Meiosis is the defining event of spermatogenesis. Spermatocytes undergo meiosis to give rise to round spermatids, which in turn metamorphose to flagellated spermatozoa that mature in the epididymis. To characterize the dynamics of gene expression during these important stages of spermatogenesis, undertook transcriptome analysis in >90% pure pachytene spermatocytes and round spermatids, and pure mature sperm of rat by massive parallel deep sequencing. The study has identified 10,719 total transcripts expressed in meiotic and post-meiotic cells, out of which 7,641 were present in all the three cell types. Most abundant transcripts were related to gametogenesis in spermatocytes and spermatids, and mitochondrial energy metabolism in sperm. Importantly, 108 transcripts were specific to spermatocytes, including Cpeb2, Dpf3, H2afy, Haus7, Plcb1, Taf9, and Tdrd7 strongly linked with meiosis. Similarly, 323 transcripts unique to round spermatids included Arpc5, Apoa1, Cntrob, Dcaf17, Ift88, and Ly6k that play essential roles in spermiogenesis. Likewise, 178 transcripts unique to sperm included Camta1, Hoxb1, and Prdx6 having assigned roles in fertility and/or embryonic development. Levels of ~16% transcripts declined from spermatocytes to sperm while two (Cd300e and Ddx17) increased. New candidate genes with possible roles in meiosis (91), spermiogenesis (298), and sperm function (171), have been identified. This study has provided new potential targets for contraception and/or treatment of male infertility. (Mol Reprod Dev, 2019; doi: 10.1002/mrd.23278)

Peripheral blood DNA methylation profiling reveals differential methylation in male infertility

Peripheral blood differential DNA methylation was studied in oligozoospermic infertile men in comparison with normozoospermic fertile controls in a case-control study. Blood samples were obtained from azoospermic and oligozoospermic infertile patients (n = 6) and normozoospermic fertile controls (n = 6) in the discovery phase, and oligo/asthenozoospermic infertile men (n = 11) and normozoospermic fertile controls (n = 10) in the validation phase followed by DNA isolation and methylation analysis. DNA methylation values were analyzed using genome wide methylation 450K BeadChip array, followed by deep sequencing of selected regions for methylation analysis in the neighborhood regions of differentially methylated CpGs. 329 differentially methylated CpG spots were identified, out of which 245 referred to the genes, representing 170 genes. Deep-sequencing analysis confirmed the methylation pattern suggested by 450K array. A thorough literature search suggested that 38 genes play roles in spermatogenesis (PDHA2, PARP12, FHIT, RPTOR, GSTM1, GSTM5, MAGI2, BCAN, DDB2, KDM4C, AGPAT3, CAMTA1, CCR6, CUX1, DNAH17, ELMO1, FNDC3B, GNRHR, HDAC4, IRS2, LIF, SMAD3, SOD3, TALDO1, TRIM27, GAA, PAX8, RNF39, HLA-C, HLA-DRB6), are testis enriched (NFATC1, NMNAT3, PIAS2, SRPK2, WDR36, WWP2), or show methylation differences between infertile cases and controls (PTPRN2, RPH3AL). This study conclude a statistically significant correlation between peripheral blood DNA methylation and male infertility, raising the hope that epigenome-based blood markers can be used for screening male infertility risk. The study also identified new candidates for spermatogenesis and fertility (FertilSteril. 2019; 112(1): 61-72.e1).

Fig : Heat map showing methylation level (β-value) in cases and controls, bar graph showing the number of hyper- and hypo-methylated CpG spots, and box whisker plot showing the average β-value in cases and controls, b) The distribution of DMCs according to the island regions, c) The distribution of DMCs according to the genomic regions, d) Venn diagram showing the distribution of DMCs in genomic regions with respect to different transcript forms

Genome-wide differential methylation analyses identify methylation signatures of male infertility

Methylation changes in a number of genes have been correlated with reduced sperm count and motility. To discover whether methylation changes in sperm DNA correlate with infertility, this case-control study used spermatozoal DNA from 38 oligo-/oligoastheno-zoospermic infertile patients and 26 normozoospermic fertile men. Genome-wide methylation analysis was undertaken using 450 K Bead Chip on spermatozoal DNA from six infertile and six fertile men to identify DMCs. This was followed by deep sequencing of spermatozoal DNA from 32 infertile patients and 20 fertile controls. Loss of spermatogenesis and fertility was correlated with 1680 differentially-methylatedCpGs (DMCs) across 1052 genes. A total of 1680 DMCs were identified, out of which 1436 were hypermethylated and 244 were hypomethylated. Classification of DMCs according to the genes identified BCAN, CTNNA3, DLGAP2, GATA3, MAGI2 and TP73 among imprinted genes, SPATA5, SPATA7, SPATA16 and SPATA22 among spermatogenesis-associated genes, KDM4C and JMJD1C, EZH2 and HDAC4 among genes which regulate methylation and gene expression, HLA-C, HLA-DRB6 and HLA-DQA1 among complementation and immune response genes, and CRISPLD1, LPHN3 and CPEB2 among other genes. Genes showing significant differential methylation in deep sequencing, i.e. HOXB1, GATA3, EBF3, BCAN and TCERG1L, are strong candidates for further investigations. The role of chance was ruled out by deep sequencing of select genes. DMCs can serve as markers for inclusion in infertility screening panels, particularly those in the genes showing differential methylation consistent with previous studies. The genes validated by deep sequencing are strong candidates for investigations of their roles in spermatogenesis (Hum Reprod. 2018; 33(12): 2256-2267).

