TEDD: a database of temporal gene expression patterns during multiple developmental periods in human and model organisms

MAPbrain: a multi-omics atlas of the primate brain

The brain is the central hub of the entire nervous system. Its development is a lifelong process guided by a genetic blueprint. Understanding how genes influence brain development is critical for deciphering the formation of human cognitive functions and the underlying mechanisms of neurological disorders. Recent advances in multi-omics techniques have now made it possible to explore these aspects comprehensively. However, integrating and analyzing extensive multi-omics data presents significant challenges. Here, we introduced MAPbrain (http://bigdata.ibp.ac.cn/mapBRAIN/), a multi-omics atlas of the primate brain. This repository integrates and normalizes both our own lab's published data and publicly available multi-omics data, encompassing 21 million brain cells from 38 key brain regions and 436 sub-regions across embryonic and adult stages, with 164 time points in humans and non-human primates. MAPbrain offers a unique, robust, and interactive platform that includes transcriptomics, epigenomics, and spatial transcriptomics data, facilitating a comprehensive exploration of brain development. The platform enables the exploration of cell type- and time point-specific markers, gene expression comparison between brain regions and species, joint analyses across transcriptome and epigenome, and navigation of cell types across species, brain regions, and development stages. Additionally, MAPbrain provides an online integration module for users to navigate and analyze their own data within the platform.

Mate-Pair Sequencing Enables Identification and Delineation of Balanced and Unbalanced Structural Variants in Prenatal Cytogenomic Diagnostics

BACKGROUND

Mate-pair sequencing detects both balanced and unbalanced structural variants (SVs) and simultaneously informs in relation to both genomic location and orientation of SVs for enhanced variant classification and clinical interpretation, while chromosomal microarray analysis (CMA) only reports deletion/duplication. Herein, we evaluated its diagnostic utility in a prospective back-to-back prenatal comparative study with CMA.

METHODS

From October 2021 to September 2023, 426 fetuses with ultrasound anomalies were prospectively recruited for mate-pair sequencing and CMA in parallel for prenatal genetic diagnosis. Balanced/unbalanced SVs and regions with absence of heterozygosity (AOH) were detected and classified independently, and comparisons were made between mate-pair sequencing and CMA to assess concordance. In addition, novel SVs were investigated for potential RNA perturbations using cultured cells, whenever available.

RESULTS

Mate-pair sequencing and CMA successfully yielded results for all 426 fetuses without the need for cell culturing. In addition, mate-pair sequencing identified 19 cases with aneuploidies, 16 cases with pathogenic simple deletions/duplications, and 5 cases with pathogenic translocations/insertions, providing a 25% incremental diagnostic yield compared to CMA (9.4%, 40/426 vs 7.6%, 32/426). Furthermore, by identifying the location and orientation of SVs, mate-pair sequencing improved the variant interpretation and/or follow-up approach for 40.0% (12) of the 30 cases with likely clinically significant deletions/duplications reported by CMA. Lastly, both platforms reported 3 cases (3/426) with multiple regions of AOH likely attributable to parental consanguinity.

CONCLUSIONS

Mate-pair sequencing detects additional balanced/unbalanced SVs and improves variant interpretation in comparison to CMA, indicating its potential to serve as a comprehensive prenatal cytogenomic diagnostic method.

GAEM: Genetic Algorithm based Expectation-Maximization for inferring Gene Regulatory Networks from incomplete data

In Bioinformatics, inferring the structure of a Gene Regulatory Network (GRN) from incomplete gene expression data is a difficult task. One popular method for inferring the structure GRNs is to apply the Path Consistency Algorithm based on Conditional Mutual Information (PCA-CMI). Although PCA-CMI excels at extracting GRN skeletons, it struggles with missing values in datasets. As a result, applying PCA-CMI to infer GRNs, necessitates a preprocessing method for data imputation. In this paper, we present the GAEM algorithm, which uses an iterative approach based on a combination of Genetic Algorithm and Expectation-Maximization to infer the structure of GRN from incomplete gene expression datasets. GAEM learns the GRN structure from the incomplete dataset via an algorithm that iteratively updates the imputed values based on the learnt GRN until the convergence criteria are met. We evaluate the performance of this algorithm under various missingness mechanisms (ignorable and nonignorable) and percentages (5%, 15%, and 40%). The traditional approach to handling missing values in gene expression datasets involves estimating them first and then constructing the GRN. However, our methodology differs in that both missing values and the GRN are updated iteratively until convergence. Results from the DREAM3 dataset demonstrate that the GAEM algorithm appears to be a more reliable method overall, especially for smaller network sizes, GAEM outperforms methods where the incomplete dataset is imputed first, followed by learning the GRN structure from the imputed data. We have implemented the GAEM algorithm within the GAEM R package, which is accessible at the following GitHub repository: https://github.com/parniSDU/GAEM.

