BS2040-Bioinformatics & SNP analysis with Galaxy - Engineering Assignment Help

Assignment Task

Task 

Introduction to Genome scale analyses and Galaxy

Resources required
The practical requires access to the Internet and a correctly configured web browser (Firefox, ideally but Chrome will suffice). Using Blackboard Collaborate to view and interact with the online class requires, at minimum, a web connected device that can play audio, but ideally a laptop or PC with headphone socket / speakers and a microphone.

Entry Skills
To take part in this practical you will need to be able to carry out the following tasks:
1. Use of web browsers, using multiple tabs / windows
2. Search online bioinformatics resources to retrieve research material
3. Recording notes and the results of your analyses in a research blog

Introduction
This practical exercise involves exploration of the Galaxy web-based bioinformatics analysis suite (Giardine et al., 2005), using an example exercise of identifying coding SNPs in a rather famous “personal genome”. This analysis, is the subject of a research paper by the Galaxy Project staff, will equip you with the skills to carry out the assessed practical task. This task involves identifying and classifying SNPs that map to the genomic region occupied by your individually assigned gene from the BLAST practical. It is important that you know you have correctly identified this gene BEFORE starting on the assessed part of the practical task. A list of the correct genes assigned to students will be published on the BS2040 Blackboard site before the practical setup session on Monday 29th March 2021. CHECK this list BEFORE starting you analyses.

Important Notes On The Execution And Support Of This Practical
Galaxy is a public, shared bioinformatics resource which, while offering substantial compute resources, is not infinite or infallible. Running practical classes live on the public server can lead to poor performance and frustration, precisely because users are doing the same thing (accessing files, carrying out analyses) at the same time. As with the BLAST Practical, we will introduce / review the practical exercise in the Practical 2 Setup session (Monday 29th March 2021), online in Blackboard Collaborate. Then you will be free to carry out the practical tasks in your own time,
supported by the module tutors, online.

Discussion Board
We have structured the preparation for the Practical to begin during the week beginning 22nd March so that you can carry out the preliminary exercises, and the practical tasks when you have time. Support will be available on the BS2040 Galaxy Discussion Board on the module Blackboard site, starting with the Introductory lecture on Wednesday 24th March. This enables prompt, specific answers to your questions, while sharing the questions and answers with the whole class. It will be greatly to your advantage if you subscribe to the discussion board, so that you get an email each time that a new post is made. The Discussion Board is NOT ASSESSED.

Galaxy Blogs
Each student has been assigned a Galaxy Practical Blog (again on the Blackboard site) where you can (if you wish) post notes, progress and links to resources. Your Galaxy Blog is also NOT ASSESSED. It is intended that by the time of the Practical Class 2 Setup session (Monday 29th March 2021 10am-2pm ONLINE) you will have completed the example exercise. The ONLINE practical setup class will give you the opportunity to ask any outstanding questions, using Collaborate. Staff moderators will be monitoring the session online, and can interact with students through webchat, audio and by screen sharing.

The instructions for your practical report specify the tasks that you should complete, how you should format your report and the arrangements for sharing the History of your Galaxy analyses. The History of your Galaxy analyses will be reviewed in the context of your report, but the History itself is NOT ASSESSED. As each task and the research that you carry out, is individual to your gene, the Practical reports will be assessed using a Grademark Rubric, based on the mark scheme at the end of this document. The practical report is due for submission online (via Blackboard / TurnitinUK) by 8am on Tuesday 4th May 2021.

The REAL practical task…
A central theme in bioinformatics is developing algorithms (programs or recipes) that allow a task to be carried out not just once, but repeatedly, many times. While bioinformatics databases contain much information, made available in useful ways through websites, it is not practical to analyse more than a few cases by “pointing and clicking”. The traditional way to approach this problem is to define an algorithm for doing the analysis and then write a computer program that acquires all of the required data, processes it according to the algorithm and then generates a set of results in the form desired. On BS2040 we do not have the time to teach you programming, but we DO have something better (in some ways!).

