4 DNA Structure The two strands of a DNA molecule are held together by weak bonds (hydrogen bonds) between the nitrogenous bases, which are paired in the interior of the double helix. The two strands of DNA are antiparallel; they run in opposite directions. The carbon atoms of the deoxyribose sugars are numbered for orientation.
5 Sequencing DNA The goal of sequencing DNA is to tell the order of the bases, or nucleotides, that form the inside of the double-helix molecule. We can do this in one of two ways: Directed Sequencing Shotgun Sequencing
6 Directed Sequencing=Primer Walking Start with genome, gene, clone, PCR product Design a primer and sequence a certain segment of the genome, usually the beginning. From that sequence, design the next primer and sequence the next segment of the genome. Continue designing primers and sequencing until the genome is completed..
7 Shotgun Sequencing Start with a whole genome or a large piece of the DNA (a BAC). Shear the DNA into many different, random segments. Sequence each of the random segments. Then, put the pieces back together again in their original order.
8 Theory Behind Shotgun Sequencing Haemophilus influenzae 1.83 Mb base Coverage unsequenced (%) 1X 37% 2X 13% 5X 0.67% 6X X 0.09% Gaps Sequences For 1.83 Mb genome, 6X coverage is Mb of sequence, or 22,000 sequencing reactions, clones ( kb insert), 500 bp average read.
9 BAC based Projects BACs are Bacterial Artificial Chromosomes. They are large transport systems that can hold pieces of DNA that are 50 to 300 kilobases. To make copies of the DNA we insert the BAC into an E. coli cell. transform in E. coli and process each BAC as individual projects chromosome break into large pieces clone into BAC vector
10 Shotgun vs. Directed: Which is the better, more efficient method? With directed, sequences are done in order and there s no puzzle to put back together. Minimal computing power is required. Primers must be continually designed and purchased. If an area is difficult to sequence, you could get stuck. Shotgun sequencing takes less time; all the sequences can be done at about the same time. Minimal cost But, the pieces have to be assembled, a time-consuming process requiring extensive computational power.
11 Whole Genome Shotgun Sequencing 1.Library construction 2. Random Sequencing Phase 3. Closure Phase a. isolate DNA a. sequence DNA (15,000 sequences/ Mb) a. assemble sequences b. close gaps b. fragment DNA c. clone DNA GGG ACTGTTC... c. edit d. annotation 4. COMPLETE GENOME SEQUENCE
12 Library Construction Construct shotgun libraries of the genome or target DNA; sizes of inserts are varied; could be small (2-3 kb), medium (8-12 kb), or fosmid (30-40 kb) Start with multiple copies of purified DNA Shear the DNA using mechanical force, breaking it into smaller pieces DNA fragments are cloned into a plasmid vector to replicate the DNA; these fragments are called inserts
13 Library Construction Insert fragment DNA into a vector such as pbr322 Transform into E. coli cells and, using an antibiotic, select for cells that have a plasmid. The plasmids carry antibiotic resistant genes. When plated in the presence of an antibiotic, the cells without a plasmid die.
14 Isolation of the plasmid DNA Template Preparation Transformed E.coli is plated onto an agar plate. Every E. coli colony will contain plasmids with the same insert. Colonies are picked & transferred to liquid media where they multiply; use 384 well high throughput plates Plasmids are isolated and suspended in a buffer.
15 Template Production Laboratory Current Capacity: 22,000,000 plasmids/year
16 Sanger Sequencing Utilize dideoxy sequencing method of chain termination (Sanger) Each plasmid is reacted with a forward and reverse primer (2 reactions for each piece of DNA). Done in high throughput manner in 384 well plates
17 Sequencing reactions -Initial dideoxy sequencing involved use of radioactive datp and 4 separate reactions (ddatp, ddttp, ddctp, ddgtp) & separation on 4 separate lanes on an acrylamide gel with detection through autoradiogram -New techologies use 4 fluorescently labeled bases and separation on capillaries and detection through a CCD camera
18 DNA sequencing
19 R primer binds, synthesis Plasmid Structure Antibiotic resistance F primer binds, synthesis
20 Sequencing Machines The DNA fragments are loaded into capillaries in the sequencing machines. Polymer in the capillaries provides a matrix for separating the DNA fragments based on size. Separation of the fragments through a matrix is called electrophoresis.
