Single-cell RNA-seq data analysis reveals functionally relevant biomarkers of early brain development and their regulatory footprints in human embryonic stem cells (hESCs).

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-seq) is a potent instrument for pinpointing biomarkers that exhibit differential expression across various cell types and developmental stages. By employing scRNA-seq on human embryonic stem cells, we aim to identify differentially expressed genes (DEGs) crucial for early-stage neuronal development. Our focus extends beyond simply identifying DEGs. We strive to investigate the functional roles of these genes through enrichment analysis and construct gene regulatory networks to understand their interactions. Ultimately, this comprehensive approach aspires to illuminate the molecular mechanisms and transcriptional dynamics governing early human brain development. By uncovering potential links between these DEGs and intelligence, mental disorders, and neurodevelopmental disorders, we hope to shed light on human neurological health and disease. In this study, we have used scRNA-seq to identify DEGs involved in early-stage neuronal development in hESCs. The scRNA-seq data, collected on days 26 (D26) and 54 (D54), of the in vitro differentiation of hESCs to neurons were analyzed. Our analysis identified 539 DEGs between D26 and D54. Functional enrichment of those DEG biomarkers indicated that the up-regulated DEGs participated in neurogenesis, while the down-regulated DEGs were linked to synapse regulation. The Reactome pathway analysis revealed that down-regulated DEGs were involved in the interactions between proteins located in synapse pathways. We also discovered interactions between DEGs and miRNA, transcriptional factors (TFs) and DEGs, and between TF and miRNA. Our study identified 20 significant transcription factors, shedding light on early brain development genetics. The identified DEGs and gene regulatory networks are valuable resources for future research into human brain development and neurodevelopmental disorders.

Bistable insulin response: The win-win solution for glycemic control.

To satisfy both the safety and rapidity of glycemic control, muscles' insulin response must be bistable, as theoretically predicted. Here, we test the bistability hypothesis by combining cellular experiments (to measure the threshold values in vitro) with mathematical modeling (to test the relevance of bistability in vivo). We examine bistability in C2C12 myotubes by both single-cell analysis (FÓ§rster resonance energy transfer) and cultured cells analysis (immunoblot). These technologies demonstrate bistable insulin response, with typical switch-on and switch-off thresholds of approximately 300 and 100 pM, respectively. Our mathematical model demonstrates the indispensability of bistability in interpreting experimental data, reveals fine details of plasma glucose-insulin dynamics, and explains unclear phenomena. These results suggest that the body's ability to simultaneously avoid both hypoglycemia and hyperglycemia is mediated by bistability. The switch-on threshold is a promising biomarker for metabolic complications due to its deep quantitative connection with body composition, which is easy to measure.

The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome.

Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. This heterogeneity in assembled transcript sets might be partially explained by sequencing depth. Here, we used real and simulated short-read sequencing data as well as long-read data to systematically investigate the impact of sequencing depths on the accuracy of assembled transcripts. We assembled and analyzed transcripts from 671 human short-read data sets and four long-read data sets. At the first level, there is a positive correlation between the number of reads and the number of recovered transcripts. However, the effect of the sequencing depth varied based on cell or tissue type, the type of read and the nature and expression levels of the transcripts. The detection of coding transcripts saturated rapidly with both short and long-reads, however, there was no sign of early saturation for noncoding transcripts at any sequencing depth. Increasing long-read sequencing depth specifically benefited transcripts containing transposable elements. Finally, we show how single-cell RNA-seq can be guided by transcripts assembled from bulk long-read samples, and demonstrate that noncoding transcripts are expressed at similar levels to coding transcripts but are expressed in fewer cells. This study highlights the impact of sequencing depth on transcript assembly.

The Dynamics, Causes, and Impacts of Mammalian Evolutionary Rates Revealed by the Analyses of Capybara Draft Genome Sequences.

Capybara (Hydrochoerus hydrochaeri) is the largest species among the extant rodents. The draft genome of capybara was sequenced with the estimated genome size of 2.6 Gb. Although capybara is about 60 times larger than guinea pig, comparative analyses revealed that the neutral evolutionary rates of the two species were not substantially different. However, analyses of 39 mammalian genomes revealed very heterogeneous evolutionary rates. The highest evolutionary rate, 8.5 times higher than the human rate, was found in the Cricetidae-Muridae common ancestor after the divergence of Spalacidae. Muridae, the family with the highest number of species among mammals, emerged after the rate acceleration. Factors responsible for the evolutionary rate heterogeneity were investigated through correlations between the evolutionary rate and longevity, gestation length, litter frequency, litter size, body weight, generation interval, age at maturity, and taxonomic order. The regression analysis of these factors showed that the model with three factors (taxonomic order, generation interval, and litter size) had the highest predictive power (R2 = 0.74). These three factors determine the number of meiosis per unit time. We also conducted transcriptome analysis and found that the evolutionary rate dynamics affects the evolution of gene expression patterns.

Genomic Locations of Conserved Noncoding Sequences and Their Proximal Protein-Coding Genes in Mammalian Expression Dynamics.

Experimental studies have found the involvement of certain conserved noncoding sequences (CNSs) in the regulation of the proximal protein-coding genes in mammals. However, reported cases of long range enhancer activities and inter-chromosomal regulation suggest that proximity of CNSs to protein-coding genes might not be important for regulation. To test the importance of the CNS genomic location, we extracted the CNSs conserved between chicken and four mammalian species (human, mouse, dog, and cattle). These CNSs were confirmed to be under purifying selection. The intergenic CNSs are often found in clusters in gene deserts, where protein-coding genes are in paucity. The distribution pattern, ChIP-Seq, and RNA-Seq data suggested that the CNSs are more likely to be regulatory elements and not corresponding to long intergenic noncoding RNAs. Physical distances between CNS and their nearest protein coding genes were well conserved between human and mouse genomes, and CNS-flanking genes were often found in evolutionarily conserved genomic neighborhoods. ChIP-Seq signal and gene expression patterns also suggested that CNSs regulate nearby genes. Interestingly, genes with more CNSs have more evolutionarily conserved expression than those with fewer CNSs. These computationally obtained results suggest that the genomic locations of CNSs are important for their regulatory functions. In fact, various kinds of evolutionary constraints may be acting to maintain the genomic locations of CNSs and protein-coding genes in mammals to ensure proper regulation.

Heterogeneous tempo and mode of conserved noncoding sequence evolution among four mammalian orders.

Conserved noncoding sequences (CNSs) of vertebrates are considered to be closely linked with protein-coding gene regulatory functions. We examined the abundance and genomic distribution of CNSs in four mammalian orders: primates, rodents, carnivores, and cetartiodactyls. We defined the two thresholds for CNS using conservation level of coding genes; using all the three coding positions and using only first and second codon positions. The abundance of CNSs varied among lineages, with primates and rodents having highest and lowest number of CNSs, respectively, whereas carnivores and cetartiodactyls had intermediate values. These CNSs cover 1.3-5.5% of the mammalian genomes and have signatures of selective constraints that are stronger in more ancestral than the recent ones. Evolution of new CNSs as well as retention of ancestral CNSs contribute to the differences in abundance. The genomic distribution of CNSs is dynamic with higher proportions of rodent and primate CNSs located in the introns compared with carnivores and cetartiodactyls. In fact, 19% of orthologous single-copy CNSs between human and dog are located in different genomic regions. If CNSs can be considered as candidates of gene expression regulatory sequences, heterogeneity of CNSs among the four mammalian orders may have played an important role in creating the order-specific phenotypes. Fewer CNSs in rodents suggest that rodent diversity is related to lower regulatory conservation. With CNSs shown to cluster around genes involved in nervous systems and the higher number of primate CNSs, our result suggests that CNSs may be involved in the higher complexity of the primate nervous system.