Biology subjects

Yang, Z.

Publications and source records attributed to Yang, Z..

29 records · Page 2Linked to original sources

bioRxiv2018

The dyslexia susceptibility KIAA0319 gene shows a highly specific expression pattern during zebrafish development supporting a role beyond neuronal migration.

Dyslexia is a common neurodevelopmental disorder that affects reading abilities and is predicted to be caused by a significant genetic component. Very few genetic susceptibility factors have been identified so far and amongst those, KIAA0319 is a key candidate. KIAA0319 is highly expressed during brain development but its function remains poorly understood. Initial RNA-interference studies in rats suggested a role in neuronal migration whereas subsequent work with double knock-out mouse models for both Kiaa0319 and its paralogue Kiaa0319-like reported effects in the auditory system but not in neuronal migration. To further understand the role of KIAA0319 during neurodevelopment, we carried out an expression study of the zebrafish orthologue at different embryonic stages. We report particularly high gene expression during the first few hours of development. At later stages, expression becomes localised in well-defined structures such as the eyes, the telencephalon and the notochord, supporting a role for kiaa0319 that is not restricted to brain development. Surprisingly, kiaa0319-like, which generally shows a similar expression pattern, was not expressed in the notochord suggesting a role specific to kiaa0319 in this structure. This study contributes to our understanding of KIAA0319 function during embryonic development which might involve additional roles in the visual system and in the notochord. Such a specific spatiotemporal expression pattern is likely to be under the controlled of tightly regulated sequences. Therefore, these data provide a framework to interpret the effects of the dyslexia-associated genetic variants that reside in KIAA0319 non-coding regulatory regions.

neuroscience↗

bioRxiv2018

The Spectre of Too Many Species

Recent simulation studies examining the performance of Bayesian species delimitation as implemented in the BPP program have suggested that BPP may detect population splits but not species divergences and that it tends to over-split when data of many loci are analyzed. Here we confirm several of these results and provide their mathematical justifications. We point out that the distinction between population and species splits made in the protracted speciation model has no influence on the generation of gene trees and sequence data, which explains why no method can use such data to distinguish between population splits and speciation. We suggest that the the protracted speciation model is unrealistic and its mechanism for assigning species status contradicts prevailing taxonomic practice. We confirm the suggestion, based on simulation, that in the case of speciation with gene flow, Bayesian model selection as implemented in BPP tends to detect population splits when the amount of data (the number of loci) increases so over-splitting is a legitimate concern. We discuss the use of a recently proposed empirical genealogical divergence index (gdi) for species delimitation and illustrate that parameter estimates produced by a full likelihood analysis as implemented in BPP provide much more reliable inference under the gdi than the approximate method PHRAPL. We suggest that the Bayesian model-selection approach is useful for identifying sympatric cryptic species while Bayesian parameter estimation under the multispecies coalescent can be used to implement empirical criteria for determining species status among allopatric populations.

evolutionary biology↗

bioRxiv2018

Time-scale separation and stochasticity conspire to impact phenotypic dynamics in the canonical and inverted Bacillus subtilis core genetic regulation circuits.

In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil. We focus on hitherto unchartered aspects of the dynamics by exploring the effect of time scale separation between transcription and translation and, as well, the effect of intrinsic molecular stochasticity. We consider these aspects of regulatory control as two possible evolutionary handles. Hence, using theory and computations, we study how the onset of oscillations breaks the excitability-based competence phenotype in two topologically close evolutionary competing circuits: the canonical \"wild-type\" regulation circuit selected by Evolution and, the indirect-feedback inverted circuit that failed to be selected by Evolution, as was shown elsewhere, due to dynamical reasons.

systems biology↗

bioRxiv2017

An internal sensor detects dietary amino acids and promotes food consumption in Drosophila

