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Sequenziamento: metodo di Sanger con ddNTP
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Sequenziamento con dideossonucleotidi
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Sequenziamento automatizzato del DNA
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+ Ligazione Inserto Vettore Clonaggio:
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Trattamento del vettore con fosfatasi
G CTTAAp pAATTC G CTTAA AATTC fosfatasi G AATTC CTTAApG GpAATTC CTTAA G DNA ligasi pAATTC G CTTAAp EcoRI GAATTC CTTAAG
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Vettori plasmidici (pBR322)
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Vettori plasmidici (pUC18)
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Non c’è complementazione
β-galattosidasi ATTIVA Ceppo di E.coli Lac Z mutante Vettore pUC LacZ parziale Complementano Ceppo di E.coli Lac Z mutante Vettore LacZ interrotto dal clonaggio Non c’è complementazione β-galattosidasi INATTIVA β-galattosidasi ATTIVA Colonie Blu Metabolizzato Terreno + X-Gal Colonie bianche Non metabolizzato β-galattosidasi INATTIVA X-Gal: 5-Bromo-4-Cloroindolil-β-galattoside (incolore)
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1° ciclo di PCR 5’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ DNA genomico Primer reverse
Primer forward 5’ 3’ 3’ 5’ DNA genomico
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ETEROGENEITA’ DEL TEMPLATO : ETEROZIGOSI PER UNA DELEZIONE
C A G T
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F P M C/C G/- C/- LOSS OF HETEROZYGOSITY
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RNA sequencing Dopo trascrizione inversa
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6 8 7/- 7/- 6 7 8 -/- CTT
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Figure 1: Illumina Flow Cell Figure 2: Prepare Genomic DNA Sample
Adapters DNA Figure 3: Attach DNA to Surface Figure 4: Bridge Amplification Adapters Dense lawn of primers DNA
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Figure 5: Fragments Become Double Stranded
Figure 6: Denature the Double-Standed Molecules Attached terminus Attached Attached terminus Free terminus Attached Figure 7: Complete Amplification Figure 8: Determine First Base Clusters Laser
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Figure 9: Image First Base Figure 10: Determine Second Base
Figure 11: Image Second Chemistry Cycle Laser Figure 12: Sequencing Over Multiple Chemistry Cycles GCTGA... Figure 13: Align Data
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Figure 3 | Genome assembly algorithms
Figure 3 | Genome assembly algorithms. A genome schematic is shown at the top with four unique regions (blue, violet, green and yellow) and two copies of a repeated region (red). Three different strategies for genome assembly are outlined below this schematic. a | Overlap-layout-consensus (OLC). All pairwise alignments (arrows) between reads (solid bars) are detected. Reads are merged into contigs (below the vertical arrow) until a read at a repeat boundary (split colour bar) is detected, leading to a repeat that is unresolved and collapsed into a single copy. b | de Bruijn assembly. Reads are decomposed into overlapping k‑mers. An example of the decomposition for k = 3 nucleotides is shown, although in practice k ranges between 31 and 200 nucleotides. Identical k‑mers are merged and connected by an edge when appearing adjacently in reads. Contigs are formed by merging chains of k‑mers until repeat boundaries are reached. If a k‑mer appears in multiple positions (red segment) in the genome, it will fragment assemblies and additional graph operations must be applied to resolve such small repeats. The k‑mer approach is ideal for short-read data generated by massively parallel sequencing (MPS). c | String graph. Alignments that may be transitively inferred from all pairwise alignments are removed (grey arrows). A graph is created with a vertex for the endpoint of every read. Edges are created both for each unaligned interval of a read and for each remaining pairwise overlap. Vertices connect edges that correspond to the reads that overlap. When there is allelic variation, alternative paths in the graph are formed. Not shown, but common to all three algorithms, is the use of read pairs to produce the final assembly product.
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