Transcription factors of the Sox protein family contain a DNA-binding HMG box and are key regulators of progenitor cell fate. Here, we report that expression of Sox30 is restricted to meiotic spermatocytes and postmeiotic haploids. mutant males are sterile owing to spermiogenic arrest at the early round spermatid stage. Specifically, in the absence of Sox30, proacrosomic vesicles fail to form a single acrosomal organelle, and spermatids arrest at step 2-3. Although most mutant spermatocytes progress through meiosis, accumulation of diplotene spermatocytes indicates a delayed or impaired transition from meiotic to postmeiotic stages. Transcriptome analysis of isolated stage-specific spermatogenic cells reveals that Sox30 controls a core postmeiotic gene expression program that initiates as early as the late meiotic cell stage. ChIP-seq analysis shows that Sox30 binds to specific DNA sequences in mouse testes, and its genomic occupancy correlates positively with expression of many postmeiotic genes including ,, and These results define Sox30 as a crucial transcription factor that controls the transition from a late meiotic to a postmeiotic gene expression program and subsequent round spermatid development.

Background RNA regulation by RNA-binding proteins (RBPs) involve extremely complicated mechanisms. MOV10 and MOV10L1 are two homologous RNA helicases implicated in distinct intracellular pathways. MOV10L1 participates specifically in Piwi-interacting RNA (piRNA) biogenesis and protects mouse male fertility. In contrast, the functional complexity of MOV10 remains incompletely understood, and its role in the mammalian germline is unknown. Here, we report a study of the biological and molecular functions of the RNA helicase MOV10 in mammalian male germ cells. Results MOV10 is a nucleocytoplasmic protein mainly expressed in spermatogonia. Knockdown and transplantation experiments show that MOV10 deficiency has a negative effect on spermatogonial progenitor cells (SPCs), limiting proliferation and in vivo repopulation capacity. This effect is concurrent with a global disturbance of RNA homeostasis and downregulation of factors critical for SPC proliferation and/or self-renewal. Unexpectedly, microRNA (miRNA) biogenesis is impaired due partially to decrease of miRNA primary transcript levels and/or retention of miRNA via splicing control. Genome-wide analysis of RNA targetome reveals that MOV10 binds preferentially to mRNAs with long 3′-UTR and also interacts with various non-coding RNA species including those in the nucleus. Intriguingly, nuclear MOV10 associates with an array of splicing factors, particularly with SRSF1, and its intronic binding sites tend to reside in proximity to splice sites. Conclusions These data expand the landscape of MOV10 function and highlight a previously unidentified role initiated from the nucleus, suggesting that MOV10 is a versatile RBP involved in a broader RNA regulatory network. Electronic supplementary material The online version of this article (10.1186/s12915-019-0659-z) contains supplementary material, which is available to authorized users.

With the tremendous increase of publicly available single-cell RNA-sequencing (scRNA-seq) datasets, bioinformatics methods based on gene co-expression network are becoming efficient tools for analyzing scRNA-seq data, improving cell type prediction accuracy and in turn facilitating biological discovery. However, the current methods are mainly based on overall co-expression correlation and overlook co-expression that exists in only a subset of cells, thus fail to discover certain rare cell types and sensitive to batch effect. Here, we developed independent component analysis-based gene co-expression network inference (ICAnet) that decomposed scRNA-seq data into a series of independent gene expression components and inferred co-expression modules, which improved cell clustering and rare cell-type discovery. ICAnet showed efficient performance for cell clustering and batch integration using scRNA-seq datasets spanning multiple cells/tissues/donors/library types. It works stably on datasets produced by different library construction strategies and with different sequencing depths and cell numbers. We demonstrated the capability of ICAnet to discover rare cell types in multiple independent scRNA-seq datasets from different sources. Importantly, the identified modules activated in acute myeloid leukemia scRNA-seq datasets have the potential to serve as new diagnostic markers. Thus, ICAnet is a competitive tool for cell clustering and biological interpretations of single-cell RNA-seq data analysis.

Mammalian spermatogenesis shows prominent chromatin and transcriptomic switches in germ cells, but it is unclear how such dynamics are controlled. Here we identify RNA helicase DDX43 as an essential regulator of the chromatin remodeling process during spermiogenesis. Testis-specific Ddx43 knockout mice show male infertility with defective histone-to-protamine replacement and post-meiotic chromatin condensation defects. The loss of its ATP hydrolysis activity by a missense mutation replicates the infertility phenotype in global Ddx43 knockout mice. Single-cell RNA sequencing analyses of germ cells depleted of Ddx43 or expressing the Ddx43 ATPase-dead mutant reveals that DDX43 regulates dynamic RNA regulatory processes that underlie spermatid chromatin remodeling and differentiation. Transcriptomic profiling focusing on early-stage spermatids combined with enhanced crosslinking immunoprecipitation and sequencing further identifies Elfn2 as DDX43-targeted hub gene. These findings illustrate an essential role for DDX43 in spermiogenesis and highlight the single-cell-based strategy to dissect cell-state-specific regulation of male germline development.