Principal Component Analysis of lncRNAs expression in contrasting genotypes - labbces/sugarcane_RNAome GitHub Wiki

Principal Component Analysis (PCA)

The PCA of the coding and non-coding genes from contrasting genotypes was plotted using the following pipeline in R.

Correr2020 - PCA Analysis of contrasting genotypes in fiber and sugar content

Genotypes are clustered based on biomass accumulation (high biomass and low biomass groups).

The genotypes in the left PCA are clustered in the same way as in the PCA published by the authors (right), available here

Note: Only protein-coding RNAs were quantified and analyzed in the authors' PCA, whereas in the present study, I am analyzing the entire composition of RNAs (non-coding and coding). The percentage explained by components 1 and 2 for the PCA of the entire set of RNAs is low compared to the PCA of coding RNAs, one explanation for this could be the high variability of non-coding RNAs not specific to the conditions presented

Perlo2022 - PCA Analysis of contrasting genotypes in fiber and sugar content

The internodes from different collections are separated by the clusters.

The clusters appear similar to the PCA clustering published by the authors (right), available here

Note: We observed an overlap in the two PCAs for internodes 8 from collections 1 and 2, and internodes Ex-5.

Hoang2017 - PCA Analysis of contrasting genotypes in fiber and sugar content

Genotypes do not appear to cluster based on sugar content (left) and tissue type (right).

This phenomenon may be attributed to variability in the quality of the RNA-seq data. These samples seem to be degraded, as evidenced by significant amounts of rRNA in some, as indicated in this table.