21 Sequence Production Laboratory Current Capacity: 40,000,000 sequences/year
22 Data Collection A laser excites the fluorescent dyes. A camera detects the fluorescence. Data collection software collects the data. Capillary array view
23 Sequencing Machine Output AACTCATCGAATCCGTACGGG AACTCATCGAATCCGTACGG AACTCATCGAATCCGTACG AACTCATCGAATCCGTAC AACTCATCGAATCCGTA AACTCATCGAATCCGT AACTCATCGAATCCG AACTCATCGAATCC AACTCATCGAATC AACTCATCGAAT AACTCATCGAA AACTCATCGA AACTCATCG AACTCATC AACTCAT AACTCA AACTC AACT AAC AA A This is a diagram of just one lane. Reading from the bottom, where the fragment is only one base long, the fluorescent dye is an A. This is the first base in the sequence. Fluorescent Sequencing Gel Four colors, one lane per sample Fluorescent Sequencing Gel Each fragment differs by one nucleotide
24 Data Analysis An chromatogram is produced and the bases are called Software assign a quality value to each base Phred & TraceTuner Read DNA sequencer traces Call bases Assign base quality values Write basecalls and quality values to output files.
26 FRAGMENTS FROM SEQUENCING PROCESS CONSENSUS SEQUENCE
27 Closure Assemble the sequence files, relate them to each other, and close gaps Involves many computational programs to identify overlapping sequences, linkages between sequences Back to the lab for hard to close gaps
28 Complicating Factors A procedure that works well in one species may not produce the same results in even a closely related species. Each genome is uniquely different in its size and how it sequences and assembles New technologies must be developed to tackle the unique characteristics and properties of difficult genomes
29 Whole Genome Shotgun Sequencing: Modifying for Eukaryotes Not restricted to bacterial organisms Sequence eukaryotes: whole genome draft sequence; same approach as with bacteria chromosome by chromosome; sequence genome using large insert bacterial artificial chromosome (BAC) clones anchored to the chromosomes combination of whole genome and chromosome by chromosome
30 Whole Genome Draft Sequencing 1.Library construction 2. Random Sequencing Phase 3. Closure Phase a. isolate DNA a. sequence DNA (15,000 sequences/ Mb) a. assemble sequences b. close gaps b. fragment DNA c. clone DNA GGG ACTGTTC... c. edit d. annotation 4. COMPLETE GENOME SEQUENCE
31 Whole Genome Draft Sequencing 1.Library construction 2. Random Sequencing Phase 3. Closure Phase a. isolate DNA b. fragment DNA c. clone DNA a. sequence DNA (15,000 sequences/ Mb) GGG ACTGTTC... a. assemble sequences b. close gaps c. edit Advantages: Saves time and money (~50 %) Disadvantages: Incomplete sequence, contains errors d. annotation 4. COMPLETE GENOME SEQUENCE
32 454 Genome Sequencing System Library prep, amplification and sequencing: 2-4 days Single sample preparation from bacterial to human genomic DNA Single amplification per genome with no cloning or cloning artifacts Picoliter volume molecular biology 100 Mb per run (4-5 hr); less than $ 20,000 per run Read lengths bases Massively parallel imaging, fluidics and data analysis Requires high genome coverage for good assembly Error rate of 1-2%
33 454-Pyrosequencing Construct Single stranded adaptor liagated DNA Perform emulsion PCR Depositing DNA Beads into the PicoTiter Plate Sequencing by Synthesis: Simultaneous sequencing of the entire genome in hundreds of thousands of picoliter-size wells Pyrophosphate signal generation
34 Expressed Sequence Tags (ESTs): Sampling the Transcriptome and Genic Regions What is an EST? single pass sequence from cdna specific tissue, stage, environment, etc. cdna library in E.coli pick individual clones template prep T7 Insert in pbluescript T3 Multiple tissues, states.. with enough sequences, can ask quantitative questions
35 Uses of EST sequencing: -Gene discovery -Digital northerns/insights into transcriptome -Genome analyses, especially annotation of genomic DNA Issues with EST sequencing: -Inherent low quality due to single pass nature -Not 100 % full length cdna clones -Redundant sequencing of abundant transcripts Address through clustering/ assembly to build consensus sequences = Gene Index, Unigene Set, Transcript Assembly
36 EST Clustering All ESTs and mrnas from an organism Cluster and Assemble Set of clustered, assembled sequences= contigs, Transcript Assembly, Tentative Consensus, Unigene Sequences which do not cluster or assemble=singletons, singlets Single pass transcript Longer, more accurate sequence of the transcript
37 Web Links for Animation on Genome Sequencing Synthesis%20Demo&Cap=&PageName=solexa%20technolo gy&pageurl=203&media=1
38 From Fragments to Finished Genome Overview of Sequencing, Assembly, and Closure Processes
40 Genome Sequencing Process Library Construction Clone Picking Template Preparation Sequencing Reactions Electrophoresis and Base Calling rdna Molecules Genome Closure Order Contigs Close Gaps Identify Repeats Finish the Genome Annotation Genome Assembly
41 Sequence Requirements 1. Free vector should be at low or undetectable level. 2. No chimeric clones. Chimeras occur two or more random fragments from separate parts of the genome recombine and end up next to each other. 3. The majority of the inserts should be of relatively uniform size. 4. Libraries need to be random and cover the whole genome.
