bitotech and ms access

UMUC RNA-Seq project

Basic steps:

1- We will use a tool called Bowtie to align our RNA-Seq data. The latter are in files called fastq files. They need to be aligned to a reference genome. These are Illumina sequence files. Read up on what Illumina is and what steps are involved RNA-Seq experiments if you are not familiar with those terms. YouTube has a couple of nice videos that shows you how the sequences are generated.

2- First download and run Bowtie using the example data given, here are some links for that: http://bowtie-bio.sourceforge.net/index.shtml AND http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml#getting-started-with-bowtie-2-lambda-phage-example

3- You can run Bowtie from Windows, or you can download and install BioLinux which has it already installed (and a host of other Bioinformatics tools). Here is the link for that: http://environmentalomics.org/bio-linux/

4- Once you have Bowtie up and running you can align the actual samples. The sample descriptions are attached in the Excel file. They come from a plant named Arabidopsis thaliana.

5- You will need to download the genome of A. thaliana to align the reads against. Here is the link to get that: ftp://ftp.ensemblgenomes.org/pub/plants/release-28/fasta/arabidopsis_thaliana/ You want the cds file (coding regions only).

6- Next download the fastq files, I will be sending you a separate email sharing those files with you from my OneDrive.

7- Align all the samples with the reference genome

8- Write a script, Perl or Phyton, to get the read counts for every gene\cds

9- Do differential expression analysis comparing the treatment samples against the controls. We’ll use DEGSeq or DESeq for that, both are R based tools.

10- Put the data, raw read counts, and differential expression results in a database. Access is fine, but you can use whatever database you like.

11- Develop search forms to allow user to query data for specific genes and\or gene descriptions.

Reference papers:

Here are a couple of papers from my lab that you can use to see how the analysis is going to be done and what is expected in the database.

1: Darwish O, Slovin JP, Kang C, Hollender CA, Geretz A, Houston S, Liu Z,

Alkharouf NW. SGR: an online genomic resource for the woodland strawberry. BMC Plant Biol. 2013 Dec 23;13:223. doi: 10.1186/1471-2229-13-223. PubMed PMID: 24364888; PubMed Central PMCID: PMC3878773.

2: Kang C, Darwish O, Geretz A, Shahan R, Alkharouf N, Liu Z. Genome-scale

transcriptomic insights into early-stage fruit development in woodland strawberry Fragaria vesca. Plant Cell. 2013 Jun;25(6):1960-78. doi: 10.1105/tpc.113.111732. Epub 2013 Jun 28. PubMed PMID: 23898027; PubMed Central PMCID: PMC3723606.