The document summarizes the process a molecular biologist would take to identify the gene causing a new disease phenotype in a patient. It involves collecting ESTs from the patient's tissue, searching for matching sequences in the human genome using BLAST, and analyzing the matching genes and variants like SNPs to see if any are known to cause the observed phenotype. The document walks through this process using a real example where an EST matches the HFE gene, and a variant changing a cysteine to tyrosine is known to cause hemochromatosis.
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
STS stands for sequence tagged site which is short DNA sequence, generally between 100 and 500 bp in length, that is easily recognizable and occurs only once in the chromosome or genome being studied.
It is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics.
One of the best websites for detailed and updated information of genetic diseases.
Set up in 1995 by the National Centre for Biotechnology Information (NCBI).
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
STS stands for sequence tagged site which is short DNA sequence, generally between 100 and 500 bp in length, that is easily recognizable and occurs only once in the chromosome or genome being studied.
It is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics.
One of the best websites for detailed and updated information of genetic diseases.
Set up in 1995 by the National Centre for Biotechnology Information (NCBI).
Genome annotation, NGS sequence data, decoding sequence information, The genome contains all the biological information required to build and maintain any given living organism.
High throughput next generation sequencing and robust transcriptome analysis help with gene expression profiling, gene annotation or discovery of non-coding RNA.
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
Transcriptomics is the study of RNA, single-stranded nucleic acid, which was not separated from the DNA world until the central dogma was formulated by Francis Crick in 1958, i.e., the idea that genetic information is transcribed from DNA to RNA and then translated from RNA into protein.
Genome annotation, NGS sequence data, decoding sequence information, The genome contains all the biological information required to build and maintain any given living organism.
High throughput next generation sequencing and robust transcriptome analysis help with gene expression profiling, gene annotation or discovery of non-coding RNA.
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
Transcriptomics is the study of RNA, single-stranded nucleic acid, which was not separated from the DNA world until the central dogma was formulated by Francis Crick in 1958, i.e., the idea that genetic information is transcribed from DNA to RNA and then translated from RNA into protein.
GPCRs are the most dynamic and most abundant all the receptors. The G protein-coupled receptor (GPCR) superfamily comprises the largest and most diverse group of proteins in mammals. GPCRs are responsible for every aspect of human biology from vision, taste, sense of smell, sympathetic and parasympathetic nervous functions, metabolism, and immune regulation to reproduction. GPCRs interact with a number of ligands ranging from photons, ions, amino acids, odorants, pheromones, eicosanoids, neurotransmitters, peptides, proteins, and hormones.
Nevertheless, for the majority of GPCRs, the identity of their natural ligands is still unknown, hence remain orphan receptors.
The simple dogma that underpins much of our current understanding of GPCRs, namely,
one GPCR gene− one GPCR protein− one functional GPCR− one G protein −one response
is showing distinct signs of wear.
To modifying the structure of a specific gene.
Gene targeting vector introduced into the cell.
Vector modifies the normal chromosomal gene through homologous recombination.
Useful in treating some human genetic disorders – Hemophilia, Duchenne Muscular Dystrophy.
Treating human diseases by genetic approaches – Gene Therapy.
Gene Therapy – Replacing the defective gene by normal copy of the gene.
Expressed sequence tag/EST is a short partial sequence, typically 200-400 bp long, of a complimentary DNA/Cdna.
EST is a short sub-sequence of a cDNA sequence.
Used to identify gene transcripts, and are instrumental in gene discovery and in gene-sequence determination.
Approximately 74.2 million ESTs are available in public databases.
EST results from one-short sequencing of a cloned cDNA.
Low-quality fragments.
Length is approximately 500 to 800 nucleotides.
Cardiotoxicity is unfortunately a common side effect of many modern chemotherapeutic agents. The mechanisms that underlie these detrimental effects on heart muscle, however, remain unclear. The Drug Toxicity Signature Generation Center at ISMMS aims to address this unresolved issue by providing a bridge between molecular changes in cells and the prediction of pathophysiological effects. I will discuss ongoing work in which we use next-generation sequencing to quantify changes in gene expression that occur in cardiac myocytes after they are treated with potentially toxic chemotherapeutic agents. I will focus in particular on the computational pipeline we are developing that integrates sophisticated sequence alignment, statistical and network analysis, and dynamical mathematical models to develop novel predictions about the mechanisms underlying drug-induced cardiotoxicity.
Jaehee Shim is a Ph.D candidate in the Biophysics and Systems Pharmacology Program at Icahn School of Medicine at Mount Sinai (ISMMS). As a part of her Ph.D. studies, she is building dynamical prediction models based on analysis of gene expression data generated by the Drug Toxicity Signature Generation Center at ISMMS. She received her B.S in Biochemistry from the University of Michigan-Dearborn. Prior to starting her Ph.D, Jaehee worked at the ISMMS Genomics Core with a team of senior scientists and gained experience in improving and troubleshooting RNA sequencing protocols using Next Generation Sequencing Platforms.
Creating custom gene panels for next-generation sequencing: optimization of 5...Thermo Fisher Scientific
Next-generation sequencing gene panels enable the examination of multiple genes, identifying previously described variants and discovering novel variants, to elucidate genetic disease. The challenges are substantial, including: identification of all genes of interest; assay optimization to create robust, reproducible, multiplex panels; and developing accurate, comprehensive, reproducible analysis pipelines.
Contents:
What does sequence mean?
Examples of sequences
Sequence Homology
Sequence Alignment
What is the use of sequence alignment?
Alignment methods
Tools for Sequence Alignment
FASTA Format
BLAST
Principle of BLAST
Variants of BLAST Program
BLAST input
BLAST output
Multiple sequence alignment
What is the use of multiple alignments?