GeTeSEPdb: A comprehensive database and online tool for the identification and analysis of gene profiles with temporal-specific expression patterns

Gene expression is dynamic and varies at different stages of processes. The identification of gene profiles with temporal-specific expression patterns can provide valuable insights into ongoing biological processes, such as the cell cycle, cell development, circadian rhythms, or responses to external stimuli such as drug treatments or viral infections. However, currently, no database defines, identifies or archives gene profiles with temporal-specific expression patterns. Here, using a high-throughput regression analysis approach, eight linear and nonlinear parametric models were fitted to gene expression profiles from time-series experiments to identify eight types of gene profiles with temporal-specific expression patterns. We curated 2684 time-series transcriptome datasets and identified 2644,370 gene profiles exhibiting temporal-specific expression patterns. The results were stored in the database GeTeSEPdb (gene profiles with temporal-specific expression patterns database, http://www.inbirg.com/GeTeSEPdb/). Moreover, we implemented an online tool to identify gene profiles with temporal-specific expression patterns from user-submitted data. In summary, GeTeSEPdb is a comprehensive web service that can be used to identify and analyse gene profiles with temporal-specific expression patterns. This approach facilitates the exploration of transcriptional changes and temporal patterns of responses. We firmly believe that GeTeSEPdb will become a valuable resource for biologists and bioinformaticians.

OrganogenesisDB: A Comprehensive Database Exploring the Cell-Type Identities and Gene Expression Dynamics during Organogenesis

Organogenesis, the phase of embryonic development that starts at the end of gastrulation and continues until birth is the critical process for understanding cellular differentiation and maturation during organ development. The rapid development of single-cell transcriptomics technology has led to many novel discoveries in understanding organogenesis while also accumulating a large quantity of data. To fill this gap, OrganogenesisDB (http://organogenesisdb.com/), which is a comprehensive database dedicated to exploring cell-type identification and gene expression dynamics during organogenesis, is developed. OrganogenesisDB contains single-cell RNA sequencing data for more than 1.4 million cells from 49 published datasets spanning various developmental stages. Additionally, 3324 cell markers are manually curated for 1120 cell types across 9 human organs and 4 mouse organs. OrganogenesisDB leverages various analysis tools to assist users in annotating and understanding cell types at different developmental stages and helps in mining and presenting genes that exhibit specific patterns and play key regulatory roles during cell maturation and differentiation. This work provides a critical resource and useful tool for deciphering cell lineage determination and uncovering the mechanisms underlying organogenesis.

The emerging and diverse roles of F-box proteins in spermatogenesis and male infertility

F-box proteins play essential roles in various cellular processes of spermatogenesis by means of ubiquitylation and subsequent target protein degradation. They are the substrate-recognition subunits of SKP1-cullin 1-F-box protein (SCF) E3 ligase complexes. Dysregulation of F‑box protein‑mediated proteolysis could lead to male infertility in humans and mice. The emerging studies revealed the physiological function, pathological evidence, and biochemical substrates of F-box proteins in the development of male germ cells, which urging us to review the current understanding of how F‑box proteins contribute to spermatogenesis. More functional and mechanistic study will be helpful to define the roles of F-box protein in spermatogenesis, which will pave the way for the logical design of F-box protein-targeted diagnosis and therapies for male infertility, as the spermatogenic role of many F-box proteins remains elusive.

Sirtuin 6 ameliorates bleomycin-induced pulmonary fibrosis via activation of lipid catabolism

Pulmonary fibrosis is a chronic and serious interstitial lung disease with little effective therapies currently. Our incomplete understanding of its pathogenesis remains obstacles in therapeutic developments. Sirtuin 6 (SIRT6) has been shown to mitigate multiple organic fibrosis. However, the involvement of SIRT6-mediated metabolic regulation in pulmonary fibrosis remains unclear. Here, we demonstrated that SIRT6 was predominantly expressed in alveolar epithelial cells in human lung tissues by using a single-cell sequencing database. We showed that SIRT6 protected against bleomycin-induced injury of alveolar epithelial cells in vitro and pulmonary fibrosis of mice in vivo. High-throughput sequencing revealed enriched lipid catabolism in Sirt6 overexpressed lung tissues. Mechanismly, SIRT6 ameliorates bleomycin-induced ectopic lipotoxicity by enhancing lipid degradation, thereby increasing the energy supply and reducing the levels of lipid peroxides. Furthermore, we found that peroxisome proliferator-activated receptor α (PPARα) was essential for SIRT6-mediated lipid catabolism, anti-inflammatory responses, and antifibrotic signaling. Our data suggest that targeting SIRT6-PPARα-mediated lipid catabolism could be a potential therapeutic strategy for diseases complicated with pulmonary fibrosis.

