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Impairment of male fertility is one of the major public health issues worldwide. Nevertheless, genetic causes of male sub- and infertility can often only be suspected due to the lack of reliable and easy-to-use routine tests. Yet, the development of a marker panel is complicated by the large quantity of potentially predictive markers. Actually, hundreds or even thousands of genes could have fertility relevance. Thus, a systematic method enabling a selection of the most predictive markers out of the many candidates is required. As a criterion for marker selection, we derived a gene-specific score, which we refer to as fertility relevance probability (FRP). For this purpose, we first categorized 2,753 testis-expressed genes as either candidate markers or non-candidates, according to phenotypes in male knockout mice. In a parallel approach, 2,502 genes were classified as candidate markers or non-candidates based on phenotypes in men. Subsequently, we conducted logistic regression analyses with evolutionary rates of genes (dN/dS), transcription levels in testis relative to other organs, and connectivity of the encoded proteins in a protein-protein interaction network as covariates. In confirmation of the procedure, FRP values showed the expected pattern, thus being overall higher in genes with known relevance for fertility than in their counterparts without corresponding evidence. In addition, higher FRP values corresponded with an increased dysregulation of protein abundance in spermatozoa of 37 men with normal and 38 men with impaired fertility. Present analyses resulted in a ranking of genes according to their probable predictive power as candidate markers for male fertility impairment. Thus, AKAP4, TNP1, DAZL, BRDT, DMRT1, SPO11, ZPBP, HORMAD1, and SMC1B are prime candidates toward a marker panel for male fertility impairment. Additional candidate markers are DDX4, SHCBP1L, CCDC155, ODF1, DMRTB1, ASZ1, BOLL, FKBP6, SLC25A31, PRSS21, and RNF17. FRP inference additionally provides clues for potential new markers, thereunder TEX37 and POU4F2. The results of our logistic regression analyses are freely available at the PreFer Genes website (https://prefer-genes.uni-mainz.de/).

Even though proteins are produced from mRNA, the correlation between mRNA levels and protein abundances is moderate in most studies, occasionally attributed to complex post-transcriptional regulation. To address this, we generate a paired transcriptome/proteome time course dataset with 14 time points during Drosophila embryogenesis. Despite a limited mRNA-protein correlation (ρ = 0.54), mathematical models describing protein translation and degradation explain 84% of protein time-courses based on the measured mRNA dynamics without assuming complex post transcriptional regulation, and allow for classification of most proteins into four distinct regulatory scenarios. By performing an in-depth characterization of the putatively post-transcriptionally regulated genes, we postulate that the RNA-binding protein Hrb98DE is involved in post-transcriptional control of sugar metabolism in early embryogenesis and partially validate this hypothesis using Hrb98DE knockdown. In summary, we present a systems biology framework for the identification of post-transcriptional gene regulation from large-scale, time-resolved transcriptome and proteome data., Proteome and transcriptome often show poor correlation, hindering the system-wide analysis of post-transcriptional regulation. Here, the authors study proteome and transcriptome dynamics during Drosophila embryogenesis and present basic mathematical models describing the temporal regulation of most protein-RNA pairs.

A decade ago, we believed that at least 300 RNA binding proteins (RBPs) were encoded in our genomes based on annotations of known or predicted RNA binding domains. Deciphering the roles of those RBPs in regulated gene expression was a vast frontier awaiting exploration. Since then, the field has developed a number of key tools that navigate the landscape of cellular RNA. These rely principally on UV crosslinking to create covalent bonds between RBPs and target RNAs in vivo , revealing not only target identities but also local binding sites upon RNA-Seq. More recently, a reverse protocol – mRNA interactome capture – has enabled the identification of the proteins that interact with mRNA. Astonishingly, the number of RBPs has grown to more than 1000, and we must now understand what they do. Here, we discuss the application of these methods to model organisms, focusing on the zebrafish Danio rerio , which provide unique biological contexts for the analysis of RBPs and their functions.

