1 2 3 4 5 6 7 8 Genomics is a science discipline that is interested in the analysis of genomes. Genome of each organism is a complex of all genes of the respective organism. The genes could be located in cytoplasm (prokaryots) nucleus (in most euckaryotic organisms), mitochondria or chloroplasts (in plants). The critical prerequisite of genomics is the knowledge of gene sequences. Functional genomics is interested in function of individual genes. With the knowledge of gene sequences (or the knowledge of the gene files in the individual organisms, i.e. the knowledge of genomes), Reverse Genetics appears that allows study their function. In comparison to ”classical” or Forward Genetics, starting with the phenotype, the reverse genetics starts with the sequence identified as a gene in the sequenced genome. The gene identification using approaches of Bioinformatics will be described later (see Lesson 02). Reverse genetics uses a spectrum of approaches that will be described in the Lesson 03 that allow isolation of sequence-specific mutants and thus their phenotype analysis. The necessity of having phenotype alterations in the forward genomics approach introduces important difference between those two approaches. Thus, the gene is no longer understood as a factor (trait) determining phenotype, but rather as a piece of DNA characterized by the unique string of nucleotides. i.e. physical DNA molecule. 9 10 11 NIH WORKING DEFINITION OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY July 17, 2000 The following working definition of bioinformatics and computational biology were developed by the BISTIC Definition Committee and released on July 17, 2000. The committee was chaired by Dr. Michael Huerta of the National Institute of Mental Health and consisted of the following members: Bioinformatics Definition Committee BISTIC Members Expert Members Michael Huerta (Chair) Gregory Downing Florence Haseltine Belinda Seto Yuan Liu Preamble Bioinformatics and computational biology are rooted in life sciences as well as computer and information sciences and technologies. Both of these interdisciplinary approaches draw from specific disciplines such as mathematics, physics, computer science and engineering, biology, and behavioral science. Bioinformatics and computational biology each maintain close interactions with life sciences to realize their full potential. Bioinformatics applies principles of information sciences and technologies to make the vast, diverse, and complex life sciences data more understandable and useful. Computational biology uses mathematical and computational approaches to address theoretical and experimental questions in biology. Although bioinformatics and computational biology are distinct, there is also significant overlap and activity at their interface. Definition The NIH Biomedical Information Science and Technology Initiative Consortium agreed on the following definitions of bioinformatics and computational biology recognizing that no definition could completely eliminate overlap with other activities or preclude variations in interpretation by different individuals and organizations. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. 11 12 13 NIH WORKING DEFINITION OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY July 17, 2000 The following working definition of bioinformatics and computational biology were developed by the BISTIC Definition Committee and released on July 17, 2000. The committee was chaired by Dr. Michael Huerta of the National Institute of Mental Health and consisted of the following members: Bioinformatics Definition Committee BISTIC Members Expert Members Michael Huerta (Chair) Gregory Downing Florence Haseltine Belinda Seto Yuan Liu Preamble Bioinformatics and computational biology are rooted in life sciences as well as computer and information sciences and technologies. Both of these interdisciplinary approaches draw from specific disciplines such as mathematics, physics, computer science and engineering, biology, and behavioral science. Bioinformatics and computational biology each maintain close interactions with life sciences to realize their full potential. Bioinformatics applies principles of information sciences and technologies to make the vast, diverse, and complex life sciences data more understandable and useful. Computational biology uses mathematical and computational approaches to address theoretical and experimental questions in biology. Although bioinformatics and computational biology are distinct, there is also significant overlap and activity at their interface. Definition The NIH Biomedical Information Science and Technology Initiative Consortium agreed on the following definitions of bioinformatics and computational biology recognizing that no definition could completely eliminate overlap with other activities or preclude variations in interpretation by different individuals and organizations. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. 13 14 There are many of on-line resources that could be used. 15 Nowadays, the resources are interconnected and could be accessed via dedicated web pages. Among the best and mostluy used www resources integrating plenty of database resources belong www portal of European Bioinformatics Institute (EBI) in Europe (Germany) and National Center of Biotechnology Information (NCBI) in the USA ( 16 Nowadays, the resources are interconnected and could be accessed via dedicated web pages. 17 18 19 20 21 Shotgun sequencing allows a scientist to rapidly determine the sequence of very long stretches of DNA. The key to this process is fragmenting of the genome into smaller pieces that are then sequenced side by side, rather than trying to read the entire genome in order from beginning to end. The genomic DNA is usually first divided into its individual chromosomes. Each chromosome is then randomly broken into small strands of hundreds to several thousand base pairs, usually accomplished by mechanical shearing of the purified genetic material. Each of the short DNA pieces is then inserted into a DNA vector (a viral genome), resulting in a viral particle containing "cloned" genomic DNA (Fig. 1). The collection of all the viral particles with all the different genomic DNA pieces is referred to as a library. Just as a library consists of a set of books that together make up all of human knowledge, a genomic library consists of a set of DNA pieces that together make up the entire genome sequence. Placing the genomic DNA within the viral genome allows bacteria infected with the virus to faithfully replicate the genomic DNA pieces. Additionally, since a little bit of known sequence is needed to start the sequencing reaction, the reaction can be primed off the known flanking viral DNA. In order to read all the nucleotides of one organism, millions of individual clones are sequenced. The data is sorted by computer, which compares the sequences of all the small DNA pieces at once (in a "shotgun" approach) and places them in order by virtue of their overlapping sequences to generate the full-length sequence of the genome (Fig. 2). To statistically ensure that the whole genome sequence is acquired by this method, an amount of DNA equal to five to ten times the length of the genome must be sequenced. (Interactive concepts in biochemistry, Rodney Boyer, Wiley, 2002, http://www.wiley.com//college/boyer/0470003790/) 22 DDBJ/EMBL/GenBank accepts both complete and incomplete genomes. Whole Genome Shotgun (WGS) sequencing projects are incomplete genomes or incomplete chromosomes that are being sequenced by a whole genome shotgun strategy. WGS projects may be annotated, but annotation is not required. The pieces of a WGS project are the contigs (overlapping reads), and they do not include any gaps. An AGP file can be submitted to indicate how the contig sequences are assembled together into scaffolds (contig sequences separated by gaps) and/or chromosomes. We must have the contig sequences without gaps as the basic units for all WGS projects. 23 24 25 26 27 BLINK is a link to the 28 29 30 31 32 33 34 35 36 - Doplnit dalsi DB (Blanka P.) 37 - Doplnit dalsi DB (Blanka P.) 38 - Doplnit dalsi DB (Blanka P.) 39 - Doplnit dalsi DB (Blanka P.) 40 S/MARt DB (saffold/matrix attached region transaction database). This database collects information about S/MARs and the nuclear matrix proteins that are supposed be involved in the interaction of these elements with the nuclear matrix. http://transfac.gbf.de/SMARtDB/index.html) 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BLINK is a link to the pre-computed BLAST search results for the respective sequence (see the next slide). 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82