Systematic comparison of the protein-protein interaction databases from a user's perspective.

In absence of periodic systematic comparisons, biologists/bioinformaticians may be forced to make a subjective selection among the many protein-protein interaction (PPI) databases and tools. We conducted a comprehensive compilation and comparison of such resources. We compiled 375 PPI resources, short-listed 125 important ones (both lists are available at startbioinfo.com), and compared the features and coverage of 16 carefully-selected databases related to human PPIs. We quantitatively compared the coverage of 'experimentally verified' as well as 'total' (experimentally verified and predicted) PPIs for these 16 databases. Coverage was compared in two ways: (a) PPIs obtained in response to gene queries using the web interfaces were compared. As a query set, 108 genes expressed differently across tissues (specific to kidney, testis, and uterus, and ubiquitous - i.e., expressed in 43 human normal tissues) or associated with certain diseases (breast cancer, lung cancer, Alzheimer's, cystic fibrosis, diabetes, and cardiomyopathy) were chosen. The coverage was also compared for the well-studied genes versus the less-studied ones. The coverage of the databases for high-quality interactions was separately assessed using a set of literature curated experimentally-proven PPIs (gold standard PPI-set); (b) the back-end-data from 15 PPI databases was downloaded and compared. Combined results from STRING and UniHI covered around 84% of 'experimentally verified' PPIs. Approximately 94% of the 'total' PPIs available across the databases were retrieved by the combined use of hPRINT, STRING, and IID. Among the experimentally verified PPIs found exclusively in each database, STRING contributed around 71% of the hits. The coverage of certain databases was skewed for some gene-types. Analysis with the gold-standard PPI-set revealed that GPS-Prot, STRING, APID, and HIPPIE, each covered ~70% of the curated interactions. The database usage frequencies did not always correlate with their respective advantages, thereby justifying the need for more frequent studies of this nature.

RNA polymerase II pausing is essential during spermatogenesis for appropriate gene expression and completion of meiosis.

Male germ cell development requires precise regulation of gene activity in a cell-type and stage-specific manner, with perturbations in gene expression during spermatogenesis associated with infertility. Here, we use steady-state, nascent and single-cell RNA sequencing strategies to comprehensively characterize gene expression across male germ cell populations, to dissect the mechanisms of gene control and provide new insights towards therapy. We discover a requirement for pausing of RNA Polymerase II (Pol II) at the earliest stages of sperm differentiation to establish the landscape of gene activity across development. Accordingly, genetic knockout of the Pol II pause-inducing factor NELF in immature germ cells blocks differentiation to spermatids. Further, we uncover unanticipated roles for Pol II pausing in the regulation of meiosis during spermatogenesis, with the presence of paused Pol II associated with double-strand break (DSB) formation, and disruption of meiotic gene expression and DSB repair in germ cells lacking NELF.

Transcriptomic analysis of the Non-Obstructive Azoospermia (NOA) to address gene expression regulation in human testis.

There is a need to understand the molecular basis of testes under Non-Obstructive Azoospermia (NOA), a state of failed spermatogenesis. There has been a lack of attention to the transcriptome at the level of alternatively spliced mRNAs (iso-mRNAs) and the mechanism of gene expression regulation. Hence, we aimed to establish a reliable iso-mRNA profile of NOA-testes, and explore molecular mechanisms - especially those related to gene expression regulation. We sequenced mRNAs from testicular samples of donors with complete spermatogenesis (control samples) and a failure of spermatogenesis (NOA samples). We identified differentially expressed genes and their iso-mRNAs via standard NGS data analyses. We then listed these iso-mRNAs hierarchically based on the extent of consistency of differential quantities across samples and groups, and validated the lists via RT-qPCRs (for 80 iso-mRNAs). In addition, we performed extensive bioinformatic analysis of the splicing features, domains, interactions, and functions of differentially expressed genes and iso-mRNAs. Many top-ranking down-regulated genes and iso-mRNAs, i.e., those down-regulated more consistently across the NOA samples, are associated with mitosis, replication, meiosis, cilium, RNA regulation, and post-translational modifications such as ubiquitination and phosphorylation. Most down-regulated iso-mRNAs correspond to full-length proteins that include all expected domains. The predominance of alternative promoters and termination sites in these iso-mRNAs indicate their gene expression regulation via promoters and UTRs. We compiled a new, comprehensive list of human transcription factors (TFs) and used it to identify TF-'TF gene' interactions with potential significance in down-regulating genes under the NOA condition. The results indicate that RAD51 suppression by HSF4 prevents SP1-activation, and SP1, in turn, could regulate multiple TF genes. This potential regulatory axis and other TF interactions identified in this study could explain the down-regulation of multiple genes in NOA-testes. Such molecular interactions may also have key regulatory roles during normal human spermatogenesis.