Biology subjects

Sun, J.

Publications and source records attributed to Sun, J..

547 records · Page 31Linked to original sources

bioRxiv2017

Genetic drivers of repeat expansion disorders localize to 3-D chromatin domain boundaries

More than 25 inherited neurological disorders are caused by the unstable expansion of repetitive DNA sequences termed short tandem repeats (STRs). A fundamental unresolved question is why specific STRs are susceptible to unstable expansion leading to severe pathology, whereas tens of thousands of normal-length repeat tracts across the human genome are relatively stable. Here, we unexpectedly discover that nearly all STRs associated with repeat expansion diseases are located at boundaries demarcating 3-D chromatin domains. We find that boundaries exhibit markedly higher CpG island density compared to loci internal to domains. Importantly, disease-associated STRs are specifically localized to ultra-dense CpG island-rich boundaries, suggesting that these loci might be hotspots for epigenetic instability and topological disruption upon unstable expansion. In Fragile X Syndrome, mutation-length expansion at the Fmr1 gene results in severe disruption of the boundary between TADs. Our data uncover higher-order chromatin architecture as a new dimension in understanding the mechanistic basis of repeat expansion disorders.

genomics↗

bioRxiv2017

A high-performance, inexpensive setup for simultaneous multi-site recording of electrophysiological signals and wide-field optical imaging of the mouse cortex

Simultaneous recording of optical and electrophysiological signals from multiple cortical areas may provide crucial information to expand our understanding of cortical function. However, the insertion of multiple electrodes into the brain may compromise optical imaging by both restricting the field of view, and interfering with the approaches used to stabilize the specimen. Existing methods that combine electrophysiological recording and optical imaging in vivo implement either multiple surface electrodes or a single electrode for deeper recordings. To address such limitation, we built a microelectrode array (hyperdrive) compatible with wide-field imaging that allows insertion of up to 12 probes into a large brain area (8 mm diameter). The developed hyperdrive is comprised of a circle of individual microdrives where probes are positioned at an angle leaving a large brain area unobstructed for wide-field imaging. Multiple tetrodes and voltage-sensitive dye imaging (VSDI) were used for simultaneous registration of spontaneous and evoked cortical activity. The electrophysiological signals were used to extract local field potential (LFP) traces, multiunit and single-unit spiking activity. To demonstrate our approach, we compared LFP and VSD signals over multiple regions of the cortex and analyzed the relationship between single-unit and global cortical population activities. The study of the interactions between cortical activity at local and global scales, such as the one presented in this work, can help to expand our knowledge of brain function.

neuroscience↗

bioRxiv2017

Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD)

Recently, the field of developmental neuroscience has aimed to uncover the developmental trajectory of the human brain and understand the changes that occur as a function of aging. Here we present an adult lifespan dataset of functional magnetic resonance imaging (fMRI) data including structural MRI and resting-state functional MRI. 494 healthy adults (age range: 19-80 years; Males=187) were recruited and completed two multi-modal MRI scan sessions in the Brain Imaging Central of Southwest University, Chongqing, China. The goals of the dataset are to give researchers the opportunity to map the developmental trajectory of structural and functional changes of human brain and to replicate previous findings.

neuroscience↗

bioRxiv2017

Rhodosporidium toruloides: A new platform organism for conversion of lignocellulose into terpene biofuels and bioproducts

BackgroundEconomical conversion of lignocellulosic biomass into biofuels and bioproducts is central to the establishment of a robust bioeconomy. This requires a conversion host that is able to both efficiently assimilate the major lignocellulose-derived carbon sources and divert their metabolites toward specific bioproducts.\n\nResultsIn this study, the carotenogenic yeast Rhodosporidium toruloides was examined for its ability to convert lignocellulose into two non-native sesquiterpenes with biofuel (bisabolene) and pharmaceutical (amorphadiene) applications. We found that R. toruloides can efficiently convert a mixture of glucose and xylose from hydrolyzed lignocellulose into these bioproducts, and unlike many conventional production hosts, its growth and productivity were enhanced in lignocellulosic hydrolysates relative to purified substrates. This organism was demonstrated to have superior growth in corn stover hydrolysates prepared by two different pretreatment methods, one using a novel biocompatible ionic liquid (IL) choline -ketoglutarate, which produced 261 mg/L of bisabolene at bench-scale, and the other using an alkaline pretreatment, which produced 680 mg/L of bisabolene in a high gravity fed-batch bioreactor. Interestingly, R. toruloides was also observed to assimilate p-coumaric acid liberated from acylated grass lignin in the IL hydrolysate, a finding we verified with purified substrates. R. toruloides was also able to consume several additional compounds with aromatic motifs similar to lignin monomers, suggesting that this organism may have the metabolic potential to convert depolymerized lignin streams alongside lignocellulosic sugars.\n\nConclusionsThis study highlights the natural compatibility of R. toruloides with bioprocess conditions relevant to lignocellulosic biorefineries and demonstrates its ability to produce non-native terpenes.

bioengineering↗

bioRxiv2017

Cross-Cultural Effects On Ensemble Coding Of Emotion In Facial Crowds

In many social situations, we make a snap judgment about crowds of people relying on their overall mood (termed \"crowd emotion\"). Although reading crowd emotion is critical for interpersonal dynamics, the sociocultural aspects of this process have not been explored. The current study examined how culture modulates the processing of crowd emotion in Korean and American observers. Korean and American participants were briefly presented with two groups of faces that were individually varying in emotional expressions and asked to choose which group between the two they would rather avoid. We found that Korean participants were more accurate than American participants overall, in line with the framework on cultural viewpoints: Holistic versus analytic processing in East Asians versus Westerners. Moreover, we found a speed advantage for other-race crowds in both cultural groups. Finally, we found different hemispheric lateralization patterns: American participants were more accurate for angry crowds presented in the left visual field and happy crowds presented in the right visual field, replicating previous studies, whereas Korean participants did not show an interaction between emotional valence and visual field. This work suggests that culture plays a role in modulating our crowd emotion perception of groups of faces and responses to them.

neuroscience↗

bioRxiv2017

STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq

MotivationFusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data.\n\nResultsWe benchmarked STAR-Fusions fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods.\n\nAvailability and implementationSTAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux.\n\nContactbhaas@broadinstitute.org

bioinformatics↗

bioRxiv2017

Applying Mondrian Cross-Conformal Prediction to Estimate Prediction Confidence on Large Imbalanced Bioactivity Datasets

Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modelling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modelling algorithms. Standard conformal prediction might not be suitable for imbalanced datasets. Therefore, Mondrian cross-conformal prediction (MCCP) which combines the Mondrian inductive conformal prediction with cross-fold calibration sets has been introduced. In this study, the MCCP method was applied to 18 publicly available datasets that have various imbalance levels varying from 1:10 to 1:1000 (ratio of active/inactive compounds). Our results show that MCCP in general performed well on cheminformatics datasets with various imbalance levels. More importantly, the method not only provides confidence of prediction and prediction regions compared to standard machine learning methods, but also produces valid predictions for the minority class. In addition, a compound similarity based nonconformity measure was investigated. Our results demonstrate that although it gives valid predictions, its efficiency is much worse than nonconformity measures obtained from supervised learning.

pharmacology and toxicology↗