Sequence Comparison and Genomes Quiz

Sequence Comparison

• Dot plots and alignments are used for comparing sequences

Mystery of the Chilean Blob

• A 13-tonne blob, washed ashore in Chile in 2003, was initially hypothesized to be various things, including giant squid, octopus, whale blubber, or an alien sea monster.
• Analysis revealed the blob to be sperm whale blubber.

Animal Cell Structure

• A diagram displaying the different components of an animal cell is included, labeled with the name of each part.

Why mtDNA?

• The rapid mutation rate in animals makes mtDNA useful for assessing relationships of individuals or groups within a species, and for identifying evolutionary relationships among species.

Mystery of the Chilean Blob - Further Questions

• Determining the individual whale the blubber came from
• Determining the birth location of the whale
• Understanding the whale's social relationships during its lifetime
• Tracking the whale's movements across the globe and through time

Mystery of the Chilean Blob - Additional Analysis

• Tracing the whale's family history through time and changes in the environment.
• Reconstructing the evolution of whale adaptations, like echolocation
• Identifying the nearest mammalian relatives of whales
• Comparing DNA beyond fossil records

Answer to all these Qs

• DNA sequences provide insights at various levels of evolutionary history, from individuals to kingdoms of life.
• This is because different parts of the genome evolve at different rates.

Individual Identification

• DNA mutations accumulate over time.
• Differences between parent and offspring are minimal (approximately 100), increasing through generations.
• DNA sequences allow establishing relationships between whales when enough samples are available.
• An understanding of whale population interactions and interbreeding is possible with DNA sequencing.
• Forensic DNA analysis is also possible to identify samples at crime scenes.

Observation of Sperm Whale Behavior

• Social groups average 10-30 animals, including mature and immature whales of both sexes.
• Social bonds within groups vary significantly in duration.
• Some associations persist for years, while others last only a few days.
• Mature male whales are not long-term members of social groups; they disperse from their natal groups.

Observation of Sperm Whale Behavior – Methodology

• Naturally sloughed whale skin from three different regions/groups was collected along with microsatellite markers, mtDNA, and a male specific gene.
• The genetic profiles of collected individuals were assessed to compare relatedness within and between groups
• Social groups were determined through photographic identification of individuals.
• Groups typically comprised approximately 26 members, largely female (79%).
• Studies confirmed the consistency of a matrilineal model.

Where the Individual was Born

• Sperm whales are found across all oceans.
• Male whales migrate between oceans, unlike female whales who typically stay in their birth region.
• mtDNA in sperm whales is passed on from mother to offspring.
• mtDNA sequences are used to trace where the whale was born from analyzing its species-typical mtDNA sequence.

Estimation of Population Size

• Measures of genetic similarity indicate population size and mating structure.
• Low diversity suggests inbreeding or a small population, while large populations show higher diversity.
• Samples from 37 whales from different areas, sequenced, had unusually low diversity, pointing to possible low evolutionary rate and/or recent ancestry.
• Global estimations of the sperm whale population are approximately 360,000.
• Genetic differences between whales were measured to determine population size

Estimation of Population Size - Further Analysis

• Genetic diversity of the population is low.
• Evolutionary rate of other mtDNA is normal, suggesting reduced diversity due to recent ancestry from a small group of founding mothers who survived the last ice age.
• Last glacial period peaked around 21,000 years ago and concluded about 11,500 years ago.

Estimation of Population Size – Time Estimates

• Estimated time since common mtDNA ancestry in sperm whales was between 6,000-25,000 years ago.
• This might correlate with the last ice age in the case of a bottleneck.
• DNA sequences help to understand how the population has changed over time.

Echolocation in Sperm Whales

• Sperm whales use echolocation to hunt, a feature they share with other predatory toothed marine mammals, like dolphins and killer whales.
• Baleen whales have filtering plates in their mouths, instead of echolocation, for feeding on plankton.

Echolocation - Evolutionary Considerations

• The theory is that both groups (toothed and baleen whales) evolved from a common ancestor approximately 30 million years ago, adapting to different lifestyles.
• One group developed echolocation, the other baleen plates.

Common Ancestral Whale

• Common ancestor of all whales must have had echolocation since it has apparently been lost in baleen whales.
• Evidence of vestigial 'melons' (echolocation sounding chambers) in baleen whales supports this hypothesis.

DNA - Evolutionary Considerations

• DNA sequences provide valuable evolutionary information, though evolution can mask the history of species through both adding and removing complex characteristics.
• Molecular data can provide a clearer picture of a species' evolutionary past than their highly modified morphology.

Computational Molecular Biology

• Genome analysis involves identifying characteristic features in a genome.
• Techniques like sequence alignment (pairwise and multiple), pattern search (repeats, motifs, domains), and database search (find similar sequences) help.
• Statistical measures include ab initio methods for gene prediction and evaluating alignment/motif significance.

