Lecture 4 - Scoring Alignments and Similarity Searches
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Questions and Answers

What does sequence similarity help identify?

  • Homologous sequences (correct)
  • Physical traits
  • Environmental factors
  • The age of organisms

    • Hamming Distance takes into account insertions and deletions when comparing sequences.

    False

    What is the primary purpose of scoring matrices in bioinformatics?

    To assign scores to matches and mismatches based on evolutionary significance.

    The method that measures the minimum number of operations to transform one sequence into another is called ________.

    <p>Edit Distance</p> Signup and view all the answers

    Match the following terms with their definitions:

    <p>Hamming Distance = Measures mismatches only Edit Distance = Includes insertions and deletions PAM matrix = Focuses on mutations over evolutionary time BLOSUM matrix = Used for distant sequence relationships</p> Signup and view all the answers

    Which of the following is NOT an application of sequence similarity?

    <p>Predicting weather patterns</p> Signup and view all the answers

    What is the goal of DNA Alignment Scoring?

    <p>To maximize the alignment score representing the best possible sequence comparison.</p> Signup and view all the answers

    What is the primary goal of the Needleman-Wunsch algorithm?

    <p>To maximize the alignment score between two sequences</p> Signup and view all the answers

    The Smith-Waterman algorithm is primarily used for global alignment of sequences.

    <p>False</p> Signup and view all the answers

    What does the Smith-Waterman algorithm allow for in sequence alignment?

    <p>Gaps and mismatches</p> Signup and view all the answers

    The Needleman-Wunsch algorithm finds the best global alignment by comparing all pairs of residues in a ______ matrix.

    <p>2-D</p> Signup and view all the answers

    Match the following alignment algorithms with their features:

    <p>Needleman-Wunsch = Global alignment with all bases included Smith-Waterman = Local alignment for matching subsequences Dynamic Programming = Method used by both algorithms Alignment Score = Process of maximizing similarity between sequences</p> Signup and view all the answers

    Which scoring matrix assumes that all mismatches are equally likely?

    <p>Identity Matrix</p> Signup and view all the answers

    Transitions are less common in evolution compared to transversions.

    <p>False</p> Signup and view all the answers

    What type of gap penalty encourages fewer, longer gaps over many shorter ones?

    <p>Affine Gap Penalty</p> Signup and view all the answers

    The fixed cost for starting a gap in sequence alignment is known as the ______.

    <p>Gap opening penalty</p> Signup and view all the answers

    What is a key limitation of the Identity Matrix in DNA alignment scoring?

    <p>It does not account for biological significance.</p> Signup and view all the answers

    Match the following types of gap penalties with their characteristics:

    <p>Constant Gap Penalty = A fixed penalty for each gap, regardless of length Affine Gap Penalty = Penalizes the gap opening more than its length</p> Signup and view all the answers

    Gaps used in sequence alignment should be excessively frequent to ensure accuracy.

    <p>False</p> Signup and view all the answers

    What term describes the penalty applied for each additional unit in an existing gap after the first unit?

    <p>Gap extension penalty</p> Signup and view all the answers

    A biologically informed scoring matrix is known as the ______ matrix.

    <p>Transition-Transversion</p> Signup and view all the answers

    What is the typical length of DNA words in the query segmentation process?

    <p>11 nucleotides</p> Signup and view all the answers

    The primary purpose of the scoring matrix in the BLAST process is to filter out low-scoring HSPs.

    <p>False</p> Signup and view all the answers

    What does the E-value in the BLAST output represent?

    <p>The likelihood that the match occurred by chance.</p> Signup and view all the answers

    In word matching, BLAST scans the database to identify sequences that contain exact or near-exact matches to the query ______.

    <p>words</p> Signup and view all the answers

    Match the aspects of the BLAST report with their descriptions:

    <p>Query sequence = The sequence you are analyzing Hits = Sequences in the database that share similarity with the query Alignment = Comparison of the hit sequence with the query Score = Quality of the alignment</p> Signup and view all the answers

    What term is used to describe the high-scoring segment pairs formed during word extension?

    <p>High-scoring segment pairs (HSPs)</p> Signup and view all the answers

    BLAST allows for mismatches or gaps during the word extension phase.

    <p>True</p> Signup and view all the answers

    What is the significance of a higher score in the BLAST alignment?

    <p>It indicates a better alignment.</p> Signup and view all the answers

    The remaining alignments after scoring are evaluated using ______ methods to calculate the E-value.