Multiple Alignment Method
Tool for multiple alignments
ClustalW input
ClustalW output
E (Expectation) value
Demerits of progressive alignment
The NCBI Boot Camp for Beginners was designed to offer an overview of the NCBI suite of resources. In the first half of the presentation, highlighted databases were covered in four main categories: literature, sequences, genes & genomes and expression & structure. The second half of the class used the apolipoprotein A as a query that was explored through many of the NCBI databases, from identifying the reference sequences to a structural analysis of the Cys130Arg variant.
Exploring the Polymerase Activity of Chikungunya Viral non structural Protein 4 (nsP4) using Molecular Modeling, e-Pharmacophore and Docking Studies
S. Prasanth Kumar, Ravi G. Kapopara, Yogesh T. Jasrai and Himanshu A. Pandya
Department of Bioinformatics, ABC, Gujarat University, Ahmedabad- 380009.
Vishal H. Desai, Chirag N. Patel, Vijay P. Mehta, S. Prasanth Kumar, Yogesh T. Jasrai and Himanshu A. Pandya. Bioinformatic analysis on Maize sugary1 gene (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Budding Researchers, pp. 173
S. prasanth kumar young scientist awarded presentationPrasanthperceptron
Recipient of Young Scientist Award for Research Article Presentation on “Emergence of Indian Tomato Yellow Leaf Curl Viral (TYLCV) Disease: Insights from Evolutionary Divergence and Molecular Prospects of Coat Protein” on an National Symposium on “Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources” held at Department of Botany, Gujarat University, Ahmedabad- 380 009 between Oct 13-15, 2011.
These are the abstracts indexed with my name in the Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources.
1. S.Prasanth Kumar, Bioinformatician Identification of Disease Genes Pharmacogenomics & Drug Design S.Prasanth Kumar, Bioinformatician S.Prasanth Kumar Dept. of Bioinformatics Applied Botany Centre (ABC) Gujarat University, Ahmedabad, INDIA www.facebook.com/Prasanth Sivakumar FOLLOW ME ON ACCESS MY RESOURCES IN SLIDESHARE prasanthperceptron CONTACT ME [email_address]
2. From Scratch Patient New Symptom Phenotype Genotype Molecular Biologist Bioinformatics
3. Note of Caution !!! Before we progress You are entitled to study the following programs/tools/web server and its working methodology NCBI – Entrez GenBank BLAST and its types MapViewer OMIM dbSNP And other available programs of NCBI
4. Molecular Biologist Point of View KEY POINT A phenotype is expressed by a Genotype Patient developed new symptom Disease Collect tissue or cells representing a developmental stage Isolate mRNA Produce cDNA Insert this cDNA into a suitable vector Produce cDNA clones Sequence these cDNA insert from either end Expressed Sequence Tags (ESTs)
5. Finding a Disease Gene EST Single pass, short 300–500 nucleotide sequences cDNA clones cDNA inserted into vector cDNA RTase mRNA RE Sequencing
6. Finding a Disease Gene Human Genome Search ESTs Results XYZ gene XYZ gene XYZ gene KEY POINT The XYZ gene expresses these ESTs.
7. Finding a Disease Gene XYZ Normal gene T XYZ gene variants C A G T SNPs Normal Genetics & Pharmacogenomics
8. To obtain information about the gene(s) causing the phenotype Unknown EST collected from patient Human Genome Which BLAST to use ? BLAST (human genome) Genome (reference only) database Annotated Human Genome Assembly MegaBlast EST matches with a Contig Query
9. What is a Contig ? NCBI assembles component sequences from the human genome sequencing project into longer sequences called contigs whose accession numbers begin with prefix “NT_” Annotated Human Genome Assembly Component Sequences Sequencing Projects Assembly
10. Compare ESTs to The Human Genome EST matches with a Contig a real SNP or a sequencing error Position 16951392
11. Identify the Genes Expressing the ESTs “ Known” genes annotated by alignment of EST and/or mRNA sequences to the assembly The assembled genome contig sequence in the region The Ab initio model genes predicted by the NCBI’s program Gnomon The alignments of the known alternatively spliced transcripts
12. Genes_seq Map as a master map Exons Introns BLAST hit HFE gene Arrow downward = forward strand Arrow upward = reverse strand The HFE gene is annotated on the forward strand of chromosome 6 sv (Sequence Viewer), pr (Reference Proteins), dl (Download Sequence), ev (Evidence Viewer), mm (Model Maker), and hm (Homologene)
13. Variation Map as a master map SNPs Can you tell which SNPs corresponds to Exons and Introns ? Click any of the links and obtain information about the location and the nucleotide variation
14. “ Fasta sequence” and “Integrated maps” panels SNP entry rs1800562 The location of the SNP, nucleotide position 16951392 on the contig NT_007592.14 of the reference assembly
15. Is the SNP non-synonymous ? GeneView Panel The query EST sequence contains a known SNP in the HFE gene that results in a cysteine to tyrosine change in the 282nd amino acid (Cys282Tyr) of the protein expressed by the longest HFE transcript variant Gene Alternatively Spliced Variants (mRNA) SNPs …… ..TAC…... …… ..U G C…… Gene mRNA SNP Tyrosine Cysteine
16. Whether the HFE Gene Variant is Known to Cause a Disease Phenotype The Cys282Tyr variant is reported to be associated with hemochromatosis
17. GeneSeeker Cytogenetic Localization Phenotype Expression Patterns Genes underlying human genetic disorders List of Candidate Genes
18. GeneSeeker Methodology DB Group-1 Localization dbs (Human)
19. GeneSeeker Methodology DB Group-2 Localization dbs (Mouse)
20. GeneSeeker Methodology DB Group-3 Phenotype & Expression Patterns