Types of Mutations

• Mutations are local changes in DNA resulting from inexact replication.
• Substitutions involve replacing one base with another, which may or may not change the protein sequence (e.g., GUU, GỤC, GUA, GUG all code for Valine). Others involve the addition or removal of bases, causing frame shifts.
• Rearrangements involve changes to the order of complete segments within a chromosome (e.g., human and mouse genomes).

Mutations' Importance

• Mutations are the source of phenotypic variation on which natural selection acts to create and change species.
• Mutations cause inherited disorders and diseases such as cancer, affecting gene alterations.
• Understanding the types, frequency, and impact of mutations is essential to understand evolution.

Why Compare Sequences

• Sequencing genomes produces massive data about new proteins, however determining their function is difficult.
• Sequence similarity helps extrapolate the function of one sequence to another.

Computational Methods in Sequence Comparison

• Graphical methods, like dotplots, aid in visual/qualitative comparisons of sequences.
• Sequence alignment determines residue-residue comparisons, recognizing conservation and variability patterns within and between identified genes or proteins.
• Database searches identify homologs of query genes/proteins.

Computational Methods in Sequence Comparison - Knowledge-Based Prediction

• Prediction methods utilize known examples, creating empirical rules stored in motif libraries which represent relationships between sequence structure and function.
• The presence of a motif in a query sequence indicates potential function.
• Multiple alignment is helpful for identifying motifs and remote homologs of genes/proteins.

Dot Plots – Graphical Comparison of Sequences

• Dot plots visually represent similarity regions in sequences, either within a sequence or between two.
• They identify regions of similarity, overlaps, rearrangements, repeats, and regions that are self-complementary.

Dot Plots – Application Examples

• Dotplot analysis of amino acid sequences aids comparison of phage λ cI and phage P22 c2 repressors.
• Dotplots comparing DNA sequences highlight similarity in C-terminal domains, showing relationship between different species.

Dot Plots – Enhancements

• Improving dotplot detection of matching regions can be achieved by filtering random matches using a sliding window analysis.
• This contrasts comparing each individual base, by instead comparing adjacent positions in the sequences only if a minimum number of matches are found.
• Window size and stringency affect the result.

Dot Plots - Types and Extensions

• Non-stringent plots give broader similarity analysis
• Stringent plots are for highlighting high specificity matches
• These analyses include using windows in both the x and y directions of the dotplot matrix giving more significant results.
• Dotplots can be used to analyze different scenarios such as overlap regions, repeats, and insertions/deletions.

Practical Applications of Dot Plots

• Analyzing overlapping sequences within a plot can be used to predict tandem duplications.
• Dotplots can identify repeats of different lengths.
• Dots that are not in a straight line reveal that segments of the DNA have different positions or may have been duplicated and will help to understand why the sequences are not identical.

Self-Complementary Regions in RNA Sequences

• RNA secondary structure analysis starts by identifying self-complementary regions, as these represent sections that might form RNA double strands.
• Regions are identified so a minimum free-energy structure can be predicted.
• A basic dotplot analysis is the simplest way to identify stretches of self-complementary regions in an RNA sequence.
• Two main approaches are available and analysis starts by listing the RNA sequence along the horizontal axis, and its complementary sequence along the vertical axis for scoring.

Self-Complementary Regions in RNA Sequences Analysis Methods

• Method 1: The sequence is listed in 5' to 3' on the horizontal axis and its complementary sequence in 5' to 3' is listed on the vertical axis. A matrix is used to score for identities and self-complementary regions appear as rows of dots from upper left to lower right in the matrix.
• Method 2: Is the complementary bases G/C, and A/U rather than identifies are scored instead. Self-complementary regions appear as diagonals from upper right to lower left in the matrix. A complementary energy matrix can be produced using these methods that helps in secondary structure prediction.

Dot Matrix Analysis of Potato Spindle Tuber Viroid

• Dot matrix analysis for potato spindle tuber viroid allows visualization and understanding of RNA secondary structure and its characteristics. The analysis can be used to find important aspects like repeated regions and segments.

Tools for Dot Plots

• Software like Dotter, Dottup (part of EMBOSS), and Compare & dotplot (part of GCG package) are used for creating dotplots.
• The EMBOSS suite provides these tools.
• Software is needed for visualizing results from dotplot analysis.

Summarizing Dot Plots

• Dot plots are useful in analyzing diagonal segments to find conserved/less-conserved parts of homologous proteins, domain homologies, overlapping sequences (e.g., in sequence assembly), internal repeats/duplications, insertions/deletions, and self-complementary regions (used in RNA secondary structure analysis).