Team Members:

Fig: Heat map of genome-wide DNA methylation. (B) Histogram showing the number of differentially-methylated CpGs (DMCs) across various β-values. (C) Box plot comparing mean β-values for hypermethylated and hypomethylated DMCs between cases and controls. (D) Percentage of DMCs showing hypermethylation and hypomethylation. (E) Distribution of DMCs on the basis of organization of gene transcript structure. (F) Distribution of DMCs on the basis of CpG island and neighborhood regions.

Poly(ADP-ribose)polymerase-2 is essential during endometrial receptivity for blastocyst implantation and regulated by the Caspase-8 dependent manner

Endometrial receptivity for embryo implantation is one of the critical events to modulate the pregnancy establishment. Understanding of endometrial receptivity molecular signaling may be helpful for contraception target exploration to control the undesired pregnancy at the same time, facilitating the assisted reproductive technologies (ART) to achieve the pregnancy in infertile individuals. We have been mapping the endometrial receptivity regulating factors, molecules since past few years; however, endometrial receptivity is a very complex process. One of the important aspects of pregnancy establishment is endometrial receptivity, where several molecular-signaling, including caspases and PARPs, are involved. In previous reports, observed PARP-1 involvement during the acquisition of the endometrial receptivity, which expression was seen in an endometrial receptivity dependent manner (Joshi et al., 2014). It has been found that PARP-1 can act together with PARP-2 in cellular functions. Therefore, investigated the PARP-2 roles during endometrial receptivity acquisition. Using the mouse model, observed PARP-2 prominent expression in the implantation region during the receptivity phase of the endometrium. The pseudopregnancy stage of endometrium presents the basal level of PARP-2 expression. However, in the contrary, the PARP-2 known regulator Caspase-8 expression and activity suppressed during the endometrial receptivity phase and remain high during the pseudopregnancy in the mouse model, suggesting the down regulation of caspase-8 to maintain the PARP-2 activity for the acquisition of endometrial receptivity. Functional intraluminally PARP-2 activity inhibition renders the poor blastocyst implantation due to poor endometrial receptivity, although, the hatched blastocysts were seen unaffected.

Further, in humanoid embryo implantation assay, found that PARP-2 activity inhibited endometrial epithelial cells resulted in the reduced outgrowth of mouse blastocyst, suggesting one of the essential functions of PARP-2 in the endometrial receptivity for blastocyst implantation. Since the caspase-8 activity was negatively regulated and PARP-2 expression was upregulated during the endometrial receptivity phase, determined whether Caspase-8 activity leads to PARP-2 downregulation (cleavage). Interestingly, in the human endometrial epithelial cells inhibition of Caspase-8 activity, the PARP-2 expression was upregulated, confirming the caspase-8 dependent negative regulation of PARP-2 during the non-receptive stage of the endometrium. Overall, caspase-8 expression and activity downregulate in result the PARP-2 expression remains stabilized to acquire the endometrium receptivity for blastocyst implantation.

Replenishment of ovarian reserve

Infertility is one of the serious adult concerns globally, common in both men and women. The major causes for female infertility are gonadal insufficiency as well as developmentally incompetent oocyte maturation. In order to understand gonadal insufficiency, clinically relevant mouse model was established with dysfunctional gonads through chemotherapeutic interventions. Chemotherapeutic agents are used for the treatment of cancer patients but frequently cause damage to the ovary due to germ cell toxicity that leads to infertility in females. Further, this model was validated by checking the expression of oocyte maturation marker namely oocyte expressed protein (OOEP) both at transcriptional as well as translational level.

Established rodent model with dysfunctional gonads is being utilized to assess the therapeutic potential of stem cells as well as natural plant extracts for gonadal restoration. Through this model, quite a few oocyte maturation markers were identified and need to be characterized further. Moreover, human orthologues of these oocyte maturation markers will be identified to predict oocyte maturation and to correlate these findings with the clinical significance. Other than this, rat model of Benign Prostatic Hyperplasia (BPH) has been established in lab and numbers of compounds have been screened to assess their therapeutic effect on BPH; one of these natural compounds has been licensed to Lumen for further clinical trials.