GSE158585
Differential gene expression analysis of Plasmodium falciparum PfCDP KO and WT
Purpose: We identified novel methyl reader domain protein in P. falciparum. Using Next Generation Sequencing, we studied the differential gene expression in PfCDP conditionally deleted P. falciparum versus wild type. Methods: Transcriptome analysis of PfCDP KO vs WT P. falciparum using high throughput RNA sequencing in triplicate (Three controls and three KO samples). The total RNA was isolated from P. falciparum WT and PfCDP KO lines, the quality of RNA was assessed using Nanodrop2000, and Bioanalyzer 2100. RNA  sequencing  libraries  were  prepared  with  Illumina-compatible  NEBNext®  Ultra™  II Directional  RNA  Library  Prep  Kit.  The  double  stranded  cDNA  was  purified using  JetSeq  Beads and the purified  cDNA  was  end-repaired, adenylated and ligated to Illumina multiplex barcode adapters as per NEBNext® Ultra™ II Directional  RNA  Library  Prep  protocol. The  libraries  were  sequenced  on  IlluminaHiSeq  4000  sequencer  for  150  bp  paired-end  chemistry. The  data obtained  from  the  sequencing  run  was  de-multiplexed  using  Bcl2fastq  software  v2.20  and FastQ  files  were  generated  based  on  the  unique  dual  barcode  sequences. The sequencing quality was assessed using the FastQC software ver. 0.11.9. The adaptor sequences and low quality bases (phred quality cutoff set at 30) were trimmed from the reads using the Trim Galore tool ver. 0.6.5. The reads that survived quality check were aligned to the Plasmodium falciparum 3D7 isolate genome (ver. 46) using the Hisat2 read alignment tool. The library strandedness was set as firststrand in accordance with the strand specific library preparation protocol. The alignement output files in the sam format were sorted and converted to the bam format using the Samtools utilities (ver 1.10). Results: The transcript abundance count data was generated using the HTSeq-count function (ver. 0.12.4). Differential gene expression analysis was performed using the DESeq2 package (ver. 3.11) in R programming environment. Genes were classified as deregulated on the basis of log2fold-change cutoff of +1 (for upregulation) and -1 (for downregulation) and p-value cutoff of 0.05. Gene Ontology analysis was performed using the GO tool hosted by the PlasmoDB web database. Data visualisation of the DGE was performed using custom scripts in R programming environment and with DESeq2 package utilities. The DGE analysis has revealed that up regulation of a subsets virulence genes family with significant p values. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: Plasmodoum falciparum transcriptome profile of WT and PfCDP lines