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Conserved sequence

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</style><div role="note" class="hatnote navigation-not-searchable">Compare <a href="Sequence_motif" title="Sequence motif">sequence motifs</a> and <a href="Protein_domain" title="Protein domain">protein domains</a>.</div>

In <a href="Evolutionary_biology" title="Evolutionary biology">evolutionary biology</a>, conserved sequences are identical or similar <a href="Sequence_(biology)" title="Sequence (biology)">sequences</a> in <a href="Nucleic_acid" title="Nucleic acid">nucleic acids</a> (<a href="DNA_sequence" class="mw-redirect" title="DNA sequence">DNA</a> and <a href="RNA" title="RNA">RNA</a>) or <a href="Peptide_sequence" class="mw-redirect" title="Peptide sequence">proteins</a> across species (<a href="Homology_(biology)#Orthology" title="Homology (biology)">orthologous sequences</a>), or within a <a href="Genome" title="Genome">genome</a> (<a href="Homology_(biology)#Paralogy" title="Homology (biology)">paralogous sequences</a>), or between donor and receptor taxa (<a href="Sequence_homology#Xenology" title="Sequence homology">xenologous sequences</a>). Conservation indicates that a sequence has been maintained by <a href="Natural_selection" title="Natural selection">natural selection</a>.

A highly conserved sequence is one that has remained relatively unchanged far back up the <a href="Phylogenetic_tree" title="Phylogenetic tree">phylogenetic tree</a>, and hence far back in <a href="Geological_time" class="mw-redirect" title="Geological time">geological time</a>. Examples of highly conserved sequences include the <a href="Ribosomal_RNA" title="Ribosomal RNA">RNA components</a> of <a href="Ribosome" title="Ribosome">ribosomes</a> present in all <a href="Domain_(biology)" title="Domain (biology)">domains</a> of life, the <a href="Homeobox" title="Homeobox">homeobox</a> sequences widespread amongst <a href="Eukaryotes" class="mw-redirect" title="Eukaryotes">eukaryotes</a>, and the <a href="TmRNA" class="mw-redirect" title="TmRNA">tmRNA</a> in <a href="Bacteria" title="Bacteria">bacteria</a>. The study of sequence conservation overlaps with the fields of <a href="Genomics" title="Genomics">genomics</a>, <a href="Proteomics" title="Proteomics">proteomics</a>, <a href="Evolutionary_biology" title="Evolutionary biology">evolutionary biology</a>, <a href="Phylogenetics" title="Phylogenetics">phylogenetics</a>, <a href="Bioinformatics" title="Bioinformatics">bioinformatics</a> and <a href="Mathematics" title="Mathematics">mathematics</a>.

<div class="mw-heading mw-heading2"><h2 id="History">History</h2></div>

<div role="note" class="hatnote navigation-not-searchable">See also: <a href="History_of_molecular_evolution" title="History of molecular evolution">History of molecular evolution</a></div>

The discovery of the role of <a href="DNA#History" title="DNA">DNA</a> in <a href="Heredity" title="Heredity">heredity</a>, and observations by <a href="Frederick_Sanger" title="Frederick Sanger">Frederick Sanger</a> of variation between animal <a href="Insulin" title="Insulin">insulins</a> in 1949,<a href="#cite_note-2">[2]</a> prompted early molecular biologists to study <a href="Taxonomy_(biology)" title="Taxonomy (biology)">taxonomy</a> from a molecular perspective.<a href="#cite_note-ReferenceA-3">[3]</a><a href="#cite_note-ReferenceB-4">[4]</a> Studies in the 1960s used <a href="DNA%E2%80%93DNA_hybridization" title="DNA–DNA hybridization">DNA hybridization</a> and protein cross-reactivity techniques to measure similarity between known <a href="Orthologous" class="mw-redirect" title="Orthologous">orthologous</a> proteins, such as <a href="Hemoglobin" title="Hemoglobin">hemoglobin</a><a href="#cite_note-5">[5]</a> and <a href="Cytochrome_c" title="Cytochrome c">cytochrome c</a>.<a href="#cite_note-6">[6]</a> In 1965, <a href="Emile_Zuckerkandl" title="Emile Zuckerkandl">Émile Zuckerkandl</a> and <a href="Linus_Pauling" title="Linus Pauling">Linus Pauling</a> introduced the concept of the <a href="Molecular_clock" title="Molecular clock">molecular clock</a>,<a href="#cite_note-7">[7]</a> proposing that steady rates of amino acid replacement could be used to estimate the time since two organisms <a href="Divergent_evolution" title="Divergent evolution">diverged</a>. While initial phylogenies closely matched the <a href="Fossil_record" class="mw-redirect" title="Fossil record">fossil record</a>, observations that some genes appeared to evolve at different rates led to the development of theories of <a href="Molecular_evolution" title="Molecular evolution">molecular evolution</a>.<a href="#cite_note-ReferenceA-3">[3]</a><a href="#cite_note-ReferenceB-4">[4]</a> <a href="Margaret_Oakley_Dayhoff" title="Margaret Oakley Dayhoff">Margaret Dayhoff's</a> 1966 comparison of <a href="Ferredoxin" title="Ferredoxin">ferredoxin</a> sequences showed that <a href="Natural_selection" title="Natural selection">natural selection</a> would act to conserve and optimise protein sequences essential to life.<a href="#cite_note-8">[8]</a>