Single-cell analysis reveals specific neuronal transition during mouse corticogenesis

Background: Currently, the mechanism(s) underlying corticogenesis is still under characterization. Methods: We curated the most comprehensive single-cell RNA-seq (scRNA-seq) datasets from mouse and human fetal cortexes for data analysis and confirmed the findings with co-immunostaining experiments. Results: By analyzing the developmental trajectories with scRNA-seq datasets in mice, we identified a specific developmental sub-path contributed by a cell-population expressing both deep- and upper-layer neurons (DLNs and ULNs) specific markers, which occurred on E13.5 but was absent in adults. In this cell-population, the percentages of cells expressing DLN and ULN markers decreased and increased, respectively, during the development suggesting direct neuronal transition (namely D-T-U). Whilst genes significantly highly/uniquely expressed in D-T-U cell population were significantly enriched in PTN/MDK signaling pathways related to cell migration. Both findings were further confirmed by co-immunostaining with DLNs, ULNs and D-T-U specific markers across different timepoints. Furthermore, six genes (co-expressed with D-T-U specific markers in mice) showing a potential opposite temporal expression between human and mouse during fetal cortical development were associated with neuronal migration and cognitive functions. In adult prefrontal cortexes (PFC), D-T-U specific genes were expressed in neurons from different layers between humans and mice. Conclusion: Our study characterizes a specific cell population D-T-U showing direct DLNs to ULNs neuronal transition and migration during fetal cortical development in mice. It is potentially associated with the difference of cortical development in humans and mice.

Dyslexia-related loci are significantly associated with language and literacy in Chinese-English bilingual Hong Kong Chinese twins

A recent genome-wide association study on dyslexia in 51,800 affected European adults and 1,087,070 controls detected 42 genome-wide significant single nucleotide variants (SNPs). The association between rs2624839 in SEMA3F and reading fluency was replicated in a Chinese cohort. This study explores the genetic overlap between Chinese and English word reading, vocabulary knowledge and spelling, and aims at replicating the association in a unique cohort of bilingual (Chinese-English) Hong Kong Chinese twins. Our result showed an almost complete genetic overlap in vocabulary knowledge (r2 = 0.995), and some genetic overlaps in word reading and spelling (r2 = 0.846, 0.687) across the languages. To investigate the region near rs2624839, we tested proxy SNPs (rs1005678, rs12632110 and rs12494414) at the population level (n = 305-308) and the within-twin level (n = 342-344 [171-172 twin pairs]). All the three SNPs showed significant associations with quantitative Chinese and English vocabulary knowledge (p < 0.05). The strongest association after multiple testing correction was between rs12494414 and English vocabulary knowledge at the within-twin level (p = 0.004). There was a trend of associations with word reading and spelling in English but not in Chinese. Our result suggested that the region near rs2624839 is one of the common genetic factors across English and Chinese vocabulary knowledge and unique factors of English word reading and English spelling in bilingual Chinese twins. A larger sample size is required to validate our findings. Further studies on the relationship between variable expression of SEMA3F, which is important to neurodevelopment, and language and literacy are encouraged.

Mate-pair genome sequencing reveals structural variants for idiopathic male infertility

Currently, routine genetic investigation for male infertility includes karyotyping analysis and PCR for Y chromosomal microdeletions to provide prognostic information such as sperm retrieval success rate. However, over 85% of male infertility remain idiopathic. We assessed 101 male patients with primary infertility in a retrospective cohort analysis who have previously received negative results from standard-of-care tests. Mate-pair genome sequencing (large-insert size library), an alternative long-DNA sequencing method, was performed to detect clinically significant structural variants (SVs) and copy-number neutral absence of heterozygosity (AOH). Candidate SVs were filtered against our in-house cohort of 1077 fertile men. Genes disrupted by potentially clinically significant variants were correlated with single-cell gene expression profiles of human fetal and postnatal testicular developmental lineages and adult germ cells. Follow-up studies were conducted for each patient with clinically relevant finding(s). Molecular diagnoses were made in 11.1% (7/63) of patients with non-obstructive azoospermia and 13.2% (5/38) of patients with severe oligozoospermia. Among them, 12 clinically significant SVs were identified in 12 cases, including five known syndromes, one inversion, and six SVs with direct disruption of genes by intragenic rearrangements or complex insertions. Importantly, a genetic defect related to intracytoplasmic sperm injection (ICSI) failure was identified in a patient with non-obstructive azoospermia, illustrating the additional value of an etiologic diagnosis in addition to determining sperm retrieval rate. Our study reveals a landscape of various genomic variants in 101 males with idiopathic infertility, not only advancing understanding of the underlying mechanisms of male infertility, but also impacting clinical management.