Genomics

Genomics relies on high-throughput technologies Automated sequencers Robotics Colony pickers and Arrayers for sequencing Microarray spotters Protein Spot-Picker and In-gel proteolytic digestion High-throughput genetics What genomics added to these recombinant-DNA techniques was automation. The innovation that made the greatest impact on genomic sequencing was the use of fluorescent dyes and capillaries in an automated sequencing system. Pictured in the slide is Applied Biosystem’s ABI 3700, which has been the most widely used instrument for large-scale sequencing. It has 96 capillaries that are fed by robotic loading from two 384-well microtiter plates. It makes a sequence run every two to three hours and can read, on average, 600–700 bases per run. Celera, the company that produced a rough draft of the human genome in three years, used 200 of these machines running 24/7 to do so. Similarly, automation was applied to the processes of spotting DNA onto slides to make microarrays and of identifying and isolating bacterial colonies to grow up DNA for sequencing. While initially applied to improving genomics techniques, high-throughput approaches are now permeating much of biology. An example of such an application is the use of robots to automate genetic screens for new mutants.

Areas of Genomics Sequencing Genome (Reference) Gene Expression Functional Genomics Proteomics Comparative Genomics Metabolomics

DNA Libraries Genomic libraries cDNA libraries [for EST sequencing] [for Genome sequencing] ESTs sequences Full Length cDNA sequences The term “library” is used for collections of DNA fragments that are cloned into a vector. “Vector” is a term used for DNA molecules whose function is to carry other pieces of DNA. The name “library” is a bit of a misnomer, because it seems to suggest that there is an ordered array of clones with an index. In fact, the collections are more akin to dumps that can be searched with a metal detector for valuable items. Most large-scale sequencing projects begin with the construction of either a genomic library or a cDNA library. Genomic libraries are used for genome-wide sequencing. cDNA libraries are made from RNA that has been reverse transcribed into cDNA and are used for EST sequencing projects. cDNA libraries are needed for EST sequencing

EST Library Expressed Sequence Tags Specific tissues and developmental stages = mRNA isolation (Conversion to cDNA) Require cloning of cDNAs Require many different tissues = good coverage of genomic information Usually sequence from 5’ or 3’ end (known as pair end or mate end sequencing) Will require more $$ to sequence both ends Usually less than 60% of genes coverage Will not have regulatory elements information Paralogs issue when figuring out the annotation and function of the gene

FL cDNA Library Full Length cDNA library Require intact length of mRNA Sequencing from both ends of the cDNA clone using the vector sequences Clone size selection (>800 bases) Require finishing of the larger clones by designing more primers internal to clone insert Should translate to a full protein Require more $$$ and effort to have the data

Next Generation(NG) Sequencing Sanger sequencing for the past 25 years Expensive, little coverage, limited nucleotide (nt) per run Ngseq (NG 2nd) has greatly reduced cost per amount of data generated, greater coverage Different technologies pending on company producing the technology (Metzker 2010 Nature Reviews/Genetics)

Next Generation(NG) Sequencing NGseq (NG 3rd) has greatly reduced cost per amount of data generated, greater coverage Much longer reads vs NG 2nd generation Different technologies pending on company producing the technology (Metzker 2010 Nature Reviews/Genetics) Ion Torrent, PacBio, Oxford Nanopore

PacBio NG 3rd

Genome Annotation Requiring Bioinformatics Ref = Koonin, E.V. and Galperin, M.Y. 2004 In: Sequence-Evolution-Function. p.196

Bioinformatics Biology, computer science, and information technology merge = a single discipline Creating and maintaining databases to store biological information eg. nucleotide, amino acid sequences Development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data Develop a comprehensive picture of normal cellular activities Involves analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures