Improved Reconstruction of In Silico Gene Regulatory Networks by Integrating Knockout and Perturbation Data

We performed computational reconstruction of the in silico gene regulatory networks in the DREAM3 Challenges. Our task was to learn the networks from two types of data, namely gene expression profiles in deletion strains (the ‘deletion data’) and time series trajectories of gene expression after some initial perturbation (the ‘perturbation data’). In the course of developing the prediction method, we observed that the two types of data contained different and complementary information about the underlying network. In particular, deletion data allow for the detection of direct regulatory activities with strong responses upon the deletion of the regulator while perturbation data provide richer information for the identification of weaker and more complex types of regulation. We applied different techniques to learn the regulation from the two types of data. For deletion data, we learned a noise model to distinguish real signals from random fluctuations using an iterative method. For perturbation data, we used differential equations to model the change of expression levels of a gene along the trajectories due to the regulation of other genes. We tried different models, and combined their predictions. The final predictions were obtained by merging the results from the two types of data. A comparison with the actual regulatory networks suggests that our approach is effective for networks with a range of different sizes. The success of the approach demonstrates the importance of integrating heterogeneous data in network reconstruction

OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps.

BackgroundOptical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples.FindingsWe present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains.ConclusionsWith the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools

A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets

We develop a statistical framework to study the relationship between chromatin features and gene expression. This can be used to predict gene expression of protein coding genes, as well as microRNAs. We demonstrate the prediction in a variety of contexts, focusing particularly on the modENCODE worm datasets. Moreover, our framework reveals the positional contribution around genes (upstream or downstream) of distinct chromatin features to the overall prediction of expression levels

SKIP controls lysosome positioning using a composite kinesin-1 heavy and light chain-binding domain

The molecular interplay between cargo recognition and regulation of the activity of the kinesin-1 microtubule motor is not well understood. Using the lysosome adaptor SKIP (also known as PLEKHM2) as model cargo, we show that the kinesin heavy chains (KHCs), in addition to the kinesin light chains (KLCs), can recognize tryptophanacidic- binding determinants on the cargo when presented in the context of an extended KHC-interacting domain. Mutational separation of KHC and KLC binding shows that both interactions are important for SKIP-kinesin-1 interaction in vitro and that KHC binding is important for lysosome transport in vivo. However, in the absence of KLCs, SKIP can only bind to KHC when autoinhibition is relieved, suggesting that the KLCs gate access to the KHCs. We propose a model whereby tryptophan-acidic cargo is first recognized by KLCs, resulting in destabilization of KHC autoinhibition. This primary event then makes accessible a second SKIP-binding site on the KHC C-terminal tail that is adjacent to the autoinhibitory IAK region. Thus, cargo recognition and concurrent activation of kinesin-1 proceed in hierarchical stepwise fashion driven by a dynamic network of inter- and intra-molecular interactions

Genome maps across 26 human populations reveal population-specific patterns of structural variation.

Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome

The light chains of kinesin-1 are autoinhibited

The light chains (KLCs) of the microtubule motor kinesin-1 bind cargoes and regulate its activity. Through their tetratricopeptide repeat domain (KLCTPR), they can recognize short linear peptide motifs found in many cargo proteins characterized by a central tryptophan flanked by aspartic/glutamic acid residues (W-acidic). Using a fluorescence resonance energy transfer biosensor in combination with X-ray crystallographic, biochemical, and biophysical approaches, we describe how an intramolecular interaction between the KLC2TPR domain and a conserved peptide motif within an unstructured region of the molecule, partly occludes the W-acidic binding site on the TPR domain. Cargo binding displaces this interaction, effecting a global conformational change in KLCs resulting in a more extended conformation. Thus, like the motor-bearing kinesin heavy chains, KLCs exist in a dynamic conformational state that is regulated by self-interaction and cargo binding. We propose a model by which, via this molecular switch, W-acidic cargo binding regulates the activity of the holoenzyme

Intermolecular CT excitons enable nanosecond excited-state lifetimes in NIR-absorbing non-fullerene acceptors for efficient organic solar cells

