Experimental methods in genome analysis

Genomic sequences are boringGATCAATGATGATAGGAATTGAAAGTGTCTTAATTACAATCCCTGTGCAATTATTAATAACTTTTTTGTT CACCTGTTCCCAGAGGAAACCTCAAGCGGATCTAAAGGAGGTATCTCCTCAAAAGCATCCTCTAATGTCA GAAGCAAGTGAGCACTGGGAAGAATACTTGAGAAAGTGGCATGCTTACGAAACTGCTAAGGTGCACCCCA GGGAGGTTGCAAAACCTGCATCTAAAGGAAAGCCCAGGCTTCCAAAGGCTTCTCCTAAGGCAACCTCCAA ACCCAAGCACAGGCATAGGAAAGCACAAATCAAGACCCCGGAGACCCTCGGGCCAAATACAAATTCCAAT AACAACATAGAAGATGATCAGGATGTCCATTCCGAACAGCACCCTTCCCAAAAGGATCTCCAGCAGCTTA AGAAAAAGCCCCGGATCGTCCTACCTTGGTGGTGTGTTTATGTTGCATGGTTTTTGGTTTTTGCTACTTC TAGCATATCCTCATTCTTCATTGTATTTTATGGACTGACTTACGGCTATGACAAGTCAATAGAATGGCTC TTTGCATCTTTTTGTTCATTCTGTCAGTCAGTTCTTCTGGTGCAGCCATCTAAAATTATACTCCTGTCAG GCTTCAGAACGAATAAACCCAAGTATTGCAAAAACCTTTCATGGTCAACCAAGTATAAATATACTGAGAT CAGGTTGGATGGAATGCGTATGCATCCAGAAGAAATGCAGAGGATACATGACCAGATCGTCCGAATCCGA GGCACGAGGATGTACCAACCCCTTACAGAAGATGAAATCAGAATATTCAAAAGAAAGAAGAGGATCAAGA GAAGAGCACTCCTGTTTCTGAGTTACATTCTAACTCACTTTATCTTTCTAGCCCTTCTGTTGATCCTTAT CGTCTTACTACGTCACACTGACTGCTTTTACTATAACCAGTTTATTCGTGATCGGTTCTCTATGGATCTT GCTACTGTGACTAAGCTGGAAGACATCTATAGATGGCTAAACAGCGTGCTGTTGCCTTTGTTACACAATG ACCTGAATCCAACATTTCTTCCTGAAAGCTCGTCTAAAATCCTTGGCCTTCCATTGATGAGGCAAGTGAG AGCAAAATCTAGTGAAAAAATGTGTCTACCTGCCGAAAAGTTTGTGCAAAACAGCATCAGAAGAGAAATT CATTGTCACCCCAAATATGGCATTGACCCAGAAGACACAAAAAACTATTCTGGCTTTTGGAATGAAGTTG ATAAGCAGGCTATAGATGAGAGTACCAATGGATTTACTTATAAGCCTCAAGGAACGCAATGGCTATATTA TTCCTATGGACTACTACACACCTATGGATCTGGAGGATATGCACTCTATTTTTTTCCAGAACAGCAGCGG TTTAATTCCACACTGAGGCTCAAAGAACTTCAAGAAAGCAATTGGCTGGATGAGAAGACATGGGCTGTGG TTTTGGAATTAACAACTTTTAATCCAGATATAAATCTGTTCTGTAGCATTTCGGTCATATTTGAAGTCTC TCAGTTAGGAGTTGTCAACACAAGCATATCTCTGCACTCTTTTTCACTTGCTGATTTTGACAGAAAAGCT TCAGCAGAAATCTACTTGTATGTGGCCATTCTCATTTTTTTCTTAGCCTACGTTGTTGATGAGGGTTGTA TCATTATGCAAGAAAGAGCCTCCTATGTGAGAAGTGTGTATAATTTGCTCAACTTTGCTTTAAAGTGCAT ATTTACTGTGTTGATTGTGCTCTTTCTCAGGAAACATTTCCTGGCCACTGGCATAATTCGGTTTTACTTG TCGAACCCAGAAGACTTCATTCCCTTTCATGCAGTTTCTCAGGTAGATCACATTATGAGGATAATTTTGG GTTTCCTGTTATTTCTGACAATTTTGAAGACCCTCAGGTATTCCAGATTCTTCTACGATGTGCGCCTGGC TCAGAGGGCCATCCAGGCTGCCCTCCCTGGCATCTGCCACATGGCATTTGTTGTGTCCGTGTATTTCTTC GTATACATGGCTTTTGGTTACCTGGTGTTTGGTCAGCATGAATGGAACTACAGTAACTTGATTCATTCCA CTCAGACAGTATTTTCCTATTGTGTCTCAGCTTTCCAGAACACTGAATTTTCCAATAACAGGATTCTGGG GGTCCTGTTCCTCTCATCTTTCATGCTGGTGATGATCTGCGTCTTGATCAACTTATTTCAGGCTGTAATT

