Assignment for Wednesday's class:

Prepare for midterm.

Assignment for Friday

Complete Assignment #6 part 1 (you can leave out the histograms, but you should have a folder in your directory on the cluster that contains the results of a blast search of one genome against a distantly related one (using the *.faa file).

Assignment for next Monday

Think about the question how new genes are created, and how genome size can increase. Everyone should have at least three distinct mechanisms.
Read The Evolutionary Fate and Consequences of Duplicate Genes

Questions on commandline blast

Questions re. take home exam #3

Questions regarding midterm.

ELSE

late heavy bombardment (also Olga's timeline of the Universe)

How old is life on Earth?

The Earth is about 4.6 Ga old, but no crustal rocks has survived from that time. The oldest rocks are no older than 4.0 Ga. But zircon crystals dated to 4.4 billion years BP are found in rocks, are considered evidence for Earth's crust having had formed and being in contact with water already 4.4 billion years BP (here and here)

Morphological Fossil Evidence:

For about a decade the oldest microfossils were considered to be about 3.5 Ga old (see here). The fossils (as interpreted by Bill Schopf) look like "modern" Cyanobacteria. Compare the time to to molecular trees of life: Is this a problem? However, the evidence for these fossils was questioned.
3.2Ga old filamentous fossils, probably of thermophilic chemotrophic prokaryotes (Rasmussen, 2000)
1.8Ga old fossils from Gunflint formation: iron-loving bacteria and cyanobacteria

Biological Signature Evidence (examples):

Oldest geological evidence for life - 3.8 Ga ago - is based on ¹³C discrimination (carbon derived from living systems often have lower delta ¹³C values than inorganic carbonates) [here]. The rocks are from Akilia island off the coast of Greenland, and severely altered by metamorphism. However, recently the evidence for that was reassessed.
3.7 billion year of rocks from the Isua formation in Greenland contain structures described as stromatholites. here in NYT, report in Nature
The amount of carbon in the Issua formation (and its discrimination against agains 13C) is interpreted by Minik Rosing to indicate a highly productive biosphere. (See Minik's presentation at the 2011 ISSOL meeting. Especially slides 6 ff are interesting - the handwritten slides were written with the sedimentary rocks - containing lots of graphite.)
2.7Ga old: probable biomarkers of cyanobacteria and of eukaryotes (Roger Summons, Roger Buick and Jochen Brocks)

See Olga's Timeline of the Universe here

sequence space

Comp. Lab 6:

Know how to move up an down in the directory hierarchy using the unix command line
Be able to transfer files to and from the bioinformatics cluster
Be able to use the programs that are part of the blast + package
Know how to get information on the different parameters you can set
Know how to use the arrow keys to move back in the command history
Know how to use the tab key for line completion

Goals class 11:

Appreciate that life may be older than the late heavy bombardment.
Know how to adjust significant levels of individual experiments to avoid fishing expeditions.
Know about the problem facing the scientific community through the underreporting of negative results.

Goals class 10

Understand how the databanks at the NCBI are different from flatfile and relational databanks.
Be able to discuss the advantages of the command line in general and blast searches via the commandline in particular.
Know which substitution matrices to use for comparing similar and for divergent sequences
Understand the different types of error with as applied to data bank searches
Know how to adjust significant levels of individual experiments to avoid fishing expeditions.
Know about the problem facing the scientific community through the underreporting of negative results.

Comp. Lab 5

Be able to connect to the linux cluster of the bioinformatics facility and execute simple comands on the command line.
Be able to use PRSS, BLAST and FASTA to assess significant sequence similarity.
Understand how the E-value is related to the possibiity of false positives.
Be able to check using the output from pairwise BLAST comparisons, if the principle transitive homology can be applied.