State-of-the-art Y6-type molecular acceptors exhibit nanosecond excited-state lifetimes despite their low optical gaps (~1.4 eV), thus allowing organic solar cells (OSCs) to achieve highly efficient charge generation with extended near-infrared (NIR) absorption range (up to ~1000 nm). However, the precise molecular-level mechanism that enables low-energy excited states in Y6-type acceptors to achieve nanosecond lifetimes has remained elusive. Here, we demonstrate that the distinct packing of Y6 molecules in film leads to a strong intermolecular charge-transfer (iCT) character of the lowest excited state in Y6 aggregates, which is absent in other low-gap acceptors such as ITIC. Due to strong electronic couplings between the adjacent Y6 molecules, the iCT-exciton energies are greatly reduced by up to ~0.25 eV with respect to excitons formed in separated molecules. Importantly, despite their low energies, the iCT excitons have reduced non-adiabatic electron-vibration couplings with the electronic ground state, thus suppressing non-radiative recombination and allowing Y6 to overcome the well-known energy gap law. Our results reveal the fundamental relationship between molecular packing and nanosecond excited-state lifetimes in NIR-absorbing Y6-type acceptors underlying the outstanding performance of Y6-based OSCs

Molecular mechanism for kinesin-1 direct membrane recognition

The cargo-binding capabilities of cytoskeletal motor proteins have expanded during evolution through both gene duplication and alternative splicing. For the light chains of the kinesin-1 family of microtubule motors, this has resulted in an array of carboxyl-terminal domain sequences of unknown molecular function. Here, combining phylogenetic analyses with biophysical, biochemical, and cell biology approaches, we identify a highly conserved membrane-induced curvature-sensitive amphipathic helix within this region of a subset of long kinesin light-chain paralogs and splice isoforms. This helix mediates the direct binding of kinesin-1 to lipid membranes. Membrane binding requires specific anionic phospholipids, and it contributes to kinesin-1\u2013dependent lysosome positioning, a canonical activity that, until now, has been attributed exclusively the recognition of organelle-associated cargo adaptor proteins. This leads us to propose a protein-lipid coincidence detection framework for kinesin-1\u2013mediated organelle transport

Long-lived and disorder-free charge transfer states enable endothermic charge separation in efficient non-fullerene organic solar cells

Funder: HKU | University Research Committee, University of Hong Kong (HKU Research Committee); doi: https://doi.org/10.13039/501100003802Abstract: Organic solar cells based on non-fullerene acceptors can show high charge generation yields despite near-zero donor–acceptor energy offsets to drive charge separation and overcome the mutual Coulomb attraction between electron and hole. Here, we use time-resolved optical spectroscopy to show that free charges in these systems are generated by thermally activated dissociation of interfacial charge-transfer states that occurs over hundreds of picoseconds at room temperature, three orders of magnitude slower than comparable fullerene-based systems. Upon free electron–hole encounters at later times, both charge-transfer states and emissive excitons are regenerated, thus setting up an equilibrium between excitons, charge-transfer states and free charges. Our results suggest that the formation of long-lived and disorder-free charge-transfer states in these systems enables them to operate closely to quasi-thermodynamic conditions with no requirement for energy offsets to drive interfacial charge separation and achieve suppressed non-radiative recombination

Emissive charge-transfer states at hybrid inorganic/organic heterojunctions enable low non-radiative recombination and high-performance photodetectors

Hybrid devices based on a heterojunction between inorganic and organic semiconductors have offered a means to combine the advantages of both classes of materials in optoelectronic devices, but, in practice, the performance of such devices has often been disappointing. Here, it is demonstrated that charge generation in hybrid inorganic–organic heterojunctions consisting of copper thiocyanate (CuSCN) and a variety of molecular acceptors (ITIC, IT-4F, Y6, PC70BM, C70, C60) proceeds via emissive charge-transfer (CT) states analogous to those found at all-organic heterojunctions. Importantly, contrary to what has been observed at previous organic–inorganic heterojunctions, the dissociation of the CT-exciton and subsequent charge separation is efficient, allowing the fabrication of planar photovoltaic devices with very low non-radiative voltage losses (0.21 ±  0.02 V). It is shown that such low non-radiative recombination enables the fabrication of simple and cost-effective near-IR (NIR) detectors with extremely low dark current (4 pA cm−2) and noise spectral density (3 fA Hz−1/2) at no external bias, leading to specific detectivities at NIR wavelengths of just under 1013 Jones, close to the performance of commercial silicon photodetectors. It is believed that this work demonstrates the possibility for hybrid heterojunctions to exploit the unique properties of both inorganic and organic semiconductors for high-performance opto-electronic devices