<div class="mw-heading mw-heading2"><h2 id="Mechanisms">Mechanisms</h2></div>

<div role="note" class="hatnote navigation-not-searchable">See also: <a href="Natural_selection" title="Natural selection">Natural selection</a> and <a href="Neutral_theory_of_molecular_evolution" title="Neutral theory of molecular evolution">Neutral theory of molecular evolution</a></div>

Over many generations, nucleic acid sequences in the <a href="Genome" title="Genome">genome</a> of an <a href="Lineage_(evolution)" title="Lineage (evolution)">evolutionary lineage</a> can gradually change over time due to random mutations and <a href="Deletion_(genetics)" title="Deletion (genetics)">deletions</a>.<a href="#cite_note-9">[9]</a><a href="#cite_note-10">[10]</a> Sequences may also recombine or be deleted due to <a href="Chromosomal_rearrangement" title="Chromosomal rearrangement">chromosomal rearrangements</a>. Conserved sequences are sequences which persist in the genome despite such forces, and have slower rates of mutation than the background mutation rate.<a href="#cite_note-11">[11]</a>

Conservation can occur in <a href="Coding_region" title="Coding region">coding</a> and <a href="Noncoding_DNA" class="mw-redirect" title="Noncoding DNA">non-coding</a> nucleic acid sequences. Highly conserved DNA sequences are thought to have functional value, although the role for many highly conserved <a href="Non-coding_DNA" title="Non-coding DNA">non-coding DNA</a> sequences is poorly understood.<a href="#cite_note-12">[12]</a><a href="#cite_note-13">[13]</a> The extent to which a sequence is conserved can be affected by varying <a href="Evolutionary_pressure" title="Evolutionary pressure">selection pressures</a>, its <a href="Robustness_(evolution)" title="Robustness (evolution)">robustness</a> to mutation, <a href="Population_genetics" title="Population genetics">population size</a> and <a href="Genetic_drift" title="Genetic drift">genetic drift</a>. Many functional sequences are also <a href="Modularity_(biology)" title="Modularity (biology)">modular</a>, containing regions which may be subject to independent <a href="Evolutionary_pressure" title="Evolutionary pressure">selection pressures</a>, such as <a href="Protein_domain#Domains_as_evolutionary_modules" title="Protein domain">protein domains</a>.<a href="#cite_note-14">[14]</a>

<div class="mw-heading mw-heading3"><h3 id="Coding_sequence">Coding sequence</h3></div>

In coding sequences, the nucleic acid and amino acid sequence may be conserved to different extents, as the degeneracy of the <a href="Genetic_code" title="Genetic code">genetic code</a> means that <a href="Synonymous_substitution" title="Synonymous substitution">synonymous mutations</a> in a coding sequence do not affect the amino acid sequence of its protein product.<a href="#cite_note-15">[15]</a>

Amino acid sequences can be conserved to maintain the <a href="Protein_structure" title="Protein structure">structure</a> or function of a protein or domain. Conserved proteins undergo fewer <a href="Amino_acid_replacement" title="Amino acid replacement">amino acid replacements</a>, or are more likely to <a href="Conservative_mutation" class="mw-redirect" title="Conservative mutation">substitute amino acids with similar biochemical properties</a>.<a href="#cite_note-16">[16]</a> Within a sequence, amino acids that are important for <a href="Protein_folding" title="Protein folding">folding</a>, structural stability, or that form a <a href="Binding_site" title="Binding site">binding site</a> may be more highly conserved.<a href="#cite_note-17">[17]</a><a href="#cite_note-18">[18]</a>

