Transfer RNAs (tRNAs) are highly-modified small non-coding RNAs that play a pivotal role in protein translation. Dysregulation in tRNA abundances or their modifications can lead to biased translation of protein-coding transcripts. Despite their central function, we currently lack a simple and cost-effective method to simultaneously quantify both tRNA abundances and modifications in a systematic manner. Here, we develop Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations, which provides quantitative estimates of both tRNA modifications and abundances in a single experiment. Notably, we demonstrate that default nanopore sequencing settings discard the vast majority of tRNA reads that are being sequenced, leading to poor sequencing yields and, more importantly, biased representations of the abundances of tRNA populations based on their transcript length. To overcome this limitation, we demonstrate that re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads, and enables us to accurately recapitulate the expected tRNA abundances. We then apply Nano-tRNAseq to wild type and mutant S. cerevisiae tRNA populations, finding that tRNA modification changes can be detected with single nucleotide and isoacceptor resolution. Indeed, we show that loss of Pus4-dependent ?55 is accompanied by a decrease of m1A58 and m5U54, demonstrating that Nano-tRNAseq is a powerful approach to reveal crosstalks and interdependencies between different tRNA modification types within the same molecule. Finally, we expose S. cerevisiae cells to diverse stress sources, finding that oxidative stress, but not heat stress, causes significant deadenylation of CCA ends in multiple tRNA isoacceptors, likely leading to rapid repression of translation. Overall, Nano-tRNAseq makes tRNA sequencing simple and cost-effective, and allows simultaneous capture of differential tRNA modifications and tRNA abundances in a single experiment.