42 Basecalling & Quality Assignments Phred & TraceTuner Read DNA sequencer traces Call bases Assign base quality values Warner Brothers, Inc. Write basecalls and quality values to output files.
43 What are phred quality values? The quality value q assigned to a base call is defined as: q = - 10 x log 10 (p) where p is the estimated error probability for that base-call.
44 OR A base-call having a probability of 1/1000 of being incorrect is assigned a quality value of 30. Probability Quality Value 1/ /10 10
46 Assembling the fragments
47 Merging two sequences overlap (19 bases) overhang (6 bases) AGCCTAGACCTACAGGATGCGCGGACACGTAGCCAGGAC CAGTACTTGGATGCGCTGACACGTAGCTTATCCGGT overhang % identity = 18/19 % = 94.7% overlap - region of similarity between regions overhang - un-aligned ends of the sequences The assembler screens merges based on: length of overlap % identity in overlap region maximum overhang size.
48 TIGR Assembler Greedy Build a rough map of fragment overlaps Pick the largest scoring overlap Merge the two fragments Repeat until no more merges can be done
49 Forward-reverse constraints The sequenced ends are facing towards each other The distance between the two fragments is known (within certain experimental error) clone length F R sequenced ends
50 Scaffolding Given a set of non-overlapping contigs order and orient them along a chromosome II I III IV III II IV I
51 Clone-mates Insert F R I II R F Vector I II R F II I F R
54 Assembly gaps physical gap group A group B sequencing gaps sequencing gap - we know the order and orientation of the contigs and have at least one clone spanning the gap physical gap - no information known about the adjacent contigs, nor about the DNA spanning the gap
55 Unifying view of assembly Assembly Scaffolding
56 Why Completeness is Important Improves characterization of genome features Gene order, replication origins Better comparative genomics Genome duplications, inversions Determination of presence and absence of particular genes and features is less subjective Missing sequence might be important (e.g., centromere) Allows researchers to focus on biology not sequencing Facilitates large scale correlation studies Controls for contamination
57 What Is Closure? Obtaining sequence that was not obtained during random sequencing which resulted in: Sequencing Gaps Physical Ends Confirming the integrity of assemblies Repeats and misassemblies Verification of Clone Coverage Confirming the base sequence of the consensus Editing Verification of Sequence Coverage
58 Sequence Validation: Sequence coverage 1X 2X 3X Sequence coverage rule: Every base in an assembly must be covered by at least two sequences of high quality. Why? Validating sequence coverage provides a high degree of confidence in the consensus base calls.
59 In this example there is an obvious discrepancy between the base calls of several of the underlying clones in this region. Sequence editor
60 Causes for gaps Non-random shotgun library Toxicity of genes or promoters in E. coli Genomic DNA difficult to clone (capsular polysaccharides) Unstable regions (low complexity) Sequencing problems Hard stops Secondary structures Very high or low GC content Small unit tandem repeats Loss of signal Homopolymeric tracts Very high or low GC content
61 Closure Challenges: Sequencing Through Secondary Structures
66 Repetitive Areas Repetitive areas are regions of high similarity within the genome/bac. Sequences in these areas may be misassembled by the Assembler. Verification of the sequence of repetitive areas: A. Identify potential repetitive areas, using repeatfinder and other tools. B. Classify repeats based on length, copy number, % similarity, structure and complexity. C. If repeats are misassembled, transpose spanning clones or obtain PCR products and sequence to verify assembly.
67 Mis-assembled repeat Clones link different repeat flanks
68 Resolved Repeat Unique flank order is correct Use linking information across the repeat (large insert clones or PCR) Consensus sequence is correct Use linked clones that have one mate in the repeat and the other anchored in unique sequence Transposon mediated libraries
69 Fasta Format > GDRFE25TF CATTGAACACTAGGAGCCATAGAC (up to 60 bases per line) GTTCAACCGTTTAAGGCAAAACTTA AATTTTGGGCAGACTCTAGATCATG GGTAATACATACTCTGGGATTACGA
70 > GDRFE25TF CATTGAACACTAGGAGCCATAGACT (up to 60 bases per line) GTTCAACCGTTTAAGGCAAAACTTA AATTTTGGGCAGACTCTAGATCATG GGTAATACATACTCTGGGATTACGA > GDRFE45TF ACTGGTTCACATGGAGGGATAGTAC (up to 60 bases per line) GACACTCCGTAGCTGGCAATCCTTA GGCTCTCAATCGAGACTCTAGTTAC TCCAATATGGGCTCATGGAACAAGA > GDRFE67TF CATTGAACACTAGGAGCCATAGATC (up to 60 bases per line) AATGTGGCGTAGCTGCCACTTGGTA TACCGTCAATCGTATTGTCTAGTTAC GGGAGATAATATGGGCTCATATGGT > Multifasta Format
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