protein and thus determine if the modified
protein is cytosolic or membrane-bound
– modifications like phosphorylation are part of common mechanisms for controlling the
behavior of a protein, for instance, activating or inactivating an enzyme.
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Post-translational modification
• phosphorylation is the addition of a phosphate (PO4) group to a protein
or a small molecule (usual to serine, tyrosine, threonine or histidine)
• In eukaryotes, protein phosphorylation is probably the most important
regulatory event
• Many enzymes and receptors are switched "on" or "off" by
phosphorylation and dephosphorylation
• Phosphorylation is catalyzed by various specific protein kinases,
whereas phosphatases dephosphorylate.
Phosphorylation
Acetylation
• Is the addition of an acetyl group, usually at the N-terminus of the protein
Farnesylation
• farnesylation, the addition of a farnesyl group
Glycosylation
• the addition of a glycosyl group to either asparagine, hydroxylysine,
serine, or threonine, resulting in a glycoprotein
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Key technologies for proteomics
1. 1-D electrophoresis and 2-D electrophoresis
• are for the separation and visualization of proteins.
2. mass spectrometry, x-ray crystallography, and NMR
(Nuclear magnetic resonance )
• are used to identify and characterize proteins
3. chromatography techniques especially affinity
chromatography
• are used to characterize protein-protein interactions.
4. Protein expression systems like the yeast two-
hybrid and FRET (fluorescence resonance energy
transfer)
• can also be used to characterize protein-protein interactions.
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Key technologies for proteomics
Reference map of lympphoblastoid
cell linePRI, soluble proteins.
• 110 µg of proteins loaded
• Strip 17cm pH gradient 4-7, SDS
PAGE gels 20 x 25 cm, 8-18.5% T.
• Staining by silver nitrate method
(Rabilloud et al.,)
• Identification by mass spectrometry.
The pinks labels on the spots indicate
the ID in Swiss-prot database
browse the SWISS-2DPAGE database for more 2d PAGE images
High-resolution two-dimensional polyacrylamide gel
electrophoresis (2D PAGE) shows the pattern of
protein content in a sample.
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Proteomics
Typically, a sample is purified to
homogeneity, crystallized, subjected to an X-
ray beam and diffraction data are collected.
X-ray crystallography is a means to
determine the detailed molecular
structure of a protein, nucleic acid or
small molecule.
With a crystal structure we can explain the
mechanism of an enzyme, the binding of an
inhibitor, the packing of protein domains, the
tertiary structure of a nucleic acid molecule
etc..
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High-throughput Biological Data
• Enormous amounts of biological data are being
generated by high-throughput capabilities; even
more are coming
– genomic sequences
– gene expression data (microarrays)
– mass spec. data
– protein-protein interaction (chromatography)
– protein structures (x-ray christallography)
– ......
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Protein structural data explosion
Protein Data Bank (PDB): 33.367 Structures (1 November 2005)
28.522 x-ray crystallography, 4.845 NMR
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Maps of hereditary information
1. Linkage maps of
genes
mini- / microsatellites
2. Banding patterns of chromosomes
physical objects with visible landmarks called banding patterns
3. DNA sequences
Contig maps (contigous clone maps)
Sequence tagged site (STS)
SNPs (Single nucloetide polymorphisms)
Following maps are used to find out how hereditary information is
stored, passed on, and implemented.
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Maps of hereditary information
• regions, 8-80bp long, repeated a variable number of times
• the distribution and the size of repeats is the marker
• inheritance of VNTRs can be followed in a family and
mapped to a pathological phenotype
• first genetic data used for personal identification
– Genetic fingerprints; in paternity and in criminal cases
Variable number tandem repeats (VNTRs, also minisatellites)
Short tandem repeat polymorphism (STRPs, also microsatellites)
• Regions of 2-7bp, repeated many times
– Usually 10-30 consecutive copies
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centromere
CGTCGTCGTCGTCGTCGTCGTCGT...
GCAGCAGCAGCAGCAGCAGCAGCA...
3bp
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Maps of hereditary information
Banding patterns of
chromosomes
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Maps of hereditary information
Banding patterns of chromosomes
petite – arm
centromere
queue - arm
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Maps of hereditary information
• Series of overlapping DNA clones of known
order along a chromosome from an organism
of interest, stored in yeast or bacterial cells as
YACs (Yeast Artificial Chromosomes) or
BACs (Bacterial Artificial Chromosomes)
• A contig map produces a fine mapping (high
resolution) of a genome
• YAC can contain up to 106bp, a BAC about
250.000bp
Contig map (also contiguous clone map)
Sequence tagged site (STS)
• Short, sequenced region of DNA, 200-600bp
long, that appears in a unique location in the
genome
• One type arises from an EST (expressed
sequence tag), a piece of cDNA
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Maps of hereditary information
1. if we know the protein involved, we can pursue
rational approaches to therapy
2. if we know the gene involved, we can devise
tests to identify sufferers or carriers
3. wereas the knowledge of the chromosomal
location of the gene is unnecessary in many
cases for either therapy or detection;
• it is required only for identifying the gene, providing a
bridge between the patterns of inheritance and the
DNA sequence
Imagine we know that a disease results from a specific
defective protein:
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Single nucleotide polymorphisms (SNPs)Single nucleotide polymorphisms (SNPs)
• SNP (pronounced ‘snip’) is a genetic
variation between individuals
• single base pairs that can be substituted,
deleted or inserted
• SNPs are distributed throughout the
genome
– average every 2000bp
• provide markers for mapping genes
• not all SNPs are linked to diseases
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Single nucleotide polymorphisms (SNPs)
• nonsense mutations:
– codes for a stop, which can truncate the
protein
• missense mutations:
– codes for a different amino acid
• silent mutations:
– codes for the same amino acid, so has no
effect
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Outlook – coming lecture
• Bioinformatics Information Resources And Networks
– EMBnet – European Molecular Biology Network
• DBs and Tools
– NCBI – National Center For Biotechnology Information
• DBs and Tools
– Nucleic Acid Sequence Databases
– Protein Information Resources
– Metabolic Databases
– Mapping Databases
– Databases concerning Mutations
– Literature Databases
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Thanks for your
attention!