Multiple Sequence Alignment

Plant Genes Annotation and Analysis

This is a series of three 3-hour exercises that guide students on the DNA Subway, an online workspace that integrates tools for genomic analysis in a student and educator-friendly environment. Exercise 1 was developed by Dr. Judy Brusslan (California State University, Long Beach). The Exercise I and II PowerPoints and Exercise II were developed by Dr. James Youngblom (California State University Stanislaus). The “Prospecting for Green Revolution Genes” presentation and Exercise III were developed by Dr. Nicholas Ewing (California State University, Sacramento) based on materials initially developed by members of the iPlant Collaborative.

Pandemic Flu Genomics Exercise

Dr. Robert Moss (Wofford College) has developed an annotation exercise on Influenza viruses.

Bioinformatics Tools Tutorial Project – KRas

This lab is an updated, stand-alone version of the bioinformatics exercise originally developed for Bio 3055 at Washington University. This exercise introduces students to the genetic basis of disease using the KRas protein.

Using BLAST and ExPASy for Genetic and Protein Analysis of H1N1 Variability

Ms. Julie Ertmann (University City High School, MO) has designed a standalone activity using BLAST for AP or second year high school biology students. This exercise uses BLAST and ExPASy for genetic and protein analysis of H1N1 variability, including mutations that confer resistance to antiviral medications. Development of this exercise was supported by an NSF Mathematics and Science Partnership grant #06344780, to B Schaal, Washington University in St. Louis. If you have questions about this activity, please email the author at: jertmann@ucityschools.org.

Investigating a Mutation in HIV-1

Students use the HIV Problem Space on the BioQuest BEDROCK Website to investigate whether a specific HIV mutation can be correlated with a decline in immune system function. In order to perform this analysis, students must generate and analyze multiple sequence alignments of HIV sequences generated from the ALIVE study.

Module TSS4: Annotation of Broad Transcription Start Sites

This module illustrates the use of computational (e.g., blastn) and experimental (e.g., RAMPAGE, CAGE, RNA PolII ChIP-Seq) data to define the narrow and wide TSS search regions for genes with broad promoters.

Module TSS2: Using Sequence Alignment to Identify a TSS

This module illustrates how pairwise (blastn) and multiple sequence alignments can be used in conjunction with RNA-Seq data and the Short Match functionality of the UCSC Genome Browser to facilitate the TSS annotation of the Antp gene in D. eugracilis.

Generating Multiple Sequence Alignments with ClustalW

Dr. Susan Parrish (McDaniel College) developed a basic lecture and weblem exercise (found at the end of the lecture) on using ClustalW to generate multiple sequence alignments, phylograms, and cladograms. This lecture and exercise are given prior to beginning the GEP annotation projects. Students who submit their GEP annotation projects early are then asked to generate multiple sequence alignments and phylograms of the putative proteins encoded within their assigned contig or fosmid, compared to those related proteins encoded by other Drosophila species of interest to the GEP.

Generating Multiple Sequence Alignments with Clustal Omega

Developed by Dr. Susan Parrish (McDaniel College), this PowerPoint presentation describes how Clustal Omega can be used to produce multiple sequence alignments. The multiple sequence alignments of the nucleotide sequences surrounding the transcription start sites can be used to identify core promoter motifs, while the multiple sequence alignments of protein sequences can be used to identify conserved domains. The presentation also includes a discussion of two strategies (UPGMA and Neighbor Joining) that are often used to construct phylogenetic trees.

Overview of Multiple Sequence Alignment Algorithms

Developed by Yu He (TA for Bio 4342), this PowerPoint presentation provides a basic overview of the common algorithms used to generate multiple sequence alignments. The presentation also illustrates how one could use Clustal Omega to generate a multiple sequence alignment for a set of orthologous proteins in order to identify conserved domains within the protein.