DNA methylation clocks for estimating biological age in Chinese cohorts

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation(DNAm)at specific CpG sites.However,a systematic comparison between DNA methylation data and other omics datasets has not yet been performed.Moreover,available DNAm age predictors are based on datasets with limited ethnic representation.To address these knowledge gaps,we generated and analyzed DNA methylation datasets from two independent Chinese cohorts,revealing age-related DNAm changes.Additionally,a DNA methylation aging clock(iCAS-DNAmAge)and a group of DNAm-based multi-modal clocks for Chinese individuals were developed,with most of them demonstrating strong predictive capabilities for chronological age.The clocks were further employed to predict factors influencing aging rates.The DNAm aging clock,derived from multi-modal aging features(compositeAge-DNAmAge),exhibited a close association with multi-omics changes,lifestyles,and disease status,underscoring its robust potential for precise biological age assessment.Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace,providing the basis for evaluating aging intervention strategies.

deCS:A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues

Single-cell RNA sequencing(scRNA-seq)is revolutionizing the study of complex and dynamic cellular mechanisms.However,cell type annotation remains a main challenge as it largely relies on a priori knowledge and manual curation,which is cumbersome and subjective.The increasing number of scRNA-seq datasets,as well as numerous published genetic studies,has motivated us to build a comprehensive human cell type reference atlas.Here,we present decoding Cell type Specificity(deCS),an automatic cell type annotation method augmented by a comprehensive collection of human cell type expression profiles and marker genes.We used deCS to annotate scRNAseq data from various tissue types and systematically evaluated the annotation accuracy under different conditions,including reference panels,sequencing depth,and feature selection strategies.Our results demonstrate that expanding the references is critical for improving annotation accuracy.Compared to many existing state-of-the-art annotation tools,deCS significantly reduced computation time and increased accuracy.deCS can be integrated into the standard scRNA-seq analytical pipeline to enhance cell type annotation.Finally,we demonstrated the broad utility of deCS to identify trait-cell type associations in 51 human complex traits,providing deep insights into the cellular mechanisms underlying disease pathogenesis.

CleftGeneDB: a resource for annotating genes associated with cleft lip and cleft palate

Cleft lip with/without cleft palate(CL/P) is one of the most common congenital human birth defects with a prevalence estimated at approximately 1/700 live births worldwide, varying with gender,ethnicity, and geographic location[1]. Significant efforts have been made to understand CL/P pathogenesis.