RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set (n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 39 untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. FASEB J. 31, 3298-3308 (2017). www.fasebj.orgRNA degradation is an intrinsic part of cellular metabolism and gene expression regulation (1) that continues after cell death. It occurs in ante-and postmortem tissues, as well as in extracted RNA during storage and handling. It is a known confounder for all RNA-based gene expression quantification methods, including Northern blot (2), quantitative RT-PCR (3), expression microarrays (4), and RNA sequencing (5, 6). Considerable effort is routinely devoted to ensuring maximum practicable RNA quality before conducting such studies. RNA sequencing (RNA-Seq) is gaining dominance as a method of choice for transcriptome-wide gene expression quantification because of its wide applicability, sensitivity, and increasing availability (7). At present, there is no consensus on the extent of RNA-quality-dependent confounding and what methods should be applied to get accurate differential expression estimates (5, 8) from RNA sequencing (RNA-Seq) data. The primary method to mitigate it is to select a tissue-, organism-, and quantification platform-specific RNA integrity cutoff and to assume that RNA degradation does not have a noticeable effect on samples above this threshold. In many cases, however, practical limitations preclude the possibility of obtaining RNA of pristine quality. Such cases may include samples collected in clinical settings, postmortem or legacy samples, and ot...