Biology subjects

Kim, S.

Publications and source records attributed to Kim, S..

At least 649 records · Page 36Linked to original sources

bioRxiv2019

Link clustering explains non-central essential genes in protein interaction networks

Essential genes (EGs) often form central nodes in protein-protein interaction (PPI) networks. However, many reports have shown that numerous EGs are non-central, suggesting that another principle governs gene essentiality. We propose link clustering as a distinct indicator of the essentiality for non-central nodes. Specifically, in various human and yeast PPI networks, we found that 29 to 47% of EGs were better characterized by link clustering than by centrality. Such non-central EGs with clustered links have significant impacts on communities at lower hierarchical levels, suggesting that their essentiality derives from functional dependency among relevant local neighbors, rather than their implication on global connectivity. Moreover, these non-central EGs exhibited several distinct characteristics: they tend to be younger and fast-evolving, and likely change their essentiality across different human cell lines and between human and mouse than central-EGs. Author summaryThe centrality in network structure was thought to be the cause of gene essentiality, as it conveys nodes importance in given networks. However, many essential genes are also found to be non-central, which leads us to ask whether a principle other than centrality may govern gene essentiality. Here we demonstrate that link clustering conveying functional dependency between nodes is the other principle characterizing gene essentiality. The link clustering explains numerous essential genes that are non-central, which are distinct from central ones regarding their molecular function and evolution. Our results clearly establish a two-dimensional principle governing gene essentiality.

systems biology↗

bioRxiv2019

Motion direction representation in multivariate electroencephalography activity for smooth pursuit eye movements

Visually-guided smooth pursuit eye movements are composed of initial open-loop and later steady-state periods. Feedforward sensory information dominates the motor behavior during the open-loop pursuit, and a more complex feedback loop regulates the steady-state pursuit. To understand the neural representations of motion direction during open-loop and steady-state smooth pursuits, we recorded electroencephalography (EEG) responses from human observers while they tracked random dot kinematograms as pursuit targets. We estimated population direction tuning curves from multivariate EEG activity using an inverted encoding model. We found significant direction tuning curves as early as 20 ms from motion onset. Direction tuning responses were generalized to later times during the open-loop smooth pursuit, but they became more dynamic during the later steady-state pursuit. The encoding quality of retinal motion direction information estimated from the early direction tuning curves was predictive of trial-by-trial variation in initial pursuit directions. These results suggest that the movement directions of open-loop smooth pursuit are guided by the representation of the retinal motion present in the multivariate EEG activity.

neuroscience↗

bioRxiv2019

A Data-Driven Transcriptional Taxonomy of Adipogenic Chemicals to Identify Emerging Metabolic Health Threats

BackgroundChemicals in disparate structural classes activate specific subsets of PPAR{gamma}s transcriptional programs to generate adipocytes with distinct phenotypes. ObjectivesOur objectives were to 1) establish a novel classification method to predict PPAR{gamma} ligands and modifying chemicals, and 2) create a taxonomy to group chemicals based on their effects on PPAR{gamma}s transcriptome and downstream metabolic functions. We tested the hypothesis that environmental adipogens highly ranked by the taxonomy, but segregated from therapeutic PPAR{gamma} ligands, would induce white but not brite adipogenesis. Methods3T3-L1 cells were differentiated in the presence of 76 chemicals (negative controls, nuclear receptor ligands known to influence adipocyte biology, potential environmental PPAR{gamma} ligands). Differentiation was assessed by measuring lipid accumulation. mRNA expression was determined by RNA-Seq and validated by RT-qPCR. A novel classification model was developed using an amended random forest procedure. A subset of environmental contaminants identified as strong PPAR{gamma} agonists were analyzed by their effects on lipid handling, mitochondrial biogenesis and cellular respiration in 3T3-L1 cells and human preadipocytes. ResultsWe used lipid accumulation and RNA sequencing data to develop a classification system that 1) identified PPAR{gamma} agonists, and 2) sorted chemicals into likely white or brite adipogens. Expression of Cidec was the most efficacious indicator of strong PPAR{gamma} activation. Two known environmental PPAR{gamma} ligands, tetrabromobisphenol A and triphenyl phosphate, which sorted distinctly from therapeutic ligands, induced white adipocyte genes but failed to induce Pgc1a and Ucp1, and induced fatty acid uptake but not mitochondrial biogenesis in 3T3-L1 cells. Moreover, two chemicals identified as highly ranked PPAR{gamma} agonists, tonalide and quinoxyfen, induced white adipogenesis without the concomitant health-promoting characteristics of brite adipocytes in mouse and human preadipocytes. DiscussionA novel classification procedure accurately identified environmental chemicals as PPAR{gamma} ligands distinct from known PPAR{gamma}-activating therapeutics. The computational and experimental framework has general applicability to the classification of as-yet uncharacterized chemicals.

