Details of task: 

Transcriptome analysis experiments enable researchers to characterize transcriptional activity (coding and non-coding), focus on a subset of relevant target genes and transcripts, or profile thousands of genes at once to obtain a global picture of genome activity. Gene expression analysis studies can provide a snapshot of actively expressed genes and transcripts under various conditions. In BTH3752 Lab Module 2, genes that express differently in both A. baumannii sensitive and resistant strains upon antibiotics treatment will be analyzed by comparing their transcriptomes. Briefly, A. baumannii will be treated with sublethal dose of antibiotics then the total RNA of the control and treated bacteria will be extracted and be sequenced using MiSeq and the resulting sequences will be analyzed using Galaxy (https://usegalaxy.org.au/)a.

 

In this exercise, you will learn how to perform an RNA-seq data analysis to investigate the transcriptome of antibiotics-sensitive and -resistant A. baumannii towards imipenem (antibiotics). There are 2 parts in this module. In part I, you will perform data analysis using Galaxy to map your data and generate a gene count table. In part II, you will be provided with specific sets of gene count tables from class results to allow you to perform your assigned comparative data analysis (refer to the table below). You will not use your own gene count table in part II. Each group will be provided with a dataset consisting of two fastq files, a genome fasta sequence and Prokka annotation files from A. baumannii ATCC BAA 1790. These files can be downloaded from the shared Google Driveb (Part I datasets available in Week 3, Part II datasets available in Week 5). Refer to the Table 1 to decide which dataset you should download.

 

Important notes for data analysis:

  • The fastq files are quite large in size (~ 1GB each file). It is recommended to download and upload these files via WiFi connection instead of mobile data.
  • You are encouraged to familarise yourself with the Galaxy pipeline by completing a tutorialc in Galaxy. Please note that the actual data analysis performed in this Lab Module will differ from the one described in the tutorial. You should always consult the RNASeq Data analysis manuald to perform the RNA-seq analysis. Do not hesitate to contact your TAs should you have questions.
  • You must report the final outcome of your analysis in the lab report that highlights the key findings and discuss the implications of these results. Your results should be discussed within the context of this project (i.e. in relation to baumannii and antimicrobial resistance). Please refer to the marking rubric for detailed marking criteria.

a-d: You can find the links and the document in Lab Module 2 section.

 

 

 

 

 

 

Table 1. Grouping for data analysis

Part I – data mapping (fastq files to be analyzed by each group) Group Part II – data comparison (tabular files to be analyzed by each group) Group
Resistant (+ 0.1MIC Imipenem):

Replicate 1

1605_0_1_1lib_1.fastq.gz

1605_0_1_1lib_2.fastq.gz

 

Replicate 2

1605_0_1_2lib_1.fastq.gz

1605_0_1_2lib_2.fastq.gz

 

 

1

 

 

 

2

Sensitive vs Resistant (no treatment)

 

65-0MIC_1.tabular

65-0MIC_2.tabular

BAA1605-0MIC_1.tabular

BAA1605-0MIC_2.tabular

1 & 2
Sensitive (+ 0.1MIC Imipenem):

Replicate 1

65_0_1_1lib_1.fastq.gz

65_0_1_1lib_2.fastq.gz

 

Replicate 2

65_0_1_2lib_1.fastq.gz

65_0_1_2lib_2.fastq.gz

 

 

3

 

 

 

4

Sensitive vs Resistant (0.1 MIC imipenem)

 

65-0.1MIC_1.tabular

65-0.1MIC_2.tabular

BAA1605-0.1MIC_1.tabular

BAA1605-0.1MIC_2.tabular

3 & 4
Resistant (no treatment):

Replicate 1

1605_0MIC_1lib_1.fastq.gz

1605_0MIC_1lib_2.fastq.gz

 

Replicate 2

1605_0MIC_2lib_1.fastq.gz

1605_0MIC_2lib_2.fastq.gz

 

 

5

 

 

 

6

Resistant (no treatment) vs Resistant (0.1

MIC imipenem)

 

BAA1605-0MIC_1.tabular

BAA1605-0MIC_2.tabular

BAA1605-0.1MIC_1.tabular

BAA1605-0.1MIC_2.tabular

5 & 6
Sensitive (no treatment): Replicate 1

65_0MIC_1lib_1.fastq.gz

65_0MIC_1lib_2.fastq.gz

 

Replicate 2

65_0MIC_2lib_1.fastq.gz

65_0MIC_2lib_2.fastq.gz

 

 

7

 

 

 

8

Sensitive (no treatment) vs Sensitive (0.1 MIC imipenem)

 

65-0MIC_1.tabular

65-0MIC_2.tabular

65-0.1MIC_1.tabular

65-0.1MIC_2.tabular

 

7 & 8

 

Submission:

Please use the BTH3752 Data Analysis template for your writing. Convert the complete work to PDF file and submit to Moodle dropbox before the due date. Submission with Turnitin report ≥ 20% similarity will not be accepted.

 

Format:

Name/Student ID/Course ID

  • Methods

Flowchart of data analysis methods

  • Results
    1. Mapping statistics
    2. Gene count
    3. Differential gene expression (DGE) analysis
    4. Heatmaps & Cluster of Orthologous genes of DGE
  • Discussion
    1. Major findings
    2. Implications of the study
    3. Limitation and future work
  • Conclusion/Summary
  • References  

Citations and referencing according to Harvard formatting o Please include citations in text when used

o http://www.lib.monash.edu.au/tutorials/citing/harvardjournals.html

 

Important note:

Word limit is applied to Discussion (<1000) only. In-text citations, in-text quotations, and subheadings (if any) are included in word count. No plus/minus 10% of word count is permissible in BTH3752 assignments.

0.5 mark will be deducted for all work with word count exceeded the limit.

 

Rubric: 

  n/a F P C D HD
1. Method (10M)            
**Complete workflow diagram included 0 1 2 3 4 5
**All steps and program included with description 0 1 2 3 4 5
             
2. Results (35M)            
** Mapping statistics: Complete mapping statistics provided 0 1 2 3 4 5
**Gene count: Table in correct format included. 0 1 2 3 4 5
**IGB viewer: Visualise the gene with the highest read count. Screenshot of the IGB is provided. 0 1 2 3 4 5
**Differential gene expression (DGE): Minimum of 2 suitable & correct figures/tables 0 1 2 3 4 5
**Differential gene expression (DGE): Figures/tables fully describe major findings 0 1 2 3 4 5
** Heatmaps & Cluster of Orthologous genes of DGE:

Minimum of 2 suitable & correct figures/tables

0 1 2 3 4 5
** Heatmaps & Cluster of Orthologous genes of DGE:

Figures/tables fully describe major findings

0 1 2 3 4 5
             
3. Discussion (35M)            
**Major finding 1: Finding with well-elaborated significance 0 1 2 3 4 5
**Major finding 1: Succinct discussion in the context of previous studies with citation of relevant papers 0 1 2 3 4 5
**Major finding 2: Finding with well-elaborated significance 0 1 2 3 4 5
**Major finding 2: Succinct discussion in the context of previous studies with citation of relevant papers 0 1 2 3 4 5
**Implications of the study: Highlight at least 1 novelty or the lack of it in this study 0 1 2 3 4 5
**Implications of the study: Discussed in the context of previous studies, cite relevant papers 0 1 2 3 4 5
**Synthesis: Reasonable & realistic points of limitations and future work 0 1 2 3 4 5
             
4. Conclusion (5M)            
**Synthesis: Succinct and precise conclusion derived from discussion 0 1 2 3 4 5
             
5. References (5M)            
**In text citations in main text: References are provided to support statements and arguments. References in text match those in the list 0 0.6 1.2 1.8 2.4 3
** Citations and referencing according to Harvard formatting 0 0.2 0.4 0.6 0.8 1
** Figures, tables, and diagrams are cited appropriately 0 0.2 0.4 0.6 0.8 1
             
6. Miscellaneous (10M)            
** Length: Length of discussion is appropriate (< 1000 words)

(exceeding the limit 1000 words would result in a deduction

of 1M for every extra 100 words)

0 1 2 3 4 5
** Grammar & clarity: Sentences are well phrased with good grammar. No spelling error is found. Writing is clear and concise 0 0.5 1.0 1.5 2.0 2.5
** Format: Use provided template. 12pt font Times New

Roman with 1.5 line spacing on standard A4 pages

0 0.5 1.0 1.5 2.0 2.5

 

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