The nucleic acid sequence of a protein coding gene may also be conserved by other selective pressures. The <a href="Codon_usage_bias" title="Codon usage bias">codon usage bias</a> in some organisms may restrict the types of synonymous mutations in a sequence. Nucleic acid sequences that cause <a href="Nucleic_acid_secondary_structure" title="Nucleic acid secondary structure">secondary structure</a> in 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.<a href="#cite_note-19">[19]</a><a href="#cite_note-20">[20]</a>

<div class="mw-heading mw-heading3"><h3 id="Non-coding">Non-coding</h3></div>

<div role="note" class="hatnote navigation-not-searchable">See also: <a href="Conserved_non-coding_sequence" title="Conserved non-coding sequence">Conserved non-coding sequence</a></div>

Non-coding sequences important for <a href="Gene_regulation" class="mw-redirect" title="Gene regulation">gene regulation</a>, such as the binding or recognition sites of <a href="Ribosome-binding_site" title="Ribosome-binding site">ribosomes</a> and <a href="Transcription_factor" title="Transcription factor">transcription factors</a>, may be conserved within a genome. For example, the <a href="Promoter_(genetics)" title="Promoter (genetics)">promoter</a> of a conserved gene or <a href="Operon" title="Operon">operon</a> may also be conserved. As with proteins, nucleic acids that are important for the structure and function of <a href="Non-coding_RNA" title="Non-coding RNA">non-coding RNA</a> (ncRNA) can also be conserved. However, sequence conservation in ncRNAs is generally poor compared to protein-coding sequences, and <a href="Base_pairs" class="mw-redirect" title="Base pairs">base pairs</a> that contribute to structure or function are often conserved instead.<a href="#cite_note-21">[21]</a><a href="#cite_note-22">[22]</a>

<div class="mw-heading mw-heading2"><h2 id="Identification">Identification</h2></div>

<div role="note" class="hatnote navigation-not-searchable">See also: <a href="Sequence_alignment" title="Sequence alignment">Sequence alignment</a></div>

Conserved sequences are typically identified by <a href="Bioinformatics" title="Bioinformatics">bioinformatics</a> approaches based on <a href="Sequence_alignment" title="Sequence alignment">sequence alignment</a>. Advances in <a href="DNA_sequencing#High-throughput_methods" title="DNA sequencing">high-throughput DNA sequencing</a> and <a href="Protein_mass_spectrometry" title="Protein mass spectrometry">protein mass spectrometry</a> has substantially increased the availability of protein sequences and whole genomes for comparison since the early 2000s.<a href="#cite_note-23">[23]</a><a href="#cite_note-24">[24]</a>

<div class="mw-heading mw-heading3"><h3 id="Homology_search">Homology search</h3></div>

Conserved sequences may be identified by <a href="Homology_(biology)" title="Homology (biology)">homology</a> search, using tools such as <a href="BLAST_(biotechnology)" title="BLAST (biotechnology)">BLAST</a>, <a href="HMMER" title="HMMER">HMMER</a>, <a rel="nofollow" class="external text" href="https://github.com/drostlab/orthologr">OrthologR</a>,<a href="#cite_note-:9-25">[25]</a> and Infernal.<a href="#cite_note-26">[26]</a> Homology search tools may take an individual nucleic acid or protein sequence as input, or use statistical models generated from <a href="Multiple_sequence_alignment" title="Multiple sequence alignment">multiple sequence alignments</a> of known related sequences. Statistical models such as <a href="Hidden_Markov_model" title="Hidden Markov model">profile-HMMs</a>, and RNA covariance models which also incorporate structural information,<a href="#cite_note-27">[27]</a> 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 as <a href="Point_accepted_mutation" title="Point accepted mutation">PAM</a> and <a href="BLOSUM" title="BLOSUM">BLOSUM</a>. 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.<a href="#cite_note-28">[28]</a>

<div class="mw-heading mw-heading3"><h3 id="Multiple_sequence_alignment">Multiple sequence alignment</h3></div>

Multiple sequence alignments can be used to visualise conserved sequences. The <a href="Clustal" title="Clustal">CLUSTAL</a> format includes a plain-text key to annotate conserved columns of the alignment, denoting conserved sequence (*), conservative mutations (:), semi-conservative mutations (.), and non-conservative mutations ( )<a href="#cite_note-30">[30]</a> Sequence logos can also show conserved sequence by representing the proportions of characters at each point in the alignment by height.<a href="#cite_note-Weblogo-29">[29]</a>

<div class="mw-heading mw-heading3"><h3 id="Genome_alignment">Genome alignment</h3></div>

