The composition of human sperm sncRNAome: a cross-country small RNA profiling

Over the last decade, numerous studies have implicated sperm-borne small non-coding RNAs (sncRNAs) in fertility and transgenerational inheritance. Spermatozoa contain a variety of small RNAs; however, inter-individual and inter-population variations in the human sperm sncRNA content (sncRNAome) have not yet been ascertained.

We performed sncRNA sequencing in 54 normozoospermic proven fertile Indian donors. We also obtained a second semen sample from 13 donors and a third semen sample from eight donors and repeated sncRNA sequencing. To better understand sperm sncRNAome similarities and variations, sncRNA sequencing data for eligible Chinese (n = 87), US (n = 14), and Spanish (n = 2) normozoospermic (fertile or presumptive fertile) samples were downloaded and analyzed in a uniform manner. sncRNA data were compared within and across populations to identify similarities and differences.

In Indian samples, rsRNAs (13.71-78.76%), YsRNAs (0.64-76.53%) and tsRNAs (5.63-35.16%) constituted the major fraction and miRNAs, piRNAs, mt-tsRNAs, and other sncRNAs constituted the minor fraction. Across three other populations, rsRNAs (11-80%) and tsRNAs (10-60%) constituted the major fraction, and YsRNAs (0.62-4.28%), miRNAs (0.41-7.37%), piRNAs (1.37-4.36%), mt-tsRNAs (0.14-4.33%), and other sncRNAs constituted the minor fraction. Only 47 miRNAs were consistent across the Indian samples, and only 17 miRNAs were consistent across the four populations. Interestingly, all piRNAs detected in Indian samples were derived from the chromosome 15 piRNA cluster, which were also predominantly present in other populations. tRNA-Gly-GCC contributed approximately 50% of the tsRNA pool across all populations. The mt-tsRNAs also originated majorly from one mt-tRNA that differed across populations. Among the rsRNAs, the maximum number of reads belonged to 28S, followed by 18S, 5S, 5.8S, and 45S in decreasing order. Y4sRNAs were the most abundant YsRNAs, while the second most common contributor differed across populations.

The human sperm sncRNAome has a 'core component' that shows small variations and a 'peripheral component' that shows significant variations across individuals and populations. The availability of the normal human sperm sncRNAome would help delineate biologically meaningful variations from sample-to-sample natural/random variations.