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Figures for this lecture can be accessed by logging onto the course D2L site at https://uwlax.courses.wisconsin.edu/

Using Genomic DNA Sequences to Discover Genes

Overview

Cytogenetic maps, genetic maps, physical maps, and sequence for MANY different organisms: Saccharomyces, C. elegans, Arabidopsis, Drosophila, zebrafish, human, etc.

 

 

Human genome originally cut it into small (!) approximately 1Mbp pieces and each piece was cloned into a separate vector

 

Clones are sequenced, sometimes without regard to their original order

 

Can order the clones into contigs using markers and then assemble the sequence

 

 

Eventually, we have a contig that consists of an entire chromosome

Eventually, we have contigs of every chromosome

 

 

Problem #1

In mammals, only about 1-2% of the genome encodes protein; about 35% is repetitive DNA; about 60% is spacer DNA

 

 

How do we sort through the genome to find the genes?

 

 

Dealing with ``The Needle in a Haystack" (or ``How to find protein-encoding genes hiding in the midst of all that other DNA)

1. Look for ORFs:

5'- ACGTGCTAATGCGAGCAGCAGCGATCGAGCTGATGCAGGCTTAAGCTAGCTAG

 

 

 

Splicing:

Often, exons are only 50 codons and introns can be as large as 10kb

5'-ACGTGCTAATGCGAGCAGCAGCgtacgtagctgatgctgatgtcagcGATCGAGCTGATGCAGGCTTAAGC

TAGCTAG

 

Consensus splice sites help computer programs find ORFs even when disrupted by introns

 

 

2.Look for CpG islands:

 

 

3.Look for association with ESTs:

 

 

4.Look for association with known cDNAs:

 

 

 

5.Look for similarity to known mouse or (now) rat genes:

 

 

 

Automation in Gene Prediction

Obviously (I hope) we want to make this automated

GENSCAN

Fly genome

AE003847.5 sequence

Results

Predictions: about 23,000 genes; maybe about 90,000 proteins in humans

 

 

Problem #2

What about noncoding RNAs? rRNA, tRNA, miRNA, etc.

 

 

 

Look for similarity to known RNAs from other critters

 

 

 

 

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