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

<div class="mw-heading mw-heading3"><h3 id="Scoring_systems">Scoring systems</h3></div>

Other approaches use measurements of conservation based on <a href="Statistical_hypothesis_testing" class="mw-redirect" title="Statistical hypothesis testing">statistical tests</a> that 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.<a href="#cite_note-35">[35]</a><a href="#cite_note-36">[36]</a>

LIST<a href="#cite_note-37">[37]</a>

<a href="#cite_note-38">[38]</a> (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<a href="#cite_note-Chang2018-39">[39]</a> 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 to <a href="Negative_selection_(natural_selection)" title="Negative selection (natural selection)">purifying selection</a> and are typically critical for normal protein function.

Other approaches such as PhyloP and PhyloHMM incorporate <a href="Phylogenetic_comparative_methods" title="Phylogenetic comparative methods">statistical phylogenetics</a> methods to compare <a href="Probability_distribution" title="Probability distribution">probability distributions</a> of 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 a <a href="Phylogenetic_tree" title="Phylogenetic tree">phylogenetic tree</a>. 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 a <a href="Likelihood-ratio_test" title="Likelihood-ratio test">likelihood-ratio test</a> or <a href="Score_test" title="Score test">score test</a>. <a href="P-value" title="P-value">P-values</a> generated from comparing the two distributions are then used to identify conserved regions. PhyloHMM uses <a href="Hidden_Markov_model" title="Hidden Markov model">hidden Markov models</a> to generate probability distributions. The PhyloP software package compares probability distributions using a <a href="Likelihood-ratio_test" title="Likelihood-ratio test">likelihood-ratio test</a> or <a href="Score_test" title="Score test">score test</a>, as well as using a GERP-like scoring system.<a href="#cite_note-40">[40]</a><a href="#cite_note-41">[41]</a><a href="#cite_note-42">[42]</a>

<div class="mw-heading mw-heading2"><h2 id="Extreme_conservation">Extreme conservation</h2></div>

<div class="mw-heading mw-heading3"><h3 id="Ultra-conserved_elements">Ultra-conserved elements</h3></div>

<a href="Ultra-conserved_element" class="mw-redirect" title="Ultra-conserved element">Ultra-conserved elements</a> or UCEs are sequences that are highly similar or identical across multiple <a href="Taxonomic_rank" title="Taxonomic rank">taxonomic groupings</a>. These were first discovered in <a href="Vertebrates" class="mw-redirect" title="Vertebrates">vertebrates</a>,<a href="#cite_note-43">[43]</a> and have subsequently been identified within widely-differing taxa.<a href="#cite_note-44">[44]</a> While the origin and function of UCEs are poorly understood,<a href="#cite_note-45">[45]</a> they have been used to investigate deep-time divergences in <a href="Amniote" title="Amniote">amniotes</a>,<a href="#cite_note-46">[46]</a> <a href="Insects" class="mw-redirect" title="Insects">insects</a>,<a href="#cite_note-47">[47]</a> and between <a href="Animals" class="mw-redirect" title="Animals">animals</a> and <a href="Plants" class="mw-redirect" title="Plants">plants</a>.<a href="#cite_note-48">[48]</a>

<div class="mw-heading mw-heading3"><h3 id="Universally_conserved_genes">Universally conserved genes</h3></div>

The most highly conserved genes are those that can be found in all organisms. These consist mainly of the <a href="NcRNA" class="mw-redirect" title="NcRNA">ncRNAs</a> and proteins required for <a href="Transcription_(biology)" title="Transcription (biology)">transcription</a> and <a href="Translation_(biology)" title="Translation (biology)">translation</a>, which are assumed to have been conserved from the <a href="Last_universal_common_ancestor" title="Last universal common ancestor">last universal common ancestor</a> of all life.<a href="#cite_note-49">[49]</a>

Genes or gene families that have been found to be universally conserved include <a href="GTP-binding_elongation_factor_family%2C_EF-Tu/EF-1A_subfamily" class="mw-redirect" title="GTP-binding elongation factor family, EF-Tu/EF-1A subfamily">GTP-binding elongation factors</a>, <a href="METAP2" title="METAP2">Methionine aminopeptidase 2</a>, <a href="Serine_hydroxymethyltransferase" title="Serine hydroxymethyltransferase">Serine hydroxymethyltransferase</a>, and <a href="ATP-binding_cassette_transporter" class="mw-redirect" title="ATP-binding cassette transporter">ATP transporters</a>.<a href="#cite_note-50">[50]</a> Components of the transcription machinery, such as <a href="RNA_polymerase" title="RNA polymerase">RNA polymerase</a> and <a href="Helicase" title="Helicase">helicases</a>, and of the translation machinery, such as <a href="Ribosomal_RNA" title="Ribosomal RNA">ribosomal RNAs</a>, <a href="Transfer_RNA" title="Transfer RNA">tRNAs</a> and <a href="Ribosomal_protein" title="Ribosomal protein">ribosomal proteins</a> are also universally conserved.<a href="#cite_note-51">[51]</a>

