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Conserved sequence

From Wikipedia, the free encyclopedia
Comparesequence motifsandprotein domains.
A multiplesequence alignmentof five mammalianhistone H1proteins
Sequences are theamino acidsfor residues 120-180 of the proteins. Residues that are conserved across all sequences are highlighted in grey. Below each site (i.e., position) of the protein sequence alignment is a key denoting conserved sites (*), sites withconservative replacements(:), sites with semi-conservative replacements (.), and sites withnon-conservative replacements( ).[1]

Inevolutionary biology,conserved sequencesare identical or similarsequencesinnucleic acids(DNAandRNA) orproteinsacross species (orthologous sequences), or within agenome(paralogous sequences), or between donor and receptor taxa (xenologous sequences). Conservation indicates that a sequence has been maintained bynatural selection.

A highly conserved sequence is one that has remained relatively unchanged far back up thephylogenetic tree,and hence far back ingeological time.Examples of highly conserved sequences include theRNA componentsofribosomespresent in alldomainsof life, thehomeoboxsequences widespread amongsteukaryotes,and thetmRNAinbacteria.The study of sequence conservation overlaps with the fields ofgenomics,proteomics,evolutionary biology,phylogenetics,bioinformaticsandmathematics.

History[edit]

See also:History of molecular evolution

The discovery of the role ofDNAinheredity,and observations byFrederick Sangerof variation between animalinsulinsin 1949,[2]prompted early molecular biologists to studytaxonomyfrom a molecular perspective.[3][4]Studies in the 1960s usedDNA hybridizationand protein cross-reactivity techniques to measure similarity between knownorthologousproteins, such ashemoglobin[5]andcytochrome c.[6]In 1965,Émile ZuckerkandlandLinus Paulingintroduced the concept of themolecular clock,[7]proposing that steady rates of amino acid replacement could be used to estimate the time since two organismsdiverged.While initial phylogenies closely matched thefossil record,observations that some genes appeared to evolve at different rates led to the development of theories ofmolecular evolution.[3][4]Margaret Dayhoff's1966 comparison offerredoxinsequences showed thatnatural selectionwould act to conserve and optimise protein sequences essential to life.[8]

Mechanisms[edit]

See also:Natural selectionandNeutral theory of molecular evolution

Over many generations, nucleic acid sequences in thegenomeof anevolutionary lineagecan gradually change over time due to random mutations anddeletions.[9][10]Sequences may also recombine or be deleted due tochromosomal rearrangements.Conserved sequences are sequences which persist in the genome despite such forces, and have slower rates of mutation than the background mutation rate.[11]

Conservation can occur incodingandnon-codingnucleic acid sequences. Highly conserved DNA sequences are thought to have functional value, although the role for many highly conservednon-coding DNAsequences is poorly understood.[12][13]The extent to which a sequence is conserved can be affected by varyingselection pressures,itsrobustnessto mutation,population sizeandgenetic drift.Many functional sequences are alsomodular,containing regions which may be subject to independentselection pressures,such asprotein domains.[14]

Coding sequence[edit]

In coding sequences, the nucleic acid and amino acid sequence may be conserved to different extents, as the degeneracy of thegenetic codemeans thatsynonymous mutationsin a coding sequence do not affect the amino acid sequence of its protein product.[15]

Amino acid sequences can be conserved to maintain thestructureor function of a protein or domain. Conserved proteins undergo feweramino acid replacements,or are more likely tosubstitute amino acids with similar biochemical properties.[16]Within a sequence, amino acids that are important forfolding,structural stability, or that form abinding sitemay be more highly conserved.[17][18]

The nucleic acid sequence of a protein coding gene may also be conserved by other selective pressures. Thecodon usage biasin some organisms may restrict the types of synonymous mutations in a sequence. Nucleic acid sequences that causesecondary structurein the mRNA of a coding gene may be selected against, as some structures may negatively affect translation, or conserved where the mRNA also acts as a functional non-coding RNA.[19][20]

Non-coding[edit]

