Biology subjects

Han, K.

Publications and source records attributed to Han, K..

7 recordsLinked to original sources

bioRxiv2018

JNK-IN-8, a c-Jun N-terminal kinase inhibitor, improves functional recovery through suppressing neuroinflammation in ischemic stroke

c-Jun N-terminal kinase (JNK), a mitogen activated protein kinase, is activated in ischemia brain injury and plays an important role in cerebral ischemic injury. Emerging studies demonstrated that JNK-IN-8 (a specific JNK inhibitor) regulates traumatic brain injury through controlling neuronal apoptosis and inflammation. However, the role of JNK-IN-8 in ischemic stroke and the underlying mechanisms of JNK-IN-8 involving neuroprotection remain poorly understood. In the present study, male rats were subjected to tMCAO (transient middle cerebral artery occlusion) followed by treatment with JNK-IN-8, and then the modified improved neurological function score (mNSS), the Foot-fault test and the level of inflammatory cytokines (IL-1{beta}, IL-6 and TNF-) were assessed. We found that JNK-IN-8-treated rats with MCAO exerted a significant improvement in spatial learning as measured by the improved mNSS, and showed sensorimotor functional recovery as measured by the Foot-fault test. JNK-IN-8 also exerted anti-inflammatory effects as indicated by decreased activation of microglia and the decreased expresson of IL-6, IL-1{beta} and TNF-. Furthermore, JNK-IN-8 suppressed the activation of JNK and subsequent activation of NF-{kappa}B signaling as indicated by the decreased level of phosphorylated JNK (p-JNK) and p65. These data suggest that JNK-IN-8 suppressed neuroinflammation and improved neurological function by inhibiting JNK/NF-{kappa}B pathway after ischemic brain injury, thus offering a new target for prevention of ischemic brain injury.

cancer biology↗

bioRxiv2017

Variational Autoencoder: An Unsupervised Model for Modeling and Decoding fMRI Activity in Visual Cortex

Goal-driven convolutional neural networks (CNN) have been shown to be able to predict and decode cortical responses to natural images or videos. Here, we explored an alternative deep neural network, variational auto-encoder (VAE), as a computational model of the visual cortex. We trained a VAE with a five-layer encoder and a five-layer decoder to learn visual representations from a diverse set of unlabeled images. Inspired by the \"free-energy principle\" in neuroscience, we modeled the brains bottom-up and top-down pathways using the VAEs encoder and decoder, respectively. Following such conceptual relationships, we found that the VAE was able to predict cortical activities observed with functional magnetic resonance imaging (fMRI) from three human subjects watching natural videos. Compared to CNN, VAE resulted in relatively lower prediction accuracies, especially for higher-order ventral visual areas. On the other hand, fMRI responses could be decoded to estimate the VAEs latent variables, which in turn could reconstruct the visual input through the VAEs decoder. This decoding strategy was more advantageous than alternative decoding methods based on partial least square regression. This study supports the notion that the brain, at least in part, bears a generative model of the visual world.

neuroscience↗

bioRxiv2017

KoVariome: Korean National Standard Reference Variome database of whole genomes with comprehensive SNV, indel, CNV, and SV analyses

High-coverage whole-genome sequencing data of a single ethnicity can provide a useful catalogue of population-specific genetic variations. Herein, we report a comprehensive analysis of the Korean population, and present the Korean National Standard Reference Variome (KoVariome). As a part of the Korean Personal Genome Project (KPGP), we constructed the KoVariome database using 5.5 terabases of whole genome sequence data from 50 healthy Korean individuals with an average coverage depth of 31x. In total, KoVariome includes 12.7M single-nucleotide variants (SNVs), 1.7M short insertions and deletions (indels), 4K structural variations (SVs), and 3.6K copy number variations (CNVs). Among them, 2.4M (19%) SNVs and 0.4M (24%) indels were identified as novel. We also discovered selective enrichment of 3.8M SNVs and 0.5M indels in Korean individuals, which were used to filter out 1,271 coding-SNVs not originally removed from the 1,000 Genomes Project data when prioritizing disease-causing variants. CNV analyses revealed gene losses related to bone mineral densities and duplicated genes involved in brain development and fat reduction. Finally, KoVariome health records were used to identify novel disease-causing variants in the Korean population, demonstrating the value of high-quality ethnic variation databases for the accurate interpretation of individual genomes and the precise characterization of genetic variations.

genomics↗

bioRxiv2017

Deep Recurrent Neural Network Reveals a Hierarchy of Process Memory during Dynamic Natural Vision

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas especially those along the dorsal stream. As a fully-observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision.

neuroscience↗

bioRxiv2017

A comprehensive portrait of cilia and ciliopathies from a CRISPR-based screen for Hedgehog signaling

