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DNA Sequencing.

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Presentation on theme: "DNA Sequencing."— Presentation transcript:

1 DNA Sequencing

2 DNA sequencing How we obtain the sequence of nucleotides of a species
…ACGTGACTGAGGACCGTG CGACTGAGACTGACTGGGT CTAGCTAGACTACGTTTTA TATATATATACGTCGTCGT ACTGATGACTAGATTACAG ACTGATTTAGATACCTGAC TGATTTTAAAAAAATATT…

3 Which representative of the species?
Which human? Answer one: Answer two: it doesn’t matter Polymorphism rate: number of letter changes between two different members of a species Humans: ~1/1,000 Other organisms have much higher polymorphism rates Population size! Just beneath the surface of the ocean floats a tiny egg. Within it's hull of follicle cells the embryo of Ciona, a sea squirt or Ascidian, is beginning to develop. The shape of the egg does not give any clue of the creature that it is going to be. Now about a third of a millimeter it is waiting to become a larva, and this larva is a rather surprising creature. The larva is developing within a few weeks. A head and a tail are evolving. When you look carefully you can see a rod that stiffens the tail. We know such a device as a notochord. A trained zoologist would identify the animal as belonging to the Phylum Chordata, and that is the same group we humans belong to. (See footnote). Also the internal organs are beginning to show. But the image is a bit deceiving. What seems to be an eye is in fact a device for equilibrium called the 'Otolith'. Above it we find the light sense organ, the 'Ocellus' So there is something suspicious about these so-called sea squirts. Freed from it's shell a familiar form has appeared. Clearly the resemblance with a tadpole larva is seen. The little creature swims for a few hours to find a good spot somewhere on a solid surface. Then a surprising thing happens. This larva is not going to evolve into a fish, amphibian or anything like that. With the front of it's head it attaches itself to a surface. Within minutes resorption of the larva tail commences and the sea squirt will stay on that same spot for all it's life

4 Why humans are so similar
Out of Africa N A small population that interbred reduced the genetic variation Out of Africa ~ 40,000 years ago Heterozygosity: H H = 4Nu/(1 + 4Nu) u ~ 10-8, N ~ 104  H ~ 410-4

5 Human population migrations
Out of Africa, Replacement “Grandma” of all humans (Eve) ~150,000yr Ancestor of all mtDNA “Grandpa” of all humans (Adam) ~100,000yr Ancestor of all Y-chromosomes Multiregional Evolution Fossil records show a continuous change of morphological features Proponents of the theory doubt mtDNA and other genetic evidence

6 DNA Sequencing – Overview
1975 Gel electrophoresis Predominant, old technology by F. Sanger Whole genome strategies Physical mapping Walking Shotgun sequencing Computational fragment assembly The future—new sequencing technologies Pyrosequencing, single molecule methods, … Assembly techniques Future variants of sequencing Resequencing of humans Microbial and environmental sequencing Cancer genome sequencing 2015

7 DNA Sequencing Goal: Find the complete sequence of A, C, G, T’s in DNA
Challenge: There is no machine that takes long DNA as an input, and gives the complete sequence as output Can only sequence ~800 letters at a time

8 DNA Sequencing – vectors
Shake DNA fragments Known location (restriction site) Vector Circular genome (bacterium, plasmid) + =

9 Different types of vectors
Size of insert Plasmid 2,000-10,000 Can control the size Cosmid 40,000 BAC (Bacterial Artificial Chromosome) 70, ,000 YAC (Yeast Artificial Chromosome) > 300,000 Not used much recently

10 DNA Sequencing – gel electrophoresis
Start at primer (restriction site) Grow DNA chain Include dideoxynucleoside (modified a, c, g, t) Stops reaction at all possible points Separate products with length, using gel electrophoresis

11 Electrophoresis diagrams

12 Reading an electropherogram
Filtering Smoothening Correction for length compressions A method for calling the letters – PHRED PHRED – PHil’s Read EDitor (by Phil Green) Newer methods may be better, but labs are reluctant to change

13 Output of PHRED: a read A read: 500-1000 nucleotides
A C G A A T C A G …A …21 Quality scores: -10log10Prob(Error) Reads can be obtained from leftmost, rightmost ends of the insert Double-barreled sequencing: (1990) Both leftmost & rightmost ends are sequenced, reads are paired

14 Method to sequence longer regions
genomic segment cut many times at random (Shotgun) Get one or two reads from each segment ~800 bp ~800 bp

15 Reconstructing the Sequence (Fragment Assembly)
reads Cover region with high redundancy Overlap & extend reads to reconstruct the original genomic region

16 Definition of Coverage
Length of genomic segment: L Number of reads: n Length of each read: l Definition: Coverage C = n l / L How much coverage is enough? Lander-Waterman model: Assuming uniform distribution of reads, C=10 results in 1 gapped region /1,000,000 nucleotides