pharmacology and toxicology↗

bioRxiv2018

Genomic perspectives on adaptation and conservation in the endangered long-tailed goral (Naemorhedus caudatus).

Native to the mountains of East Asia, the long-tailed goral (Naemorhedus caudatus) is a vulnerable wild ungulate in the tribe Caprini. To understand key conservation issues related to fragmentation and subsequent endangerment of this montane species, we sequenced and analyzed the genome of a long-tailed goral to explore historical demography, contemporary levels of genetic diversity, and potential immune response. When compared to ten additional mammalian reference genomes, we identified 357 positively selected genes (PSGs) in the long-tailed goral and 364 PSGs in the Caprini lineage. Gene Ontology analyses showed statistical enrichment in biological processes related to immune function and in genes and pathways related to blood coagulation. We also identified low levels of heterozygosity (0.00114) in the long-tailed goral along with decreases in population size relative to other species of Caprini. Finally, we provide evidence for positive selection on the muscle development gene myostatin (MSTN) in the Caprini lineage, which may have increased the muscle development and climbing ability in the caprine common ancestor. Low effective population size and decreased heterozygosity of the long-tailed goral raise conservation concern about the effects of habitat fragmentation, over harvest, and inbreeding on this vulnerable species.

bioinformatics↗

bioRxiv2018

Nucleoid size scaling and intracellular organization of translation across bacteria

The scaling of organelles with cell size is thought to be exclusive to eukaryotes. Here, we demonstrate that similar scaling relationships hold for the nucleoid in bacteria. Despite the absence of a nuclear membrane, nucleoid size strongly correlates with cell size, independent of changes in DNA amount and across various nutrient conditions. This correlation is observed in diverse bacteria, revealing a near-constant ratio between nucleoid and cell size for a given species. As in eukaryotes, the nucleocytoplasmic ratio in bacteria varies greatly among species. This spectrum of nucleocytoplasmic ratios is independent of genome size, and instead appears linked to the average cell size of the population. Bacteria with different nucleocytoplasmic ratios have different biophysical properties of the cytoplasm, impacting the mobility and localization of ribosomes. Together, our findings identify new organizational principles and biophysical features of bacterial cells, implicating the nucleocytoplasmic ratio and cell size as determinants of the intracellular organization of translation.

microbiology↗

bioRxiv2018

Leveraging collective regulatory effects of long-range DNA methylations to predict gene expressions and estimate their effects on phenotypes in cancer

DNA methylation of various genomic regions plays an important role in regulating gene expression in diverse biological contexts. However, most genome-wide studies have focused on the effect of 1) methylation in cis, not in trans and 2) a single CpG, not the collective effects of multiple CpGs, on gene expression. In this study, we developed a statistical machine learning model, geneEXPLORER (gene expression prediction by long-range epigenetic regulation), that quantifies the collective effects of both cis- and trans- methylations on gene expression. By applying geneEXPLORER to The Cancer Genome Atlas (TCGA) breast and lung cancer data, we found that most genes are affected by methylations of as much as 10Mb from promoter regions or more, and the long-range methylation explains 50% of the variation in gene expression on average, far greater than cis-methylation. The highly predictive genes are related to breast cancer, especially oncogenes and suppressor genes. Further, the predicted gene expressions could predict clinical phenotypes such as breast tumor status and estrogen receptor status (AUC=0.999, 0.94 respectively) as accurately as the measured gene expression levels. These results suggest that geneEXPLORER provides a means for accurate imputation of gene expression, which can be further used to predict clinical phenotypes.

bioinformatics↗

bioRxiv2018

SKN-1/Nrf2 regulation of neuromuscular function in response to oxidative stress requires EGL-15/FGF Receptor and DAF-2/insulin Receptor signaling in Caenorhabditis elegans.

