Goal class 25:
- Know about different approaches to detect HGT events (phylogenetic conflict and using bllast as proxy, gene presence absence, composition based)
- Know about the advantages and disadvantages to use bipartion based analysis to identify phylogenetic conflict.
- Understand why embedded quartets are advantagous.
- Know about the problems associated with shotgun genome sequencing of multicelluar organisms that live with their symbionts and other bacteria - these genome sequences should be considered metagenome sequences.
- Understand that binning based on composition and coverage can help identify genes from the host and differentiate them form bacterial genes. (But might classify genes recently transferred to the host as belonging to bacteria.)
- Understand the demonstration that the UNC tardigrade genome contigs contained many genes not part of the tardigrade genome.
- Know about the difference between supertree and supermatrix approaches, and appreciate the advantages and disadvantages of each approach.
Goals class 24:
- Appreciate the power of PSI-blast to find divergent homologs
- Know the principle behind PSI blast searches
- Be aware of the problems that a corruption of the scoring matrix causes
- Know what the consequence of this corruption means for the E-value of a match.
- Understand the meaning of the E-value cut-off for inclusion in the next iteration
- Know the meaning of the E-value of a hit in a PSI blast search
- Know about the problem in estimating the expected numbers of false positives in PSI blast searches
- Appreciate that building the profile / scoring matrix can use a different databank as compared to the final search
- Know a few possible applications for PSI or Hmmer searches
- Know that HGT, genome duplications, and introgression can lead to non-gradual evolution
- Know examples for biochemical pathways likely assembled through HGT.
Goals class 23:
- Know that the dN/dS>1 approach can be used to detect positive selection and that this approach is often difficult to apply in case the alignment is unreliable (which results in more non-synonymous substitutions).
- Know that the dN/dS<1 approach to detect purifying selection may not always reflect a selection for function.
- Understand that selection can act at the level of the gene (selfish genetic elements), at the level of of the individual in the population, and possibly through the competition between populations and communities.
- Understand the link between positive selection and selective sweep.
- Know different approaches of how selective sweeps can be detected.
- Know about archaic admixtures to modern human populations
- Understand the mitochondrial Eve and Y chromosome Adam concept, and why this does not work for other genes.
Goals class 22
- Know what the terms positive, negative, and neutral selection mean and what frequent synonyms for these terms are.
- Know how to infer the type of selection using synonymous and non-synonymous substitutions.
- Know that one can infer the type of selection from the rate with which a gene goes to fixation.
- Be able to discuss the terms positive and diversifying selection
Goals class 21
- Know the difference between mutation and substitution.
- Understand why for neutral mutations the mutation rate equals the substitution rate.
- Understand that even with very large populations, most mutations that provide a small selective advantage go extinct due to genetic drift.
- Understand how population size impacts the time it takes for fixation of a neutral mutation
- Understand that individual genes have evolved from an ancestral gene, but that if one considers many genes, these ancestral genes did not exist in a single organism.
- This is true for Y-chromosome Adam and mitochondrial Eve (and for all the other genes found in humans), but also applies to the "tree" of life.
Goals Class 20:
- Know how
- lack of resolution,
- lineage sorting,
- gene transfer,
- introgression, and
- systematic artifacts
- can lead to differences between gene and "species" trees.
Goals class 19:
- Know the names and characteristics of the different types of homology
- Know about the different ways the tree of life can be rooted.
- Be able to read bipartition tables
- Know the basic structure with which programs in phylip work.
- Know how bootstrap samples are created
- Know the principle behind parsimony analysis and Occam's razor (or Ockham's razor, aka lex parsimoniae)
- Know the similarity and differences between parsimony and maximum likelihood based phylogenetic reconstruction.
- Know about the relationship between maximum likelihood, posterior and prior probability.
Goals class 18
- Know about different approaches (distance, parsimony, maximum likelihood, Bayesian) to reconstruct evolutionary history from molecular data
- Know about advantages and disadvantages of the different approaches:
Why is maximum likelihood considered advantageous over maximum parsimony ?
Which problems of
likelihood analysis is addressed through the Bayesian approach?
Why are algorithmic distance
based approaches still popular?
Goals class 17
- Be able to identify trees with identical topology
- Know about different approaches to root a tree
- Know which rearrangements do and which do not change the meaning of a tree or of a tree topology
- Know about different approaches to reconstruct evolutionary history from molecular data
Goals class 16:
- Know abut genes in pieces and the intron early versus intron late debate
- Know the main arguments in favor of introns late (Why is the TPI intron not a strong argument?)
