Data Walkthrough: Background

Transcription

1 Data Walkthrough: Background File Types FASTA Files FASTA files are text-based representations of genetic information. They can contain nucleotide or amino acid sequences. For this activity, students will be working with a FASTA file which contains the nucleotide sequence of the mitochondrial hypervariable region II (mthvrii). Every FASTA sequence contains two main parts: a header line, beginning with > and containing the name and details of the sequence, and the sequence information. A FASTA file can contain multiple sequences so long as every header line begins with > and has a unique identifier. Most programs which process FASTA files allow files to be uploaded directly, but FASTA files can be opened in a text editor (such as Notepad) to be viewed and modified. Figure 1 FASTA format for the mthvrii sequence Variant Call Format (VCF) Files VCF files are text-based, tab-delimited, files containing information about where and how an observed sequence differed from the reference. These files contain a large amount of information about both the quality and frequency of reads, although the specific types of information will vary depending on what equipment was used to generate the VCF. Between the variety of information, and the condensed manner in which it is presented, VCF files can be overwhelming; therefore this data walkthrough uses a trimmed down VCF containing only the information necessary to complete our analysis process. The general format of a VCF file consists of two sections: a header section of rows beginning with ##, and a content section containing a table of information for the different variants observed. The header section contains information about the data used to generate the file (alignment tool, reference sequence, etc), as well as specifics about what types of information are presented in the table below. The tables always contain the same column headers: CHROM the chromosome where the variant is located POS the position of variant within that chromosome (each type of mutation observed has its own line in the VCF, so if a both single nucleotide change and an insert were observed at the same point, that position will have multiple rows assigned to it) ID if the reference is annotated with known mutation, they are indicated here REF what base/bases appear in the reference

2 ALT the alternate base/bases observed, multiple entries are separated by commas QUAL quality metric; higher numbers indicate more certainty in the accuracy of the read FILTER a combined measure of quality and frequency, a variant must pass both to be considered accurate and will indicate if either failed (LowGQ or LowVarFrequency) INFO general information about the variants observed FORMAT the order in which sample specific information will be presented, types of information are separated by colons, : [SAMPLE NAME] sample-specific information presented in the order described in format. There may be multiple samples represented in a single VCF file. Figure 2 Full VCF format, opened in Excel For this demo set of data, we have trimmed the VCFs down to the information vital to our analysis. We have kept the chromosome, position, reference, alternate, and filter information unchanged. In addition we kept the Allelic Depth (AD) information, but renamed it Read Frequency (RF) to avoid confusion over the terms allelic and depth (especially since the hypervariable regions are non-coding and allele is usually used with genes), to function as a tiebreaker when a position has multiple valid variants. Our abridged VCF is shown below, opened in both Excel (which formats the table to columns) and in Word (which keeps the tab delimiters, but will not always align columns neatly).

3 Figure 3 Trimmed VCF file opened in Excel (left) and Word (right). Clustal Omega Clustal Omega is a multiple alignment tool which compares FASTA sequences (nucleotide or protein) to determine how similar they are. It is a free, online tool provided at Figure 4 Clustal Omega input page. In this activity, students will import the mthvrii sequences they ve generated using the reference and VCF files into Clustal Omega and use the resultant similarity matrix to determine which are most genetically similar.

4 Data Walkthrough: Workflow References and Variants The first step of analysis is to generate the complete sequence for each individual. Since entire genomes can be extremely long, the sequencer doesn t write out the entire sequence for every sample. Instead, it generates a file listing only the places where the sample differed from the reference, this file is in a variant call format and referred to as a VCF. We re not looking at an entire genome though, and the hypervariable region (HVR) we re using is only about 430 base pairs (bp) long, so we can generate the full sequence fairly easily using the reference as a template and making the changes indicated in the VCF. Generate a sample specific sequence 1. Open Reference FASTA in Notepad (or text-editing program of your choice) 2. Copy/Save As to make a new, sample specific FASTA a. Be sure to change the header row to indicate which sample it represents 3. Open the appropriate VCF in Excel or Word (Notepad doesn t always format correctly) 4. Using the VCF, make the appropriate changes to the sample FASTA a. Only variants which pass filter should be considered. If the filter column has LowVariantFreq (did not pass the frequency filter) or LowGQ (did not pass the quality filter), the variant shouldn t be used. b. Use read frequencies (RF) to pick the most frequent of multiple, valid mutations at a single point. 5. Once all changes are made, save the file. 6. Repeat as necessary until all samples have FASTA sequences saved. Additional Advice for Editing FASTAs In notepad, when View>status bar is checked, you can use the col in the lower right hand corner to know which position you re at (number is for the position to the RIGHT of the cursor) It s often easier to add indels (inserts or deletions) last, since they ll change positon numbers for the rest of the FASTAs

5 Multiple Sequence Alignment Once all the sequences have been made, it s necessary to align and compare them. Since we ve used the same reference as the basis for inputting variants, alignment isn t going to be difficult, but the alignment program will highlight which nucleotides differ between samples and allows us to quantify the differences. 1. Go to Clustal Omega ( an online multiple sequence alignment tool 2. Input all the FASTAs you want to align 3. Make sure it s set to align DNA and click submit 4. Once it s finished aligning: a. Automatically brings up the alignment page i. Nucleotides with perfect matches are marked by * ii. Gaps which have been added are marked as 5. Go to the Results Summary tab and click the Percent Identity Matrix a. Matrix indicates that the row and column headers are going to be the same. b. Take a moment to review the matrix. Be sure to note any obvious patterns, and their possible explanations, before continuing. c. The matrix can used directly in the browser, or copied into Excel i. Do not copy header rows (which begin with #) ii. Paste into Excel, each row will now be in a single cell iii. Highlight the cells, navigate to the data tab and select Text to Columns in the Data Tools box. iv. Follow the prompts using Fixed Width as the data type 6. Use the percent identity matrix to identify most and least similar matches for each example sample Other useful tools on Clustal Omega Clustal Omega uses the presence and absence of mutations to predict how closely samples are related, since samples containing the same mutation are likely to have inherited it through a common ancestor. The Phylogenetic Tree tab displays this prediction similarly to how you may represent your immediate relatives on a family tree.