The ZEB2 transcription factor has been demonstrated to play important roles in hematopoiesis and leukemic transformation. ZEB1 is a close family member of ZEB2 but has remained more enigmatic concerning its roles in hematopoiesis. Here, we show using conditional loss-of-function approaches and bone marrow (BM) reconstitution experiments that ZEB1 plays a cell-autonomous role in hematopoietic lineage differentiation, particularly as a positive regulator of monocyte development in addition to its previously reported important role in T-cell differentiation. Analysis of existing single-cell (sc) RNA sequencing (RNA-seq) data of early hematopoiesis has revealed distinctive expression differences betweenZeb1andZeb2in hematopoietic stem and progenitor cell (HSPC) differentiation, withZeb2being more highly and broadly expressed thanZeb1except at a key transition point (short-term HSC [ST-HSC]➔MPP1), wherebyZeb1appears to be the dominantly expressed family member. Inducible genetic inactivation of bothZeb1andZeb2using a tamoxifen-inducible Cre-mediated approach leads to acute BM failure at this transition point with increased long-term and short-term hematopoietic stem cell numbers and an accompanying decrease in all hematopoietic lineage differentiation. Bioinformatics analysis of RNA-seq data has revealed that ZEB2 acts predominantly as a transcriptional repressor involved in restraining mature hematopoietic lineage gene expression programs from being expressed too early in HSPCs. ZEB1 appears to fine-tune this repressive role during hematopoiesis to ensure hematopoietic lineage fidelity. Analysis of Rosa26 locus–based transgenic models has revealed thatZeb1as well asZeb2cDNA-based overexpression within the hematopoietic system can drive extramedullary hematopoiesis/splenomegaly and enhance monocyte development. Finally, inactivation ofZeb2alone orZeb1/2together was found to enhance survival in secondary MLL-AF9 acute myeloid leukemia (AML) models attesting to the oncogenic role of ZEB1/2 in AML.

Acute myeloid leukemia (AML) is a diverse malignancy originating from myeloid progenitor cells, with significant genetic and clinical variability. Modern classification systems like those from the World Health Organization (WHO) and European LeukemiaNet use immunophenotyping, molecular genetics, and clinical features to categorize AML subtypes. This classification highlights crucial genetic markers such as FLT3, NPM1 mutations, and MLL-AF9 fusion, which are essential for prognosis and directing targeted therapies. The MLL-AF9 fusion protein is often linked with therapy-resistant AML, highlighting the risk of relapse due to standard chemotherapeutic regimes. In this sense, factors like the ZEB, SNAI, and TWIST gene families, known for their roles in epithelial–mesenchymal transition (EMT) and cancer metastasis, also regulate hematopoiesis and may serve as effective therapeutic targets in AML. These genes contribute to cell proliferation, differentiation, and extramedullary hematopoiesis, suggesting new possibilities for treatment. Advancing our understanding of the molecular mechanisms that promote AML, especially how the bone marrow microenvironment affects invasion and drug resistance, is crucial. This comprehensive insight into the molecular and environmental interactions in AML emphasizes the need for ongoing research and more effective treatments.

Background: The advancement of hybrid sequencing technologies is increasingly expanding genome assemblies that are often annotated using hybrid sequencing transcriptomics, leading to improved genome characterization and the identification of novel genes and isoforms in a wide variety of organisms. Results: We developed an easy-to-use genome-guided transcriptome annotation pipeline that uses assembled transcripts from hybrid sequencing data as input and distinguishes between coding and long non-coding RNAs by integration of several bioinformatic approaches, including gene reconciliation with previous annotations in GTF format. We demonstrated the efficiency of this approach by correctly assembling and annotating all exons from the chicken SCO-spondin gene (containing more than 105 exons), including the identification of missing genes in the chicken reference annotations by homology assignments. Conclusions: Our method helps to improve the current transcriptome annotation of the chicken brain. Our pipeline, implemented on Anaconda/Nextflow and Docker is an easy-to-use package that can be applied to a broad range of species, tissues, and research areas helping to improve and reconcile current annotations. The code and datasets are publicly available at https://github.com/cfarkas/annotate_my_genomes

