Biology subjects

Mineta, K.

Publications and source records attributed to Mineta, K..

8 recordsLinked to original sources

bioRxiv2022

The canonical E2Fs together with RETINOBLASTOMA-RELATED are required to establish quiescence during plant development

Maintaining stable and transient quiescence in differentiated and stem cells, respectively, requires repression of the cell cycle. The plant RETINOBLASTOMA-RELATED (RBR) has been implicated in stem cell maintenance, presumably by forming repressor complexes with E2F transcription factors. Surprisingly we find that mutations in all three canonical E2Fs do not compromise the cell cycle, but similarly to RBR silencing, result in overproliferation. Contrary to the growth arrest upon RBR silencing, when exit from proliferation to differentiation is inhibited, the e2fabc mutant develops enlarged organs with supernumerary stem and differentiated cells as the quiescence is compromised. While E2F, RBR and the M-phase regulatory MYB3Rs are part of the DREAM repressor complexes, and recruited to overlapping groups of targets, they regulate distinct sets of genes. Only the loss of E2Fs but not the MYB3Rs interferes with quiescence, which might be due to the ability of E2Fs to control both G1-S and some key G2-M targets. We conclude that collectively the three canonical E2Fs in complex with RBR have central roles in establishing cellular quiescence during organ development, leading to enhanced plant growth.

plant biology↗

bioRxiv2021

DeepSVP: Integration of genotype and phenotype for structural variant prioritization using deep learning

MotivationStructural genomic variants account for much of human variability and are involved in several diseases. Structural variants are complex and may affect coding regions of multiple genes, or affect the functions of genomic regions in different ways from single nucleotide variants. Interpreting the phenotypic consequences of structural variants relies on information about gene functions, haploinsufficiency or triplosensitivity, and other genomic features. Phenotype-based methods to identifying variants that are involved in genetic diseases combine molecular features with prior knowledge about the phenotypic consequences of altering gene functions. While phenotype-based methods have been applied successfully to single nucleotide variants as well as short insertions and deletions, the complexity of structural variants makes it more challenging to link them to phenotypes. Furthermore, structural variants can affect a large number of coding regions, and phenotype information may not be available for all of them. ResultsWe developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information. We incorporate phenotypes linked to genes, functions of gene products, gene expression in individual celltypes, and anatomical sites of expression, and systematically relate them to their phenotypic consequences through ontologies and machine learning. DeepSVP significantly improves the success rate of finding causative variants in several benchmarks and can identify novel pathogenic structural variants in consanguineous families. Availabilityhttps://github.com/bio-ontology-research-group/DeepSVP Contactrobert.hoehndorf@kaust.edu.sa

bioinformatics↗

bioRxiv2020

A single neuron subset governs a single coactive neuron circuit in Hydra vulgaris , representing a prototypic feature of neural evolution

The last common ancestor of Bilateria and Cnidaria is believed to be one of the first animals to develop a nervous system over 500 million years ago. Many of the genes involved in the neural function of the advanced nervous system in Bilateria are well conserved in Cnidaria1. Thus, Cnidarian representative species, Hydra, is considered to be a living fossil and a good model organism for the study of the putative primitive nervous system in its last common ancestor. The diffuse nervous system of Hydra consists of several peptidergic neuron subsets. However, the specific functions of these subsets remain unclear. Using calcium imaging, here we show that the neuron subsets that express neuropeptide, Hym-1762,3 function as motor neurons to evoke longitudinal contraction. We found that all neurons in a subset defined by the Hym-176 gene (Hym-176A) or its paralogs (Hym-176B) expression4 are excited simultaneously, which is then followed by longitudinal contraction. This indicates not only that these neuron subsets are motor neurons but also that a single molecularly defined neuron subset forms a single coactive motor circuit. This is in contrast with the Bilaterian nervous system, where a single molecularly defined neuron subset harbors multiple coactive circuits, showing a mixture of neurons firing with different timings5. Furthermore, we found that the two motor circuits, one expressing Hym-176B in the body column and the other expressing Hym-176A in the foot, are coordinately regulated to exert region-specific contraction. Our results demonstrate that one neuron subset is likely to form a monofunctional circuit as a minimum functional unit to build a more complex behavior in Hydra. We propose that this simple feature (one subset, one circuit, one function) found in Hydra is a fundamental trait of the primitive nervous system.

neuroscience↗

bioRxiv2020

Integrated metabolic modeling, culturing and transcriptomics explains enhanced virulence of V. cholerae during co-infection with ETEC

Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models to explore the effect of co-infection of the diarrheagenic pathogen Vibrio cholerae (V. cholerae) with another enteric pathogen, enterotoxigenic E. coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual-infections by the two pathogens. In vitro co-culture systems confirmed that V. cholerae growth is enhanced in co-cultures relative to single-cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNAseq analysis of its co-cultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by non-metabolic factors. Single gene essentiality analysis predicted conditionally-independent genes that are essential for the pathogen’s growth in both single- and co-infection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections.Importance Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen’s growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single and co-infections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae (V. cholerae) in single and co-infections with enterotoxigenic E. coli (ETEC), which co-occur in large fraction of diarrheagenic patients. Co-infection model predictions showed that V. cholerae growth capabilities are enhanced in presence of ETEC relative to V. cholerae single-infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, co-cultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in co-culture relative to V. cholerae single-cultures while ETEC growth was suppressed. Dual RNAseq analysis of the co-cultures also confirmed that the transcriptome of V. cholerae is distinct during co-infection compared to single infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knock out simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single and co-infections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single and co-infections, thus designing inhibitors against those targets would provide a broader spectrum coverage against cholera infections.View Full Text

systems biology↗

bioRxiv2020

Massively parallel single-cell genome sequencing enables high-resolution analysis of soil and marine microorganisms

To improve our understanding of the environmental microbiome, we developed a single-cell genome sequencing platform, named SAG-gel, which utilizes gel beads for single-cell isolation, cell lysis, and whole genome amplification (WGA) for sequencing. SAG-gel enables serial, parallel and independent reactions of > 100,000 single cells in a single tube, delivering high-quality genome recovery with storable randomized single-cell genome libraries. From soil and marine environmental sources, we acquired 734 partial genomes that are recapitulated in 231 species, 35% of which were assigned as high-to-medium qualities. We found that each genome to be almost unique and 98.7% of them were newly identified, implying the complex genetic diversities across 44 phyla. The various metabolic capabilities including virulence factors and biosynthetic gene clusters were found across the lineages at single-cell resolution. This technology will accelerate the accumulation of reference genomes of uncharacterized environmental microbes and provide us new insights for their roles.

genomics↗

bioRxiv2019

Machine Learning Reveals Spatiotemporal Genome Evolution in Asian Rice Domestication

Domestication is anthropogenic evolution that fulfills mankinds critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized past genomic introgressions between them as traces of domestication. Here we show the genome-wide introgressive region (IR) map of Asian rice, by utilizing 4,587 accession genotypes with a stable outgroup species, particularly at the finest resolution through a machine learning-aided method. The IR map revealed that 14.2% of the rice genome consists of IRs, including both wide IRs (recent) and narrow IRs (ancient). This introgressive landscape with their time calibration indicates that introgression events happened in multiple genomic regions over multiple periods. From the correspondence between our wide IRs and the so-called selective sweep regions, we provide a definitive answer to a long-standing controversy over the evolutionary origin of Asian rice domestication, single or multiple origins: It heavily depends upon which regions you pay attention to, implying that wider genomic regions represent immediate short history of Asian rice domestication as a likely support to the single origin, while its ancient history is interspersed in narrower traces throughout the genome as a possible support to the multiple origin.

plant biology↗

bioRxiv2019

Ontology-based prediction of cancer driver genes

Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity, many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.

bioinformatics↗

bioRxiv2018

Finding Nemo’s Genes: A chromosome-scale reference assembly of the genome of the orange clownfish Amphiprion percula

The iconic orange clownfish, Amphiprion percula, is a model organism for studying the ecology and evolution of reef fishes, including patterns of population connectivity, sex change, social organization, habitat selection and adaptation to climate change. Notably, the orange clownfish is the only reef fish for which a complete larval dispersal kernel has been established and was the first fish species for which it was demonstrated that anti-predator responses of reef fishes could be impaired by ocean acidification. Despite its importance, molecular resources for this species remain scarce and until now it lacked a reference genome assembly. Here we present a de novo chromosome-scale assembly of the genome of the orange clownfish Amphiprion percula. We utilized single-molecule real-time sequencing technology from Pacific Biosciences to produce an initial polished assembly comprised of 1,414 contigs, with a contig N50 length of 1.86 Mb. Using Hi-C based chromatin contact maps, 98% of the genome assembly were placed into 24 chromosomes, resulting in a final assembly of 908.8 Mb in length with contig and scaffold N50s of 3.12 and 38.4 Mb, respectively. This makes it one of the most contiguous and complete fish genome assemblies currently available. The genome was annotated with 26,597 protein coding genes and contains 96% of the core set of conserved actinopterygian orthologs. The availability of this reference genome assembly as a community resource will further strengthen the role of the orange clownfish as a model species for research on the ecology and evolution of reef fishes.

genomics↗