show Abstracthide AbstractNext-generation RNA sequencing (RNA-seq) has revolutionized our ability to analyze transcriptomes. Current RNA-seq methods are highly reproducible, but each has biases resulting from different modes of RNA preparation, reverse transcription, and adaptor addition, leading to variability between methods. Moreover, the transcriptome cannot be profiled comprehensively as highly structured RNAs, such as tRNAs and snoRNAs, are refractory to conventional RNA-seq methods. Recently, we developed a new method for strand-specific RNA-seq using thermostable group II intron reverse transcriptases (TGIRTs). TGIRTs have high processivity and fidelity plus a novel template-switching activity that enables addition of an RNA-seq adaptor during cDNA synthesis without using RNA-ligase. Here, we used TGIRT-seq to obtain RNA-seq datasets from well-characterized human RNA reference samples and compared them to previous datasets obtained for these RNAs by the Illumina TruSeq v2 and v3 methods. We find that TGIRT-seq recapitulates the relative abundance of human transcripts and RNA spike-ins in ribo-depleted, fragmented RNA samples similarly to the non-strand-specific TruSeq v2 and better than the strand-specific TruSeq v3 method. Moreover, TGIRT-seq is simpler and more strand-specific than TruSeq v3, gives more uniform 5’ to 3’ gene coverage than either TruSeq method, and eliminates sequence biases from random hexamer priming inherent to TruSeq. TGIRT-seq also detects more splice junctions, particularly near the 5’ ends of genes than does TruSeq v3, even in fragmented RNAs. Finally, TGIRT-seq enables simultaneous profiling of mRNAs and lncRNAs in the same RNA-seq as structured small ncRNAs, including tRNAs, which are essentially absent from TruSeq libraries.