It’s an algorithm (not an Al Gore rhythm!)
As you are now aware, Galaxy is a bioinformatics workbench that allows the linking together of data and analysis programs using a web interface, to carry out a task (as in the example exercise – finding the new, exonic SNPs in the Archbishop’s genome). It was evident that the procedure could have been carried out for a whole genome, a chromosome or even a single gene, just by changing the genome coordinate range analysed. In this way, the Galaxy History (the record of steps taken in the analysis – in the right-hand pane) is the implementation of an algorithm – one that finds SNPs and analyses whether they are in exons, or introns. Indeed, Galaxy Histories can be extracted to form a “workflow” that can be run many times on hundreds of thousands of datasets. This constitutes a computer program, except it can only run within the Galaxy environment. It is not a general solution to a task (that is the algorithm), but will accomplish it automatically, within Galaxy.

“Adapt or die…” (it’s a quote not an instruction!)
The aim of this practical exercise is to adapt the algorithm used to analyse theArchbishop’s SNPs, to analyse SNPs within “your” assigned human genes from the BLAST practical. In doing so you will work within Galaxy to find a way to do this for just one gene, but also extend the analysis to identify SNPs that lie within coding and non-coding parts of the gene. While coding SNPs that change amino acids, are the most likely candidates for disease causing mutations, many genetic diseases are caused by mutations in the gene promoter, splice sites and regulatory sequences.
Assessing whether non-coding SNPs may have deleterious effects is outside the scope of this practical, but is a major area of activity in human genomics.

F: Tasks to complete for your practical report
The central aim of the practical is to collect SNPs from dbSNP version 153 (the version of the database supported by Galaxy for the hg38 genome assembly) that overlap the genomic region associated with assigned gene. This dataset is referred to as “dbSNP153” in the UCSC Table Browser. While SNPs within exons can be readily found using the method described in the example exercise, the challenge is to classify the overlapping SNPs as exonic* or intronic, or located within the “putative promoter” region of your gene. For the purposes of this practical we will use the region 5000bp 5´ or “upstream” (i.e. in the opposite direction to which the gene is transcribed) of the Transcription Start Site (TSS) as being the location of the “putative promoter”. The TSS can be defined as the coordinate of the first nucleotide of the reference mRNA (transcript) for the human version of your assigned gene, as identified in the BLAST practical. You should clearly state which RefSeq reference transcript you are using, including its accession number and version. You should also clearly refer to each task (i.e. as F1, F2, etc.) within the relevant sections of your report.

Task F1
Locating the coordinates of your assigned gene: Using the reference mRNA (transcript) for the human version of your gene, identified in the BLAST practical, you should find the coordinate range that this covers within the latest* human genome (GRCh38 / hg38) assembly. Also, make a note of the strand (+ or -) of the gene so that you calculate the coordinate range 5000 bp upstream of the TSS. One approach is to examine the NCBI Gene entry for your gene, as you did in the BLAST Practical. By mousing over the transcript variant that you identified in the BLAST practical, you will activate the pop-up window that contains the genomic location (“Location:...“). You will need to combine these coordinates with the chromosome number (e.g. Chr7:123456-678910) to generate the complete coordinates. Another approach is to use BLAT at the UCSC Genome Browser website and the sequence of the reference mRNA to locate the coordinates*.

Task F2
Extending the range: Some SNPs can influence gene expression, despite not being included in the transcript. They may be located in the promoter, and so change the gene’s expression activity by changing the rate of transcription initiation, for example. You should extend the coordinate range by 5000 bp, to include the region upstream of the Transcription Start Site. NB: for genes on the “+ “strand this involves subtracting 5000 from the “start” coordinate, BUT adding 5000 to the stop coordinate for genes that lie on the “-” or “complement” strand.

Task F3
Getting the SNPs: Using the coordinate range that you have calculated extract ALL the SNPs that map to this interval, from the latest version of dbSNP applicable to the hg38 assembly – dbSNP 153. NB: Galaxy defaults to the “Common dbSNP(153) (dbSNP153Common)” track if you select dbSNP 153, BUT as some disease causing SNPs are very rare, we need the “All dbSNP(153)(dbSnp153)” track instead – select this from the “table:” dropdown menu. 

