Biology subjects

Yu, K.

Publications and source records attributed to Yu, K..

10 recordsLinked to original sources

bioRxiv2018

Comprehensive transcriptomic analysis of cell lines as models of primary tumor samples across 22 tumor types

Cancer cell lines are commonly used as models for cancer biology. While they are limited in their ability to capture complex interactions between tumors and their surrounding environment, they are a cornerstone of cancer research and many important findings have been discovered utilizing cell line models. Not all cell lines are appropriate models of primary tumors, however, which may contribute to the difficulty in translating in vitro findings to patients. Previous studies have leveraged public datasets to evaluate cell lines as models of primary tumors, but they have been limited in scope to specific tumor types and typically ignore the presence of tumor infiltrating cells in the primary tumor samples. We present here a comprehensive pan-cancer analysis utilizing approximately 9,000 transcriptomic profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia to evaluate cell lines as models of primary tumors across 22 different tumor types. After adjusting for tumor purity in the primary tumor samples, we performed correlation analysis and differential gene expression analysis between the primary tumor samples and cell lines. We found that cell-cycle pathways are consistently upregulated in cell lines, while no pathways are consistently upregulated across the primary tumor samples. In a case study, we compared colorectal cancer cell lines with primary tumor samples across the colorectal subtypes and identified three colorectal cell lines that were derived from fibroblasts rather than tumor epithelial cells. Lastly, we propose a new set of cell lines panel, the TCGA-110, which contains the most representative cell lines from 22 different tumor types as a more comprehensive and informative alternative to the NCI-60 panel. Our analysis of the other tumor types are available in our web app (http://comphealth.ucsf.edu/TCGA110) as a resource to the cancer research community, and we hope it will allow researchers to select more appropriate cell line models and increase the translatability of in vitro findings.

bioinformatics↗

bioRxiv2018

miRBaseConverter: An R/Bioconductor Package for Converting and Retrieving miRNA Name, Accession, Sequence and Family Information in Different Versions of miRBase

BackgroundmiRBase is the primary repository for published miRNA sequence and annotation data, and serves as the \"go-to\" place for miRNA research. However, the definition and annotation of miRNAs have been changed significantly across different versions of miRBase. The changes cause inconsistency in miRNA related data between different databases and articles published at different times. Several tools have been developed for different purposes of querying and converting the information of miRNAs between different miRBase versions, but none of them individually can provide the comprehensive information about miRNAs in miRBase and users will need to use a number of different tools in their analyses.\n\nResultsWe introduce miRBaseConverter, an R package integrating the latest miRBase version 22 available in Bioconductor to provide a suite of functions for converting and retrieving miRNA name (ID), accession, sequence, species, version and family information in different versions of miRBase. The package is implemented in R and available under the GPL-2 license from the Bioconductor website (http://bioconductor.org/packages/miRBaseConverter/). A Shiny-based GUI suitable for non-R users is also available as a standalone application from the package and also as a web application at http://nugget.unisa.edu.au:3838/miRBaseConverter. miRBaseConverter has a built-in database for querying miRNA information in all species and for both pre-mature and mature miRNAs defined by miRBase. In addition, it is the first tool for batch querying the miRNA family information. The package aims to provide a comprehensive and easy-to-use tool for miRNA research community where researchers often utilize published miRNA data from different sources.\n\nConclusionsThe Bioconductor package miRBaseConverter and the Shiny-based web application are presented to provide a suite of functions for converting and retrieving miRNA name, accession, sequence, species, version and family information in different versions of miRBase. The package will serve a wide range of applications in miRNA research and could provide a full view of the miRNAs of interest.

genomics↗

bioRxiv2018

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping, and transcriptomic profiling

HighlightGenome-wide linkage and homology mapping revealed 17 genomic regions through a high-density einkorn wheat genetic map constructed using RAD-seq, and transcription levels of 20 candidate genes were explored using RNA-seq.\n\nAbstractUnderstanding the genetic architecture of grain size is a prerequisite to manipulate the grain development and improve the yield potential in crops. In this study, we conducted a whole genome-wide QTL mapping of grain size related traits in einkorn wheat by constructing a high-density genetic map, and explored the candidate genes underlying QTL through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 SNP markers assigned to 1551 bins in seven chromosomes. Strong collinearity and high genome coverage of this map were revealed with the physical maps of wheat and barley. Six grain size related traits were surveyed in five agro-climatic environments with 80% or more broad-sense heritability. In total, 42 QTL were identified and assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variations. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing provided 4959 genes differentially expressed between the two parents. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTL, indicating that the starch biosynthesis pathway played a vital role on grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat, the underlying genes enables the understanding of grain development and wheat genetic improvement, and the map facilitates the mapping of quantitative traits, map-based cloning, genome assembling and comparative genomics in wheat taxa.

genetics↗

bioRxiv2018

Vascular defects of DYRK1A knockouts are ameliorated by modulating calcium signaling in zebrafish

