SESSION 2

SUMMARY

Bioinformatics analysis of genomic annotations mostly consist on the manipulation of plain text files in which data are encapsulated into columns. The interplay between the rows and the columns of one or more flat files allows the bioinformatician an easy and efficient generation of new knowledge through the comparisons and the calculation of certain statistics. We will use the UCSC Table browser to explore how these files are, focusing on the gene annotations by RefSeq. Galaxy is an excellent web-based genome analysis tool designed for experimental people with no computational background. Basically, it is possible to perform with this web server most tasks that are usually automatized through the use of Linux environments in Bioinformatics labs. Our main purpose here is to show the potential of Galaxy for the management of basic genome information (e.g. lists of genes), while in posterior sessions we will focus on Galaxy services for massive sequencing information.

TABLE OF CONTENTS:

1. The UCSC Table browser

2. Starting issues with Galaxy

3. Playing with gene lists

4. Extracting new knowledge

5. Bibliography

Step 1: The UCSC Table browser

[ETC: 25 mins]

Open the UCSC Table browser

[http://genome.ucsc.edu/cgi-bin/hgTables]

• • Explore the Table browser interface

  • We will work with the mouse genome (mm10 assembly)

  • Select the NCBI RefSeq track and the UCSC RefSeq (refGene) table

  • Finally, let us work with the genome (region)

  • Press the summary/statistics button to see the totals

• • Go back to the Table browser main site

  • Press the get output button (output format: all fields from selected table)

• • Go back to the Table browser main site

  • Define output format to selected fields from primary and related tables

  • Press the get output button

  • Choose name, chrom, strand, txStart, txEnd, name2

  • Press the get output button

• • Go back to the Table browser main site

  • Keep the selected fields from primary and related tables option

  • Press the get output button

  • Switch the refSeqStatus table on

  • Press the allow selection button

  • Click over the option status

  • Press the get output button

  • Explore the current status of the list of transcripts

• • Go back to the Table browser main site

  • Set the output format to sequence (genomic)

  • Choose CDS and extract the sequences. Check the Start/Stop codons

  • Repeat with the promoter sequence (1 Kb) option

  • Play with the options to distinguish each element in a separate sequence

• • Reset the output format to selected fields from primary and related tables

  • Press the (filter) create button

  • Define the search on genes in chr1, strand + and >= 10 exons

  • Press the get output button

  • Add the exonCount to the fields to display

  • Press the get output button

  • Next, add to the filter those genes that are Validated and Reviewed

  • Press the get output button

• • Go back to the Table browser main site

  • Clear the filter

  • Press the paste list button

  • Type these gene names: Nanog, Sox2, Pou5f1, Myc

  • Press the summary/statistics button to see the totals

  • Go back to the Table browser main site

  • Get their name, chrom, strand, txStart, txEnd, name2 and refSeqStatus

  • How many transcripts per gene do you see in the list?

  • Go back to the Table browser main site

  • Change the output format (custom track)

  • Visualize these results (genes) in the graphical UCSC genome browser

• • Explore the LiftOver tool interface

Step 2. Starting issues with Galaxy

[ETC: 10 mins]

Open Galaxy main server or reach other servers here:

1. • [https://usegalaxy.org/]

• • • Register into Galaxy to work with your own account (confirmation e-mail)

• • • Open the Get Data menu on the Tools

    • Click on the UCSC Main table browser

    • Configure UCSC table browser for:

- D. melanogaster (BDGPR5/dm3)

- RefSeq genes, region: genome

- Output format: all fields from the table

• • • Press the get output button

    • Next, press Send query to Galaxy (2-5 mins)

• • • Focus on the History (on the right panel)

    • Click over the name of this job "1 UCSC Main on D. melanogaster..."

