Biology subjects

Hu, H.

Publications and source records attributed to Hu, H..

275 records · Page 16Linked to original sources

bioRxiv2017

Continuous gene flow contributes to low global species abundance and distribution of a marine model diatom

Diatoms emerged in the Mesozoic period and presently constitute one of the main primary producers in the worlds ocean and are of a major economic importance. In the current study, using whole genome sequencing of ten accessions of the model diatom Phaeodactylum tricornutum, sampled at broad geospatial and temporal scales, we draw a comprehensive landscape of the genomic diversity within the species. We describe strong genetic subdivisions of the accessions into four genetic clades (A-D) with constituent populations of each clade possessing a conserved genetic and functional makeup, likely a consequence of the limited dispersal of P. tricornutum in the open ocean. We further suggest dominance of asexual reproduction across all the populations, as implied by high linkage disequilibrium. Finally, we show limited yet compelling signatures of genetic and functional convergence inducing changes in the selection pressure on many genes and metabolic pathways. We propose these findings to have significant implications for understanding the genetic structure of diatom populations in nature and provide a framework to assess the genomic underpinnings of their ecological success and impact on aquatic ecosystems where they play a major role. Our work provides valuable resources for functional genomics and for exploiting the biotechnological potential of this model diatom species.

genomics↗

bioRxiv2017

GEM: A manifold learning based framework for reconstructing spatial organizations of chromosomes

Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, Chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to elucidate the underlying 3D spatial organizations of chromosomes from Hi-C data. Unlike previous chromatin structure reconstruction methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances between distal genomic loci, GEM is able to reconstruct an ensemble of chromatin conformations by directly embedding the neigh-boring affinities from Hi-C space into 3D Euclidean space based on a manifold learning strategy that considers both the fitness of Hi-C data and the biophysical feasibility of the modeled structures, which are measured by the conformational energy derived from our current biophysical knowledge about the 3D polymer model. Extensive validation tests on both simulated interaction frequency data and experimental Hi-C data of yeast and human demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also reconstructed accurate chromatin structures that agreed well with the hold-out or independent Hi-C data and sparse geometric restraints derived from the previous fluorescence in situ hybridization (FISH) studies. In addition, as GEM can generate accurate spatial organizations of chromosomes by integrating both experimentally-derived spatial contacts and conformational energy, we for the first time extended our modeling method to recover long-range genomic interactions that are missing from the original Hi-C data. All these results indicated that GEM can provide a physically and physiologically valid 3D representations of the organizations of chromosomes and thus serve as an effective and useful genome structure reconstructor.

bioinformatics↗

bioRxiv2017

Melanism patches up the defective cuticular morphological traits through promoting the up-regulation of cuticular protein-coding genes in Bombyx mori

Melanin and cuticular proteins are important cuticle components in insect. Cuticle defects caused by mutations in cuticular protein-encoding genes can hinder melanin deposition. However, the effects of melanin variation on cuticular protein-encoding genes and the corresponding morphological traits associated with these genes are remain largely unknown. Using Bombyx mori as a model, we showed that the melanism levels during larval cuticle pigmentation correlated positively with the expression of cuticular protein-encoding genes. This correlation stemmed from the simultaneous induction of these genes by the melanin precursors. More importantly, the effect of the melanism background on the cuticles induced the up-regulation of other functionally redundant cuticular protein-encoding genes to rescue the morphological and adaptive defects caused by the dysfunction of some mutated cuticular proteins, and the restorative ability increased with increasing melanism levels, which gives a novel evidence that melanism enhances insect adaptability. These findings deepen our understanding of the interactions among cuticle components, as well as their importance in the stabilizing of the normal morphology and function of the cuticle.

genetics↗

bioRxiv2017

Secretogranin-II Plays A Critical Role In Zebrafish Neurovascular Modeling

Summary statementNeurons expressing sgIIb align with central arteries in hindbrain. We show that sgIIb is critical for neurovascular modeling the larval zebrafish mediated by MAPK and PI3K/AKT signaling in vivo.\n\nAbstractSecretoneurin (SN) is a neuropeptide derived from specific proteolytic processing of the precursor secretogranin II (SgII). In zebrafish and other teleosts there are 2 paralogs we previously named sgIIa and sgIIb. Our results showed that neurons expressing sgIIb were aligned with central arteries in hindbrain, demonstrating a close neurovascular association. Both sgIIb-/- and sgIIa-/- /sgIIb-/- mutant embryos were defective in hindbrain central artery development, while artery development in sgIIa-/- mutant embryos was not affected. Hindbrain arterial and venous network identities were not affected in sgIIb-/- mutant embryos, and the mRNA levels of Notch and VEGF pathway-related genes were not altered. However, the activation of MAPK and PI3K/AKT pathways were inhibited in sgIIb-/- mutant embryos. Injection of a synthetic SNb mRNA or delivery of the protein kinase activator N-arachidonoyl-L-serine could partially rescue the central artery developmental defects in the sgIIb mutants. This study provides the first in vivo evidence that sgIIb plays a critical role in neurovascular modeling the hindbrain.

developmental biology↗

bioRxiv2017

TIDE: predicting translation initiation sites by deep learning

MotivationTranslation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-AUG codons), which makes it challenging to predict TISs and study the underlying regulatory mechanisms. Meanwhile, the advent of several high-throughput sequencing techniques for profiling initiating ribosomes at single-nucleotide resolution, e.g., GTI-seq and QTI-seq, provides abundant data for systematically studying the general principles of translation initiation and the development of computational method for TIS identification.\n\nMethodsWe have developed a deep learning based framework, named TITER, for accurately predicting TISs on a genome-wide scale based on QTI-seq data. TITER extracts the sequence features of translation initiation from the surrounding sequence contexts of TISs using a hybrid neural network and further integrates the prior preference of TIS codon composition into a unified prediction framework.\n\nResultsExtensive tests demonstrated that TITER can greatly outperform the state-of-the-art prediction methods in identifying TISs. In addition, TITER was able to identify important sequence signatures for individual types of TIS codons, including a Kozak-sequence-like motif for AUG start codon. Furthermore, the TITER prediction score can be related to the strength of translation initiation in various biological scenarios, including the repressive effect of the upstream open reading frames (uORFs) on gene expression and the mutational effects influencing translation initiation efficiency.\n\nAvailabilityTITER is available as an open-source software and can be downloaded from https://github.com/zhangsaithu/titer\n\nContactlzhang20@mail.tsinghua.edu.cn and zengjy321@tsinghua.edu.cn

bioinformatics↗