Biology subjects

Ji, S.

Publications and source records attributed to Ji, S..

6 recordsLinked to original sources

bioRxiv2018

DeepCDpred: Inter-residue Distance and Contact Predictionfor Improved Prediction of Protein Structure.

Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving the prediction of the amino acid residues that contact in their 3D structure. For an average globular protein, around 92% of all residue pairs are non-contacting, therefore accurate prediction of only a small percentage of inter-amino acid distances could increase the number of constraints to guide structure determination. We have trained deep neural networks to predict inter-residue contacts and distances. Distances are predicted with an accuracy better than most contact prediction techniques. Addition of distance constraints improved de novo structure predictions for test sets of 158 protein structures, as compared to using the best contact prediction methods alone. Importantly, usage of distance predictions allows the selection of better models from the structure pool without a need for an external model assessment tool. The results also indicate how the accuracy of distance prediction methods might be improved further.

bioinformatics↗

bioRxiv2018

Dimethylarsenic acid (DMA) accumulation positively correlates with realgar-induced subchronic toxicity in rats

The toxicity of realgar depends largely on different arsenic species accumulation and distribution in the body. Here, after continuous oral administration of different doses of realgar for 90 days and subsequent 60-day withdrawal period, clinical observations, food consumption, body weights, blood biochemistry, hematology, and histomorphological examination of rats were performed. Realgar 40mg{middle dot}kg-1{middle dot}d-1 and 170 mg{middle dot}kg-1{middle dot}d-1 of realgar (which is equivalent to 40-fold and 100-fold the maximum clinical dose, respectively) can cause toxicity in rats, including degreased body weight, peripheral blood neutrality abnormal ratio of granulocytes and lymphocytes, hypercoagulability of the blood, liver and kidney tissue damage, liver and kidney may be the main toxic target organs of realgar. The no observed adverse effect level (NOAEL) dose is 10 mg{middle dot}kg-1. At the same time, the content and distribution of arsenic species in tissues were determined. The content of total arsenic (tAs) and Dimethylarsenic acid (DMA) in the tissues of the realgar group was significantly higher than those of the control group. After 60 days of discontinuation, the DMA content in the realgar group decreased, but it was still higher than that in the control group, and liver and kidney damage occurred during the administration period basically returned to normal. Therefore, the authors speculated that when the DMA content in the tissue exceeds a certain range, liver and kidney toxicity will be induced. However, when the DMA content is lower than the above threshold after drug withdrawal, the liver and kidney lesions can return to normal.

pharmacology and toxicology↗

bioRxiv2018

NormExpression: an R package to normalize gene expression data using evaluated methods

Data normalization is a crucial step in the gene expression analysis as it ensures the validity of its downstream analyses. Although many metrics have been designed to evaluate the current normalization methods, the different metrics yield inconsistent results. In this study, we designed a new metric named Area Under normalized CV threshold Curve (AUCVC) and applied it with another metric mSCC to evaluate 14 commonly used normalization methods, achieving consistency in our evaluation results using both bulk RNA-seq and scRNA-seq data from the same library construction protocol. This consistency has validated the underlying theory that a sucessiful normalization method simultaneously maximizes the number of uniform genes and minimizes the correlation between the expression profiles of gene pairs. This consistency can also be used to analyze the quality of gene expression data. The gene expression data, normalization methods and evaluation metrics used in this study have been included in an R package named NormExpression. NormExpression provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis.

bioinformatics↗

bioRxiv2018

miRNAs play important roles in aroma weakening during the shelf life of ‘Nanguo’ pear after cold storage

