basic terms:

Basic terms:Basic terms: SimilaritySimilarity - measurable quantity. - measurable quantity.

Similarity- applied to proteins using concept of Similarity- applied to proteins using concept of conservative substitutionsconservative substitutions

IdentityIdentity percentagepercentage

HomologyHomology-specific term indicating -specific term indicating relationship by evolutionrelationship by evolution

Basic terms:Basic terms: Orthologs: homologous sequences found Orthologs: homologous sequences found

in in two or moretwo or more species, that have the species, that have the same function (i.e. alpha- hemoglobin).same function (i.e. alpha- hemoglobin).

Basic terms:Basic terms: Orthologs: homologous sequences found Orthologs: homologous sequences found

it it two or moretwo or more species, that have the species, that have the same function (i.e. alpha- hemoglobin).same function (i.e. alpha- hemoglobin).

Paralogs: homologous sequences found in Paralogs: homologous sequences found in the the samesame species that arose by gene species that arose by gene duplication. ( alpha and beta hemoglobin).duplication. ( alpha and beta hemoglobin).

Pairwise comparisonPairwise comparison DotplotDotplot

All against all comparison.All against all comparison.• Every position is compared with every other Every position is compared with every other

position.position.



position.position.• Nucleic acids and proteins have polarity.Nucleic acids and proteins have polarity.



position.position.• Nucleic acids and proteins have polarity.Nucleic acids and proteins have polarity.• Typically only one direction makes biological Typically only one direction makes biological

sense. sense.



position.position.• Nucleic acids and proteins have polarity.Nucleic acids and proteins have polarity.• Typically only one direction makes biological Typically only one direction makes biological

sense. sense. 5’ to 3’ or amino terminus to carboxyl terminus.5’ to 3’ or amino terminus to carboxyl terminus.

Simple plotSimple plot Window: size of sequence block used for Window: size of sequence block used for

comparison. In previous example:comparison. In previous example: window = 1window = 1

Stringency = Number of matches required Stringency = Number of matches required to score positive. In previous example:to score positive. In previous example: stringency = 1 (required exact match)stringency = 1 (required exact match)

GATCGTACCATGGAATCGTCCAGATCAGATC + (4/4)

GATCGATC

GATC - (0/4)- (0/4)+ (2/4)

WINDOW = 4; STRINGENCY = 2

DotPlot

Dot PlotDot Plot

Compare two sequences in every register.Compare two sequences in every register. Vary size of window and stringency Vary size of window and stringency

depending upon sequences being compared.depending upon sequences being compared. For nucleotide sequences typically start with For nucleotide sequences typically start with

window = 21; stringency = 14window = 21; stringency = 14 Protein - start with smaller window : 3, Protein - start with smaller window : 3,

stringency 1 or 2.stringency 1 or 2. Important to test different stringencies.Important to test different stringencies.

Intergenic comparisonIntergenic comparison Nucleotide sequence Nucleotide sequence

contains three domains.contains three domains. 50 - 350 - Strong conservation50 - 350 - Strong conservation

• Indel places comparison Indel places comparison out of registerout of register

450 - 1300 - Slightly weaker 450 - 1300 - Slightly weaker conservationconservation

1300 - 2400 - Strong 1300 - 2400 - Strong conservationconservation

Scoring AlignmentsScoring Alignments Quality ScoreQuality Score: :

Score x for match, -y for mismatch; Score x for match, -y for mismatch;


Score x for match, -y for mismatch; Score x for match, -y for mismatch; • Penalty for:Penalty for:

Creating GapCreating Gap Extending a gapExtending a gap


QualityQuality = [10(match)] = [10(match)]


QualityQuality = [10(match)] + [-1(mismatch)] = [10(match)] + [-1(mismatch)]


QualityQuality = [10(match)] + [-1(mismatch)] - = [10(match)] + [-1(mismatch)] - [(Gap Creation Penalty)(#of Gaps)[(Gap Creation Penalty)(#of Gaps)


QualityQuality = [10(match)] + [-1(mismatch)] - = [10(match)] + [-1(mismatch)] - [(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total [(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total

length of Gaps)]length of Gaps)]

Scoring scheme incorporates an evolutionary Scoring scheme incorporates an evolutionary model--model--


QualityQuality = [10(match)] + [-1(mismatch)] - = [10(match)] + [-1(mismatch)] - [(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total length of [(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total length of

Gaps)]Gaps)]

Scoring scheme incorporates an evolutionary model--Scoring scheme incorporates an evolutionary model--

Matches are conservedMatches are conserved



Gaps)]Gaps)]

Scoring scheme incorporates an evolutionary model--Scoring scheme incorporates an evolutionary model--Matches are conservedMatches are conserved

Mismatches are divergencesMismatches are divergences



Gaps)]Gaps)]

Scoring scheme incorporates an evolutionary model--Scoring scheme incorporates an evolutionary model--Matches are conservedMatches are conservedMismatches are divergencesMismatches are divergences

Gaps are more likely to disrupt function, hence greater Gaps are more likely to disrupt function, hence greater penalty than mismatch.penalty than mismatch.


