coRdon: an R package for codon usage analysis and prediction of gene expressivity

master's thesis

• Title (croatian): Razvoj paketa coRdon u programskom jeziku R za analizu korištenja sinonimnih kodona i predviđanje ekspresije gena
• Author: Anamaria Elek
• Mentor: Kristian Vlahoviček (mentor)
• Committee member: Kristian Vlahoviček (predsjednik povjerenstva)
• Committee member: Damjan Franjević (član povjerenstva)
• Committee member: Sven Jelaska (član povjerenstva)
• Committee member: Rosa Karlić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Biology); Zagreb
• Defense date and country: 2018-09-13, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Biology

Abstract

Not all synonymous codons are used with equal frequency in prokaryotic genomes - this
selective preference is termed codon usage (CU) bias and is an independent determinant of gene
expression regulation at the level of translation. The synonymous codons corresponding to the
most abundant cognate tRNA are considered optimal for translation. Codon usage bias can
therefore be used to predict the relative expression levels of genes, by comparing CU bias of a
specific gene to the CU bias of a set of genes known to be highly expressed. This approach can
be efficiently used to predict highly expressed genes within a single genome but has also been
demonstrated relevant at the level of entire microbial communities – metagenomes. This is
possible because CU bias is shared among the microbial species in the same environment. By
analysing CU bias of a metagenome, one can identify genes with high predicted expression
across the given ecological niche, and identify enriched functions, i.e. the functional fingerprint
of the analysed microbial community. Software tools to efficiently analyse and visualize
metagenomics data in the context of translational optimisation and CU bias are scarce and this
limits the ability to generate useful knowledge. As the part of this thesis, I have developed a
Bioconductor-based R package for comprehensive analysis of CU and CU-based gene
expressivity. The package also includes several methods for visualization of CU, and the CUbased functional analysis of annotated DNA sequences. The package is fast and flexible enough
to handle even the largest metagenomics datasets.

Abstract (english)

U genomima različitih prokariota svi sinonimni kodoni ne koriste se jednakom učestalošću -
njihovo selektivno korištenje zaseban je mehanizam regulacije ekspresije gena na razini
translacije. Sinonimni kodoni koje prepoznaju najbrojnije tRNA molekule u stanici smatraju se
optimiziranima za translaciju. Stoga se selektivno korištenje sinonimnih kodona može koristiti
za predviđanje relativne ekspresivnosti gena, uspoređujući obrazac korištenja kodona u
određenom genu s kodonima koji se učestalo pojavljuju u skupu visoko eksprimiranih gena. Na
ovaj način moguće je identificirati potencijalno jako eksprimirane gene na razini genoma, ali
još važnije, i na razini čitavih metagenoma, jer je pokazano da je uzorak selektivnog korištenja
kodona zajednički organizmima unutar iste mikrobne zajednice, bez obzira na njihovu
filogenetsku udaljenost. Stoga je analizirajući korištenje kodona na razini metagenoma moguće
predvidjeti koji geni su relativno visoko eksprimirani u određenoj mikrobnoj zajednici, kao i
koje funkcije su zastupljene među tim genima - tzv. funkcijski otisak mikrobne zajednice. U
sklopu ovog rada razvila sam paket u programskom jeziku R, baziran na sintaksi i smjernicama
projekta Bioconductor, za kompletnu analizu korištenja sinonimnih kodona i ekspresivnosti
gena. Uz to što omogućava računanje više različitih statistika koje kvantificiraju korištenje
sinonimnih kodona, paket uključuje i nekoliko metoda za vizualizaciju korištenja sinonimnih
kodona, omogućava funkcionalnu analizu anotiranih slijedova DNA te je dovoljno brz i
fleksibilan za analizu velikih količina metagenomskih podataka.

• Keywords: translational optimization; functional analysis; metagenomics
• Keywords (croatian): translacijska optimizacija; funkcijska analiza; metagenomika
• Language: english
• URN:NBN: urn:nbn:hr:217:686131
• Study programme: Title: Molecular Biology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra molekularne biologije (magistar/magistra molekularne biologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2018-09-28 09:48:18