Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis.

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings.

scPlant: A versatile framework for single-cell transcriptomic data analysis in plants.

Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users.

ChIP-Hub provides an integrative platform for exploring plant regulome.

Plant genomes encode a complex and evolutionary diverse regulatory grammar that forms the basis for most life on earth. A wealth of regulome and epigenome data have been generated in various plant species, but no common, standardized resource is available so far for biologists. Here, we present ChIP-Hub, an integrative web-based platform in the ENCODE standards that bundles >10,000 publicly available datasets reanalyzed from >40 plant species, allowing visualization and meta-analysis.

Architecture of gene regulatory networks controlling flower development in Arabidopsis thaliana.

Floral homeotic transcription factors (TFs) act in a combinatorial manner to specify the organ identities in the flower. However, the architecture and the function of the gene regulatory network (GRN) controlling floral organ specification is still poorly understood. In particular, the interconnections of homeotic TFs, microRNAs (miRNAs) and other factors controlling organ initiation and growth have not been studied systematically so far.

The HTPmod Shiny application enables modeling and visualization of large-scale biological data.

The wave of high-throughput technologies in genomics and phenomics are enabling data to be generated on an unprecedented scale and at a reasonable cost. Exploring the large-scale data sets generated by these technologies to derive biological insights requires efficient bioinformatic tools. Here we introduce an interactive, open-source web application (HTPmod) for high-throughput biological data modeling and visualization.

Spatial features for Escherichia coli genome organization.

Background: In bacterial genomes, the compactly encoded genes and operons are well organized, with genes in the same biological pathway or operons in the same regulon close to each other on the genome sequence. In addition, the linearly close genes have a higher probability of co-expression and their protein products tend to form protein-protein interactions. However, the organization features of bacterial genomes in a three-dimensional space remain elusive.

Dissecting the chromatin interactome of microRNA genes.

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes.

Structural and energetic analyses of SNPs in drug targets and implications for drug therapy.

Mutations in drug targets can alter the therapeutic effects of drugs. Therefore, evaluating the effects of single-nucleotide polymorphisms (SNPs) on drug-target binding is of significant interest. This study focuses on the analysis of the structural and energy properties of SNPs in successful drug targets by using the data derived from HapMap and the Therapeutic Target Database.

The sequencing bias relaxed characteristics of Hi-C derived data and implications for chromatin 3D modeling.

The 3D chromatin structure modeling by chromatin interactions derived from Hi-C experiments is significantly challenged by the intrinsic sequencing biases in these experiments. Conventional modeling methods only focus on the bias among different chromatin regions within the same experiment but neglect the bias arising from different experimental sequencing depth. We now show that the regional interaction bias is tightly coupled with the sequencing depth, and we further identify a chromatin structure parameter as the inherent characteristics of Hi-C derived data for chromatin regions.

Oxidative DNA damage is important to the evolution of antibiotic resistance: evidence of mutation bias and its medicinal implications.

Several (1) studies have revealed that the reactive oxygen species (ROS) induced by antibacterial stimulation accelerates the evolution of antibiotic resistance, which uncovered new links between oxygen rise and evolution and inspired new strategies to prevent antibiotic resistance. Considering many other mechanisms cause DNA mutations aside from ROS damage, evaluating the significance of oxidative DNA damage in the development of antibiotic resistance is of great interest. In this study, we examined the ratio of G:C > T:A transversion to G:C > A:T transition in drug-resistant Escherichia coli and Mycobacterium tuberculosis and found that it is significantly higher than the background values.

Can medical genetics and evolutionary biology inspire drug target identification?

New strategies for target identification are urgently needed to tackle the current productivity challenges in drug discovery. By examining successful human drug targets, it can be seen that approximately 50% are associated with genetic disorders. Further analysis shows that these successfully targeted genes share some common evolutionary features, which strongly suggests that evolutionary information can help identify drug targets with the greatest potential for therapeutic development.

Exploring the common molecular basis for the universal DNA mutation bias: revival of Löwdin mutation model.

Recently, numerous genome analyses revealed the existence of a universal G:C→A:T mutation bias in bacteria, fungi, plants and animals. To explore the molecular basis for this mutation bias, we examined the three well-known DNA mutation models, i.e.

[Human appropriation of net primary production in the middle reach of Heihe River basin].

Based on Miami model, this paper calculated the human appropriation of net primary production (HANPP) in the middle reach of Heihe River basin, discussed the relations between the HANPP and ecosystem diversity, and compared the values of HANPP and ecological footprint (EF) in sustainability assessment. The results showed that the increase of HANPP decreased the ecosystem diversity, and the current average HANPP in study area was 38.61%.