The transcription factor Nrf2 plays a critical role in the organism wide-regulation of the antioxidant stress response. The Nrf2 homolog SKN-1 functions in the intestine cell non-autonomously to negatively regulate neuromuscular (NMJ) function in Caenorhabditis elegans. To identify additional molecules that mediate SKN-1 signaling to the NMJ, we performed a candidate screen for suppressors of aldicarb-resistance caused by acute treatment with the SKN-1 activator, arsenite. We identified two receptor tyrosine kinases, EGL-15 (fibroblast growth factor receptor, FGFR) and DAF-2 (insulin-like peptide receptor, IR) that are required for NMJ regulation in response to stress. Through double mutant analysis, we found that EGL-15 functions downstream of SKN-1 and SPHK-1 (sphingosine kinase), and that the EGL-15 ligand EGL-17 FGF and canonical EGL-15 effectors are required for oxidative stress-mediated regulation of NMJ function. DAF-2 also functions downstream of SKN-1, independently of DAF-16/FOXO, to regulate NMJ function. Through tissue-specific rescue experiments, we found that FGFR signaling functions primarily in the hypodermis, whereas IR signaling is required in multiple tissues. Our results support the idea that the regulation of NMJ function by SKN-1 occurs via a complex organism-wide signaling network involving RTK signaling in multiple tissues.

neuroscience↗

bioRxiv2018

Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling.

Gene expression profiling is an effective way to provide insights into cell function. However, for heterogeneous tissues, bulk RNA-Seq can only provide the average gene expression profile for all cells from the tissue, making the interpretation of the sequencing result challenging. Single-cell RNA-seq, on the other hand, generates transcriptomic profiles of individual cell and cell types, making it a powerful method to decode the heterogeneity in complex tissues. The retina is a heterogeneous tissue composed of multiple cell types with distinct functions. Here we report the first single-nuclei RNA-seq transcriptomic study on human neural retinal tissue to identify transcriptome profile for individual cell types. Six retina samples from three healthy donors were profiled and RNA-seq data with high quality was obtained for 4730 single nuclei. All seven major cell types were observed from the dataset and signature genes for each cell type were identified by differential gene express analysis. The gene expression of the macular and peripheral retina was compared at the cell type level, showing significant improvement from previous bulk RNA-seq studies. Furthermore, our dataset showed improved power in prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrated that feasibility of obtaining single cell transcriptome from human frozen tissues to provide additional insights that is missed by either the human bulk RNA-seq or the animal models.

genomics↗

bioRxiv2018

De novo profiling of RNA viruses in Anopheles malaria vector mosquitoes from forest ecological zones in Senegal and Cambodia

BackgroundMosquitoes are colonized by a large but mostly uncharacterized natural virome of RNA viruses. Anopheles mosquitoes are efficient vectors of human malaria, and the composition and distribution of the natural RNA virome may influence the biology and immunity of Anopheles malaria vector populations.\n\nResultsAnopheles vectors of human malaria were sampled in forest village sites in Senegal and Cambodia, including Anopheles funestus, Anopheles gambiae group sp., and Anopheles coustani in Senegal, and Anopheles hyrcanus group sp., Anopheles maculatus group sp., and Anopheles dirus in Cambodia. Small and long RNA sequences were depleted of mosquito host and de novo assembled to yield non-redundant contigs longer than 500 nucleotides. Analysis of the assemblies by sequence similarity to known virus families yielded 125 novel virus sequences, 39 from Senegal Anopheles and 86 from Cambodia. Important monophyletic virus clades in the Bunyavirales and Mononegavirales orders are found in these Anopheles from Africa and Asia. Small RNA size and abundance profiles were used to cluster non-host RNA assemblies that were unclassified by sequence similarity. 39 unclassified non-redundant contigs >500 nucleotides strongly matched a pattern of classic RNAi processing of viral replication intermediates, and 1566 unclassified contigs strongly matched a pattern consistent with piRNAs. Analysis of piRNA expression in Anopheles coluzzii after infection with Onyong nyong virus (family Togaviridae) suggests that virus infection can specifically alter abundance of some piRNAs.\n\nConclusionsRNA viruses ubiquitously colonize Anopheles vectors of human malaria worldwide. At least some members of the mosquito virome are monophyletic with other arthropod viruses. However, high levels of collinearity and similarity of Anopheles viruses at the peptide level is not necessarily matched by similarity at the nucleotide level, indicating that Anopheles from Africa and Asia are colonized by closely related but clearly diverged virome members. The interplay between small RNA pathways and the virome may represent an important part of the homeostatic mechanism maintaining virome members in a commensal or nonpathogenic state, and host-virome interactions could influence variation in malaria vector competence.