    • Press the Information icon to see the file size of this output

    • Press the EYE icon to visualize this dataset

    • Scroll along the content: each line corresponds to a gene transcript

    • Study the name of the attributes (columns)

    • Press the PENCIL to change the Name of this dataset to "Fly genes (dm3)"

Step 3. Playing with gene lists

[ETC: 15 mins]

Let us go to work on our "Fly genes (dm3)" dataset

• • • First, we will select only certain attributes of the transcript:

    • Open the Text Manipulation menu

    • Click on the Cut columns from a table

    • Use the description on the right to select these columns (in this order):

chrom, txStart, txEnd, strand, exonCount, name2, name

• • • Execute the query

    • Open the results with the EYE icon and check the content

    • Edit the Name of this new dataset to "Fly genes (dm3, compact)"

• • • Second, we will narrow the search down to one chromosome

    • Open the Filter and Sort menu

    • Click on the Filter data on any column

    • Use this function to get the list of genes in the chromosome 'chr2L' (positive strand)

    • Execute and check the correctness of the output

    • Refine this list by removing out all genes with less than 10 exons

• • • Click on the Sort data

    • Sort our current dataset by gene name

    • Edit the Name of this new dataset to "Fly genes (dm3, processed)"

• • • Open the Join, Subtract and Group menu

    • Click on the Group data

    • Find out how to count the number of genes in our processed dataset

    • Edit the Name of this new dataset to "Fly genes (dm3, summary)"

Step 4. Extracting knowledge

[ETC: 10 mins]

Let us go to work on our Fly genes (dm3, summary) data set to annotate their GO function:

1. 1. • Open BIOMART in a new tab of your browser

      • Choose the database ENSEMBL GENES

      • Choose the dataset Drosophila melanogaster

      • Click on Filters (left menu)

      • Select chr2L in the REGION box

      • Press the Count button on top to see how many genes are included

      • Click on Attributes (left menu)

      • Open the GENE section and switch on the Gene Name field (off all the other boxes)

      • Open the EXTERNAL section to select GO term accession and the GO Term Name

      • Click on Results (top menu) to visualize a preview

      • Click over the Unique results only box

      • Choose TSV (Tab Separated Value) format instead of HTML (web)

      • Select compressed file (.gz) to save time and space

      • Press the Go button and wait

      • Save the file mart_export.txt.gz in your Desktop

1. 1. • Go back to our Galaxy session

      • Press the Download/Upload icon on top (left, Tools)

      • Choose local files button

      • Press Start, close the window once the uploading is finished

      • A new job has been incorporated into the history

      • Press the EYE icon to visualize this new dataset

      • Edit the Name of this new dataset "Fly genes (GO)"

• • • Open the Join, Subtract and Group menu

    • Click on the Join two Datasets

    • Combine our "Fly genes (dm3, summary)" with the new "Fly genes (GO)"

    • Keep the header lines before executing the job

    • Explore the GO functions that annotate genes in chr2L using this function

    • Edit the Name of this new dataset to "Fly genes (dm3, summary, GO)"

• • • Open the Filter and Sort menu

    • Click on the Select lines

    • Use this service to count how many genes are related to 'dorsal closure'

    • Find how many genes are involved in 'transcription factor activity'

    • Repeat the same for other biological functions (e.g. 'proliferation', 'apoptosis', etc.)

    • Choose a name to your History and open you register of Saved histories

Bibliography

• E. Blanco. Fundamentos de Informatica en Entornos Bioinformaticos (spanish, 242 pages). Editorial UOC. ISBN: 978-84-9029-998-2.

• E. Blanco. Genomica Computacional (spanish, 248 pages). Editorial UOC. ISBN: 978-84-9029-910-4.

• Goecks, J, Nekrutenko, A, Taylor, J and The Galaxy Team. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.Genome Biol. 2010 Aug 25;11(8):R86.

• Blankenberg D, Von Kuster G, Coraor N, Ananda G, Lazarus R, Mangan M, Nekrutenko A, Taylor J. Galaxy: a web-based genome analysis tool for experimentalists. Current Protocols in Molecular Biology. 2010 Jan; Chapter 19:Unit 19.10.1-21.

• Giardine B, Riemer C, Hardison RC, Burhans R, Elnitski L, Shah P, Zhang Y, Blankenberg D, Albert I, Taylor J, Miller W, Kent WJ, Nekrutenko A. Galaxy: a platform for interactive large-scale genome analysis. Genome Research. 2005 Oct; 15(10):1451-5.

For further references, see this Galaxy web site