    <p>statistical</p> Signup and view all the answers

    Which of the following best describes the alignment in a BLAST report?

    <p>Detailed comparison including matches, mismatches, and gaps</p> Signup and view all the answers

    What does a positive score in a PAM matrix indicate?

    <p>Amino acid changes occur more frequently than expected</p> Signup and view all the answers

    BLOSUM matrices are based on observed substitutions in blocks of conserved sequences with gaps.

    <p>False</p> Signup and view all the answers

    What is the significance of PAM250?

    <p>It represents an expectation of 250 amino acid changes per 100 amino acids.</p> Signup and view all the answers

    BLOSUM62 is widely used because it clusters sequences sharing at least _____ identity.

    <p>62%</p> Signup and view all the answers

    Match the following PAM and BLOSUM concepts:

    <p>PAM250 = Moderately divergent sequences BLOSUM62 = 62% identity threshold PAM = Conservative mutations BLOSUM = Distant evolutionary relationships</p> Signup and view all the answers

    Which statement about BLOSUM matrices is true?

    <p>They are based on actual observed substitutions.</p> Signup and view all the answers

    A higher BLOSUM number indicates that the matrix is meant for more distantly related sequences.

    <p>False</p> Signup and view all the answers

    What do you need to count when creating a BLOSUM matrix?

    <p>Amino acid pairs aligned at specific positions.</p> Signup and view all the answers

    The BLOSUM matrix scores alignments based on _____ regions of protein families.

    <p>conserved</p> Signup and view all the answers

    What do PAM matrices primarily focus on?

    <p>Conservative mutations in closely related sequences</p> Signup and view all the answers

    Study Notes

    Bioinformatics Lecture 4: Scoring Alignments and Similarity Searches

    • The lecture covers scoring alignments and similarity searches in bioinformatics.
    • The workflow presented emphasizes the sequential steps from DNA sequencing to genome annotation and expression analysis, including marker-trait associations, population analysis, and genotyping.
    • Dotplots are graphical tools used to visually represent the relationship between two sequences by plotting matching residues in a matrix.

    Dotplots

    • Definition: A dotplot is a graphical tool used to visualize the relationship between two sequences. Matching residues are plotted in a matrix creating a visual representation of similarity or identity regions across sequences.
    • Axes representation: Sequences are assigned to the x and y axes and matches appear as dots where the sequences agree.
    • Visualization: Diagonal lines on a dotplot indicate regions of high similarity or identity between sequences.
    • Dotplots are useful for spotting duplications, inversions, and repeats within sequences.
    • Advantages: Easy visualization of regions shared between sequences, and identification of structural features like repeats, duplications, inversions, or palindromes.
    • Software: MUMmer is a widely used tool for creating dotplots, particularly in genome comparisons. Other tools such as Genard Dotter also allow for the creation of the dotplots.
    • Limitations: Limited scalability as the matrix size increases exponentially, resulting in cluttered displays, sensitivity to noise in repetitive regions, and lack of quantitative measures.

    Sequence Similarity

    • Definition: Sequence similarity refers to the degree of likeness between two nucleotide or protein sequences. Similarity can be quantified by various methods depending on the type of sequence comparison.
    • Methods to assess sequence similarity:
      • Hamming distance: Measures the number of mismatches between sequences of equal length.
      • Edit Distance/Levenshtein Distance: Measures the minimum number of operations (insertions, deletions, or substitutions) required to transform one sequence into another. Accounts for indels and substitutions.

    Scoring Matrices

    • Definition: Matrices that assign scores to different types of matches and mismatches based on the evolutionary or functional significance of the changes. They're commonly used in protein alignments.
    • Examples: PAM (Point Accepted Mutation): Used for mutations over evolutionary time. BLOSUM (Blocks Substitution Matrix): Used for distant sequence relationships.

    DNA Alignment Scoring

    • Definition: DNA alignment scoring refers to assigning numerical values to matches, mismatches, and gaps. It aims to represent and maximize the best alignment with a balancing act between matches and differences.
    • Importance: Provides a quantitative way to compare sequences, and measure similarity that helps identify evolutionary relationships and functional similarities between sequences.
    • Identity matrix: The simplest scoring matrix that assumes all mismatches and mutations are equally likely.
    • Transition-Transversion matrix: A more biologically-informed matrix that gives higher scores to transitions (changes within the purine or pyrimidine class).
    • Gap Penalties: Penalizes gaps (insertions and deletions) to prevent introducing too many gaps in the alignment.
      • Constant gap penalty: A fixed penalty for every gap
      • Affine gap penalty: Penalizes gap initiation more than gap extension. This encourages fewer but longer gaps.

