Coding and regulatory transcriptome comparisons between fertile and infertile spermatozoa identify RNA signatures of male infertility

Transcriptomic analysis of the HPT axis in a model of oligoasthenozoospermia induced by Adenine in rats

Male infertility is most commonly caused by oligozoospermia, and its pathogenesis is still poorly understood at the molecular level. This study used RNA sequencing (RNA-Seq) technology to identify candidate genes and regulatory pathways that regulate semen quality in the hypothalamic, pituitary, and testicular tissues of healthy rats and Adenine-induced oligozoospermia model rats. Semen quality testing and histological analysis of testicular tissues were performed on both groups of rats. We identified 627, 692, and 437 differentially expressed genes in the hypothalamus, pituitary gland, and testes, respectively. Functional analysis indicates that "neuronal projections," "positive regulation of hormone biosynthetic process," and "neuroactive ligand-receptor interaction pathways" are closely related to the hypothalamic-pituitary-testicular (HPT) axis hormone regulation and sperm production. Seven genes (Pomc, Rxfp1, Tac1, Npy, Insl3, Hsd3b3, Lhcgr) have been identified as key candidate genes responsible for regulating sperm quality within the HPT axis, potentially affecting rat reproductive function by influencing testicular development and testosterone secretion. These data provide a theoretical basis for further understanding the molecular mechanisms of reproductive performance in a rat model of oligoasthenozoospermia.

Small RNAs: an ideal choice as sperm quality biomarkers

Spermatozoa were classically known as vehicles for the delivery of the paternal genome to the oocyte. However, in 1962, spermatozoa were discovered to carry significant amounts of RNA in them, which raised questions about the significance of these molecules in such a highly specialized cell. Scientific research in the last six decades has investigated the biological significance of sperm RNAs by various means. Irrespective of what sperm RNAs do, their presence in spermatozoa has attracted attention for their exploitation as biomarkers of fertility. Research in this direction started in the year 2000 and is still underway. A major hurdle in this research is the definition of the standard human sperm RNAome. Only a few normozoospermic samples have been analyzed to define the normal sperm RNAome. In this article, we provide a perspective on the suitability of sperm RNAs as biomarkers of fertility and the importance of defining the normal sperm RNAome before we can succeed in identifying RNA-based biomarkers of sperm quality and fertility. The identification of sperm RNA biomarkers of fertility can be exploited for quality screening of donor sperm samples, explain infertility in idiopathic cases, and RNA therapeutics for the treatment of male infertility.

Proteomic Landscape of Human Sperm in Patients with Different Spermatogenic Impairments

Although the proteome of sperm has been characterized, there is still a lack of high-throughput studies on dysregulated proteins in sperm from subfertile men, with only a few studies on the sperm proteome in asthenozoospermic and oligoasthenozoospermic men. Using liquid chromatography–mass spectrometry (LC-MS/MS) along with bioinformatics analyses, we investigated the proteomic landscape of sperm collected from subfertile men (n = 22), i.e., asthenozoospermic men (n = 13), oligoasthenozoospermic men (n = 9) and normozoospermic controls (n = 31). We identified 4412 proteins in human sperm. Out of these, 1336 differentially abundant proteins were identified in 70% of the samples. In subfertile men, 32 proteins showed a lower abundance level and 34 showed a higher abundance level when compared with normozoospermic men. Compared to normozoospermic controls, 95 and 8 proteins showed a lower abundance level, and 86 and 1 proteins showed a higher abundance level in asthenozoospermic and oligoasthenozoospermic men, respectively. Sperm motility and count were negatively correlated with 13 and 35 and positively correlated with 37 and 20 differentially abundant proteins in asthenozoospermic and oligoasthenozoospermic men, respectively. The combination of the proteins APCS, APOE, and FLOT1 discriminates subfertile males from normozoospermic controls with an AUC value of 0.95. Combined APOE and FN1 proteins discriminate asthenozoospermic men form controls with an AUC of 1, and combined RUVBL1 and TFKC oligoasthenozoospermic men with an AUC of 0.93. Using a proteomic approach, we revealed the proteomic landscape of sperm collected from asthenozoospermic or oligoasthenozoospermic men. Identified abundance changes of several specific proteins are likely to impact sperm function leading to subfertility. The data also provide evidence for the usefulness of specific proteins or protein combinations to support future diagnosis of male subfertility.

miRNA Profiling of Major Testicular Germ Cells Identifies Stage-Specific Regulators of Spermatogenesis

