Standardizing RNA quality is key to interpreting RNA-seq data as a compromised sample can mask the underlying biology. The challenge remains when evaluating RNA quality in samples with high RNA fragmentation. For example, programmed fragmentation and cytoplasmic expulsion, integral to sperm maturation, is a prime example of the complexities of interpreting RNA-seq data, given that fragmentation can be random and\or targeted. To meet this challenge, we developed an algorithm that accurately measures RNA quality in samples with high fragmentation, such as spermatozoa. The integrity of 1,000 previously identified abundant sperm transcripts were independently visualized and evaluated using the Transcript Integrity Index (TII) algorithm to identify intact transcripts. Full-length transcripts from visual and the TII algorithm were evaluated for testis preference in humans using the GTEx tissues database. Samples were then filtered by the Interquartile Range (IQR), identifying those in which the greatest number of transcripts failed to pass the visual or TII thresholds. Transcript lists were overlapped, forming the set of intact transcripts used as TII standards. Each sample was re-evaluated as a function of this TII set of intact transcripts, with poor quality samples identified as those failing in the largest number of transcripts. While ontologically enriched in roles related to spermatogenesis and/or fertilization, samples did not segregate based on birth outcome. The TII algorithm proved an effective means to identify samples of similar quality from sperm, a cell type enriched in biologically fragmented RNAs. The algorithm should facilitate other studies using samples compromised by high levels of RNA fragmentation, such as Formalin-Fixed Paraffin-Embedded samples. Requisite to assessing male health, TII provides a solution to the long-sought-after standard that identifies samples of similar quality.
Keywords: RNA-seq; Sperm; sample quality; transcript integrity.