DYRK1A is a major causative gene in Down syndrome (DS). Reduced incidence of solid tumors and vascular anomalies in DS patients suggests a role of DYRK1A in angiogenesis, but in vivo evidence is lacking. Here, we used zebrafish dyrk1aa mutant embryos to understand DYRK1A function in the cerebral vasculature formation. Zebrafish dyrk1aa mutants exhibited cerebral hemorrhage and defects in angiogenesis of central arteries in the developing hindbrain. Such phenotypes were rescued by wild-type dyrk1aa mRNA, but not by a kinase-dead form, indicating the importance of DYRK1A kinase activity. Chemical screening using a bioactive small molecule library identified a calcium chelator, EGTA, as one of the hits that most robustly rescued the hemorrhage. Vascular defects of mutants were also rescued by independent modulation of calcium signaling by FK506. Furthermore, the transcriptomic analyses supported the alterations of calcium signaling networks in dyrk1aa mutants. Together, our results suggest that dyrk1aa plays an essential role in angiogenesis and in maintenance of the developing cerebral vasculature via regulation of calcium signaling, which may have therapeutic potential for DYRK1A-related vascular diseases.

developmental biology↗

bioRxiv2018

Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. To address this question, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples, spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types, and identify cancer type specific subclonal patterns of driver gene mutations, fusions, structural variants and copy-number alterations, as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution, and provide an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

cancer biology↗

bioRxiv2017

AQMM: Enabling Absolute Quantification of Metagenome and Metatranscriptome

Metatranscriptome has become increasingly important along with the application of next generation sequencing in the studies of microbial functional gene activity in environmental samples. However, the quantification of target active gene is hindered by the current relative quantification methods, especially when tracking the sharp environmental change. Great needs are here for an easy-to-perform method to obtain the absolute quantification. By borrowing information from the parallel metagenome, an absolute quantification method for both metagenomic and metatranscriptomic data to per gene/cell/volume/gram level was developed. The effectiveness of AQMM was validated by simulated experiments and was demonstrated with a real experimental design of comparing activated sludge with and without foaming. Our method provides a novel bioinformatic approach to fast and accurately conduct absolute quantification of metagenome and metatranscriptome in environmental samples. The AQMM can be accessed from https://github.com/biofuture/aqmm.

bioinformatics↗

bioRxiv2017

The evolutionary history of 2,658 cancers

Cancer develops through a process of somatic evolution. Here, we use whole-genome sequencing of 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution of mutational processes, and driver mutation sequences of 39 cancer types. The early phases of oncogenesis are driven by point mutations in a small set of driver genes, often including biallelic inactivation of tumour suppressors. Early oncogenesis is also characterised by specific copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma. By contrast, increased genomic instability, a nearly four-fold diversification of driver genes, and an acceleration of point mutation processes are features of later stages. Copy-number alterations often occur in mitotic crises leading to simultaneous gains of multiple chromosomal segments. Timing analysis suggests that driver mutations often precede diagnosis by many years, and in some cases decades, providing a window of opportunity for early cancer detection.

cancer biology↗

bioRxiv2017

An insula-central amygdala circuit for behavioral inhibition

Predicting which substances are suitable for consumption during foraging is critical for animals to survive. While food-seeking behavior is extensively studied, the neural circuit mechanisms underlying avoidance of potentially poisonous substances remain poorly understood. Here we examined the role of the insular cortex (IC) to central amygdala (CeA) circuit in the establishment of such avoidance behavior. Using anatomic tracing approaches combined with optogenetics-assisted circuit mapping, we found that the gustatory region of the IC sends direct excitatory projections to the lateral division of the CeA (CeL), making monosynaptic excitatory connections with distinct populations of CeL neurons. Specific inhibition of neurotransmitter release from the CeL-projecting IC neurons prevented mice from acquiring the \"no-go\" response, while leaving the \"go\" response largely unaffected in a tastant (sucrose/quinine)-reinforced \"go/no-go\" task. Furthermore, selective activation of the IC-CeL pathway with optogenetics drove unconditioned lick suppression in thirsty animals, induced aversive responses, and was sufficient to instruct conditioned action suppression in response to a cue predicting the optogenetic activation. These results indicate that activity in the IC-CeL circuit is necessary for establishing anticipatory avoidance responses to an aversive tastant, and is also sufficient to drive learning of such anticipatory avoidance. This function of the IC-CeL circuit is likely important for guiding avoidance of substances with unpleasant tastes during foraging in order to minimize the chance of being poisoned.\n\nSignificance StatementThe ability to predict which substances are suitable for consumption is critical for survival. Here we found that activity in the insular cortex (IC) to central amygdala (CeA) circuit is necessary for establishing avoidance responses to an unpleasant tastant, and is also sufficient to drive learning of such avoidance responses. These results suggest that the IC-CeA circuit is critical for behavioral inhibition in anticipation of potentially poisonous substances during foraging.

neuroscience↗

bioRxiv2017

Ranking quantitative resistance to Septoria tritici blotch in elite wheat cultivars using automated image analysis

Quantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis (AIA) of 21420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

plant biology↗

bioRxiv2017

The central amygdala controls learning in the lateral amygdala

Both the lateral and the central nuclei of the amygdala are required for adaptive behavioral responses to environmental cues predicting threats. While experience-driven synaptic plasticity in the lateral amygdala is thought to underlie the formation of association between a sensory stimulus and an ensuing threat, how the central amygdala participates in such learning process remains unclear. Here we show that a specific class of central amygdala neurons, the protein kinase C-{delta}-expressing neurons, is essential for the synaptic plasticity underlying learning in the lateral amygdala, as it is required for lateral amygdala neurons to respond to unconditioned stimulus, and furthermore carries information about the unconditioned stimulus to instruct learning. Our results uncover an amygdala functional organization that may play a key role in diverse learning processes.

neuroscience↗