The primary cilium organizes Hedgehog signaling, shapes embryonic development and is the unifying cause of the ciliopathies. We conducted a functional genomic screen for Hedgehog signaling by engineering antibiotic-based selection of Hedgehog-responsive cells and applying genome-wide CRISPR-mediated gene disruption. The screen robustly identifies factors required for ciliary signaling with few false positives or false negatives. Characterization of hit genes uncovers novel components of several ciliary structures including a protein complex containing {varepsilon}- and {delta}- tubulin that is required for centriole maintenance. The screen also provides an unbiased tool for classifying ciliopathies and reveals that many forms of congenital heart defects are ciliopathies. Collectively, this screen enables a systematic analysis of ciliary function and of ciliopathies and also defines a versatile platform for dissecting signaling pathways through CRISPR-based screening.

genetics↗

bioRxiv2017

Multiple reference genome sequences of hot pepper reveal the massive evolution of plant disease resistance genes by retroduplication

Transposable elements (TEs) provide major evolutionary forces leading to new genome structure and species diversification. However, the role of TEs in the expansion of disease resistance gene families has been unexplored in plants. Here, we report high-quality de novo genomes for two peppers (Capsicum baccatum and C. chinense) and an improved reference genome (C. annuum). Dynamic genome rearrangements involving translocations among chromosome 3, 5 and 9 were detected in comparison between C. baccatum and the two other peppers. The amplification of athila LTR-retrotransposons, members of the gypsy superfamily, led to genome expansion in C. baccatum. In-depth genome-wide comparison of genes and repeats unveiled that the copy numbers of NLRs were greatly increased by LTR-retrotransposon-mediated retroduplication. Moreover, retroduplicated NLRs exhibited great abundance across the angiosperms, with most cases lineage-specific and thus recent events. Our study revealed that retroduplication has played key roles in the emergence of new disease-resistance genes in plants.

plant biology↗

bioRxiv2016

Contribution of mobile elements to the uniqueness of human genome with more than 15,000 human-specific insertions

Mobile elements (MEs) collectively constituted to at least 51% of the human genome. Due to their past incremental accumulation and ongoing DNA transposition of members from certain subfamilies, MEs serve as a significant source for both inter- and intra-species genetic diversity during primate and human evolution. Since MEs can exert direct impact on gene function via a plethora of mechanism, it is believed that the ME-derived genetic diversity has contributed to the phenotypic differences between human and non-human primates, as well as among human populations and individuals. To define the specific contribution of MEs in making Human sapiens as a biologically unique species, we aim to compile a complete list of MEs that are only uniquely present in the human genome, i.e., human-specific MEs (HS-MEs).\n\nBy making use of the most recent reference genome sequences for human and many other primates and a unbiased more robust and integrative multi-way comparative genomic approach, we identified a total of 15,463 HS-MEs. This list of HS-MEs represents a 120% increase from prior studies with over 8,000 being newly identified as HS-MEs. Collectively, these ~15,000 HS-MEs have contributed to a total of 15 million base pair (Mbp) sequence increase through insertion, generation of target site duplications, and transductions, as well as a 0.5 Mbp sequence loss via insertion- mediated deletions, leading to a net total of 14.5 Mbp genome size increase. Other new observations made with these HS-MEs include: 1) identification of several additional ME subfamilies with significant transposition activities not visible with prior smaller datasets (e.g. L1HS, L1PA2, and HERV-K); 2) A clear similarity of the retrotransposition mechanism among L1, Alus, and SVAs that is distinct from HERVs based on the pre- integration site sequence motifs; 3) Y-chromosome as a strikingly hot target for HS-MEs, particularly for LTRs, which showed an insertion rate 15 times higher than the genome average; 4) among the ME types, SVAs seem to show a very strong bias in inserting into existing SVAs. Among the HS-MEs, more than 8,000 elements were integrated into the vicinity of ~4900 unique genes, in regions including CDS, untranslated exon regions, promoters, and introns of protein coding genes, as well as promoters and exons of non- coding RNAs. In seven cases, MEs participate in protein coding. Furthermore, 1,213 HS-MEs contributed to a total of 3,124 experimentally identified binding sites for 146 of the 161 transcriptional factors in association with 622 genes. All these data suggest that these HS-MEs, despite being very young, already showed sufficient sign for their participation in gene function via regulation of transcription, splicing, and protein coding, with more potential for future participation.\n\nIn conclusion, our results demonstrate that the amount of MEs uniquely occurred in the human genome is much higher than previously known, and we predict that the same is true regarding their impact on human genome evolution and function. The comprehensive list of HS-MEs provides an important reference resource for studying the impact of DNA transposition in human genome evolution and gene function.

evolutionary biology↗