genomics↗

bioRxiv2018

The whale shark genome reveals how genomic and physiological properties scale with body size

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and is a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 81 animals and yeast. We examined scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic features also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: GC content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to large introns highly enriched in repetitive elements such as CR1-like LINEs, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale sharks genome had an expansion of gene families related to fatty acid metabolism and neurogenesis, with the slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan, and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

genomics↗

bioRxiv2018

Dosage Matters: A Randomized Controlled Trial of Rehabilitation Dose in the Chronic Phase after Stroke

Background and PurposeFor stroke rehabilitation, task-specific training in animal models and human rehabilitation trials is considered important to trigger inherent neuroplasticity, promote motor learning, and functional recovery. Little is known, however, about what constitutes an effective dosage of therapy.\n\nMethodsThis is a parallel group, four arm, single blind, phase I, randomized control trial of four dosages of upper extremity therapy delivered in an outpatient setting during the chronic phase after stroke. Participants were randomized into groups that varied in total dosage of therapy (i.e., 0, 15, 30, or 60 hours). Seven hundred and four participants were assessed for eligibility, 50 were eligible to enroll, 45 were randomized, 44 participated and 41 completed the study. Planned primary analyses used linear mixed effects regression to model baseline to post-intervention changes in the Motor Activity Log-Quality of Movement rating (MALQ) and the Wolf Motor Function Test (WMFT) time score as a function of therapy dosage. A series of hierarchical models were constructed using the MALQ and WMFT.\n\nResultsWe observed a significant dose response curve: the greater the dosage of training, the greater the change in MALQ, with the dose by week slope parameter of 0.0045 ({Delta}MAL/hour/week; p = 0.0011; 95% CI = [0.0019; 0.0071]). Over the 3 weeks of therapy, this corresponds to a gain of 0.81 in MALQ for the 60 hour dose.\n\nConclusionsFor mild-to-moderately impaired stroke survivors, the dosage of a patient-centered, task specific motor therapy was shown to systematically influence the gain in quality of arm use in the natural environment, but not functional capacity as measured in the laboratory. We highlight the importance of recovery outcomes that capture arm use vs. functional capacity.\n\nClinical Trial RegistrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT 01749358

clinical trials↗

bioRxiv2018

An anti-Gn glycoprotein antibody from a convalescent patient potently inhibits the infection of severe fever with thrombocytopenia syndrome virus

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease localized to China, Japan, and Korea that is characterized by severe hemorrhage and a high fatality rate. Currently, no specific vaccine or treatment has been approved for this disease. To develop a therapeutic agent for SFTS, we isolated antibodies from a phage-displayed antibody library that was constructed from a patient who recovered from SFTS virus (SFTSV) infection. One antibody, designated as Ab10, was reactive to the Gn envelope glycoprotein of SFTSV and protected host cells and A129 mice from infection in both in vitro and in vivo experiments. Notably, Ab10 protected 80% of mice, even when injected 5 days after inoculation with a lethal dose of SFTSV. Using cross-linker assisted mass spectrometry and alanine scanning, we located the non-linear epitope of Ab10 on the Gn glycoprotein domain II and an unstructured stem region, suggesting that Ab10 may inhibit a conformational alteration that is critical for cell membrane fusion between the virus and host cell. Ab10 reacted to recombinant Gn glycoprotein in Gangwon/Korea/2012, HB28, and SD4 strains. Additionally, based on its epitope, we predict that Ab10 binds the Gn glycoprotein in 247 of 272 reported SFTSV isolates previously reported. Together, these data suggest that Ab10 has potential to be developed into a therapeutic agent that could protect against more than 90% of reported SFTSV isolates.\n\nAuthor summarySevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease localized to China, Japan, and Korea. This tick-borne virus has infected more than 5,000 humans with a 6.4% to 20.9% fatality rate. Currently, there are no prophylactic or therapeutic measures against this virus. Historically, antibodies from patients who recovered from viral infection have been used to treat new patients. Until now, one recombinant monoclonal antibody was approved for the prophylaxis of respiratory syntial virus infection. We selected 10 antibodies from a patient who recovered from SFTS and found that one antibody potently inhibited SFTS viral infection in both test tube and animal studies. We determined the binding site of this antibody to SFTS virus, which allowed us to predict that this antibody could bind 247 out of 272 SFTS virus isolates reported up to now. We anticipate that this antibody could be developed into a therapeutic measure against SFTS.

