bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing inhibitors of mutant isocitrate dehydrogenase using a suite of pre-clinical discovery assays
Authors: Urban Daniel J. , Martinez Natalia J. , Davis Mindy I. , Brimacombe Kyle R. , Cheff Dorian M. , Lee Tobie D. , Henderson Mark J. , Titus Steven A. , Pragani Rajan , Rohde Jason M. , Wang Yuhong , Karavadhi Surendra , Shah Pranav , Lee Olivia W. , Wang Amy , McIver Andrew , Zheng Hongchao , Wang Xiaodong , Xu Xin , Jadhav Ajit , Simeonov Anton , Shen Min , Boxer Matthew B. , Hall Matthew D. 
Published: April 2017

AbstractIsocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are key metabolic enzymes that are mutated in a variety of cancers to confer a gain-of-function activity resulting in the accumulation and secretion of an oncometabolite, D-2-hydroxyglutarate (2-HG). Accumulation of 2-HG can result in epigenetic dysregulation and a block in cellular differentiation, suggesting these mutations play a role in neoplasia. Based on its potential as a cancer target, a number of small molecule inhibitors have been developed to specifically inhibit mutant forms of IDH (mIDH1 and mIDH2). Here, a panel of mIDH inhibitors were systematically profiled using biochemical, cell-based, and tier-one ADME techniques. We quantified the biochemical effect of each inhibitor on mIDH1 (R132H and R132C) and mIDH2 (R172Q). The effect of these inhibitors on 2-HG concentrations in seven cell lines representing five different IDH1 mutations in both 2D and 3D cell cultures was assessed. Target engagement of these inhibitors was analyzed utilizing cellular thermal shift assays (CETSA), the effects of inhibitors on reversing 2-HG-induced block on leukemic cellular differentiation. We conclude from our mIDH1 assay panel that AG-120 and a Novartis inhibitor exhibited excellent activity in all biochemical and most cellular assays. While AG-120 has superior DMPK properties, it lacks efficacy a leukemic differentiation model. In conclusion, we present a comprehensive suite ofin vitropreclinical drug development assays that can be used as a tool-box to identify lead compounds for mIDH drug discovery programs, as well as what we believe is the most comprehensive publically available dataset on the top mIDH inhibitors.
Testing the principles of Mendelian randomization: Opportunities and complications on a genomewide scale
Authors: Taylor M , Tansey KE , Lawlor DA , Bowden J , Evans DM , Davey Smith G , Timpson NJ 
Published: April 2017

ABSTRACTBackgroundMendelian randomization (MR) uses genetic variants as instrumental variables to assess whether observational associations between exposures and disease reflect causal relationships. MR requires genetic variants to be independent of factors that confound observational associations.MethodsUsing data from the Avon Longitudinal Study of Parents and Children, associations within and between 121 phenotypes and 13,720 genetic variants (from the NHGRI-EBI GWAS catalog) were examined to assess the validity of MR assumptions.ResultsAmongst 7,260 pairwise comparisons between the 121 phenotypes, 2,188 (30%) provided evidence of association, where 363 were expected at the 5% level (observed:expected ratio=6.03; 95% CI: 5.42, 6.70; χ2=9682.29; d.f. =1, P≤1x10-50). Amongst 1,660,120 pairwise associations between phenotypes and genotypes, 86,748 (5.2%) gave evidence of association at the same threshold, where 83,006 were expected (observed:expected ratio=1.05; 95% CI: 1.04, 1.05; χ2=117.57; d.f. =1, P=2.15x10-27). Amongst 1,171,764 pairwise associations between the phenotypes and LD pruned independent genetic variants, 60,136 (5.1%) gave evidence of association, where 58,588 were expected (observed:expected ratio=1.03; 95% CI: 1.03, 1.08; χ2= 43.05; d.f. = 1, P=5.33x10-11).ConclusionThese results confirm previously observed patterns of phenotypic correlation. They also provide evidence of a substantially lower level of association between genetic variants and phenotypes, with residual inflation the likely product of indistinguishable real genetic association, multiple variables measuring the same biological phenomena, or pleiotropy. These results reflect the favorable properties of genetic instruments for estimating causal relationships, but confirm the need for functional information or analytical methods to account for pleiotropic events.
Genetic control of age-related gene expression and complex traits in the human brain
Authors: Martin Trevor , Fraser Hunter B. 
Published: April 2017

