Footprints of a trypanosomatid RNA world: pre-small subunit rRNA processing by spliced leader addition trans-splicing

The addition of a capped mini-exon [spliced leader (SL)] through trans-splicing is essential for the maturation of RNA polymerase (pol) II-transcribed polycistronic pre-mRNAs in all members of the Trypanosomatidae family. This process is an inter-molecular splicing reaction that follows the same basic rules of cis-splicing reactions. In this study, we demonstrated that mini-exons were added to precursor ribosomal RNA (pre-rRNA) are transcribed by RNA pol I, including the 5' external transcribed spacer (ETS) region. Additionally, we detected the SL-5'ETS molecule using three distinct methods and located the acceptor site between two known 5'ETS rRNA processing sites (A' and A1) in four different trypanosomatids. Moreover, we detected a polyadenylated 5'ETS upstream of the trans-splicing acceptor site, which also occurs in pre-mRNA trans-splicing. After treatment with an indirect trans-splicing inhibitor (sinefungin), we observed SL-5'ETS decay. However, treatment with 5-fluorouracil (a precursor of RNA synthesis that inhibits the degradation of pre-rRNA) led to the accumulation of SL-5'ETS, suggesting that the molecule may play a role in rRNA degradation. The detection of trans-splicing in these molecules may indicate broad RNA-joining properties, regardless of the polymerase used for transcription.

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.