See also:Conserved non-coding sequence

Non-coding sequences important forgene regulation,such as the binding or recognition sites ofribosomesandtranscription factors,may be conserved within a genome. For example, thepromoterof a conserved gene oroperonmay also be conserved. As with proteins, nucleic acids that are important for the structure and function ofnon-coding RNA(ncRNA) can also be conserved. However, sequence conservation in ncRNAs is generally poor compared to protein-coding sequences, andbase pairsthat contribute to structure or function are often conserved instead.[21][22]

Identification[edit]

See also:Sequence alignment

Conserved sequences are typically identified bybioinformaticsapproaches based onsequence alignment.Advances inhigh-throughput DNA sequencingandprotein mass spectrometryhas substantially increased the availability of protein sequences and whole genomes for comparison since the early 2000s.[23][24]

Homology search[edit]

Conserved sequences may be identified byhomologysearch, using tools such asBLAST,HMMER,OrthologR,[25]and Infernal.[26]Homology search tools may take an individual nucleic acid or protein sequence as input, or use statistical models generated frommultiple sequence alignmentsof known related sequences. Statistical models such asprofile-HMMs,and RNA covariance models which also incorporate structural information,[27]can be helpful when searching for more distantly related sequences. Input sequences are then aligned against a database of sequences from related individuals or other species. The resulting alignments are then scored based on the number of matching amino acids or bases, and the number of gaps or deletions generated by the alignment. Acceptable conservative substitutions may be identified using substitution matrices such asPAMandBLOSUM.Highly scoring alignments are assumed to be from homologous sequences. The conservation of a sequence may then be inferred by detection of highly similar homologs over a broad phylogenetic range.[28]

Multiple sequence alignment[edit]

A sequence logo for the LexA-binding motif ofgram-positivebacteria. As theadenosineat position 5 is highly conserved, it appears larger than other characters.[29]

Multiple sequence alignments can be used to visualise conserved sequences. TheCLUSTALformat includes a plain-text key to annotate conserved columns of the alignment, denoting conserved sequence (*), conservative mutations (:), semi-conservative mutations (.), and non-conservative mutations ( )[30]Sequence logos can also show conserved sequence by representing the proportions of characters at each point in the alignment by height.[29]

Genome alignment[edit]

This image from the ECR browser[31]shows the result of aligning different vertebrate genomes to the human genome at the conservedOTX2gene. Top: Gene annotations ofexonsandintronsof the OTX2 gene. For each genome, sequence similarity (%) compared to the human genome is plotted. Tracks show thezebrafish,dog,chicken,western clawed frog,opossum,mouse,rhesus macaqueandchimpanzeegenomes. The peaks show regions of high sequence similarity across all genomes, showing that this sequence is highly conserved.

Whole genome alignments (WGAs) may also be used to identify highly conserved regions across species. Currently the accuracy andscalabilityof WGA tools remains limited due to the computational complexity of dealing with rearrangements, repeat regions and the large size of many eukaryotic genomes.[32]However, WGAs of 30 or more closely related bacteria (prokaryotes) are now increasingly feasible.[33][34]

Scoring systems[edit]

Other approaches use measurements of conservation based onstatistical teststhat attempt to identify sequences which mutate differently to an expected background (neutral) mutation rate.

The GERP (Genomic Evolutionary Rate Profiling) framework scores conservation of genetic sequences across species. This approach estimates the rate of neutral mutation in a set of species from a multiple sequence alignment, and then identifies regions of the sequence that exhibit fewer mutations than expected. These regions are then assigned scores based on the difference between the observed mutation rate and expected background mutation rate. A high GERP score then indicates a highly conserved sequence.[35][36]

LIST[37] [38](Local Identity and Shared Taxa) is based on the assumption that variations observed in species closely related to human are more significant when assessing conservation compared to those in distantly related species. Thus, LIST utilizes the local alignment identity around each position to identify relevant sequences in the multiple sequence alignment (MSA) and then it estimates conservation based on the taxonomy distances of these sequences to human. Unlike other tools, LIST ignores the count/frequency of variations in the MSA.