Making sense of genomic seqs

• Look for repeats

• HMM analysis

• Compare genomes to each other

• Compare to other kind of experimental data

– Which kinds of data can you think of?

Other kinds of data

1. mRNA (EST)

2. RNA sequences & structures

3. Protein sequences

4. Protein structures

5. SNPs, polymorphisms

6. Gene expression (microarray)

7. Protein expression (2D protein gels)

8. Protein interaction

9. Metabolic pathways

10. Regulatory pathways

Transcript databases

• RefSeq contains full length sequences of mRNAs, carefully reviewed– Currently 5.000 human sequences

• dbEST contains 5’ and 3’ reads of random cDNAs

– Currently 3.7 mio. human seqs

ESTs

• UniGene: Merge (cluster) any two ESTs when >100 bp are identical

• 3.7 mio -> 104.214 clusters

ESTsUniGene: total # clusters 104.214 Cluster size Number of clusters

1 37503 2 14605 3-4 15912 5-8 10798 9-16 5978 17-32 4143 33-64 3658 65-128 4117 129-256 4109 257-512 2317 513-1024 743 1025-2048 227 2049-4096 68 4097-8192 29 8193-16384 6 16385-32768 1

Some statistics

Copies # different mRNA # of mRNAs per per cell species abundance level_________________________________________5 4000 20.00050 3250 162.500200 2500 500.0001000 250 250.000

_____________________________

Total 10.000 932.500

More statistics

1.000 5.000 10.000 50.000 250.000 1.000.000

5 0.53 2.65 5.22 23.52 73.83 99.53

50 5.22 23.52 41.5 93.15 100 100

200 16.31 65.78 88.29 100 100 100

1000 65.8 99.53 100 100 100 100

Abundancelevel

Size of EST database

Solutions

• Sequence ESTs from many cell types, rare transcripts might be abundant in other tissues.

• Use subtraction / normalization procedures prior to sequencing

Transcripts: what can we learn?

• Comparing genome sequences to transcripts allows: – Confirmation of gene predictions– Experimental identification of Exons/Introns, 5’

UTRs, 3’ UTRs– Alternative splicing

• Asses the relative abundance of transcripts.

Protein databases

• SwissProt: Carfully curated / annotated database of experimentally determined protein sequences: 115.105 entries

• PIR: Protein Identification Ressource: 283.175 entries.

• Translated nucleotide databases: nr, trEMBL, RefSeqP m. m.

Gene ontology

• Gene Ontology controlled vocabulary that can be applied to all organisms

• The three organizing principles of GO are molecular function, biological process and cellular component

Combining EST frequencies with GO

EST frequncies from blood-fed vs. non-blood-fed mosquitos grouped by function

Proteomics

What for?