The establishment and maintenance of nucleosome-free regions (NFRs) are prominent processes within chromatin dynamics. Transcription factors, ATP-dependent chromatin remodeling complexes (CRCs) and DNA sequences are the main factors involved. In Saccharomyces cerevisiae, CRCs such as RSC contribute to chromatin opening at NFRs, while other complexes, including ISW1a, contribute to NFR shrinking. Regarding DNA sequences, growing evidence points to poly(dA:dT) tracts as playing a direct role in active processes involved in nucleosome positioning dynamics. Intriguingly, poly(dA:dT)-tract-containing NFRs span asymmetrically relative to the location of the tract by a currently unknown mechanism. In order to obtain insight into the role of poly(dA:dT) tracts in nucleosome remodeling, we performed a systematic analysis of their influence on the activity of ISW1a and RSC complexes. Our results show that poly(dA:dT) tracts differentially affect the activity of these CRCs. Moreover, we found differences between the effects exerted by the two alternative tract orientations. Remarkably, tract-containing linker DNA is taken as exit DNA for nucleosome sliding catalyzed by RSC. Our findings show that defined DNA sequences, when present in linker DNA, can dictate in which direction a remodeling complex has to slide nucleosomes and shed light into the mechanisms underlying asymmetrical chromatin opening around poly(dA:dT) tracts.

The identification of new proteins that regulate the function of one of the main cellular phosphatases, protein phosphatase 1 (PP1), is essential to find possible pharmacological targets to alter phosphatase function in various cellular processes, including the initiation and development of multiple diseases. IIIG9 is a regulatory subunit of PP1 initially identified in highly polarized ciliated cells. In addition to its ciliary location in ependymal cells, we recently showed that IIIG9 has extraciliary functions that regulate the integrity of adherens junctions. In this review, we perform a detailed analysis of the expression, localization, and function of IIIG9 in adult and developing normal brains. In addition, we provide a 3D model of IIIG9 protein structure for the first time, verifying that the classic structural and conformational characteristics of the PP1 regulatory subunits are maintained. Our review is especially focused on finding evidence linking IIIG9 dysfunction with the course of some pathologies, such as ciliopathies, drug dependence, diseases based on neurological development, and the development of specific high-malignancy and -frequency brain tumors in the pediatric population. Finally, we propose that IIIG9 is a relevant regulator of PP1 function in physiological and pathological processes in the CNS.

Background/Objectives: Preeclampsia (PE) is a major cause of maternal and perinatal morbidity and mortality, particularly in low- and middle-income countries. Early-onset PE (EOP) and late-onset PE (LOP) are distinct clinical entities with differing pathophysiological mechanisms and prognoses. However, few studies have explored differential risk factors for EOP and LOP in Latin American populations. This study aimed to identify and assess clinical risk factors for predicting EOP and LOP in a cohort of pregnant women from Bogotá, Colombia, using traditional statistics and machine learning (ML). Methods: A cross-sectional observational study was conducted on 190 pregnant women diagnosed with PE (EOP = 80, LOP = 110) at a tertiary hospital in Bogotá between 2017 and 2018. Risk factors and perinatal outcomes were collected via structured interviews and clinical records. Traditional statistical analyses were performed to compare the study groups and identify associations between risk factors and outcomes. Eleven ML techniques were used to train and externally validate predictive models for PE subtype and secondary outcomes, incorporating permutation-based feature importance to enhance interpretability. Results: EOP was significantly associated with higher maternal education and history of hypertension, while LOP was linked to a higher prevalence of allergic history. The best-performing ML model for predicting PE subtype was linear discriminant analysis (recall = 0.71), with top predictors including education level, family history of perinatal death, number of sexual partners, primipaternity, and family history of hypertension. Conclusions: EOP and LOP exhibit distinct clinical profiles in this cohort. The combination of traditional statistics with ML may improve early risk stratification and support context-specific prenatal care strategies in similar settings.