Important questions

• Documentation: comparative genomics for documenting different species.

• Use: identifying natural products with medical relevance.

• Protection: identifying resistance genes in beech trees.

• An organism/tissue can be examined under different experimental conditions, e.g. which gene is upregulated or downregulated.

• A complete genome, including regulatory regions and introns, is not important if you are only interested in genes/proteins.

• Reference-based approach.

• De novo approach.

• The k-mer size should not be too small so that parts of the sequence that occur more frequently can be distinguished from each other.

• For repetitive patterns, should be larger than the repetitive pattern.

• Ideally choose so that each k-mer occurs only once.

• gives the maximum possible overlap of the k-mers, which increases specificity.

• If , the contig could not be extended and would consist only of k-mers.

• If , errors can occur.

• FASTQ: sequence plus quality values.

• FASTA: sequence only, as a file format.

• Collect and select individual pieces of information.

• Combine and integrate information into a database.

• Present the information, e.g. through a GUI/API.

The database may be incomplete.

• Protein databases: linear growth, limited by laboratory work.

• Sequence databases: exponential growth, because technology becomes better and faster.

RefSeq and GenBank

• Intrinsic = information that can be extracted from the sequence itself.

• Extrinsic = information obtained by comparison with other sequences/models.

• Position-specific scoring matrices used to identify motifs in biological sequences (DNA, RNA, protein).

1. Training data.

2. Create a count matrix.

3. Add pseudocounts.

4. Calculate the Kullback-Leibler distance for each position.

5. The sum of the Kullback-Leibler distances for each position gives the PSSM score for the sequence.

6. Difference between a scoring matrix (BLOSUM62) and a PSSM.

• BLOSUM62 is position-independent: the score for substituting G with A is the same at every position.

• PSSM is position-specific: the score for substituting G with A depends on the position.

Cellular Component, Molecular Function, Biological Process.

• Assign GO terms to genes for functional annotation.

• Standardized terminology makes categorization possible.

• Each gene is described with specific GO terms; the path to get there stays the same, so less data has to be stored.

• HMMs can find motifs even when the length changes due to insertions/deletions, and motifs can be used to assign function to sequences.

• PSSMs are position-specific but only work with fixed length; insertions/deletions strongly change scores. PSSMs can still recognize motifs and assign function.

• BLOSUM62 is position-independent and gives no information about function.

• KEGG shows the organization of genes in different metabolic pathways.

• KEGG assigns each gene a KO term that functionally describes it.

• The database contains orthologs with experimentally characterized genes/proteins.

• KEGG Mapper creates metabolic pathways as a network of KO terms.

• Homology refers only to evolutionary relationships.

• Sequence similarity is not part of the concept of homology; it measures how much two sequences match.

• Sequences that are more similar than expected by chance are evolutionarily related, i.e. homologous.

• Experimental annotation.

• Electronic annotation, most common.

• Curated non-experimental annotation.

• Describing gene function.

• Restricted vocabulary.

• Hierarchical organization.

• Directed acyclic graph.

• 3 sub-ontologies.

• Evidence codes.

• Orthologs are homologous sequences that were separated by a speciation event.

1. Speciation event: reproductive isolation of two populations leads to separation of genetic lineages.

2. Isolated evolution of the sequences.

3. The resulting sequences are called orthologs.

• In reference-based assembly, a sufficiently well-annotated genome of the organism already exists. The reads can then simply be mapped to it. It is like a puzzle with the solution picture already available.

• De novo assembly joins overlapping sequence reads with sufficient similarity into longer sequences, also called contigs. The contigs reconstruct the original transcript. De novo assembly is a puzzle without a template.

• If a genome is available, reference-based assembly is always the better and easier approach. For transcript analysis, for example, different isoforms can be compared more easily with the reference-based approach. Split reads and exon-intron boundaries can also be identified, as well as which introns were spliced out. It can also reveal which transcripts are completely missing from the dataset.

• Which assembly approach do you use? Reference-based approach.

• What do you need for this? A reference genome.

• PacBio and Nanopore have the “problem” that only about 85% of reads are correct, so around 15% contain errors.

• PacBio reads often show insertions.

• Nanopore sequencing often shows deletions, especially when the same nucleotide repeats several times.

• Illumina sequencing is about 99% correct but can only generate short reads.

• Therefore Nanopore and Illumina are combined, and the sequences are compared. Nanopore provides long reads that are corrected by short Illumina reads.

• Many sequences can be sequenced in parallel.

• It is automatable.

• Read accuracy is high, about 99.3% per read.

• Many sequences can be sequenced in parallel.

• It is automatable.

• Read accuracy is high, about 99.3% per read.

• Only short reads can be generated.

• Sequencing quality decreases toward the end of the read.

• A cluster consists of many copies of a sequence. When sequencing starts, nucleotides are incorporated.

• It can happen that not all DNA polymerases in the cluster incorporate a nucleotide, even though they should have.

• As a result, these sequences are no longer synchronized with the cluster.

• Over the course of sequencing, these errors accumulate, so by the end of 125 sequenced bases the signal is no longer as good as at the beginning.

• An isoform arises in eukaryotes through alternative splicing, meaning it is a possible transcript of a gene.

• Multiple proteins can arise from one transcript.