AbstractAge is the primary risk factor for many of the most common human diseases—particularly neurodegenerative diseases—yet we currently have a very limited understanding of how each individual’s genome affects the aging process. Here we introduce a method to map genetic variants associated with age-related gene expression patterns, which we call temporal expression quantitative trait loci (teQTL). We found that these loci are markedly enriched in the human brain and are associated with neurodegenerative diseases such as Alzheimer’s disease and Creutzfeldt-Jakob disease. Examining potential molecular mechanisms, we found that age-related changes in DNA methylation can explain some cis-acting teQTLs, and that trans-acting teQTLs can be mediated by microRNAs. Our results suggest that genetic variants modifying age-related patterns of gene expression, acting through both cis- and trans-acting molecular mechanisms, could play a role in the pathogenesis of diverse neurological diseases.
Lethal Haplotypes and Candidate Causal Mutations in Angus Cattle
Authors: Hoff Jesse L. , Decker Jared E. , Schnabel Robert D. , Taylor Jeremy F. 
Published: April 2017

AbstractBackgroundIf unmanaged, high rates of inbreeding in livestock populations adversely impact their reproductive fitness. In beef cattle, historical selection strategies have increased the frequency of several segregating fatal autosomal recessive polymorphisms. Selective breeding has also decreased the extent of haplotypic diversity genome-wide. By identifying haplotypes for which homozygotes are not observed but would be expected based on their frequency, developmentally lethal recessive loci can be localized. This analysis comes without the need for observation of the loss-associated phenotype (e.g., failure to implant, first trimester abortion, deformity at birth). In this study, haplotypes were estimated for 3,961 registered Angus individuals using 52,545 SNP loci using findhap v2, which exploited the complex pedigree among the individuals in this population.ResultsSeven loci were detected to possess haplotypes that were not observed in homozygous form despite a sufficiently high frequency and pedigree-based expectation of homozygote occurrence. These haplotypes were identified as candidates for harboring autosomal recessive lethal alleles. Of the genotyped individuals, 109 were resequenced to an average 27X depth of coverage to identify putative loss-of-function alleles genome-wide and had variants called using a custom in-house developed pipeline. For the candidate lethal-harboring haplotypes present in these bulls, sequence-called genotypes were used to identify concordant variants. In addition, whole-genome sequence imputation of variants was performed into the set of 3,961 genotyped animals using the 109 resequenced animals to identify candidate lethal recessive variants at the seven loci.ConclusionsSelective breeding programs could utilize the predicted lethal haplotypes associated with SNP genotypes. Sequencing and other methods for identifying the causal variants underlying these haplotypes can allow for more efficient methods of management such as gene editing. These two methods in total will reduce the negative impacts of inbreeding on fertility and maximize overall genetic gains.
DeepBound: Accurate Identification of Transcript Boundaries via Deep Convolutional Neural Fields
Authors: Shao Mingfu , Ma Jianzhu , Wang Sheng 
Published: April 2017

AbstractMotivationReconstructing the full-length expressed transcripts (a.k.a. the transcript assembly problem) from the short sequencing reads produced by RNA-seq protocol plays a central role in identifying novel genes and transcripts as well as in studying gene expressions and gene functions. A crucial step in transcript assembly is to accurately determine the splicing junctions and boundaries of the expressed transcripts from the reads alignment. In contrast to the splicing junctions that can be efficiently detected from spliced reads, the problem of identifying boundaries remains open and challenging, due to the fact that the signal related to boundaries is noisy and weak.ResultsWe present DeepBound, an effective approach to identify boundaries of expressed transcripts from RNA-seq reads alignment. In its core DeepBound employs deep convolutional neural fields to learn the hidden distributions and patterns of boundaries. To accurately model the transition probabilities and to solve the label-imbalance problem, we novelly incorporate the AUC (area under the curve) score into the optimizing objective function. To address the issue that deep probabilistic graphical models requires large number of labeled training samples, we propose to use simulated RNA-seq datasets to train our model. Through extensive experimental studies on both simulation datasets of two species and biological datasets, we show that DeepBound consistently and significantly outperforms the two existing methods.AvailabilityDeepBound is freely available athttps://github.com/realbigws/DeepBound.Contactmingfu.shao@cs.cmu.edu,realbigws@gmail.com
Running Promotes Spatial Bias Independently of Adult Neurogenesis
Authors: Snyder Jason S. , Cahill Shaina P. , Frankland Paul W. 
Published: April 2017

