Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or ‘cerQTL’, and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level.

Infection after renal transplantation remains a major cause of morbidity and death, especially infection from the extensively drug-resistant bacteria, A. baumannii. A total of fourteen A. baumannii isolates were isolated from the donors’ preserved fluid from DCD (donation after cardiac death) renal transplantation and four isolates in the recipients’ draining liquid at the Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, from March 2013 to November 2014. An outbreak of A. baumannii emerging after DCD renal transplantation was tracked to understand the transmission of the pathogen. PFGE displayed similar DNA patterns between isolates from the same hospital. Antimicrobial susceptibility tests against thirteen antimicrobial agents were determined using the K-B diffusion method and eTest. Whole-genome sequencing was applied to investigate the genetic relationship of the isolates. With the clinical data and research results, we concluded that the A. baumannii isolates 3R1 and 3R2 was probably transmitted from the donor who acquired the bacteria during his stay in the ICU, while isolate 4R1 was transmitted from 3R1 and 3R2 via medical manipulation. This study demonstrated the value of integration of clinical profiles with molecular methods in outbreak investigation and their importance in controlling infection and preventing serious complications after DCD transplantation.

Intercellular interactions play a central role at the tissue and whole organism level modulating key cellular functions in normal and disease states. Studies of cell-cell communications are challenging due to ensemble averaging effects brought about by intrinsic heterogeneity in cellular function which requires such studies to be conducted with small populations of cells. Most of the current methods for producing and studying such small cell populations are complex to implement and require skilled personnel limiting their widespread utility in biomedical research labs. We present a simple and rapid method to produce small populations with varying size of epithelial cells (10–50 cells/population) with high-throughput (~1 population/second) on flat surfaces via patterning of extracellular matrix (ECM) proteins and random seeding of cells. We demonstrate that despite inherent limitations of non-contact, drop-on-demand piezoelectric inkjet printing for protein patterning, varying mixtures of ECM proteins can be deposited with high reproducibility and level of control on glass substrates using a set of dynamically adjustable optimized deposition parameters. We demonstrate high consistency for the number of cells per population (~1 cell standard error of mean), the population’s size (~0.2 coefficient of variation) and shape, as well as accurate spatial placement of and distance between colonies of a panel of metaplastic and dysplastic esophageal epithelial cells with differing adhesion and motility characteristics. The number of cells per colony, colony size and shape can be varied by dynamically varying the amount of ECM proteins deposited per spatial location and the number of spatial locations on the substrate. The method is applicable to a broad range of biological and biomedical studies including cell-cell communications, cellular microenvironment, migration, and stimulus response.

Whole genome sequencing (WGS) is a promising strategy to unravel variants or genes responsible for human diseases and traits. However, there is a lack of robust platforms for a comprehensive downstream analysis. In the present study, we first proposed three novel algorithms, sequence gap-filled gene feature annotation, bit-block encoded genotypes and sectional fast access to text lines to address three fundamental problems. The three algorithms then formed the infrastructure of a robust parallel computing framework, KGGSeq, for integrating downstream analysis functions for whole genome sequencing data. KGGSeq has been equipped with a comprehensive set of analysis functions for quality control, filtration, annotation, pathogenic prediction and statistical tests. In the tests with whole genome sequencing data from 1000 Genomes Project, KGGSeq annotated several thousand more reliable non-synonymous variants than other widely used tools (e.g. ANNOVAR and SNPEff). It took only around half an hour on a small server with 10 CPUs to access genotypes of ∼60 million variants of 2504 subjects, while a popular alternative tool required around one day. KGGSeq's bit-block genotype format used 1.5% or less space to flexibly represent phased or unphased genotypes with multiple alleles and achieved a speed of over 1000 times faster to calculate genotypic correlation.

Precise spatial positioning and isolation of mammalian cells is a critical component of many single cell experimental methods and biological engineering applications. Although a variety of cell patterning methods have been demonstrated, many of these methods subject cells to high stress environments, discriminate against certain phenotypes, or are a challenge to implement. Here, we demonstrate a rapid, simple, indiscriminate, and minimally perturbing cell patterning method using a laser fabricated polymer stencil. The stencil fabrication process requires no stencil-substrate alignment, and is readily adaptable to various substrate geometries and experiments.

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy.

Male courtship display is common in many animals; in some cases, males engage in courtship indiscriminately, spending significant time and energy courting heterospecifics with whom they have no chance of mating or producing viable offspring. Due to high costs and few if any benefits, we might expect mechanisms to evolve to reduce such misdirected courtship (or ‘reproductive interference’). In Habronattus jumping spiders, males frequently court heterospecifics with whom they do not mate or hybridize; females are larger and are voracious predators, posing a severe risk to males who court indiscriminately. In this study, we examined patterns of misdirected courtship in a natural community of four sympatric Habronattus species (H. clypeatus, H. hallani, H. hirsutus, and H. pyrrithrix).

We used direct field observations to weigh support for two hypotheses (differential microhabitat use and species recognition signaling) to explain how these species reduce the costs associated with misdirected courtship. We show that, while the four species of Habronattus do show some differences in microhabitat use, all four species still overlap substantially, and in three of the four species individuals equally encountered heterospecifics and conspecifics. Males courted females at every opportunity, regardless of species, and in some cases, this led to aggression and predation by the female. These results suggest that, while differences in microhabitat use might reduce misdirected courtship to some extent, co-existence of these four species may be possible due to complex communication (i.e. species-specific elements of a male’s courtship display). This study is the first to examine misdirected courtship in jumping spiders. Studies of misdirected courtship and its consequences in the field are limited and may broaden our understanding of how biodiversity is maintained within a community.