Content deleted Content added
GreenC bot (talk | contribs) Rescued 1 archive link. Wayback Medic 2.5 per WP:URLREQ#nih.gov |
Link suggestions feature: 3 links added. |
||
Line 98:
===Non-coding multiple sequence alignment===
[[Non-coding DNA]] regions, especially [[transcription factor]] binding sites (TFBSs), are conserved, but not necessarily evolutionarily related, and may have converged from non-common ancestors. Thus, the assumptions used to align protein sequences and DNA coding regions are inherently different from those that hold for TFBS sequences. Although it is meaningful to align DNA coding regions for homologous sequences using mutation operators, alignment of binding site sequences for the same transcription factor cannot rely on evolutionary related mutation operations. Similarly, the evolutionary operator of point mutations can be used to define an edit distance for coding sequences, but this has little meaning for TFBS sequences because any sequence variation has to maintain a certain level of specificity for the binding site to function. This becomes specifically important when trying to align known TFBS sequences to build supervised models to predict unknown locations of the same TFBS. Hence, Multiple Sequence Alignment methods need to adjust the underlying evolutionary hypothesis and the operators used as in the work published incorporating neighbouring base thermodynamic information <ref name=Salama2013>{{cite journal |vauthors=Salama RA, Stekel DJ |title=A non-independent energy-based multiple sequence alignment improves prediction of transcription factor binding sites |journal=Bioinformatics |volume=29 |issue=21 |pages=2699–704 |date=November 2013 |pmid=23990411 |doi=10.1093/bioinformatics/btt463 |doi-access=free}}</ref> to align the binding sites searching for the lowest thermodynamic alignment conserving specificity of the binding site.
==Optimization==
Line 115:
The necessary use of heuristics for multiple alignment means that for an arbitrary set of proteins, there is always a good chance that an alignment will contain errors. For example, an evaluation of several leading alignment programs using the [[List of sequence alignment software#Benchmarking|BAliBase benchmark]] found that at least 24% of all pairs of aligned amino acids were incorrectly aligned.<ref name="nuin2006">{{cite journal |vauthors=Nuin PA, Wang Z, Tillier ER |year=2006 |title=The accuracy of several multiple sequence alignment programs for proteins |journal=BMC Bioinformatics |doi=10.1186/1471-2105-7-471 |pmid=17062146 |volume=7 |pmc=1633746 |pages=471 |doi-access=free}}</ref> These errors can arise because of unique insertions into one or more regions of sequences, or through some more complex evolutionary process leading to proteins that do not align easily by sequence alone. As the number of sequence and their divergence increases many more errors will be made simply because of the heuristic nature of MSA algorithms. [[List of alignment visualization software|Multiple sequence alignment viewers]] enable alignments to be visually reviewed, often by inspecting the quality of alignment for annotated functional sites on two or more sequences. Many also enable the alignment to be edited to correct these (usually minor) errors, in order to obtain an optimal 'curated' alignment suitable for use in phylogenetic analysis or comparative modeling.<ref>{{cite web |title=Manual editing and adjustment of MSAs |publisher=European Molecular Biology Laboratory |year=2007 |url=http://www.embl.de/~seqanal/MSAcambridgeGenetics2007/MSAmanualAdjustments/MSAmanualAdjustments.html |access-date=March 7, 2010 |archive-url=https://web.archive.org/web/20150924000135/http://www.embl.de/~seqanal/MSAcambridgeGenetics2007/MSAmanualAdjustments/MSAmanualAdjustments.html |archive-date=September 24, 2015 |url-status=dead}}</ref>
However, as the number of sequences increases and especially in genome-wide studies that involve many MSAs it is impossible to manually curate all alignments. Furthermore, manual curation is subjective. And finally, even the best expert cannot confidently align the more ambiguous cases of highly diverged sequences. In such cases it is common practice to use automatic procedures to exclude unreliably aligned regions from the MSA. For the purpose of phylogeny reconstruction (see below) the Gblocks program is widely used to remove alignment blocks suspect of low quality, according to various cutoffs on the number of gapped sequences in alignment columns.