Adequate protein intake is crucial for animals. Despite the recent progress in understanding protein hunger and satiety in the fruit fly Drosophila melanogaster, how fruit flies assess prospective dietary protein sources and ensure protein consumption remains elusive. We show here that three specific amino acids, L-glutamate (L-Glu), L-alanine (L-Ala), and L-aspartate (L-Asp), rapidly promote food consumption in fruit flies when present in food. The effect of dietary amino acids to promote food consumption is independent of mating experience and internal nutritional status. Genetic analysis identifies six brain neurons expressing diuretic hormone 44 (DH44) as a sensor of dietary amino acids. DH44+ neurons can be directly activated by these three amino acids, and are both necessary and sufficient for dietary amino acids to promote food consumption. By conducting single cell RNAseq analysis, we also identify an amino acid transporter, CG13248, which is highly expressed in DH44+ neurons and is required for dietary amino acids to promote food consumption. Therefore, these data suggest that dietary amino acids may enter DH44+ neurons via CG13248 and modulate their activity and hence food consumption. Taken together, these data identify an internal amino acid sensor in the fly brain that evaluate food sources post-ingestively and facilitates adequate protein intake.

neuroscience↗

bioRxiv2017

Deficit in parietal memory network underlies auditory hallucination: a longitudinal study

Auditory hallucination is a prominent and common symptom in schizophrenia. Previous neuroimaging studies have yielded mixed results of its brain network deficits. We proposed a novel hypothesis that parietal memory network, centered at the precuneus, plays a critical role in auditory hallucination. This network is adjacent and partially overlaps with the default mode network, and has been associated with brain function of familiarity labelling in memory processing. Using a longitudinal design and a large cohort of first-episode, drug-naive schizophrenia patients, we examined this hypothesis and further investigated whether the functional connectivity patterns of the parietal memory network can serve as a neuroimaging marker for auditory hallucination and help to predict future treatment effects. Resting-state scans from 59 first-episode drug-naive schizophrenic patients (27 with and 32 without hallucination) and 53 healthy control subjects were acquired at the baseline test, and 56 of them were scanned again after two months. Functional connectivity strength within the parietal memory network and between this network and memory hubs was across the three groups at baseline and follow-up scans. Results showed that decreased functional connectivity strength within the parietal memory network was specific to the auditory hallucination group (p = 0.009, compare to the healthy subjects; p = 0.029, compare to the patients without hallucination), with the precuneus representing the largest group difference. The intra-network connectivity strength of the precuneus negatively correlated with the severity of hallucination at the baseline scan (r = -0.437, p = 0.029), and it was significantly increased after two-month medication (p = 0.039). Logistic regression analysis and crossvalidation test demonstrated that the functional connectivity strength of the precuneus and precuneus-hippocampus connectivity could differentiate patients with or without auditory hallucination with a sensitivity of 0.750 and a specificity of 0.708. Moreover, crossvalidation test showed that these imaging features at the baseline scan well predicted the extents of positive symptom improvement in the hallucination group after the two-month medication (R2 = 0.433, p = 0.022). Our results provide evidence for a critical role of the parietal memory network underlying auditory hallucination, and further propose a novel neuroimaging marker for identifying patients, accessing severity, and prognosis of treatment effect for auditory hallucination.\n\nAbbreviations

neuroscience↗

bioRxiv2017

Using phylogenomic data to explore the effects of relaxed clocks and calibration strategies on divergence time estimation: Primates as a test case

Primates have long been a test case for the development of phylogenetic methods for divergence time estimation. Despite a large number of studies, however, the timing of origination of crown Primates relative to the K-Pg boundary and the timing of diversification of the main crown groups remain controversial. Here we analysed a dataset of 372 taxa (367 Primates and 5 outgroups, 61 thousand base pairs) that includes nine complete primate genomes (3.4 million base pairs). We systematically explore the effect of different interpretations of fossil calibrations and molecular clock models on primate divergence time estimates. We find that even small differences in the construction of fossil calibrations can have a noticeable impact on estimated divergence times, especially for the oldest nodes in the tree. Notably, choice of molecular rate model (auto-correlated or independently distributed rates) has an especially strong effect on estimated times, with the independent rates model producing considerably more ancient estimates for the deeper nodes in the phylogeny. We implement thermodynamic integration, combined with Gaussian quadrature, in the program MCMCTree, and use it to calculate Bayes factors for clock models. Bayesian model selection indicates that the auto-correlated rates model fits the primate data substantially better, and we conclude that time estimates under this model should be preferred. We show that for eight core nodes in the phylogeny, uncertainty in time estimates is close to the theoretical limit imposed by fossil uncertainties. Thus, these estimates are unlikely to be improved by collecting additional molecular sequence data. All analyses place the origin of Primates close to the K-Pg boundary, either in the Cretaceous or straddling the boundary into the Palaeogene.