• Disease targets

• Gene finding

• Secondary modifications

• Measuring expression levels

• Protein-protein interactions

Whats new?

• Mass spectrometry was invented turn of century (Thomson)

• Noble price to Aston 1930s

• MALDI-TOF (Henzel et al, 1993)

• Nano-electro-spray (Wilm, Mann 1996s) coupled to tandem mass spectrometer

• Noble price 2002 to John B. Fenn and Koichi Tanaka

M + e- => M+· + 2e-

MALDI matrix assisted laser desorption ionizationTOF time-of-flight

Nanoelectrospray ionization – tandem mass spectrometry (MS-MS)

Positive ESI-MS m/z spectrum of the protein hen egg white lysozyme.The sample was analysed in a solution of 1:1 (v/v) acetonitrile : 0.1% aqueous formic acid and the m/z spectrum shows a

Gaussian-type distribution of multiply charged ions ranging from m/z 1101.5 to 2044.6. Each peak represents the intact protein molecule carrying a different number of charges (protons). The peak width is greater than that of the singly charged ions seen in the leucine enkephalin spectrum, as the isotopes associated with these multiply charged ions are not clearly resolved as they were in the case of the singly charged ions. The individual peaks in the multiply charged series become closer together at lower m/z values and, because the molecular weight is the same for all of the peaks, those with more charges appear at lower m/z values than do those with fewer charges (M. Mann, C. K. Meng, J. B. Fenn, Anal. Chem., 1989, 61, 1702).

 The m/z values can be expressed as follows: m/z = (MW + nH+) n

where m/z = the mass-to-charge ratio marked on the abscissa of the spectrum;MW = the molecular weight of the samplen = the integer number of charges on the ionsH = the mass of a proton = 1.008 Da. If the number of charges on an ion is known, then it is simply a matter of reading the m/z value from the spectrum and solving

the above equation to determine the molecular weight of the sample. Usually the number of charges is not known, but can be calculated if the assumption is made that any two adjacent members in the series of multiply charged ions differ by one charge.

 For example, if the ions appearing at m/z 1431.6 in the lysozyme spectrum have “n” charges, then the ions at m/z 1301.4 will have “n+1” charges, and the above equation can be written again for these two ions:

 1431.6 = (MW + nH+) and 1301.4 = (MW + (n+1)H+) n (n+1)These simultaneous equations can be rearranged to exclude the MW term:  n(1431.6) –nH+ = (n+1)1301.4 – (n+1)H+ and so: n(1431.6) = n(1301.4) +1301.4 – H+ therefore: n(1431.6-1301.4) = 1301.4 – H+ and: n = (1301.4 - H+)

(1431.6 – 1301.4) hence the number of charges on the ions at m/z 1431.6 = 1300.4 = 10.

130.2 Putting the value of n back into the equation: 1431.6 = (MW + nH+)

n gives 1431.6 x 10 = MW + (10 x 1.008) and so MW = 14,316 – 10.08 therefore MW = 14,305.9 Da The observed molecular weight is in good agreement with the theoretical molecular weight of hen egg lysozyme (based on

average atomic masses) of 14305.1438 Da. This may seem long-winded but fortunately the molecular weight of the sample can be calculated automatically, or at least

semi-automatically, by the processing software associated with the mass spectrometer. This is of great help for multi-component mixture analysis where the m/z spectrum may well contain several overlapping series of multiply charged ions, with each component exhibiting completely different charge states.

 Using electrospray or nanospray ionisation, a mass accuracy of within 0.01% of the molecular weight should be achievable, which in this case represents +/- 1.4 Da.

2D-gel electrophoresis

Conclusions on helper data

1. mRNA (EST)

2. RNA sequences & structures

3. Protein sequences

4. Protein structures

5. SNPs, polymorphisms

6. Gene expression (microarray)

7. Protein expression (2D protein gels)

8. Protein interaction

9. Metabolic pathways

10. Regulatory pathways