Bioinformatics: Genomics and Sequence Data

• Bioinformatics' core goal is to impart biological relevance to sequence data.

Bioinformatics Origins and Definition

• Bioinformatics is derived from "Bio," signifying biology, and "Informatique," the French term for "data processing."
• Bioinformatics involves using computers to gather, analyze, and store biological information.

The Genomics Revolution

• DNA consists of adenine (A), guanine (G), cytosine (C), and thymine (T).
• A genome encompasses all of the genetic material found within an organism's chromosomes.
• Genomics involves scrutinizing genes and their roles.

The Human Genome Project (HGP)

• The HGP aimed to determine the complete sequence of approximately 3 billion base pairs (bp).
• The HGP sought to pinpoint all genes (roughly 20,000 to 25,000).
• The HGP aimed to store the information and create accessibility for study, and was completed in 2003.

Potential Benefits of Genomic Sequencing

• Molecular medicine could benefit from identifying genes tied to genetic disorders like Alzheimer's and certain cancers.
• Rapid and specific diagnostic tests can be developed.
• Gene therapy is a possibility to treat defective genes.
• DNA analysis of a 5,300-year-old corpse discovered in 1991 had its genome sequenced and published in 2012.
• Examination of the iceman revealed he likely had brown eyes, was blood group O, and was lactose intolerant.
• DNA profiling advancements enable suspect identification from crime scene DNA, exoneration of the wrongly accused, identifying victims of war and catastrophes, establishing paternity, and matching organ donors with recipients.

Bioinformatics is essential for managing large datasets

• There are over 36,000 completed genomes, with thousands more in progress thanks to bioinformatics support.
• Bioinformatics facilitates storage analysis, and comparison of the datasets.
• The human genome, comprising 3 billion bp, can be processed because of bioinformatics.
• The human genome could fill 200 telephone books and would take 9.5 years to read aloud.

Bioinformatics Applications

• Bioinformatics can provide answers more quickly
• Bioinformatics uses in silico analysis faster than in vitro methods.
• Results generated in silico still require validation in the lab.

Bioinformatics Sequence Assembly

• DNA sequencers produce overlapping sequences of about 500bp.
• Sequence fragments must be assembled correctly along the chromosome.
• Sequence assembly leads to a consensus DNA sequence.
• During the HGP, bioinformatics tools assembled hundreds of thousands of overlapping sequence fragments.

Bioinformatics and Gene Finding

• Less than 2% of the human genome codes for proteins.
• Gene prediction tools search for sequence features that appear at particular sites within eukaryotic genes to complete specific roles during transcription and translation.

Eukaryotic Genes

• Eukaryotic gene structures have TATA boxes that occur 30 bp upstream from the start site
• Translation start sites (ATG encodes the first Methionine)
• The Eukaryotic gene structures have Intron/Exon splice sites (GT....AG)
• Termination codon (TGA, TAA or TAG).

Protein Sequence Translation

• The initial step is to translate DNA into a theoretical protein sequence.
• Then to locate the open reading frame (ORF), beginning with the start codon (ATG).

Protein Sequence Analysis

• Translated protein sequences aid in spotting similar sequences with known functions.
• Protein domains tend to remain conserved during evolution.
• Proteins sharing sequence similarities across species likely share similar functions.
• An ongoing bioinformatics challenge is assigning protein function.

Genome Annotation

• Genome Annotation involves adding biological information to sequences, which serves as a valuable reference for scientists studying gene function.
• Protein annotation includes location of ORFs, gene structure, regulatory elements, biochemical function, conserved domains, and protein interactions.

Data Storage and Databases

• Scientists generate significant quantities of data.
• Multiple kinds of data should be stored including various species, gene names and locations, mutation phenotypes, protein structures and functions, protein domains and interactions.

Data Handling

• Sequence databases require consistency in the way data is entered
• W.R. Pearson introduced the FAST Alignment (FASTA) format in 1985.
• The FASTA format is widely used for reading and reporting sequence data.
• In FASTA format, lines begins with > followed by a return.

FASTA Format Explained

• gi|386828 represents the geninfo number, assigned by the NCBI to each sequence entry.
• gb|AAA59172.1 reveals that GenBank was the source database.
• gb|AAA59172.1 shows database accession number AAA59172.1.

Sequence resources

• GenBank is a major archive of nucleic acid sequences maintained by the US National Center for Biotechnology Information (NCBI).
• Over 135 million sequences have been deposited into GenBank.
• Each sequence entry in GenBank represents a unique entry.
• Accession numbers are unique identifiers for a single sequence.
• Accession numbers serve as the best method for finding specific entries in sequence databases.
• UniProt is a major archive of protein sequences largely derived from translated gene sequences.
• NCBI hosts an interconnected database system including journal articles (PubMed), genetic diseases (OMIM), polymorphisms (SNP), and gene expression (GEO).

NCBI Entrez

• NCBI offers ENTREZ for parallel searches through multiple data archives.

Database Searching

• Most search engines offer a simple web query, but advanced search using Boolean operators (“AND” / “OR”) are also available for a complex option.