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Max Bachour

Jessica Chen. Max Bachour. High throughput sequencing technique that can collect a large amount of data at a fast rate. Works by partially digesting a genome or big strand of DNA into small overlapping fragments

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Max Bachour

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  1. Jessica Chen Max Bachour

  2. High throughput sequencing technique that can collect a large amount of data at a fast rate. • Works by partially digesting a genome or big strand of DNA into small overlapping fragments • These small fragments are sequenced and fragments that overlap are matched together. Shotgun or 454 sequencing

  3. Steps Behind 454 sequencing • The genome is fragmented and the fragments are denatured. • Fragments are amplified and assigned to beads. One fragment per one microbead. • Each bead is placed in the wells of a fiber optic slide. • Packing beads placed in all the wells.

  4. Steps Behind 454 sequencing • Solution of one nucleoside is flooded onto tray. • If base added is next in the sequence, it will be added to the single stranded DNA on the bead. • When a nucleoside is added to DNA, 2 phosphates are given out • Enzymes in packing beads convert phosphate groups to ATP and then the ATP to light energy.

  5. Steps Behind 454 sequencing • Computer and camera detect light in a certain well as a certain base is added to the tray. • Base is washed off and process is repeated with another base. • End product is large amount of fragments sequenced.

  6. Genome Sequence Analysis Contig Assembly Identifying open reading frames (ORF) using gene prediction programs

  7. What is the initial problem with assembly? Sequenced fragmented DNA CONTIG 2 CONTIG 1 Incorrectly Assembled DNA Sequence

  8. How is this problem solved? Sequenced fragmented DNA Masked DNA Sequence Assembled DNA Sequence CONTIG 3 CONTIG 1 CONTIG 5 CONTIG 4 CONTIG 2

  9. How do we identify genes? • Use gene prediction programs (Fgenesh, Genscan, Genemark) to determine potential genes; also determine any repeat sequences • Enter contig • Which of the predicted genes are most likely existing genes?  Use BLAST

  10. How do we use BLAST?  tblastn all predicted genes against an EST database (ESTDB) Why ESTDB? – record of all known/identified mRNA (cDNA library) Why tblastn? -- amino acid sequence more likely to be conserved  use blastn and blastp -blastp: determine expression of gene

  11. Analyzing BLAST data • Critical data: • e-value • %match • EST source

  12. Advantages and Disadvantages • Fast sequencing at a high volume • Cheap compared to other methods • Much higher coverage protection • Repetitive sequences can disrupt computer program into thinking that unrelated sequences are in fact connected. • More prone to error and missing sequences

  13. Drastically changed genomics in a very short amount of time

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