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Shi, Q.

Publications and source records attributed to Shi, Q..

10 recordsLinked to original sources

The mitochondrial DNA content can not predict the embryo viability

ObjectiveTo investigate whether the mitochondrial DNA content could predict the embryo viability\n\nDesignRetrospective analysis.\n\nSettingReproductive genetics laboratory\n\nPatient(s)A total of 421 biopsied samples obtained from 129 patients\n\nIntervention(s)Embryo biopsies samples underwent whole genome amplification (WGA) and were tested by next generation sequencing (NGS) and array Comparative Genomic Hybridization (aCGH), 30 samples were selected randomly to undergo quantitative real-time polymerase chain reaction (qPCR).\n\nMain Outcome Measure(s)Those embryos which obtained the consistent chromosome status determined both aCGH and NGS platform were further classified. We investigated the relationship of mtDNA content with several factors including female patient age, embryo morphology, chromosome status, and live birth rate of both blastocysts and blastomeres.\n\nResult(s)A total of 386 (110 blastomeres and 276 blastocysts) out of 399 embryos showed consistent chromosome status outcome. We found no statistically difference was observed in aneuploid and euploid blastocysts (p=0.14), the same phenomenon was observed in aneuploid and euploid blastomeres (p=0.89). Similarly, the mtDNA content was independent of female patient age, embryo morphology and live birth rate.\n\nConclusion(s)The mtDNA content did not provide a reliable prediction of the viability of blastocysts to initiate a pregnancy.

ecology

Functional characterization of retinal ganglion cells using tailored nonlinear modeling

There are 20-50 functionally- and anatomically-distinct ganglion cell types in the mammalian retina; each type encodes a unique feature of the visual world and conveys it via action potentials to the brain. Individual ganglion cells receive input from unique presynaptic retinal circuits, and the characteristic patterns of light-evoked action potentials in each ganglion cell type therefore reflect computations encoded in synaptic input and in postsynaptic signal integration and spike generation. Unfortunately, there is a dearth of tools for characterizing retinal ganglion cell computation. Therefore, we developed a statistical model, the separable Nonlinear Input Model, capable of characterizing the large array of distinct computations reflected in retinal ganglion cell spiking. We recorded ganglion cell responses to a correlated noise (\"cloud\") stimulus designed to accentuate the important features of retinal processing in an in vitro preparation of mouse retina and found that this model accurately predicted ganglion cell responses at high spatiotemporal resolution. It identified multiple receptive fields (RFs) reflecting the main excitatory and suppressive components of the response of each neuron. Most significantly, our model succeeds where others fail, accurately identifying ON-OFF cells and segregating their distinct ON and OFF selectivity and demonstrating the presence of different types of suppressive receptive fields. In total, our computational approach offers rich description of ganglion cell computation and sets a foundation for relating retinal computation to retinal circuitry.

neuroscience

Molecular Mechanisms Governing Shade Responses in Maize

Light is one of the most important environmental factors affecting plant growth and development. Plants use shade avoidance and shade tolerance strategies to adjust their growth and development thus increase their success in the competition for incoming light. To investigate the mechanism of shade responses in maize (Zea mays), we examined the anatomical and transcriptional dynamics of the early shade response in seedlings of the B73 inbred line. Transcriptome analysis identified 912 differentially expressed genes, including genes involved in light signaling, auxin responses, and cell elongation pathways. Grouping transcription factor family genes and performing enrichment analysis identified multiple types of transcription factors that are differentially regulated by shade and predicted putative core genes responsible for regulating shade avoidance syndrome. For functional tests, we ectopically over-expressed ZmHB53, a type II HD-ZIP transcription factor gene significantly induced by shade, in Arabidopsis thaliana. Transgenic Arabidopsis plants overexpressing ZmHB53 exhibited narrower leaves, earlier flowering, and enhanced expression of shade-responsive genes, suggesting that ZmHB53 participates in the regulation of shade responses in maize. This study increases our understanding of the regulatory network of the shade response in maize and provides a useful resource for maize genetics and breeding.\n\nHighlightOur findings not only increase the understanding of the regulatory network of the shade avoidance in maize, and also provide a useful resource for maize genetics and breeding.

plant biology

Repeated Measures Regression In Laboratory, Clincal And Enviromental Research - Different Between/Within Subject Slopes And Common Misconceptions