ABSTRACTDifferent memory systems offer distinct advantages to navigational behavior. The hippocampus forms complex associations between environmental stimuli, enabling flexible navigation through space. In contrast, the dorsal striatum associates discrete cues and favorable behavioral responses, enabling habit-like, automated navigation. While these two systems often complement one another, there are instances where striatal-dependent responses (e.g. approach a cue) conflict with hippocampal representations of spatial goals. In conflict situations, preference for spatial vs. response strategies varies across individuals and depends on previous experience, plasticity and the integrity of these two memory systems. Here, we investigated the role of adult hippocampal neurogenesis and exercise on mouse search strategies in a water maze task that can be solved with either a hippocampal-dependent place strategy or a striatal-dependent cue-response strategy. We predicted that inhibiting adult neurogenesis would impair hippocampal function and shift behavior towards striatal-dependent cue responses. However, blocking neurogenesis in a transgenic nestin-TK mouse did not affect strategy choice. We then investigated whether a pro-neurogenic stimulus, running, would bias mice towards hippocampal-dependent spatial strategies. While running indeed promoted spatial strategies, it did so even when neurogenesis was inhibited in nestin-TK mice. These findings indicate that exercise-induced increases in neurogenesis are not always required for enhanced cognitive function. Furthermore, our data identify exercise as a potentially useful strategy for promoting flexible, cognitive forms of memory in habit-related disorders that are characterized by excessive responding to discrete cues.
Feature extraction through Wavelet decomposition for automatic detection of landmarks on Cephalogram Images
Authors: Vasamsetti Srikanth , Sardana Viren , Kumar Prasoon , Sardana H.K 
Published: April 2017

AbstractManual cephalogram marking has long way from marking on tracing sheet to availability of commercial software's for cephalometric analysis. With the effort involved in manual marking and time consumption, it becomes imperative for modern science to envisage algorithms which could automatically locate landmarks on the cephalogram images and perform various analysis. In this work, we herby propose a wavelet transform based feature extraction algorithm for detection of landmark on cephalogram images. 15 landmarks were detected on the images using wavelet transform and all landmarks were detected within the acceptable accuracy limits. This algorithm may have a promising approach in detection of further anatomical landmarks automatically and analysis and thus may help orthodontic practioners in better and faster treatment planning.
An evolutionarily conserved leucine zipper-like motif accounts for strong tetramerization capabilities of SEPALLATA-like MADS-domain transcription factors controlling flower development
Authors: Rümpler Florian , Theißen Günter , Melzer Rainer 
Published: April 2017

