slides5spring08 - Introduction to Genetic Analysis Ninth...

Info iconThis preview shows pages 1–13. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Introduction to Genetic Analysis Ninth Edition Anthony J. F. Griffiths, Susan R. Wessler, Richard C. Lewontin, and Sean B. Carroll CHAPTERS 13 and 19 Genomes and Genomics Evolutionary Genetics Copyright 2008 W H Freeman and Company The logic of creating a sequence map of the genome Figure 13-2 Clones are selected for sequencing randomly Sequences of clones are assembled using computer programs (e.g., Arachne, Celera Assembler, JAZZ) Contig is the term used for an assembled sequence Neanderthal bone sample for DNA sequencing Figure 13-1 Modern high-throughput techniques even allow the assembly of genomes of extinct organisms (Neanderthal, cave bear, etc.). Genome sequencing is highly automated Figure 13-3 End reads from multiple inserts may be overlapped to produce a contig Figure 13-4 The Sanger method needs a primer to start Paired-end reads may be used to join two sequence contigs Figure 13-5 Gaps are inevitable, but contigs can be linked using long insert clones (e.g., fosmids or BACs). Strategy for whole-genome shotgun sequencing assembly Figure 13-6 So genome assemblies are sets of contigs linked with gaps. Whole-genome shotgun sequencing assembly Despite the existence of gaps, the sequences that can be assembled in this manner are sufficient to identify genes. The information content of the genome includes binding sites Figure 13-9 In fact, it is possible not only to identify protein-coding genes , it is also possible to identify the intron-exon structure of genes, the associated 5 and 3 untranslated regions ( UTRs ), the sites responsible for polyadenylation of transcripts, promoters and other (some) regulatory elements . Finally, regions that encode RNAs (regulatory or even catalytic) can be found. cDNAs and ESTs reveal exons or gene ends in genome searches Genome annotation is imperfect. This is a complex problem for several reasons: 1. The sequences that define intron-exon borders are very short (i.e. GT-AG) and there are exceptions. 2. Many regulatory sequences remain unknown. 3. Functional non-coding RNAs have few distinctive sequences. Figure 13-10 cDNAs and ESTs reveal exons or gene ends in genome searches Annotation can be improved using cDNA and EST data.- Sequences of cDNAs can highlight exons.- ESTs (expressed sequence tags) are a special kind of cDNA sequence. They are produced by single pass sequencing of cDNAs (which is more economical) Even with cDNA/EST sequences, annotation is difficult due to factors like alternative splicing . Figure 13-10 For example, the mouse and human genome have large syntenic blocks of genes in common. 1. Synteny is a term used to indicate genes that are in the same order in two different genomes....
View Full Document

Page1 / 73

slides5spring08 - Introduction to Genetic Analysis Ninth...

This preview shows document pages 1 - 13. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online