Biology subjects

Luo, J.

Publications and source records attributed to Luo, J..

313 records · Page 18Linked to original sources

bioRxiv2017

Funmap2: an R package for QTL mapping using longitudinal phenotypes

QTL mapping is a powerful tool to infer the complexity of the genetic architecture underlying phenotypic traits, and has been extended to include longitudinal traits measured at multiple temporal/spatial points. Here, we introduce the R package Funmap2 based on the functional mapping framework, which integrates biological prior knowledge into the statistical model. Specifically, the functional mapping framework is engineered to include longitudinal curves that describes the genetic effects, and the covariance matrix of the trait of interest. Funmap2 may automatically choose the type of longitudinal curve and covariance matrix by information criterion. Funmap2 is available for download at https://github.com/wzhy2000/Funmap2.

genetics↗

bioRxiv2017

A chemosensory switch couples genetic sex to behavioral valence

As a fundamental dimension of internal state, biological sex modulates neural circuits to generate naturally occurring behavioral variation. Understanding how and why circuits are tuned by sex can provide important insights into neural and behavioral plasticity. Here, we find that sexually dimorphic behavioral responses to C. elegans ascaroside sex pheromones are implemented by the functional modulation of shared chemosensory circuitry. In particular, the sexual state of a single sensory neuron pair, ADF, determines the nature of an animal's behavioral response regardless of the sex of the rest of the body. Genetic feminization of ADF causes males to be repelled by, rather than attracted to, ascarosides, while masculinization of ADF is sufficient to make ascarosides attractive to hermaphrodites. Genetic sex modulates ADF function by tuning chemosensation: ADF is able to detect the ascaroside ascr#3 only in males, a consequence of cell-autonomous action of the master sexual regulator tra-1. Genetic sex regulates behavior in part through the conserved DMRT gene mab-3, whose male-specific expression in ADF promotes ascaroside attraction. The sexual modulation of ADF has a key role in reproductive fitness, as feminization or ablation of ADF renders males unable to use ascarosides to locate mates. These results demonstrate that DMRT genes can functionally modulate shared neural circuits; moreover, they reveal an adaptive mechanism in which chromosomal sex controls a cell-autonomous switch that tunes sensory function, determines behavioral valence, and promotes reproductive fitness.

neuroscience↗

bioRxiv2017

Transcription activator-coactivator specificity is mediated by a large and dynamic fuzzy protein-protein complex

Transcription activation domains (ADs) are inherently disordered proteins that often target multiple coactivator complexes, but the specificity of these interactions is not understood. Efficient activation by yeast Gcn4 requires tandem Gcn4 ADs and four activator-binding domains (ABDs) on its target, the Mediator subunit Med15. Multiple ABDs are a common feature of coactivator complexes. We find that the large Gcn4-Med15 complex is heterogeneous, containing nearly all possible AD-ABD interactions. This complex forms using a dynamic fuzzy protein-protein interface where ADs use hydrophobic residues to bind hydrophobic surfaces of the ABDs in multiple orientations. This combinatorial mechanism allows individual interactions of low affinity and specificity to generate a biologically functional, specific, and higher affinity complex despite lacking a defined protein-protein interface. This binding strategy is likely representative of many activators that target multiple coactivators and allows great flexibility in combinations of activators that synergize to regulate genes with variable coactivator requirements.

molecular biology↗

bioRxiv2017

Ennet: exert enhaner-only somatic mutations to discover potential cancer-driving biological networks

Whole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, including ESR1, SMAD3, MYC, EGFR, BCL2 and PAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.

bioinformatics↗

bioRxiv2017

UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants

Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease-related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated SNP data show that 32% of UniProtKB variants co-locate with 8% of ClinVar SNPs. The majority of co-located UniProtKB disease-associated variants (86%) map to pathogenic ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.

genomics↗

bioRxiv2017

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision

Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety of biological contexts involving in AS, such as development and diseases. We assembled splicing (epi)genetic code, DeepCode, for human embryonic stem cell (hESC) differentiation by integrating heterogeneous features of genomic sequences, 16 histone modifications with a multi-label deep neural network. With the advantages of epigenetic features, DeepCode significantly improves the performance in predicting the splicing patterns and their changes during hESC differentiation. Meanwhile, DeepCode reveals the superiority of epigenomic features and their dominant roles in decoding AS patterns, highlighting the necessity of including the epigenetic properties when assembling a more comprehensive splicing code. Moreover, DeepCode allows the robust predictions across cell lineages and datasets. Especially, we identified a putative H3K36me3-regulated AS event leading to a nonsense-mediated mRNA decay of BARD1. Reduced BARD1 expression results in the attenuation of ATM/ATR signalling activities and further the hESC differentiation. These results suggest a novel candidate mechanism linking histone modifications to hESC fate decision. In addition, when trained in different contexts, DeepCode can be expanded to a variety of biological and biomedical fields.

bioinformatics↗

bioRxiv2017

Homology-based hydrogen bond information improves crystallographic structures in the PDB

Crystallographic structure models in the Protein Data Bank (PDB) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H-bond) distances as a source of information. However, H-bond restraints can improve structures, especially at low resolution where diffraction data are limited. To improve low-resolution structure refinement, we present methods for deriving H-bond information either globally from well-refined high-resolution structures from the PDB-REDO databank, or specifically from on-the-fly constructed sets of homologous high-resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low-resolution structures. Using approximately 60 years of CPU-time in massively parallel computing, we constructed a new instance of the PDB-REDO databank, a novel resource to help biologists gain insight on protein families or on specific structures, as we demonstrate with examples.

biochemistry↗