Alexandre Rossi Paschoal

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Abstract Surveying antimicrobial resistance (AMR) is essential to track its evolution and spread. Alignment-based annotation tools use strict identity (>80%) cutoffs to distinguish between non-resistant (NRP) and resistant proteins (ARP) only annotating proteins similar to those in their databases. Deep learning and Hidden Markov Models (HMM) based tools also depend on protein alignment at some level.

Abstract Plant mitochondrial and plastid genomes typically show pervasive, genome-wide transcription. Little is known, however, about the utility of organelle noncoding RNAs, which often make up most of the transcriptome. Here, we suggest that long-read sequencing data combined with dedicated RNA databases could help identify putative functional organelle noncoding transcripts.