evolutionary biology↗

bioRxiv2017

SSEalign: accurate function prediction of bacterial unannotated protein, based on effective training dataset

The functions of numerous bacterial proteins remain unknown because of the variety of their sequences. The performances of existing prediction methods are highly weak toward these proteins, leading to the annotation of \"hypothetical protein\" deposited in NCBI database. Elucidating the functions of these unannotated proteins is an urgent task in computational biology. We report a method about secondary structure element alignment called SSEalign based on an effective training dataset extracting from 20 well-studied bacterial genomes. The experimentally validated same genes in different species were selected as training positives, while different genes in different species were selected as training negatives. Moreover, SSEalign used a set of well-defined basic alignment elements with the backtracking line search algorithm to derive the best parameters for accurate prediction. Experimental results showed that SSEalign achieved 91.2% test accuracy, better than existing prediction methods. SSEalign was subsequently applied to identify the functions of those unannotated proteins in the latest published minimal bacteria genome JCVI-syn3.0. Results indicated that At least 99 proteins out of 149 unannotated proteins in the JCVI-syn3.0 genome could be annotated by SSEalign. In conclusion, our method is effective for the identification of protein homology and the annotation of uncharacterized proteins in the genome.

bioinformatics↗

bioRxiv2017

PANINI: Pangenome Neighbor Identification for Bacterial Populations

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, in the current era of population genomics, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here we introduce PANINI, a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding. PANINI is browser-based and integrates with the Microreact platform for rapid online visualisation and exploration of both core and accessory genome evolutionary signals together with relevant epidemiological, geographic, temporal and other metadata. Several case studies with single-and multi-clone pneumococcal populations are presented to demonstrate ability to identify biologically important signals from gene content data. PANINI is available at http://panini.wgsa.net/ and code at http://gitlab.com/cgps/panini

microbiology↗

bioRxiv2017

P53 toxicity is a hurdle to CRISPR/CAS9 screening and engineering in human pluripotent stem cells

CRISPR/Cas9 has revolutionized our ability to engineer genomes and to conduct genome-wide screens in human cells. While some cell types are easily modified with Cas9, human pluripotent stem cells (hPSCs) poorly tolerate Cas9 and are difficult to engineer. Using a stable Cas9 cell line or transient delivery of ribonucleoproteins (RNPs) we achieved an average insertion or deletion efficiency greater than 80%. This high efficiency made it apparent that double strand breaks (DSBs) induced by Cas9 are toxic and kill most treated hPSCs. Cas9 toxicity creates an obstacle to the high-throughput use CRISPR/Cas9 for genome-engineering and screening in hPSCs. We demonstrated the toxic response is tp53-dependent and the toxic effect of tp53 severely reduces the efficiency of precise genome-engineering in hPSCs. Our results highlight that CRISPR-based therapies derived from hPSCs should proceed with caution. Following engineering, it is critical to monitor for tp53 function, especially in hPSCs which spontaneously acquire tp53 mutations.

molecular biology↗

bioRxiv2017

Neural decoding of visual stimuli varies with fluctuations in global network efficiency

Functional magnetic resonance imaging (fMRI) studies have shown that neural activity fluctuates spontaneously between different states of global synchronization over a timescale of several seconds. Such fluctuations generate transient states of high and low correlation across distributed cortical areas. It has been hypothesized that such fluctuations in global efficiency might alter patterns of activity in local neuronal populations elicited by changes in incoming sensory stimuli. To test this prediction, we used a linear decoder to discriminate patterns of neural activity elicited by face and motion stimuli presented periodically while participants underwent time-resolved fMRI. As predicted, decoding was reliably higher during states of high global efficiency than during states of low efficiency, and this difference was evident across both visual and non-visual cortical regions. The results indicate that slow fluctuations in global network efficiency are associated with variations in the pattern of activity across widespread cortical regions responsible for representing distinct categories of visual stimulus. More broadly, the findings highlight the importance of understanding the impact of global fluctuations in functional connectivity on specialised, stimulus driven neural processes.

neuroscience↗

bioRxiv2016

Segregation between the parietal memory network and the default mode network: Effects of spatial smoothing and model order in ICA

A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network (DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network (PMN). Independent component analysis (ICA) is the most common data-driven method of extracting PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determination in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high-order model across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

neuroscience↗