<ref name="castresana2000">{{cite journal |vauthors=Castresana J |title=Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis |journal=Molecular Biology and Evolution |volume=17 |issue=4 |pages=540–52 |date=April 2000 |pmid=10742046 |doi=10.1093/oxfordjournals.molbev.a026334 |doi-access=free}}</ref> However, these criteria may excessively filter out regions with insertion/deletion events that may still be aligned reliably, and these regions might be desirable for other purposes such as detection of positive selection. A few alignment algorithms output site-specific scores that allow the selection of high-confidence regions. Such a service was first offered by the SOAP program,<ref name="loytynojaMilinkovitch2001">{{cite journal |vauthors=Löytynoja A, Milinkovitch MC |title=SOAP, cleaning multiple alignments from unstable blocks |journal=Bioinformatics |volume=17 |issue=6 |pages=573–4 |date=June 2001 |pmid=11395440 |doi=10.1093/bioinformatics/17.6.573 |doi-access=free}}</ref> which tests the robustness of each column to perturbation in the parameters of the popular alignment program CLUSTALW. The T-Coffee program<ref name=poirotOTooleNotredame2003>{{cite journal |vauthors=Poirot O, O'Toole E, Notredame C |title=Tcoffee@igs: A web server for computing, evaluating and combining multiple sequence alignments |journal=Nucleic Acids Res. |volume=31 |issue=13 |pages=3503–6 |date=July 2003 |pmid=12824354 |pmc=168929 |doi=10.1093/nar/gkg522}}</ref> uses a library of alignments in the construction of the final MSA, and its output MSA is colored according to confidence scores that reflect the agreement between different alignments in the library regarding each aligned residue. Its extension, Transitive Consistency Score (TCS), uses T-Coffee [[Library (computing)|libraries]] of pairwise alignments to evaluate any third party MSA. Pairwise projections can be produced using fast or slow methods, thus allowing a trade-off between speed and accuracy.<ref name=TCS2014MBE>{{cite journal|last=Chang|first=JM|author2=Di Tommaso, P |author3=Notredame, C|title=TCS: A New Multiple Sequence Alignment Reliability Measure to Estimate Alignment Accuracy and Improve Phylogenetic Tree Reconstruction.|journal=Molecular Biology and Evolution|date=June 2014|volume=31|issue=6|pages=1625–37|doi=10.1093/molbev/msu117|pmid=24694831|doi-access=free}}</ref><ref name=TCS_2015_NAR>{{cite journal |vauthors=Chang JM, Di Tommaso P, Lefort V, Gascuel O, Notredame C |title=TCS: a web server for multiple sequence alignment evaluation and phylogenetic reconstruction |journal=Nucleic Acids Res. |volume=43 |issue=W1 |pages=W3–6 |date=July 2015 |pmid=25855806 |pmc=4489230 |doi=10.1093/nar/gkv310}}</ref> Another alignment program that can output an MSA with confidence scores is FSA,<ref name=bradley2009>{{cite journal |vauthors=Bradley RK, Roberts A, Smoot M, Juvekar S, Do J, Dewey C, Holmes I, Pachter L |title=Fast statistical alignment |journal=PLOS Comput. Biol. |volume=5 |issue=5 |pages=e1000392 |date=May 2009 |pmid=19478997 |pmc=2684580 |doi=10.1371/journal.pcbi.1000392 |bibcode=2009PLSCB...5E0392B |doi-access=free}}</ref> which uses a [[statistical model]] that allows calculation of the uncertainty in the alignment. The HoT (Heads-Or-Tails) score can be used as a measure of site-specific alignment uncertainty due to the existence of multiple co-optimal solutions.<ref name=landanGraur2008>{{cite book |vauthors=Landan G, Graur D |title=Biocomputing 2008 |chapter=Local reliability measures from sets of co-optimal multiple sequence alignments |journal=Pac Symp Biocomput |pages=15–24 |date=2008 |pmid=18229673 |doi=10.1142/9789812776136_0003 |isbn=978-981-277-608-2}}</ref> The GUIDANCE program<ref name="penn2010">{{cite journal |vauthors=Penn O, Privman E, Landan G, Graur D, Pupko T |title=An alignment confidence score capturing robustness to guide tree uncertainty |journal=Molecular Biology and Evolution |volume=27 |issue=8 |pages=1759–67 |date=August 2010 |pmid=20207713 |pmc=2908709 |doi=10.1093/molbev/msq066}}</ref> calculates a similar site-specific confidence measure based on the robustness of the alignment to uncertainty in the guide tree that is used in progressive alignment programs. An alternative, more statistically justified approach to assess alignment uncertainty is the use of probabilistic evolutionary models for joint estimation of phylogeny and alignment. A Bayesian approach allows calculation of posterior probabilities of estimated phylogeny and alignment, which is a measure of the confidence in these estimates. In this case, a [[posterior probability]] can be calculated for each site in the alignment. Such an approach was implemented in the program BAli-Phy.<ref name="redelingsSuchard2005">{{cite journal |vauthors=Redelings BD, Suchard MA |title=Joint Bayesian estimation of alignment and phylogeny |journal=Syst. Biol. |volume=54 |issue=3 |pages=401–18 |date=June 2005 |pmid=16012107 |doi=10.1080/10635150590947041 |doi-access=free}}</ref>
There are free programs available for visualization of multiple sequence alignments, for example [[Jalview]] and [[UGENE]].
| |||