ABSTRACTThe development of angiosperm flowers is regulated by homeotic MIKC-type MADS-domain transcription factors that activate or repress target genes via the formation of DNA-bound, organ specific tetrameric complexes. The protein-protein interaction (PPI) capabilities differ considerably between different MIKC-type proteins. The floral homeotic protein SEPALLATA3 (SEP3) acts as a hub that incorporates numerous other MADS-domain proteins into tetrameric complexes that would otherwise not form. However, the molecular mechanisms that underlie these promiscuous interactions remain largely unknown. In this study we created a collection of amino acid substitution mutants of SEP3 to quantify the contribution of individual residues on protein tetramerization during DNA-binding, employing methods of molecular biophysics. We show that leucine residues at certain key positions form a leucine zipper structure that is essential for tetramerization of SEP3, whereas the introduction of physicochemically very similar residues at respective sites impedes the formation of DNA-bound tetramers. Comprehensive molecular evolutionary analyses of MADS-domain proteins from a diverse set of flowering plants revealed exceedingly high conservation of the identified leucine residues within SEP3-subfamily proteins throughout angiosperm evolution. In contrast, MADS-domain proteins that are unable to tetramerize among themselves exhibit preferences for other amino acids at homologous sites. Our findings indicate that the subfamily-specific conservation of amino acid residues at just a few key positions account for subfamily-specific interaction capabilities of MADS-domain transcription factors and shaped the present-day structure of the PPI network controlling flower development.
SMC progressively aligns chromosomal arms inCaulobacter crescentusbut is antagonized by convergent transcription
Authors: Tran Ngat T. , Laub Michael T. , Le Tung B. K. 
Published: April 2017

SUMMARYThe Structural Maintenance of Chromosomes (SMC) complex plays an important role in chromosome organization and segregation in most living organisms. InCaulobacter crescentus, SMC is required to align the left and the right arms of the chromosome that run in parallel down the long axis of the cell. However, the mechanism of SMC-mediated alignment of chromosomal arms remains elusive. Here, using a genome-wide chromosome conformation capture assay, chromatin immunoprecipitation with deep sequencing, and microscopy of single cells, we show thatCaulobacterSMC is recruited to the centromericparSsite and that SMC-mediated arm alignment depends on the chromosome partitioning protein ParB. We provide evidence that SMC likely tethers theparS-proximal regions of the chromosomal arms together, promoting arm alignment. Strikingly, the co-orientation of SMC translocation and the transcription of highly-expressed genes is crucial for the alignment ofparS-proximal regions of the chromosomal arms. Highly-transcribed genes nearparSthat are oriented against SMC translocation disrupt arm alignment suggesting that head-on transcription interferes with SMC translocation. Our results demonstrate a tight interdependence of bacterial chromosome organization and global patterns of transcription.
OGT binds a conserved C-terminal domain of TET1 to regulate TET1 activity and function in development
Authors: Hrit Joel , Li Cheng , Martin Elizabeth Allene , Goll Mary , Panning Barbara 
Published: April 2017

AbstractMammalian TET enzymes oxidize 5-methylcytosine to 5-hydroxymethylcytosine and higher oxidized derivatives. TETs are targets of the enzyme OGT, which post-translationally modifies intracellular proteins in response to cellular nutrient status. The biological implications of the OGT-TET interaction have not been thoroughly explored. Here, we show for the first time that modification of TET1 by OGT enhances its activityin vitro. We identify a previously uncharacterized domain of TET1 responsible for binding to OGT and report a point mutation that disrupts the OGT-TET1 interaction. Finally, we show that the interaction between TET1 and OGT is necessary for TET1 to rescuetetmutant zebrafish hematopoetic stem cell formation, suggesting that OGT promotes TET1’s function in development. Our results demonstrate regulation of TET activity by OGTin vitroandin vivo. These results link metabolism and epigenetic control, which may be relevant to the developmental and disease processes regulated by these two enzymes.
Complexity and conservation of regulatory landscapes underlie evolutionary resilience of mammalian gene expression
Authors: Berthelot Camille , Villar Diego , Horvath Julie E. , Odom Duncan T. , Flicek Paul 
Published: April 2017

AbstractTo gain insight into how mammalian gene expression is controlled by rapidly evolving regulatory elements, we jointly analysed promoter and enhancer activity with downstream transcription levels in liver samples from twenty species. Genes associated with complex regulatory landscapes generally exhibit high expression levels that remain evolutionarily stable. While the number of regulatory elements is the key driver of transcriptional output and resilience, regulatory conservation matters: elements active across mammals most effectively stabilise gene expression. In contrast, recently-evolved enhancers typically contribute weakly, consistent with their high evolutionary plasticity. These effects are observed across the entire mammalian clade and robust to potential confounders, such as gene expression level. Overall, our results illuminate how the evolutionary stability of gene expression is profoundly entwined with both the number and conservation of surrounding promoters and enhancers.HighlightsGene expression levels and stability are linked to the number of elements in the regulatory landscape.Conserved regulatory elements associate with tightly controlled, highly expressed genes.Recently evolved enhancers weakly influence gene expression, but promoters are similarly active regardless of conservation.The interplay between complexity of the regulatory landscape and conservation of individual promoters and enhancers shapes gene expression in mammals.
GSA-Genie: a web application for gene set analysis
Authors: Zhang Zhe , Taylor Deanne 
Published: April 2017