Aminode[39]combines multiple alignments with phylogenetic analysis to analyze changes in homologous proteins and produce a plot that indicates the local rates of evolutionary changes. This approach identifies the Evolutionarily Constrained Regions in a protein, which are segments that are subject topurifying selectionand are typically critical for normal protein function.

Other approaches such as PhyloP and PhyloHMM incorporatestatistical phylogeneticsmethods to compareprobability distributionsof substitution rates, which allows the detection of both conservation and accelerated mutation. First, a background probability distribution is generated of the number of substitutions expected to occur for a column in a multiple sequence alignment, based on aphylogenetic tree.The estimated evolutionary relationships between the species of interest are used to calculate the significance of any substitutions (i.e. a substitution between two closely related species may be less likely to occur than distantly related ones, and therefore more significant). To detect conservation, a probability distribution is calculated for a subset of the multiple sequence alignment, and compared to the background distribution using a statistical test such as alikelihood-ratio testorscore test.P-valuesgenerated from comparing the two distributions are then used to identify conserved regions. PhyloHMM useshidden Markov modelsto generate probability distributions. The PhyloP software package compares probability distributions using alikelihood-ratio testorscore test,as well as using a GERP-like scoring system.[40][41][42]

Extreme conservation[edit]

Ultra-conserved elements[edit]

Ultra-conserved elementsor UCEs are sequences that are highly similar or identical across multipletaxonomic groupings.These were first discovered invertebrates,[43]and have subsequently been identified within widely-differing taxa.[44]While the origin and function of UCEs are poorly understood,[45]they have been used to investigate deep-time divergences inamniotes,[46]insects,[47]and betweenanimalsandplants.[48]

Universally conserved genes[edit]

The most highly conserved genes are those that can be found in all organisms. These consist mainly of thencRNAsand proteins required fortranscriptionandtranslation,which are assumed to have been conserved from thelast universal common ancestorof all life.[49]

Genes or gene families that have been found to be universally conserved includeGTP-binding elongation factors,Methionine aminopeptidase 2,Serine hydroxymethyltransferase,andATP transporters.[50]Components of the transcription machinery, such asRNA polymeraseandhelicases,and of the translation machinery, such asribosomal RNAs,tRNAsandribosomal proteinsare also universally conserved.[51]

Applications[edit]

Phylogenetics and taxonomy[edit]

Sets of conserved sequences are often used for generatingphylogenetic trees,as it can be assumed that organisms with similar sequences are closely related.[52]The choice of sequences may vary depending on the taxonomic scope of the study. For example, the most highly conserved genes such as the 16S RNA and other ribosomal sequences are useful for reconstructing deep phylogenetic relationships and identifying bacterialphylainmetagenomicsstudies.[53][54]Sequences that are conserved within acladebut undergo some mutations, such ashousekeeping genes,can be used to study species relationships.[55][56][57]Theinternal transcribed spacer(ITS) region, which is required for spacing conserved rRNA genes but undergoes rapid evolution, is commonly used to classifyfungiand strains of rapidly evolving bacteria.[58][59][60][61]

Medical research[edit]

As highly conserved sequences often have important biological functions, they can be useful a starting point for identifying the cause ofgenetic diseases.Manycongenital metabolic disordersandLysosomal storage diseasesare the result of changes to individual conserved genes, resulting in missing or faulty enzymes that are the underlying cause of the symptoms of the disease. Genetic diseases may be predicted by identifying sequences that are conserved between humans and lab organisms such asmice[62]orfruit flies,[63]and studying the effects ofknock-outsof these genes.[64]Genome-wide association studiescan also be used to identify variation in conserved sequences associated with disease or health outcomes. More than two dozen novel potential susceptibility loci have been discovered for Alzehimer's disease.[65][66]

Functional annotation[edit]

Identifying conserved sequences can be used to discover and predict functional sequences such as genes.[67]Conserved sequences with a known function, such as protein domains, can also be used to predict the function of a sequence. Databases of conserved protein domains such asPfamand theConserved Domain Databasecan be used to annotate functional domains in predicted protein coding genes.[68]

See also[edit]

References[edit]

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