biochemistry↗

bioRxiv2018

RNA polymerases display collaborative and antagonistic group behaviors over long distances through DNA supercoiling

Transcription by RNA polymerases (RNAPs) is essential for cellular life. Genes are often transcribed by multiple RNAPs. While the properties of individual RNAPs are well appreciated, it remains less explored whether group behaviors can emerge from co-transcribing RNAPs under most physiological levels of gene expression. Here, we provide evidence in Escherichia coli that well-separated RNAPs can exhibit collaborative and antagonistic group dynamics. Co-transcribing RNAPs translocate faster than a single RNAP, but the density of RNAPs has no significant effect on their average speed. When a promoter is inactivated, RNAPs that are far downstream from the promoter slow down and experience premature dissociation, but only in the presence of other co-transcribing RNAPs. These group behaviors depend on transcription-induced DNA supercoiling, which can also mediate inhibitory dynamics between RNAPs from neighboring divergent genes. Our findings suggest that transcription on topologically-constrained DNA, a norm across organisms, can provide an intrinsic mechanism for modulating the speed and processivity of RNAPs over long distances according to the promoters on/off state.

microbiology↗

bioRxiv2018

Learning Gene Networks Underlying Clinical Phenotypes Using SNP Perturbations

Recent technologies are generating an abundance of genome sequence data and molecular and clinical phenotype data, providing an opportunity to understand the genetic architecture and molecular mechanisms underlying diseases. Previous approaches have largely focused on the co-localization of single-nucleotide polymorphisms (SNPs) associated with clinical and expression traits, each identified from genome-wide association studies and expression quantitative trait locus (eQTL) mapping, and thus have provided only limited capabilities for uncovering the molecular mechanisms behind the SNPs influencing clinical phenotypes. Here we aim to extract rich information on the functional role of trait-perturbing SNPs that goes far beyond this simple co-localization. We introduce a computational framework called Perturb-Net for learning the gene network that modulates the influence of SNPs on phenotypes, using SNPs as naturally occurring perturbation of a biological system. Perturb-Net uses a probabilistic graphical model to directly model both the cascade of perturbation from SNPs to the gene network to the phenotype network and the network at each layer of molecular and clinical phenotypes. Perturb-Net learns the entire model by solving a single optimization problem with an extremely fast algorithm that can analyze human genome-wide data within a few hours. In our analysis of asthma data, for a locus that was previously implicated in asthma susceptibility but for which little is known about the molecular mechanism underlying the association, Perturb-Net revealed the gene network modules that mediate the influence of the SNP on asthma phenotypes. Many genes in this network module were well supported in the literature as asthma-related.

bioinformatics↗

bioRxiv2018

Identifying functional targets from transcription factor binding data using SNP perturbation

Transcription factors (TFs) play a key role in transcriptional regulation by binding to DNA to initiate the transcription of target genes. Techniques such as ChIP-seq and DNase-seq provide a genome-wide map of TF binding sites but do not offer direct evidence that those bindings affect gene expression. Thus, these assays are often followed by TF perturbation experiments to determine functional binding that leads to changes in target gene expression. However, such perturbation experiments are costly and time-consuming, and have a well-known limitation that they cannot distinguish between direct and indirect targets. In this study, we propose to use the naturally occurring perturbation of gene expression by genetic variation captured in population SNP and expression data to determine functional targets from TF binding data. We introduce a computational methodology based on probabilistic graphical models for isolating the perturbation effect of each individual SNP, given a large number of SNPs across genomes perturbing the expression of all genes simultaneously. Our computational approach constructs a gene regulatory network over TFs, their functional targets, and further downstream genes, while at the same time identifying the SNPs perturbing this network. Compared to experimental perturbation, our approach has advantages of identifying direct and indirect targets, and leveraging existing data collected for expression quantitative trait locus mapping, a popular approach for studying the genetic architecture of expression. We apply our approach to determine functional targets from the TF binding data for a lymphoblastoid cell line from the ENCODE Project, using SNP and expression data from the HapMap 3 and 1000 Genomes Project samples. Our results show that from TF binding data, functional target genes can be determined by SNP perturbation of various aspects that impact transcriptional regulation, such as TF concentration and TF-DNA binding affinity.