When using repeated measures linear regression models to make causal inference in laboratory, clinical and environmental research, it is often assumed that the Within Subject association of differences (or changes) in predictor value across replicates is the same as the Between Subject association of differences in those predictor values. But this is often false, for example with body weight as the predictor and blood cholesterol the outcome i) a 10 pound weight increase in the same adult more greatly a higher increase in cholesterol in that adult than does ii) one adult weighing 10 pounds more than a second reflect increased cholesterol levels in the first adult as the weigh difference in i) more closely tracks higher body fat while that in ii) is also influenced by heavier adults being taller. Hence to make causal inferences, different Within and Between subject slopes should be separately modeled. A related misconception commonly made using generalized estimation equations (GEE) and mixed models (MM) on repeated measures (i.e. for fitting Cross Sectional Regression) is that the working correlation structure used only influences variance of model parameter estimates. But only independence working correlation guarantees the modeled parameters have any interpretability. We illustrate this with an example where changing working correlation from independence to equicorrelation qualitatively biases parameters of GEE models and show this happens because Between and Within Subject slopes for the predictor variables differ. We then describe several common mechanisms that cause Within and Between Subject slopes to differ as; change effects, lag/reverse lag and spillover causality, shared within subject measurement bias or confounding, and predictor variable measurement error. The misconceptions noted here should be better publicized in laboratory, clinical and environmental research. Repeated measures analyses should compare Within and Between subject slopes of predictors and when they differ, investigate the reasons this has happened.\n\nHIGHLIGHTSWhen using repeated measures with time varying predictors variables in laboratory, clinical and environmental research: O_LICross sectional regressions with any working correlation structure other than independence often give non-meaningful results\nC_LIO_LIBetween/Within subject decomposition of slopes should be undertaken when making causal inferences\nC_LIO_LIInvestigators should investigate the reasons Between and Within Subject slopes differ if this occurs\nC_LI

epidemiology

Human salivary amylase gene copy number impacts oral and gut microbiomes

Host genetic variation influences the composition of the human microbiome. While studies have focused on associations between the microbiome and single nucleotide polymorphisms in genes, their copy number (CN) can also vary. Here, in a study of human subjects including a 2-week standard diet, we relate oral and gut microbiome to CN at the AMY1 locus, which encodes the gene for salivary amylase, active in starch degradation. We show that although diet standardization drove gut microbiome convergence, AMY1-CN influenced oral and gut microbiome composition and function. The gut microbiomes of low-AMY1-CN subjects had an enhanced capacity for breakdown of complex carbohydrates. Those of high-AMY1 subjects were enriched in microbiota linked to resistant starch fermentation, had higher fecal SCFAs, and drove higher adiposity when transferred to germfree mice. Gut microbiota results were validated in a larger separate population. This study establishes AMY1-CN as a genetic factor patterning microbiome composition and function.

genetics

Adomaviruses: an emerging virus family provides insights into DNA virus evolution

Adenoviruses, papillomaviruses, and polyomaviruses are collectively known as small DNA tumor viruses. Although it has long been recognized that small DNA tumor virus oncoproteins and capsid proteins show a variety of structural and functional similarities, it is unclear whether these similarities reflect descent from a common ancestor, convergent evolution, horizontal gene transfer among virus lineages, or acquisition of genes from host cells. Here, we report the discovery of a dozen new members of an emerging virus family, the Adomaviridae, that unite a papillomavirus/polyomavirus-like replicase gene with an adenovirus-like virion maturational protease. Adomaviruses were initially discovered in a lethal disease outbreak among endangered Japanese eels. New adomavirus genomes were found in additional commercially important fish species, such as tilapia, as well as in reptiles. The search for adomavirus sequences also revealed an additional candidate virus family, which we refer to as xenomaviruses, in mollusk datasets. Analysis of native adomavirus virions and expression of recombinant proteins showed that the virion structural proteins of adomaviruses are homologous to those of both adenoviruses and another emerging animal virus family called adintoviruses. The results pave the way toward development of vaccines against adomaviruses and suggest a framework that ties small DNA tumor viruses into a shared evolutionary history. Author SummaryIn contrast to cellular organisms, viruses do not encode any universally conserved genes. Even within a given family of viruses, the amino acid sequences encoded by homologous genes can diverge to the point of unrecognizability. Although members of an emerging virus family, the Adomaviridae, encode replicative DNA helicase proteins that are recognizably similar to those of polyomaviruses and papillomaviruses, the functions of other adomavirus genes have been difficult to identify. Using a combination of laboratory and bioinformatic approaches, we identify the adomavirus virion structural proteins. The results link adomavirus virion protein operons to those of other midsize non-enveloped DNA viruses, including adenoviruses and adintoviruses.