    PAM Matrices

    • Definition: PAM matrices measure the evolutionary distances using the number of mutations that have occurred in one amino acid per 100 amino acids. This matrix measures the evolutionary distance.
    • Origin: 1,572 mutations observed within 71 closely related protein sequences (≥85% sequence identity) were used to build the PAM1 matrix.
    • Usage: More commonly used for aligning sequences that are more closely related. For more distantly related sequences, PAM250 is commonly used.
    • Key Concept: Specific mutations occurring at higher probability over time help identify a greater distance of evolutionary time between sequences.

    BLOSUM Matrices

    • Definition: BLOSUM matrices generate and use alignments from highly conserved regions of proteins.
    • Key Concept: Created from regions (blocks) of high conservation (no significant changes over time) within proteins, meaning that these regions have been preserved in evolution, and are typically used to detect more distant evolutionary relationship.
    • Usage: Primarily used to align more distantly related protein sequences. Lower BLOSUM numbers (eg, BLOSUM45) are used to compare more distantly related sequences whereas higher BLOSUM numbers (e.g., BLOSUM80) are suitable for more closely related sequences, and BLOSUM62 is the most widely used matrix.

    BLAST (Basic Local Alignment Search Tool)

    • Definition: A widely used algorithm that searches a database of sequences to find similar or homologous regions to a query sequence, crucial for identifying homologous sequences and assessing biological relevance.
    • Works by finding potential matches in the Database (hits or Seeds) then extending them and building a HSP.

    Multiple Sequence Alignment (MSA)

    • Definition: Aligns three or more biological sequences to identify similar and conserved regions across sequences; revealing evolutionary relationships and functional elements.
    • Objectives: Maximize similarity, reveal evolutionary relationships, and identify conserved regions for functional/structural understanding.
    • Applications: Phylogenetics, functional analysis, and protein structure prediction.

    Methods for MSA

    • Progressive Alignment: Aligns sequences pairwise starting with those with the highest similarity. Aligns progressively, and faster but sensitive to initial alignment errors which propagate as more sequences are aligned. (e.g., ClustalW)
    • Iterative Alignment: Refines an initial alignment by repeatedly realigning subsequences to improve overall score. More accurate than progressive, but computationally more intensive. (e.g., MUSCLE).
    • Consensus-Based Alignment: Combines results from different alignment methods, and weights their reliability. More reliable when aligning divergent sequences but can be slower due to multiple alignment steps. (e.g., T-Coffee).

    Challenges in MSA

    • Gaps and Indels: Introducing gaps to incorporate or accommodate insertions/deletions, especially within sequences with varying lengths.
    • Divergence: Large evolutionary distances may create a significant challenge when aligning divergent sequences.
    • Computational Complexity: Aligning many sequences computationally demands more intensive calculations and processing time.

    Global and Local Alignments

    • These are two approaches to sequence alignment that have distinct algorithms, advantages, and usage scenarios. Global alignment (e.g., Needleman-Wunsch) is for similar-sized sequences expected to align across the entire length. Local Alignment (eg Smith-Waterman) is more flexible, and is to find and align similar segments within the sequence, even if the sequences have large dissimilar segments.

    Needleman-Wunsch

    • A general method of performing sequence comparison.
    • Goal: To maximize the alignment score between two sequences.
    • Finds the best global alignment, including all bases/amino acids from both sequences.
    • Two-step dynamic programming approach:
      • All pairs of residues are scored in a matrix using a scoring system.
      • The highest scoring path is the best alignment.

    Smith-Waterman

    • A dynamic programming approach for identifying local regions of similarity.
    • Goal: Maximizes the alignment score for local regions; rather than finding alignment across the entirety of a sequence.
    • Key feature: Allows for gaps and mismatches and is optimal for substrings, ideal for dissimilar sequences.

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    Biotech 4BI3 Bioinformatics Lecture Notes PDF

    Description

    Test your knowledge on sequence similarity and alignment algorithms in bioinformatics. This quiz covers various methods such as Hamming Distance, Needleman-Wunsch, and Smith-Waterman algorithms, as well as their applications and scoring matrices. Challenge yourself with matching terms to definitions and identifying key concepts.

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