<div class="mw-heading mw-heading2"><h2 id="Applications">Applications</h2></div>

<div class="mw-heading mw-heading3"><h3 id="Phylogenetics_and_taxonomy">Phylogenetics and taxonomy</h3></div>

Sets of conserved sequences are often used for generating <a href="Phylogenetic_tree" title="Phylogenetic tree">phylogenetic trees</a>, as it can be assumed that organisms with similar sequences are closely related.<a href="#cite_note-52">[52]</a> 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 bacterial <a href="Phylum" title="Phylum">phyla</a> in <a href="Metagenomics" title="Metagenomics">metagenomics</a> studies.<a href="#cite_note-53">[53]</a><a href="#cite_note-54">[54]</a> Sequences that are conserved within a <a href="Clade" title="Clade">clade</a> but undergo some mutations, such as <a href="Housekeeping_gene" title="Housekeeping gene">housekeeping genes</a>, can be used to study species relationships.<a href="#cite_note-55">[55]</a><a href="#cite_note-56">[56]</a><a href="#cite_note-57">[57]</a> The <a href="Internal_transcribed_spacer" title="Internal transcribed spacer">internal transcribed spacer</a> (ITS) region, which is required for spacing conserved rRNA genes but undergoes rapid evolution, is commonly used to classify <a href="Fungi" class="mw-redirect" title="Fungi">fungi</a> and strains of rapidly evolving bacteria.<a href="#cite_note-58">[58]</a><a href="#cite_note-59">[59]</a><a href="#cite_note-60">[60]</a><a href="#cite_note-61">[61]</a>

<div class="mw-heading mw-heading3"><h3 id="Medical_research">Medical research</h3></div>

As highly conserved sequences often have important biological functions, they can be useful a starting point for identifying the cause of <a href="Genetic_disease" class="mw-redirect" title="Genetic disease">genetic diseases</a>. Many <a href="Inborn_error_of_metabolism" class="mw-redirect" title="Inborn error of metabolism">congenital metabolic disorders</a> and <a href="Lysosomal_storage_disease" title="Lysosomal storage disease">Lysosomal storage diseases</a> are 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 as <a href="Laboratory_mouse" title="Laboratory mouse">mice</a><a href="#cite_note-62">[62]</a> or <a href="Drosophila_melanogaster" title="Drosophila melanogaster">fruit flies</a>,<a href="#cite_note-63">[63]</a> and studying the effects of <a href="Gene_knockout" title="Gene knockout">knock-outs</a> of these genes.<a href="#cite_note-64">[64]</a> <a href="Genome-wide_association_study" title="Genome-wide association study">Genome-wide association studies</a> can 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.<a href="#cite_note-65">[65]</a><a href="#cite_note-66">[66]</a>

<div class="mw-heading mw-heading3"><h3 id="Functional_annotation">Functional annotation</h3></div>

Identifying conserved sequences can be used to discover and predict functional sequences such as genes.<a href="#cite_note-67">[67]</a> 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 as <a href="Pfam" title="Pfam">Pfam</a> and the <a href="Conserved_Domain_Database" title="Conserved Domain Database">Conserved Domain Database</a> can be used to annotate functional domains in predicted protein coding genes.<a href="#cite_note-68">[68]</a>

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<ul><li><a href="Evolutionary_developmental_biology" title="Evolutionary developmental biology">Evolutionary developmental biology</a></li>

<li><a href="NAPP_(database)" title="NAPP (database)">NAPP (database)</a></li>

<li><a href="Segregating_site" title="Segregating site">Segregating site</a></li>

<li><a href="Sequence_alignment" title="Sequence alignment">Sequence alignment</a></li>

<li><a href="Sequence_alignment_software" class="mw-redirect" title="Sequence alignment software">Sequence alignment software</a></li>

<li><a href="UCbase" title="UCbase">UCbase</a></li>

<li><a href="Ultra-conserved_element" class="mw-redirect" title="Ultra-conserved element">Ultra-conserved element</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

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