microbiology

Advanced whole genome sequencing and analysis of fetal genomes from amniotic fluid

Amniocentesis is typically performed to identify large chromosomal abnormalities within the fetus. Here we demonstrate that it is feasible to generate an accurate whole genome sequence (WGS) of a fetus from an amniotic sample. DNA from cells and the amniotic fluid were isolated and sequenced from 31 amniocenteses. Concordance of variant calls between the two DNA sources and with parental libraries was high. Two fetal genomes were found to harbor potentially detrimental variants in CHD8 and LRP1, variations in these genes have been associated with Autism Spectrum Disorder (ASD) and Keratosis pilaris atrophicans, respectively. We also discovered drug sensitivities and carrier information of fetuses for a variety of diseases. In this study, we demonstrate for the first time the sequencing of the whole genome of fetuses from amniotic fluid and show that much more information than large chromosomal abnormalities can be gained from an amniocentesis.

genomics

Resilience mechanisms of small intestinal lactobacilli to the toxicity of soybean oil fatty acids

Over the past century, soybean oil (SBO) consumption in the United States increased dramatically. The main SBO fatty acid, linoleic acid (18:2), inhibits in vitro the growth of lactobacilli, beneficial members of the small intestinal microbiota. Human-associated lactobacilli have declined in prevalence in Western microbiomes, but how dietary changes may have impacted their ecology is unclear. Here, we compared the in vitro and in vivo effects of 18:2 on Lactobacillus reuteri and L. johnsonii. Directed evolution in vitro in both species led to strong 18:2 resistance with mutations in genes for lipid biosynthesis, acid stress, and the cell membrane or wall. Small-intestinal Lactobacillus populations in mice were unaffected by chronic and acute 18:2 exposure, yet harbored both 18:2- sensitive and resistant strains. This work shows that extant small intestinal lactobacilli are protected from toxic dietary components via the gut environment as well as their own capacity to evolve resistance.

microbiology

A Fluorogenic Array Tag for Temporally Unlimited Single Molecule Tracking

Cellular processes take place over many timescales, prompting the development of precision measurement technologies that cover milliseconds to hours. Here we describe ArrayG, a bipartite fluorogenic system composed of a GFP-nanobody array and monomeric wtGFP binders. The free binders are initially dim but brighten 15 fold upon binding the array, suppressing background fluorescence. By balancing rates of intracellular binder production, photo-bleaching, and stochastic binder exchange on the array, we achieved temporally unlimited tracking of single molecules. Fast (20-180Hz) tracking of ArrayG tagged kinesins and integrins, for thousands of frames, revealed repeated state-switching and molecular heterogeneity. Slow (0.5 Hz) tracking of single histones for as long as 1 hour showed fractal dynamics of chromatin. We also report ArrayD, a DHFR-nanobody-array tag for dual color imaging. The arrays are aggregation resistant and combine high brightness, background suppression, fluorescence replenishment, and extended choice of fluorophores, opening new avenues for seeing and tracking single molecules in living cells.

biophysics

A fluorogenic nanobody array tag for prolonged single molecule imaging in live cells

Prolonged single molecule imaging in live cells requires labels that do not aggregate, have high contrast, and are photo-stable. To address these requirements, we have generated arrays of modular protein domains that function as fluorophore recruitment platforms. ArrayG, a linear repeat of GFP-nanobodies, recruits free monomeric wild-type GFP, which brightens ~15-fold upon binding the array. The fluorogenic ArrayG tag effectively eliminates background fluorescence from free binders, a major impediment to high-throughput acquisition of long trajectories in recruitment based imaging strategies. The photo-stability of ArrayG and consistently low background made it possible to continuously track single integrins for as long as 105 seconds (2100 frames). Prolonged tracking of both kinesin and integrin revealed repeated state-switching events, a measurement capability that is crucial to a mechanistic understanding of complex cellular processes. We also report an orthogonal array tag, based on a DHFR-nanobody, for prolonged dual color imaging of single molecules.

biophysics