- Appreciate the contributions that spliceosomal introns make to the molecular biology of eukaryotes
- Know what the term Go domain refers to (not the Japanese board game, but the scientist Mitiko Go) and how this relates to introns
- Know about the theory that connects introns to the origin of the nuclear envelope
Goals class 15:
- Understand the controversy about the term monophyletic, and how the different interpretations lead to different taxonomies.
- Know the difference between local and global alignments.
- Know how gaps, insertions, repeated domains, and regions of low complexity look like in a dotplot analysis.
- Understand how dynamic programming can guarantee an alignment with an optimal alignment score in case of a pairwise alignment.
- Understand the principle of the progressive alignment approach and the potential downstream problems caused by this analysis.
- Appreciate that multiple sequence alignments can have different goals: pleasing to the human observer; matching sites that in the 3D structure occupy the corresponding location; be certain that alignment columns only contain homologous sites (else align them to gaps).
Goals class 14:
- Know what the terms synapomorphy, sympleisiomorphy, autapomorphy, and homoplasy mean.
- Know how these terms are related to mono-, para, and polyphyletic groups.
- Know about Ashlock's redefinition of monophyletic
- Know the definition of a clade, and why it is not applicable in case of unrooted trees.
- Be able to discuss the goals of a natural taxonomy
Goals for class 13:
- Know the possible fates of duplicated genes (non-, sub-, and neo-functionalization), and the frequency of the different outcomes.
- Know how to compare two bacterial or archaeal chromosomes using a gene plot.
- Understand the power of simple scripts to run programs and to process the output of programs
- Appreciate the use of hashes as an efficient data structure linking keys and values
- (more discussion of the next couple of goals in class 14)
- Understand genome structure of prokaryotic genomes (Ori, leading/lagging strand, terminus of replication).
- Know about strand bias and how to use cumulative strand-bias to find the origin and terminus of replication.
- Understand the type of recombination that lead to gene plots where most of the matches are along the two diagonals.
- Know the two possible reasons for this process.
Comp. Labs:
- Know how to align sequences using different approaches, and which are more appropriate for subsequent phylogenetic reconstruction.
- Be able to generate a codon based alignment
- Understand the most frequently used Multiple Sequence Alignment (MSA) formats, and how to coonvert one format into another.
- Be able to connect to the linux cluster of the bioinformatics facility and execute simple comands on the command line.
- 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
- Be able to assess if two sequences are significantly similar
Goals class 11
- Understand that the evolution of genomes is best depicted as a network.
- Understand the Coral of Life metaphor and the possibility that now extinct lineages have contributed to the gene pool of extant organisms.
- Know that transfered genes that are inhereted by the descendants of the recient are a valuable marker to form groups of related organisms.
- Understand the gen-plot like diagrams, and what they imply for the occurance and fixation of intra chomosomal recombination.
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 commandline 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 Margaret Dayhoff's accomplishments
Goals class 9:
- Understand the meaning of phylogeny
- Understand the tree-of-life and coral-of-life concepts
- 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 usual cut-offs for Z-scores, P- and E-values.
- Understand that neutral evolution can lead to an irreversible increase in complexity.
- 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 about the problem facing the scientific community through the underreporting of negative results.
- Understand the problems that result from ownership of database entries (know a few examples).
- Know at least some processes in evolution that go beyond gradual evolution by natural selection.
Goals Class 7:
- Know about the discussion on competition and cooperation, social Darwinism and mutual aid.
- Understand that Darwin while an abolitionist was a child of this times.
- Appreciate the difference between supervised databanks and simple repositories.
- Know about the advantage of the databanks at the NCBI.
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.
- Understand that neutral evolution can lead to an irreversible increase in complexity.
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 the role of ancient gene duplications in rooting the tree of life.
- Understand how the origin of the recent ebola outbreak has been followed using molecular data.
- Know a few examples for how the study of molecular evolution has been important for biology, medicine, criminal law, ...
- 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 preceded a genetic system based on nucleic acid like molecules.
(no biopolymer life (autocatalytic reaction cycles) -> single biopolymer life ("RNA world") -> two biopolymer life)
Goals Class 3:
- Understand that RNA can be both genetic material and catalyst
- Know what else supports the RNA-world concept
- 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.
Goals Class 2:
- 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
- Recognize 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 take-home exams and computer lab 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.