Task F4a
Selecting coding exonic SNPs: Using the example exercise as a guide, locate the SNPs that occur in the coding exons* of your gene. As the hg38 assembly does not support the “UCSC Genes” track used in the example exercise, you should use the “NCBI RefSeq” track instead. Referring to the example exercise will assist you in finding the coding exonic SNPs, in your gene. *NB: Many genes have multiple transcript variants that may differ by the inclusion or exclusion of particular exons – as we are interested in whether SNPs occur within an exon of ANY transcript, you should check
to see if the individual SNPs (with unique rsIDs) have been counted more than once (for example one SNP might occur in an exon included in 3 of
4 transcript variants, and another might occur in an exon of all four transcripts – in the former case, the SNP will be counted 3 times and in the latter 4 times. The Galaxy tools “Unique occurrences of each record”, “Group data by a column...” and “Count occurrences of each record” can help identify if particular SNPs are listed more than once (although they all do slightly different things, so care is required!).

Task F4b
Selecting Intronic SNPs: Using the example exercise as a guide, locate the SNPs that occur in the introns* of your gene (HINT: the intermediate Table Browser page has an option that will help). As for the exons, you should use the “NCBI RefSeq” track.
*NB: Genes with multiple transcript variants may differ by the inclusion or fusion of particular introns (when exons are skipped)– as we are interested in whether SNPs occur within an intron of ANY transcript, you should check to see if the individual SNPs (with unique rsIDs) have been counted more than once, as for exons. Also, due to exon skipping some SNPs may be in an exon in one transcript, but in an intron in another transcript (because the exon is skipped). As a result, your list of exonic and intronic SNPs may OVERLAP.

Task F5
Comparing the discovered SNPs: Compare the SNPs that you have located in your analyses, with those listed on the appropriate OMIM page – you may have
located a SNP that is associated with the disease caused by mutations in your gene OR NOT.

G: Questions to answer in your report
The answers to the questions below represent the minimal set of results to demonstrate completion of the practical exercise. Failing to present AN ANSWER to each of these questions will represent insufficient effort in addressing the task of the practical exercise. You should clearly identify your answer to each question in the results section of your report (G1, G2 etc)

Question G1
How many SNPs (as determined by Galaxy access to the latest supported version of dbSNP (“All dbSNP(153)(dbSnp153 are found within the entire coordinate range of your assigned gene (i.e. covered by the Reference mRNA PLUS 5000 bp upstream of the Transcription Start Site (TSS) of your gene? You should indicate the number, the coordinate range, and describe your method.

Question G2                                                                                                                                                                                                                                                    How many SNPs (as determined by Galaxy access to the latest supported version of dbSNP (“All dbSNP(153)(dbSnp153)”) are found within the putative promoter region of your assigned gene (i.e. the 5000 bp upstream of the TSS)? You should indicate the number, the coordinate range, and describe your method.

Question G3
How many SNPs (as determined by Galaxy access to the latest supported version of dbSNP (“All dbSNP(153)(dbSnp153)”) are within coding exons of
your assigned gene. You should indicate the number, the coordinate range, and describe your method.

Question G4
How many SNPs, in total, (as determined by Galaxy access to the latest supported version of dbSNP (“All dbSNP(153)(dbSnp153”) are located i introns of your assigned gene? You should indicate the number, the coordinate range, and describe your method.

Question G5
Are any of the SNPs that you have located in your Galaxy analyses, annotated as mutations that cause the genetic disease with which your gene is associated? If so, indicate their Reference SNP cluster IDs (rsIDs) and / or variant descriptions in your report. You should compare the identifiers (rsIDs) of SNPs, annotated as causative from your disease gene’s OMIM page, with those located in your Galaxy analyses. If you do not find any corresponding SNPs between the two sources, explain why this may be the case.

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