AbstractGene set analysis is often used to interpret results from upstream analysis through predefined gene sets that are linked to biological features such as cell cycle or tumorgenesis. Gene sets have been defined in the literature via various criteria and are archived by numerous databases. We compiled over 2.3 million gene sets from 17 sources, and made them accessible through a web application, GSA-Genie. Selected gene sets can be analyzed online using one of 16 statistical methods. These methods can be grouped into two strategies: test of gene set over-representation within a gene list, or comparison of a gene-level statistics between gene set and background. GSA-Genie operates on a Shiny web server, hosted in a cloud instance within Amazon Web Services. GSA-Genie offers a broad selection of gene sets and statistical methods comparing to existing tools. GSA-Genie is freely available athttp://gsagenie.awsomics.org.
A measure of agreement across numerous conditions: Reproducibility of co-expression networks across tissues
Authors: Cáceres Alejandro , González Juan R. 
Published: April 2017

AbstractThere is great interest to study how co-expression gene networks change across tissues. However, the reproducibility assessment of these studies is challenged by a lack of fully confirmatory experiments from independent researchers. While an increment in the number of studies with expression data for several tissues is expected, statistical measures are still needed to assess the reproducibility between studies. We identified a gap in the statistical literature concerning the assessment of agreement between studies across numerous conditions. The gap precluded us to test, using standard statistics, the level of agreement between the GTEX (RNAseq) and BRAINEAC (microarray) studies to distinguish the structure of co-expression networks across four brain tissues. We propose a generalization of a classical measure of agreement, Cohen’s κ, derive its distributional characteristics and determine its reliability properties. In the gene expression studies, our generalization of κ showed full agreement for genome-wide networks in BRAINEAC benchmarked against GTEX, and highest agreement for brain specific pathways. Our highly interpretable measure can contribute to anticipated efforts on reproducibility research.
GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads
Authors: Chu Chong , Li Xin , Wu Yufeng 
Published: April 2017

AbstractBackgroundClosing gaps in draft genomes is an important post processing step in genome assembly. It leads to more complete genomes, which benefits downstream genome analysis such as annotation and genotyping. Several tools have been developed for gap closing. However, these tools don’t fully utilize the information contained in the sequence data. For example, while it is known that many gaps are caused by genomic repeats, existing tools often ignore many sequence reads that originate from a repeat-related gap.ResultsIn this paper, we propose a new approach called GAPPadder for gap closing. The main advantage of GAPPadder is that it uses more information in sequence data for gap closing. In particular, GAPPadder finds and uses reads that originate from repeate-related gaps. We show that these repeat-associated reads are useful for gap closing, even though they are ignored by all existing tools. Other main features of GAPPadder include utilizing the information in sequence reads with different insert sizes and performing two-stage local assembly of gap sequences. We compare GAPPadder with GapCloser, GapFiller and Sealer on one bacterial genome, human chromosome 14 and the human whole genome with paired-end and mate-paired reads with both short and long insert sizes. Empirical results show that GAPPadder can close more gaps than these existing tools. Besides closing gaps on draft genomes assembled only from short sequence reads, GAPPadder can also be used to close gaps for draft genomes assembled with long reads. We show GAPPadder can close gaps on the bed bug genome and the Asian sea bass genome that are assembled partially and fully with long reads respectively. We also show GAPPadder is efficient in both time and memory usage. The software tool, GAPPadder, is available for download athttps://github.com/Reedwarbler/GAPPadder.