17 Repeats Bacterial genomes: 5% Mammals: 50% Repeat types:
Low-Complexity DNA (e.g. ATATATATACATA…) Microsatellite repeats (a1…ak)N where k ~ 3-6 (e.g. CAGCAGTAGCAGCACCAG) Transposons SINE (Short Interspersed Nuclear Elements) e.g., ALU: ~300-long, 106 copies LINE (Long Interspersed Nuclear Elements) ~4000-long, 200,000 copies LTR retroposons (Long Terminal Repeats (~700 bp) at each end) cousins of HIV Gene Families genes duplicate & then diverge (paralogs) Recent duplications ~100,000-long, very similar copies

18 Sequencing and Fragment Assembly
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT 3x109 nucleotides 50% of human DNA is composed of repeats Error! Glued together two distant regions

19 What can we do about repeats?
Two main approaches: Cluster the reads Link the reads

20 What can we do about repeats?
Two main approaches: Cluster the reads Link the reads

21 What can we do about repeats?
Two main approaches: Cluster the reads Link the reads

22 Sequencing and Fragment Assembly
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT 3x109 nucleotides A R B ARB, CRD or ARD, CRB ? C R D

23 Sequencing and Fragment Assembly
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT 3x109 nucleotides

24 Strategies for whole-genome sequencing
Hierarchical – Clone-by-clone Break genome into many long pieces Map each long piece onto the genome Sequence each piece with shotgun Example: Yeast, Worm, Human, Rat Online version of (1) – Walking Start sequencing each piece with shotgun Construct map as you go Example: Rice genome Whole genome shotgun One large shotgun pass on the whole genome Example: Drosophila, Human (Celera), Neurospora, Mouse, Rat, Dog

25 Hierarchical Sequencing

26 Hierarchical Sequencing Strategy
a BAC clone map genome Obtain a large collection of BAC clones Map them onto the genome (Physical Mapping) Select a minimum tiling path Sequence each clone in the path with shotgun Assemble Put everything together

27 Methods of physical mapping
Goal: Make a map of the locations of each clone relative to one another Use the map to select a minimal set of clones to sequence Methods: Hybridization Digestion

28 1. Hybridization p1 pn Short words, the probes, attach to complementary words Construct many probes Treat each BAC with all probes Record which ones attach to it Same words attaching to BACS X, Y  overlap

29 2. Digestion Restriction enzymes cut DNA where specific words appear
Cut each clone separately with an enzyme Run fragments on a gel and measure length Clones Ca, Cb have fragments of length { li, lj, lk }  overlap Double digestion: Cut with enzyme A, enzyme B, then enzymes A + B

30 Online Clone-by-clone The Walking Method

31 The Walking Method Build a very redundant library of BACs with sequenced clone-ends (cheap to build) Sequence some “seed” clones “Walk” from seeds using clone-ends to pick library clones that extend left & right

32 Walking: An Example

33 Walking off a Single Seed
Low redundant sequencing Many sequential steps

34 Walking off a single clone is impractical
Cycle time to process one clone: 1-2 months Grow clone Prepare & Shear DNA Prepare shotgun library & perform shotgun Assemble in a computer Close remaining gaps A mammalian genome would need 15,000 walking steps !

35 Walking off several seeds in parallel
Efficient Inefficient Few sequential steps Additional redundant sequencing In general, can sequence a genome in ~5 walking steps, with <20% redundant sequencing

36 Some Terminology insert a fragment that was incorporated in a circular genome, and can be copied (cloned) vector the circular genome (host) that incorporated the fragment BAC Bacterial Artificial Chromosome, a type of insert–vector combination, typically of length kb read a long word that comes out of a sequencing machine coverage the average number of reads (or inserts) that cover a position in the target DNA piece shotgun the process of obtaining many reads sequencing from random locations in DNA, to detect overlaps and assemble

37 Whole Genome Shotgun Sequencing
cut many times at random plasmids (2 – 10 Kbp) forward-reverse paired reads known dist cosmids (40 Kbp) ~800 bp ~800 bp

38 Fragment Assembly (in whole-genome shotgun sequencing)

39 We need to use a linear-time algorithm
Fragment Assembly Given N reads… Where N ~ 30 million… We need to use a linear-time algorithm

40 Steps to Assemble a Genome
Some Terminology read a long word that comes out of sequencer mate pair a pair of reads from two ends of the same insert fragment contig a contiguous sequence formed by several overlapping reads with no gaps supercontig an ordered and oriented set (scaffold) of contigs, usually by mate pairs consensus sequence derived from the sequene multiple alignment of reads in a contig 1. Find overlapping reads 2. Merge some “good” pairs of reads into longer contigs 3. Link contigs to form supercontigs 4. Derive consensus sequence ..ACGATTACAATAGGTT..

41 1. Find Overlapping Reads
(read, pos., word, orient.) aaactgcag aactgcagt actgcagta … gtacggatc tacggatct gggcccaaa ggcccaaac gcccaaact ctgcagtac acggatcta ctactacac tactacaca (word, read, orient., pos.) aaactgcag aactgcagt acggatcta actgcagta cccaaactg cggatctac ctactacac ctgcagtac gcccaaact ggcccaaac gggcccaaa gtacggatc tacggatct tactacaca aaactgcagtacggatct aaactgcag aactgcagt … gtacggatct tacggatct gggcccaaactgcagtac gggcccaaa ggcccaaac actgcagta ctgcagtac gtacggatctactacaca gtacggatc ctactacac tactacaca

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