Cold storage is commonly employed to delay senescence in Nanguo pears after harvest. However, this technique also causes fruit aroma weakening. MicroRNAs play important roles in plant development and in eliciting responses to abiotic environmental stressors. In this study, the miRNA transcript profile of the fruit at the first day (C0, LT0) move in and out of cold storage and the optimum tasting period (COTP, LTOTP) during shelf life at room temperature were analyzed, respectively. More than 300 known miRNAs were identified in Nanguo pears; 176 and 135 miRNAs were significantly differentially expressed on the C0 vs. LT0 and on the COTP vs. LTOTP, respectively. After prediction the target genes of these miRNAs, LOX2S, LOX1_5, HPL, and ADH1 were found differentially expressed, which were the key genes during aroma formation. The expression pattern of these target genes and the related miRNAs were identified by RT-PCR. Mdm-miR172a-h, mdm-miR159a/b/c, mdm-miR160a-e, mdm-miR395a-i, mdm/ppe-miR399a, mdm/ppe-miR535a/b, and mdm-miR7120a/b negatively regulated target gene expression. These results indicate that miRNAs play key roles in aroma weakening in refrigerated Nanguo pear and provide valuable information for studying the molecular mechanisms of miRNAs in the aroma weakening of fruits due to cold storage.

molecular biology↗

bioRxiv2017

Long-term consolidation switches goal proximity coding from hippocampus to retrosplenial cortex

Recent research indicates the hippocampus may code the distance to the goal during navigation of newly learned environments. It is unclear however, whether this also pertains to highly familiar environments where extensive systems-level consolidation is thought to have transformed mnemonic representations. Here we recorded fMRI while University College London and Imperial College London students navigated virtual simulations of their own familiar campus (> 2 years of exposure) and the other campus learned days before scanning. Posterior hippocampal activity tracked the proximity to the goal in the newly learned campus, but not in the familiar campus. By contrast retrosplenial cortex tracked the distance to the goal in the familiar campus, but not in the recently learned campus. These responses were abolished when participants were guided to their goal by external cues. These results open new avenues of research on navigation and consolidation of spatial information and help advance models of how neural circuits support navigation in novel and highly familiar environments.\n\nSignificance StatementHistorically, research on the hippocampal formation has focused on its role in long-term memory and navigation - often in isolation. No study to date has directly compared realistic navigation within familiar with recently learned environments, nor has it been explored how the neural substrates, along with computational codes, may change. In this study, we show for the first time, a shift from hippocampal to cortical coding of distance to a goal during active navigation. This study bridges the gap between memory consolidation and navigation, and paves the way for more functional and realistic understanding of the hippocampus.

neuroscience↗

bioRxiv2017

A pooled sequencing approach identifies a candidate meiotic driver in Drosophila

Meiotic drive occurs when a selfish element increases its transmission frequency above the Mendelian ratio by hijacking the asymmetric divisions of female meiosis. Meiotic drive causes genomic conflict and potentially has a major impact on genome evolution, but only a few drive loci of large effect have been described. New methods to reliably detect meiotic drive are therefore needed, particularly for discovering moderate-strength drivers that are likely to be more prevalent in natural populations than strong drivers. Here we report an efficient method that uses sequencing of large pools of backcross (BC1) progeny to test for deviations from Mendelian segregation genome-wide of single-nucleotide polymorphisms (SNPs) that distinguish the parental strains. We show that meiotic drive can be detected by a characteristic pattern of decay in distortion of SNP frequencies, caused by recombination unlinking the driver from distal loci. We further show that control crosses allow allele-frequency distortion caused by meiotic drive to be distinguished from distortion resulting from developmental effects. We used this approach to test whether chromosomes with extreme telomere-length differences segregate at Mendelian ratios, as telomeric regions are a potential hotspot for meiotic drive due to their roles in meiotic segregation and multiple observations of high rates of telomere sequence evolution. Using four different pairings of long and short telomere strains, we find no evidence that extreme telomere-length variation causes meiotic drive in Drosophila. However, we identify one candidate meiotic driver in a centromere-linked region that shows an ~8% increase in transmission frequency, corresponding to a ~54:46 segregation ratio. Our results show that candidate meiotic drivers of moderate strength can be readily detected and localized in pools of F1 progeny.

genetics↗