bioinformatics↗

bioRxiv2018

Protect TUDCA stimulated CKD-derived hMSCs against the CKD-Ischemic disease via upregulation of PrPC

Although autologous human mesenchymal stem cells (hMSCs) are a promising source for regenerative stem cell therapy, the barriers associated with pathophysiological conditions in this disease limit therapeutic applicability to patients. We proved treatment of CKD-hMSCs with TUDCA enhanced the mitochondrial function of these cells and increased complex I & IV enzymatic activity, increasing PINK1 expression and decreasing mitochondrial O2*- and mitochondrial fusion in a PrPC-dependent pathway. Moreover, TH-1 cells enhanced viability when co-cultured in vitro with TUDCA-treated CKD-hMSC. In vivo, tail vein injection of TUDCA-treated CKD-hMSCs into the mouse model of CKD associated with hindlimb ischemia enhanced kidney recovery, the blood perfusion ratio, vessel formation, and prevented limb loss, and foot necrosis along with restored expression of PrPC in the blood serum of the mice. These data suggest that TUDCA-treated CKD-hMSCs are a promising new autologous stem cell therapeutic intervention that dually treats cardiovascular problems and CKD in patients.

cell biology↗

bioRxiv2018

A combination of transcription factors mediates inducible interchromosomal pairing

Remodeling of the three-dimensional organization of a genome has been previously described (e.g. condition-specific pairing or looping), but it remains unknown which factors specify and mediate such shifts in chromosome conformation. Here we describe an assay, MAP-C (Mutation Analysis in Pools by Chromosome conformation capture), that enables the simultaneous characterization of hundreds of cis or trans-acting mutations for their effects on a chromosomal contact or loop. As a proof of concept, we applied MAP-C to systematically dissect the molecular mechanism of inducible interchromosomal pairing between HAS1pr-TDA1pr alleles in Saccharomyces yeast. We identified three transcription factors, Leu3, Sdd4 (Ypr022c), and Rgt1, whose collective binding to nearby DNA sequences is necessary and sufficient for inducible pairing between binding site clusters. Rgt1 contributes to the regulation of pairing, both through changes in expression level and through its interactions with the Tup1/Ssn6 repressor complex. HAS1pr-TDA1pr is the only locus with a cluster of binding site motifs for all three factors in both S. cerevisiae and S. uvarum genomes, but the promoter for HXT3, which contains Leu3 and Rgt1 motifs, also exhibits inducible homolog pairing. Altogether, our results demonstrate that specific combinations of transcription factors can mediate condition-specific interchromosomal contacts, and reveal a molecular mechanism for interchromosomal contacts and mitotic homolog pairing.

genomics↗

bioRxiv2018

Synthetic chromosome fusion: effects on genome structure and function

As part of the Synthetic Yeast 2.0 (Sc2.0) project, we designed and synthesized synthetic chromosome I. The total length of synI is [~]21.4% shorter than wild-type chromosome I, the smallest chromosome in Saccharomyces cerevisiae. SynI was designed for attachment to another synthetic chromosome due to concerns of potential instability and karyotype imbalance. We used a variation of a previously developed, robust CRISPR-Cas9 method to fuse chromosome I to other chromosome arms of varying length: chrIXR (84kb), chrIIIR (202kb) and chrIVR (1Mb). All fusion chromosome strains grew like wild-type so we decided to attach synI to synIII. Through the investigation of three-dimensional structures of fusion chromosome strains, unexpected loops and twisted structures were formed in chrIII-I and chrIX-III-I fusion chromosomes, which depend on silencing protein Sir3. These results suggest a previously unappreciated 3D interaction between HMR and the adjacent telomere. We used these fusion chromosomes to show that axial element Red1 binding in meiosis is not strictly chromosome size dependent even though Red1 binding is enriched on the three smallest chromosomes in wild-type yeast, and we discovered an unexpected role for centromeres in Red1 binding patterns.

synthetic biology↗