Goals class 9:

Understand the meaning of phylogeny
Understand that neutral evolution can lead to an irreversible increase in complexity.
Distinguish false positives and false negatives, especially with respect to databank searches
Understand the impact of E-value cutoff in blast
Understand the impact of the low complexity filter in blast

Goals class 8:

Understand the difference between P and E values
Know about the usual cut-offs for Z-scores, P- and E-values.
Understand the tree-of-life and coral-of-life concepts
Be able to discuss the process that may lead to the decay of significance
Know what fishing expeditions and the Bonferroni correction are about
Know at least some processes in evolution that go beyond gradual evolution by natural selection

Comp Lab 4

Be able to use advanced search and the index function to formulate searches on PubMed
Learn about google scholar and other literature databanks
Understand that most databank searches have already been pre-computed and that you can access the results through BLINK and related sequences
Appreciate that protein sequences contain many more links to related sequences than nucleotide sequences.
Understand the value that bibliography programs such as endnote, zotero, or mendeley provide

Goals Class 7

Understand the problems that result from ownership of database entries (know a few examples).
Appreciate the difference between supervised databanks and simple repositories.
Know about the advantage of the databanks at the NCBI.
Understand how to analyze exponential growth / decay.

Goals class 6:

Know the differences between Lamarck's and Darwin's theory, mutationism, and the modern synthesis.
Understand the power and the limitations of the tree of life image.
Understand that without selection for function, sequences would have diverged beyond recognition.

Computer lab 3

Learn how to align structures that do not show any significant sequence similarity between their primary sequences.
Understand that protein structure is much more conserved than the primary sequence of proteins.
Appreciate that similarity in the arraignment of secondory structure elements of complex protein structures is a strong argument for homology.

Goals class 5:

Appreciate that without selection for function two sequences would have diverged beyond recognition in a few hundred million years.
Understand the different meanings of the term evolution ( "As in evolution of the universe" vs "Nothing in biology makes sense if not considered in the light of evolution" .
Appreciate the power of natural selection
Understand that other mechanisms in addition to natural selection might be at play in biological evolution

Goals class 4:

Understand a few different approaches on how life has been defined/characterized.
Be able to discuss how viruses fit into the concepts of life and living things.
Understand that the evolution of Daisyworld does not represent natural selection.
Be able to discuss pros and cons of NASA's definition of life.
Understand the argument that life and inheritance might have preceeded a genetic system based on nucleic acid like molecules. (nobiopolymer life (autocatalytic reaction cycles) -> single biopolymer life ("RNA world") -> two biopolymer life)

Computer lab 2

Using SPDBV be able to dissect protein strictures into individual subunits.
Learn how to align protein structures in SPDBV.
Appreciate that structure is much more conserved than primary sequence.
Understand that linking multiple subunits together that each are in a different phase of the catalytic cycle, can smooth out Energy barriers (similar to a four cylinder engine, where only one phase runs downhill ...) .

Goals class 3:

Know a few examples for the study of molecular evolution being helpful in other areas of biology.
Understand that different mechanisms (gene duplication, gene transfer, lineage fusion) can lead to many homologs coexisting in a single cell, or even in a single multi subunit enzyme.
Know about the different ways protein coding genes can evolve.
Understand how the origin of the recent ebola outbreak has been followed using molecular data.
Know that some proteins evolve so slowly that they remain recognizable homologs after more than 7 billion years of evolution.

Com. Lab 1

Know where to download SPDBV.
Know how to load a pdb file into the viewer.
Be able to select the different cursors.
Understand what the different cursors do.
Be able to display the molecule in different grades of complexity (carton, back bone only, molecular surfaces).
Know how to select amino acids that are part of the binding pocket.
Know how to apply different color schemes to the molecule (CPK, seconday structure) to different parts of the molecule (backbone, Ribbon, side chains).

Goals class 2:

Understand that RNA can be both genetic material and catalyst
Know what else supports the RNA-world concept
Understand the homology concept used evolutionary biology
Know that most significantly similar complex sequences (in their primary sequence) are homologous, and that not all homologous sequences are significantly similar in a pairwise comparison of the primary sequence.
Know the difference between primary, secondary and tertiary structure
Recognise secondary structure elements
Know that the combinatoric protein space is huge, but highly connected
Be able to explain, how functional proteins might have evolved despite combinatoric protein being huge

Goals class 1:

Know how to contact the instructor and TA.
Understand how your performance will be assessed and graded.
Understand that the assignments are an important part of this course, and that they will be graded.
Know at least three examples for the connection between bioinformatics and the study of molecular evolution.
Understand why significant sequence similarity implies likely shared ancestry and similar function, but that the reverse (non-significant sequence similarity implies independent origin) is not true.