Spermatogenesis is tightly controlled at transcriptional, post-transcriptional, and epigenetic levels by various regulators, including miRNAs. This study deals with the identification of miRNAs critical to the three important stages of germ cell development (spermatocytes, round spermatids, and mature sperm) during spermatogenesis. We used high-throughput transcriptome sequencing to identify the differentially expressed miRNAs in the pachytene spermatocytes, round spermatids, and mature sperm of rat. We identified 1843 miRNAs that were differentially expressed across the three stages of germ cell development. These miRNAs were further categorized into three classes according to their pattern of expression during spermatogenesis: class 1 - miRNAs found exclusively in one stage and absent in the other two stages; class 2 - miRNAs found in any two stages but absent in the third stage; class 3 - miRNAs expressed in all the three stages. Six hundred forty-six miRNAs were found to be specific to one developmental stage, 443 miRNAs were found to be common across any two stages, and 754 miRNAs were common to all the three stages. Target prediction for ten most abundant miRNAs specific to each category identified miRNA regulators of mitosis, meiosis, and cell differentiation. The expression of each miRNA is specific to a particular developmental stage, which is required to maintain a significant repertoire of target mRNAs in the respective stage. Thus, this study provided valuable data that can be used in the future to identify the miRNAs involved in spermatogenic arrest at a particular stage of the germ cell development.

Qualitative and quantitative assessment of sperm miRNAs identifies hsa-miR-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p as potential biomarkers of male infertility and sperm quality

BACKGROUND

In contrast with the preceding stages of the germ cells, spermatozoa are unusually rich in small non-coding RNAs in comparison to the coding RNAs. These small RNAs may have had an essential role in the process of spermatogenesis or may have critical roles in the post-fertilization development. Sporadic efforts have identified a few differentially expressed miRNAs in infertile individuals, which do not replicate in other studies.

METHODS

In order to identify miRNAs signatures of infertility or poor sperm quality, we compared miRNA differential expression data across nine datasets, followed by their analysis by real-time PCR in a case-control study. This was followed by the validation of potential biomarkers in yet another set of cases and controls. For this, total RNA was isolated from 161 sperm samples. miRNA expression levels in infertile cases and fertile controls were measured using TaqMan real-time PCR. Meta-analyses of two miRNAs (hsa-miR-9-3p and hsa-miR-122-5p) were performed using Comprehensive Meta-Analysis Software (version 2). All statistical analyses were performed with the help of GraphPad Prism Software (version 8).

RESULTS

Literature search identified seven miRNAs (hsa-let-7a-5p, hsa-miR-9-3p, hsa-miR-22-5p, has-miR-30b-5p, hsa-miR-103-3p, hsa-miR-122-5p and hsa-miR-335-5p) showing consistent dysregulation in infertility across a minimum of four studies. In the discovery phase, six miRNAs showed strong association with infertility with four (hsa-miR-9-3p, hsa-miR-30b-5p, hsa-miR-103-3p and hsa-miR-122-5p) showing consistent differential regulation across all sub-groups. Receiver operating characteristic (ROC) curve analysis showed that the area under curve of > 0.75 was achieved by three (hsa-mir-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) miRNAs. In the validation phase, these three miRNAs showed consistent association with infertility (hsa-mir-9-3p, hsa-miR-30b-5p, and hsa-miR-122-5p). Meta-analysis on hsa-miR-122-5p showed its significant quantitative association with infertility [Hedge's g = -2.428, p = 0.001 (Random effects)].

CONCLUSIONS

Three miRNAs (hsa-miR-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) have strong linkage with infertility and a high potential as sperm quality biomarkers.

Epigenetic Alterations in Cryopreserved Human Spermatozoa: Suspected Potential Functional Defects

Background: Gene set enrichment analysis (GSEA) was conducted on raw data, and alternative splicing (AS) events were found after mRNA sequencing of human spermatozoa. In this study, we aimed to compare unknown micro-epigenetics alternations in fresh and cryopreserved spermatozoa to evaluate the effectivity of cryopreservation protocols. Methods: Spermatozoa were divided into three groups: fresh spermatozoa (group 1), cryoprotectant-free vitrified spermatozoa (group 2), and conventionally frozen spermatozoa (group 3). Nine RNA samples (three replicates in each group) were detected and were used for library preparation with an Illumina compatible kit and sequencing by the Illumina platform. Results: Three Gene Ontology (GO) terms were found to be enriched in vitrified spermatozoa compared with fresh spermatozoa: mitochondrial tRNA aminoacylation, ATP-dependent microtubule motor activity, and male meiotic nuclear division. In alternative splicing analysis, a number of unknown AS events were found, including functional gene exon skipping (SE), alternative 5′ splice sites (A5SS), alternative 3′ splice sites (A3SS), mutually exclusive exon (MXE), and retained intron (RI). Conclusions: Cryopreservation of spermatozoa from some patients can agitate epigenetic instability, including increased alternative splicing events and changes in crucial mitochondrial functional activities. For fertilization of oocytes, for such patients, it is recommended to use fresh spermatozoa whenever possible; cryopreservation of sperm is recommended to be used only in uncontested situations.