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Multiple sequence alignment

Multiple sequence alignment is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Multiple sequence alignment rather than just read about it. In short: Multiple sequence alignment (MSA) is the process or the result of sequence alignment of three or more biological sequences, generally protein, DNA, or RNA. These alignments are used to infer evolutionary relationships via phylogenetic analysis and can highlight homologous features between sequences.

Multiple sequence alignment — main illustration
Multiple sequence alignment — illustration

Key takeaways

  • Multiple sequence alignment belongs to biology; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Multiple sequence alignment to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Multiple sequence alignment from memory before moving on to harder problems.

Reference excerpt

Multiple sequence alignment (MSA) is the process or the result of sequence alignment of three or more biological sequences, generally protein, DNA, or RNA. These alignments are used to infer evolutionary relationships via phylogenetic analysis and can highlight homologous features between sequences. Alignments highlight mutation events such as point mutations (single amino acid or nucleotide changes), insertion mutations and deletion mutations, and alignments are used to assess sequence conservation and infer the presence and activity of protein domains, tertiary structures, secondary structures, and individual amino acids or nucleotides. Multiple sequence alignments require more sophisticated methodologies than pairwise alignments, as they are more computationally complex. Most multiple sequence alignment programs use heuristic methods rather than global optimization because identifying the optimal alignment between more than a few sequences of moderate length is prohibitively computationally expensive. However, heuristic methods generally cannot guarantee high-quality solutions and have been shown to fail to yield near-optimal solutions on benchmark test cases.

Problem statement Given m {\displaystyle m} sequences S i {\displaystyle S_{i}} , i = 1 , ⋯ , m {\displaystyle i=1,\cdots ,m} similar to the form below:

S := { S 1 = ( S 11 , S 12 , … , S 1 n 1 ) S 2 = ( S 21 , S 22 , ⋯ , S 2 n 2 ) ⋮ S m = ( S m 1 , S m 2 , … , S m n m ) {\displaystyle S:={\begin{cases}S_{1}=(S_{11},S_{12},\ldots ,S_{1n_{1}})\\S_{2}=(S_{21},S_{22},\cdots ,S_{2n_{2}})\\\,\,\,\,\,\,\,\,\,\,\vdots \\S_{m}=(S_{m1},S_{m2},\ldots ,S_{mn_{m}})\end{cases}}}

A multiple sequence alignment is taken of this set of sequences S {\displaystyle S} by inserting any amount of gaps needed into each of the S i {\displaystyle S_{i}} sequences of S {\displaystyle S} until the modified sequences, S i ′ {\displaystyle S'_{i}} , all conform to length L ≥ max { n i ∣ i = 1 , … , m } {\displaystyle L\geq \max\{n_{i}\mid i=1,\ldots ,m\}} and no values in the sequences of S {\displaystyle S} of the same column consists of only gaps. The mathematical form of an MSA of the above sequence set is shown below:

… excerpt ends here. Continue reading the full article.

Illustrations

Multiple sequence alignment: First 90 positions of a protein multiple sequence alignment of instances of the acidic ribosomal protein P0 (L10E) from several organisms. Generated with ClustalX.
First 90 positions of a protein multiple sequence alignment of instances of the acidic ribosomal protein P0 (L10E) from several organisms. Generated with ClustalX.
Multiple sequence alignment: A profile hidden Markov model (HMM) modelling a multiple sequence alignment
A profile hidden Markov model (HMM) modelling a multiple sequence alignment
Multiple sequence alignment: Non-homologous exon alignment by an iterative method (a), and by a phylogeny-aware method (b)
Non-homologous exon alignment by an iterative method (a), and by a phylogeny-aware method (b)
Multiple sequence alignment: Alignment of the seven Drosophila caspases colored by motifs as identified by MEME. When motif positions and sequence alignments are generated independently, they often correlate well but not perfectly, as in this example.
Alignment of the seven Drosophila caspases colored by motifs as identified by MEME. When motif positions and sequence alignments are generated independently, they often correlate well but not perfectly, as in this example.

Worked examples

Example 1 — a first encounter with Multiple sequence alignment

Start with the simplest possible case. Write down what Multiple sequence alignment claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Multiple sequence alignment before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Multiple sequence alignment ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Multiple sequence alignment

In research
Multiple sequence alignment appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Multiple sequence alignment in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Multiple sequence alignment is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics, Computational phylogenetics, Markov models, so understanding it makes those chapters shorter.
In everyday life
Look for Multiple sequence alignment outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Multiple sequence alignment in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Multiple sequence alignment means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Multiple sequence alignment out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Multiple sequence alignment in simple terms?

Multiple sequence alignment (MSA) is the process or the result of sequence alignment of three or more biological sequences, generally protein, DNA, or RNA. These alignments are used to infer evolutionary relationships via phylogenetic analysis and can highlight homologous features between sequences.

Why does Multiple sequence alignment matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Multiple sequence alignment?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Multiple sequence alignment.

Tags

  • Bioinformatics
  • Computational phylogenetics
  • Markov models
  • NP-complete problems

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