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In this Wiki I'll walk through the transcription-related analyses of Portulaca amilis and P. oleracea that formed the basis for our recent paper

Gilman IS, Moreno-Villena J, Lewis ZR, Goolsby EW, Edwards EJ. submitted. Gene co-expression networks reveal orthology among multiple photosynthetic pathways in Portulaca

that investigated the two photosynthetic systems of Portulaca (C4 and CAM). I'll try to include everything necessary to reproduce our results and figures.

The two main sources of information we are using to investigate Portulaca's C4+CAM system are 1) the P. amilis genome and 2) transcripts from a CAM induction experiment. All raw RNAseq data can be found on the NCBI's SRA under BioProject PRJNA732408, and the P. amilis genome is hosted on Phtyozome. These data will be used separately to understand the transcript abundance of genes and their genomic context in the P. amilis genome. The P. amilis transcriptome was also used during the genome annotation process, but in this wiki I'll stick to

1. P. oleracea de novo transcriptome assembly
2. transcript differential abundance analyses (aka 'differential expression')
3. gene co-expression network analysis
4. cis-element analysis

I've found this review by Babarinde et al. (2019) to be very helpful in understanding the mechanics and design of RNAseq projects. References within that review, as well as this paper by Wilhelmsson et al. (2019) highlight that there are trade offs between different methods, and that employing a few different methods or a consensus of results is best if possible. During the evolution of this paper I worked through many transcriptome assembly processes with varying filtering and trimming stringencies, multiple read quantification tools (RSEM, STAR, Kallisto), multiple clustering techniques (maSigPro, WGCNA, and custom methods), and multiple quantification programs (EdgeR, DESeq2, and sleuth), but I'll mostly show the final analyses here.