QualityQuality = [10(match)] + [-1(mismatch)] - = [10(match)] + [-1(mismatch)] - [(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total length of Gaps)][(Gap Creation Penalty)(#of Gaps) +(Gap Ext. Pen.)(Total length of Gaps)]

Scoring scheme incorporates an evolutionary model--Scoring scheme incorporates an evolutionary model--Matches are conservedMatches are conservedMismatches are divergencesMismatches are divergencesGaps are more likely to disrupt function, hence greater penalty than mismatch.Gaps are more likely to disrupt function, hence greater penalty than mismatch.

Introduction of a gap (indel) penalized more Introduction of a gap (indel) penalized more than extension of a gap.than extension of a gap.

Z Score (standardized score)Z Score (standardized score) Z = (ScoreZ = (Scorealignmentalignment - Average Score - Average Scorerandomrandom))

Standard Deviationrandom

Quality Score:Randomization•Program takes sequence and randomizes it X times (user select).•Determines average quality score and standard

deviation with randomized sequences•Compare randomized scores with Quality score to help determine if alignment is potentially significant.

RandomizationRandomization It has become clear thatIt has become clear that

Sequences appear to evolve in a Sequences appear to evolve in a “word” like fashion.“word” like fashion.• 26 letters of the alphabet--combined to 26 letters of the alphabet--combined to

make words. make words. • Words actually communicate information.Words actually communicate information.

Randomization should actually occur at Randomization should actually occur at the level of strings of nucleotides (2-4). the level of strings of nucleotides (2-4).

Global AlignmentGlobal Alignment Global - Compares all possible Global - Compares all possible

alignments of two sequences and alignments of two sequences and presents the presents the one with the greatest one with the greatest number of matches and the fewest number of matches and the fewest gapsgaps. .


alignments of two sequences and alignments of two sequences and presents the presents the one with the greatest one with the greatest number of matches and the fewest number of matches and the fewest gapsgaps..

Alignment will “run” from one end of the Alignment will “run” from one end of the longest sequence, to the other end. longest sequence, to the other end.


alignments of two sequences and alignments of two sequences and presents the presents the one with the greatest one with the greatest number of matches and the fewest number of matches and the fewest gapsgaps..


Best for closely related sequences.Best for closely related sequences.

Global AlignmentGlobal Alignment Global - Compares all possible alignments of Global - Compares all possible alignments of

two sequences and presents the two sequences and presents the one with the one with the greatest number of matches and the fewest greatest number of matches and the fewest gapsgaps..


Best for closely related sequences.Best for closely related sequences. Can miss short regions of strongly conserved Can miss short regions of strongly conserved

sequence. sequence.

Local AlignmentLocal Alignment

Identifies segments of alignment with the Identifies segments of alignment with the highest possible score.highest possible score.


Identifies segments of alignment with the Identifies segments of alignment with the highest possible score.highest possible score.

Align sequences, extends aligned regions in Align sequences, extends aligned regions in both directions until score falls to zero.both directions until score falls to zero.


Identifies segments of alignment with the highest Identifies segments of alignment with the highest possible score.possible score.

Align sequences, extends aligned regions in both Align sequences, extends aligned regions in both directions until score falls to zerodirections until score falls to zero..

Best for comparing sequences whose relationship is Best for comparing sequences whose relationship is unknown.unknown.

Global Alignment:

Local Alignment:

Blast 2

Basic Local Alignment Search Tool

E (expect) valueE (expect) value: number of hits expected by randomchance in a database of same size.

Larger numerical value = lower significance

HIV sequence

http://www.ncbi.nlm.nih.gov/blast/bl2seq/bl2.html

http://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?cmd=&txt=&save=&cfm=&term=&list_uids=60256&db=nucleotide&extrafeat=24&view=fasta&dispmax=20&SendTo=on&__from=&__to=&__strand=

Both Global and Local alignment programs will Both Global and Local alignment programs will (almost) (almost) alwaysalways give a match. give a match.


It is important to determine if the match is It is important to determine if the match is biologically relevant.biologically relevant.



Not necessarily relevant: Low complexity Not necessarily relevant: Low complexity regions.regions. Sequence repeats (glutamine runs)Sequence repeats (glutamine runs)



Not necessarily relevant: Low complexity Not necessarily relevant: Low complexity regions.regions. Sequence repeats (glutamine runs)Sequence repeats (glutamine runs) Transmembrane regions (high in hydrophobes)Transmembrane regions (high in hydrophobes)



Not necessarily relevant: Low complexity Not necessarily relevant: Low complexity regions.regions. Sequence repeats (glutamine runs)Sequence repeats (glutamine runs) Transmembrane regions (high in hydrophobes)Transmembrane regions (high in hydrophobes)

If working with coding regions, you are If working with coding regions, you are typically better off typically better off comparing proteincomparing protein sequencessequences. Greater information content.. Greater information content.

basic terms:

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