Last lecture summary

recombinant DNA technology DNA polymerase (copy DNA), restriction endonucleases (cut DNA), ligases (join DNA) DNA cloning – vector (plasmid, BAC), PCR genome mapping relative locations of genes are established by following inheritance patterns visual appearance of a chromosome when stained and examined under a microscope the order and spacing of the genes, measured in base pairs sequence map

genetic markers polymorphic (alternative alleles) restriction fragment length polymorphisms (RFLPs) some restriction sites exist as two alleles simple sequence length polymorphisms (SSLPs) repeat sequences, minisatellites (repeat unit up to 25 bp), microsatellites (repeat unit of 2-4 bp) single nucleotide polymorphisms (SNPs, pron.: “snips”) Positions in a genome where some individuals have one nucleotide and others have a different nucleotide RFLPSSLP

New stuff

DNA sequencing Sanger method, chain-termination method, developed 1974, Nobel prize in chemistry 1980 The key principle: use of dideoxynucleotide triphosphates (ddNTPs) as DNA chain terminators. source: dNTPddNTP

source: wikipedia

Shotgun sequencing

Target DNA Copies of target DNA Shotgun (restriction endonuclease) Sequence each short piece (read, ~1kbp) Sequence assembly Consensus Finalizing (directed read) source: slides by Martin Farach-Colton contig

Problems with repeats in the assembly source: Brown T. A., Genomes. 2nd ed.

Human genome project (HGP) Determine the sequence of haploid human genome Govermentally funded (DOE) Began in 1990, working draft published in 2001, complete in 2003, last chromosome finished in 2006 Cost: $3 billion Whose genome was sequenced? The “reference genome” is a composite from several people who donated blood samples.

Celera - competition begins In 1998, a similar privately funded quest was launched by the American researcher Craig Venter and his company Celera Genomics. Finish the genome sequencing within 3 years for $300,000,000. Celera wanted to patent identified genes. Celera promised to release data annually (while the HGP daily). However, Celera would, unlike HGP, not permit free redistribution or scientific use of the data. HGP was compelled to release ( ) the first draft of the human genome before Celera for this reason.

How did it finish? March 2000 – president Clinton announced that the genome sequence could not be patented, and should be made freely available to all researchers. The statement sent Celera's stock plummeting and dragged down the biotechnology-heavy Nasdaq. The biotechnology sector lost about $50 billion in two days. Celera and HGP annouced jointly the draft sequence in The drafts covered about 83% of the genome. Improved drafts were announced in 2003 and 2005, filling in to ≈92% of the sequence currently.

Human genome – some facts 3 billions bps, ~ – genes Only 1.1 – 1.4 % of the genome sequence codes for proteins. State of completion: best estimate – 92.3% is complete problematic unfinished regions: centromeres, telomeres (both contain highly repetitive sequences), some unclosed gaps It is likely that the centromeres and telomeres will remain unsequenced until new technology is developed

Databases Genome is stored in databases Primary database (NCBI) – Genebank ( Additional data and annotation, tools for visualizing and searching UCSC ( ) … University of California – Santa Cruz Ensembl ( ) … EBI+Sanger Chromosome largest #1 = 250 Mbp, smallest #21 = 48 Mbp

Hierarchical genome shotgun – HGS Hierarchical genome shotgun, hierarchical shotgun sequencing, clone-by-clone sequencing, map-based shotgun sequencing, clone contig sequencing Adopted by HGP Strategy “map first, sequence second” Create physical map Divide chromosomes into smaller fragments. Order (map) them to correspond to their respective locations on the chromosomes. Determine the base sequence of each of the mapped fragments.

Multiplied genomic DNA BAC fragments 160 kbp Minimum tiling path (MTP) BAC to be sequenced Shotgun clones 1 kbp Sequencing and assembly restriction endonuclease clone in BAC restriction endonuclease clone in plasmid

Minimum tiling path (MTP) MTP – the lowest possible number of BACs to cover the sequence. MTP BACs are selected for sequencing.

Hierarchical genome shotgun – HGS 1. Map genome As genetic markers (landmarks), short tagged sites (STS) were used (200 to 500 base pair DNA sequence that has a single occurrence in the genome) 2. Copy target DNA 3. Make BAC library cleave randomly (partial cleavage by restriction endonuclease) all target DNA copies into ~160kbp fragments, clone them in BACs 4. Physically map all BACs 5. Identify a minimum tiling path (MTP) BACs 6. Shotgun sequence only BACs at MTP Divide BACs into ~1kbp fragments, do plasmid cloning, reconstruct BAC sequence 7. Fill in gaps between BACS 8. Merge into consensus sequence

Coverage As it was shown, individual nucleotides are read more than once. Coverage is the average number of reads representing a given nucleotide in the reconstructed sequence. Let’s say that for a source strand of length G = 100 Kbp we sequence R = reads of average legth L = 500. Thus, we collect N = RL = 750 Kbps of data. So we have sequenced on average every bp in the source N/G = 7.5 times. The coverage is 7.5X Coverage in HGS adopted by HGP was 8X.

Whole genome shotgun – WGS Adopted by Celera, expensive and time consuming mapping is skipped, high coverage (20x) needed, new algorithms for assembly, repeats are problematic (HGP data used by Celera)

Genome assembly Can be very computationally intensive when dealt at the whole genome level. Major challenges: sequence errors – can be corrected by drawing consensus sequence from an alignment of multiple overlapped sequences contamination by bacterial vectors – can be removed using filtering programs prior to assembly repeats Popular programs developed within HGP and still used: PHRED and PHRAP

PHRED Base caller – convert raw data from a sequencing instrument into sequences and scores, score reflects the likelihood the base is correct/incorrect ideal case real case

PHRAP Sequence assembler Takes PHRED base-call files with quality scores as input. Aligns individual fragments in a pairwise fashion. The base quality information is taken into account during the pairwise alignment.