The Maternal-to-Zygotic transition (MZT) is a reprograming process encompassing zygotic genome activation (ZGA) and the clearance of maternally-provided mRNAs. While some factors regulating MZT have been identified, there are thousands of maternal RNAs whose function has not been ascribed yet. Here, we have performed a proof-of-principle CRISPR-RfxCas13d maternal screening targeting mRNAs encoding protein kinases and phosphatases in zebrafish and identified Bckdk as a novel post-translational regulator of MZT. Bckdk mRNA knockdown caused epiboly defects, ZGA deregulation, H3K27ac reduction and a partial impairment of miR-430 processing. Phospho-proteomic analysis revealed that Phf10/Baf45a, a chromatin remodeling factor, is less phosphorylated upon Bckdk depletion. Further, phf10 mRNA knockdown also altered ZGA and Phf10 constitutively phosphorylated rescued the developmental defects observed after bckdk mRNA depletion. Altogether, our results demonstrate the competence of CRISPR-RfxCas13d screenings to uncover new regulators of early vertebrate development and shed light on the post-translational control of MZT mediated by protein phosphorylation.

Early embryonic developmental programs are guided by the coordinated interplay between maternally inherited and zygotically manufactured RNAs and proteins. Although these processes happen concomitantly and affecting gene function during this period is bound to affect both pools of mRNAs, it has been challenging to study their expression dynamics separately.
By employing SLAM-seq, a nascent mRNA labeling transcriptomic approach, in a developmental time series we observe that over half of the early zebrafish embryo transcriptome consists of maternal-zygotic genes, emphasizing their pivotal role in early embryogenesis. We provide an hourly resolution of de novo transcriptional activation events and follow nascent mRNA trajectories, finding that most de novo transcriptional events are stable throughout this period. Additionally, by blocking microRNA-430 function, a key post transcriptional regulator during zebrafish embryogenesis, we directly show that it destabilizes hundreds of de novo transcribed mRNAs from pure zygotic as well as maternal-zygotic genes. This unveils a novel miR-430 function during embryogenesis, fine-tuning zygotic gene expression.
These insights into zebrafish early embryo transcriptome dynamics emphasize the significance of post-transcriptional regulators in zygotic genome activation. The findings pave the way for future investigations into the coordinated interplay between transcriptional and post-transcriptional landscapes required for the establishment of animal cell identities and functions.

Differential expression analysis of RNA sequencing (RNA-seq) data can identify changes in cellular RNA levels, but provides limited information about the kinetic mechanisms underlying such changes. Nucleotide recoding RNA-seq methods (NR-seq; e.g., TimeLapse-seq, SLAM-seq, etc.) address this shortcoming and are widely used approaches to identify changes in RNA synthesis and degradation kinetics. While advanced statistical models implemented in user-friendly software (e.g., DESeq2) have ensured the statistical rigor of differential expression analyses, no such tools that facilitate differential kinetic analysis with NR-seq exist. Here, we report the development of Bayesian analysis of the kinetics of RNA (bakR; https:// github.com/simonlabcode/bakR), an R package to address this need. bakR relies on Bayesian hierarchical modeling of NR-seq data to increase statistical power by sharing information across transcripts. Analyses of simulated data confirmed that bakR implementations of the hierarchical model outperform attempts to analyze differential kinetics with existing models. bakR also uncovers biological signals in real NR-seq data sets and provides improved analyses of existing data sets. This work establishes bakR as an important tool for identifying differential RNA synthesis and degradation kinetics.

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define transcriptional states of colorectal cancer cells and signals controlling their development by performing single-cell transcriptome analysis of tumors and matched non-cancerous tissues of twelve colorectal cancer patients. We defined patient-overarching colorectal cancer cell clusters characterized by differential activities of oncogenic signaling pathways such as mitogen-activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient-derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen-activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR-BRAF-MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories. Our results highlight directional cancer cell development as a driver of non-genetic cancer cell heterogeneity and re-routing of trajectories as a response to targeted therapy.

Spermatogonial stem cells (SSCs) are essential for male fertility. Here, we report that mouse SSC generation is driven by a transcription factor (TF) cascade controlled by the homeobox protein, RHOX10, which acts by driving the differentiation of SSC precursors called pro-spermatogonia (ProSG). We identify genes regulated by RHOX10 in ProSG in vivo and define direct RHOX10-target genes using several approaches, including a rapid temporal induction assay: iSLAMseq. Together, these approaches identify temporal waves of RHOX10 direct targets, as well as RHOX10 secondary-target genes. Many of the RHOX10-regulated genes encode proteins with known roles in SSCs. Using an in vitro ProSG differentiation assay, we find that RHOX10 promotes mouse ProSG differentiation through a conserved transcriptional cascade involving the key germ-cell TFs DMRT1 and ZBTB16. Our study gives important insights into germ cell development and provides a blueprint for how to define TF cascades.

It is currently assumed that 3D chromosomal organization plays a central role in transcriptional control. However, depletion of cohesin and CTCF affects the steady-state levels of only a minority of transcripts. Here, we use high-resolution Capture Hi-C to interrogate the dynamics of chromosomal contacts of all annotated human gene promoters upon degradation of cohesin and CTCF. We show that a majority of promoter-anchored contacts are lost in these conditions, but many contacts with distinct properties are maintained, and some new ones are gained. The rewiring of contacts between promoters and active enhancers upon cohesin degradation associates with rapid changes in target gene transcription as detected by SLAM sequencing (SLAM-seq). These results provide a mechanistic explanation for the limited, but consistent, effects of cohesin and CTCF depletion on steady-state transcription and suggest the existence of both cohesin-dependent and -independent mechanisms of enhancer-promoter pairing.

Here, we present Scribe (https://github.com/aristoteleo/Scribe-py), a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe employs restricted directed information to determine causality by estimating the strength of information transferred from a potential regulator to its downstream target. We apply Scribe and other leading approaches for causal network reconstruction to several types of single-cell measurements and show that there is a dramatic drop in performance for \"pseudotime\"-ordered single-cell data compared with true time-series data. We demonstrate that performing causal inference requires temporal coupling between measurements. We show that methods such as \"RNA velocity\" restore some degree of coupling through an analysis of chromaffin cell fate commitment. These analyses highlight a shortcoming in experimental and computational methods for analyzing gene regulation at single-cell resolution and suggest ways of overcoming it.

mRNA translation decodes nucleotide into amino acid sequences. However, translation has also been shown to affect mRNA stability depending on codon composition in model organisms, although universality of this mechanism remains unclear. Here, using three independent approaches to measure exogenous and endogenous mRNA decay, we define which codons are associated with stable or unstable mRNAs in human cells. We demonstrate that the regulatory information affecting mRNA stability is encoded in codons and not in nucleotides. Stabilizing codons tend to be associated with higher tRNA levels and higher charged/total tRNA ratios. While mRNAs enriched in destabilizing codons tend to possess shorter poly(A)-tails, the poly(A)-tail is not required for the codon-mediated mRNA stability. This mechanism depends on translation; however, the number of ribosome loads into a mRNA modulates the codon-mediated effects on gene expression. This work provides definitive evidence that translation strongly affects mRNA stability in a codon-dependent manner in human cells.