The objective of this exercise is to consider the human genome project (HGP), and relevant to any one of human chromosomes ascertaining gene-like patterns in the ORFs. Problem-statement and suggested exercise/tasks (a) Obtain the genome data on a human chromosome at NCBI site. Get the physical and genetic atlas for these chromosomes that contain information on known genes. Identify ORF regions.
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Open reading frames in $E .$ coll In this problem, we will search the $E$. coli genome for open reading frames. The actual genome sequence of $E$. coli is available on the book's website. (a) Write a program that scans the DNA sequence and records the distance between start and stop codons in each of the three ORFs on the forward strand. You may skip the calculation for the reverse strand. You can find an example of this code implemented in Matlab on the book's website. (b) Plot the distribution of ORF lengths $L$ and compare it with that expected for random DNA calculated in Problem 4.7 (c) Estimate a cut-off value $L_{\text {cut }}$, above which the ORFs are statistically significant, that is, the number of observed ORFs with $L>L$ cut is much greater than expected by chance. (Problem courtesy of Sharad Ramanathan.)
You have the following sequence reads from a genomic clone of the Homo sapiens genome: Read 1: ATGCGATCTGTGAGCCGAGTCTTTA Read 2: AACAAAAATGTTGTTATTTTTATTTCAGATG Read 3: TTCAGATGCGATCTGTGAGCCGAG Read 4: TGTCTGCCATTCTTAAAAACAAAAATGT Read 5: TGTTATTTTTATTTCAGATGCGA Read 6: AACAAAAATGTTGTTATT a. Use these six sequence reads to create a sequence contig of this part of the $H .$ sapiens genome. b. Translate the sequence contig in all possible reading frames. c. Go to the BLAST page of the National Center for Biotechnology Information, or NCBI (http://www.ncbi. nlm.nih.gov/BLAST/, Appendix B) and see if you can identify the gene of which this sequence is a part by using each of the reading frames as a query for proteinprotein comparison (BLASTp).
Jhankar T.
What two genetic features define an open reading frame (ORF) and why do we search for known homologs of predicted ORFs during genome annotation?
Madhur L.
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