Molecular phylogenomics investigates evolutionary relationships based on genomic data. However, despite genomic sequence conservation, changes in protein interactions can occur relatively rapidly and may cause strong functional diversification. To investigate such functional evolution, we here combine phylogenomics with interaction proteomics. We develop this concept by investigating the molecular evolution of the shelterin complex, which protects telomeres, across 16 vertebrate species from zebrafish to humans covering 450 million years of evolution. Our phylointeractomics screen discovers previously unknown telomere-associated proteins and reveals how homologous proteins undergo functional evolution. For instance, we show that TERF1 evolved as a telomere-binding protein in the common stem lineage of marsupial and placental mammals. Phylointeractomics is a versatile and scalable approach to investigate evolutionary changes in protein function and thus can provide experimental evidence for phylogenomic relationships., Since protein interactions can be sensitive to small sequence changes, phylogenomics alone gives limited insight into protein functional evolution. Here, the authors illustrate how the combination of phylogenomics and interaction proteomics helps elucidate protein functional evolution with a study of the shelterin complex evolution.

During the maternal-to-zygotic transition (MZT), transcriptionally silent embryos rely on post-transcriptional regulation of maternal mRNAs until zygotic genome activation (ZGA). RNA-binding proteins (RBPs) are important regulators of post-transcriptional RNA processing events, yet their identities and functions during developmental transitions in vertebrates remain largely unexplored. Using mRNA interactome capture, we identified 227 RBPs in zebrafish embryos before and during ZGA, hereby named the zebrafish MZT mRNA-bound proteome. This protein constellation consists of many conserved RBPs, some of which are potential stage-specific mRNA interactors that likely reflect the dynamics of RNA–protein interactions during MZT. The enrichment of numerous splicing factors like hnRNP proteins before ZGA was surprising, because maternal mRNAs were found to be fully spliced. To address potentially unique roles of these RBPs in embryogenesis, we focused on Hnrnpa1. iCLIP and subsequent mRNA reporter assays revealed a function for Hnrnpa1 in the regulation of poly(A) tail length and translation of maternal mRNAs through sequence-specific association with 3′ UTRs before ZGA. Comparison of iCLIP data from two developmental stages revealed that Hnrnpa1 dissociates from maternal mRNAs at ZGA and instead regulates the nuclear processing of pri-mir-430 transcripts, which we validated experimentally. The shift from cytoplasmic to nuclear RNA targets was accompanied by a dramatic translocation of Hnrnpa1 and other pre-mRNA splicing factors to the nucleus in a transcription-dependent manner. Thus, our study identifies global changes in RNA–protein interactions during vertebrate MZT and shows that Hnrnpa1 RNA-binding activities are spatially and temporally coordinated to regulate RNA metabolism during early development.

Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface.

Trypanosomes are masters of adaptation to different host environments during their complex life cycle. Large-scale proteomic approaches provide information on changes at the cellular level, and in a systematic way. However, detailed work on single components is necessary to understand the adaptation mechanisms on a molecular level. Here, we have performed a detailed characterization of a bloodstream form (BSF) stage-specific putative flagellar host adaptation factor Tb927.11.2400, identified previously in a SILAC-based comparative proteome study. Tb927.11.2400 shares 38% amino acid identity with TbFlabarin (Tb927.11.2410), a procyclic form (PCF) stage-specific flagellar BAR domain protein. We named Tb927.11.2400 TbFlabarin-like (TbFlabarinL), and demonstrate that it originates from a gene duplication event, which occurred in the African trypanosomes. TbFlabarinL is not essential for the growth of the parasites under cell culture conditions and it is dispensable for developmental differentiation from BSF to the PCF in vitro. We generated TbFlabarinL-specific antibodies, and showed that it localizes in the flagellum. Co-immunoprecipitation experiments together with a biochemical cell fractionation suggest a dual association of TbFlabarinL with the flagellar membrane and the components of the paraflagellar rod.