Biology subjects

Sasaki, E.

Publications and source records attributed to Sasaki, E..

4 recordsLinked to original sources

bioRxiv2018

Single-cell transcriptome analysis of human, marmoset and mouse embryos reveals common and divergent features of preimplantation development

The mouse embryo is the canonical model for mammalian preimplantation development. Recent advances in single-cell profiling allow detailed analysis of embryogenesis in other eutherian species, including human, to distinguish conserved from divergent regulatory programs and signalling pathways in the rodent paradigm. Here, we identify and compare transcriptional features of human, marmoset and mouse embryos by single-cell RNA-seq. Zygotic genome activation correlates with the presence of Polycomb Repressive Complexes in all three species, while ribosome biogenesis emerges as a predominant attribute in primate embryos, supporting prolonged translation of maternally deposited RNAs. We find that transposable element expression signatures are species-, stage- and lineage-specific. The pluripotency network in the primate epiblast lacks certain regulators operative in mouse, but encompasses WNT components and genes associated with trophoblast specification. Sequential activation of GATA6, SOX17 and GATA4 markers of primitive endoderm identity is conserved in primates. Unexpectedly, OTX2 is also associated with primitive endoderm specification in human and nonhuman primate blastocysts. Our cross-species analysis demarcates both conserved and primate-specific features of preimplantation development and underscores the molecular adaptability of early mammalian embryogenesis.

developmental biology↗

bioRxiv2018

A High-throughput Neurohistological Pipeline for Brain-Wide Mesoscale Connectivity Mapping of the Common Marmoset

Understanding the connectivity architecture of entire vertebrate brains is a fundamental but difficult task. MRI based methods offer whole brain coverage, but remain indirect in the approach to connectivity mapping. Recent progress has been made in directly mapping whole-brain connectivity architecture in the mouse at the mesoscopic scale. The basic approach uses tracer injections systematically placed on a grid of locations spanning the brain and computational analysis of the resulting whole brain data sets. Scaling this approach to bigger primate brains poses nontrivial technical challenges. Here we present an integrated neurohistological pipeline as well as a grid-based tracer injection strategy for systematic mesoscale connectivity mapping in the common Marmoset (Callithrix jacchus). Individual brains are sectioned into [~]1700 20{micro}m sections using the tape transfer technique, permitting high quality 3D reconstruction of a series of histochemical stains (Nissl, myelin) interleaved with tracer labelled sections. Combining the resulting 3D volumes, containing informative cytoarchitectonic markers, with in-vivo and ex-vivo MRI, and using an integrated computational pipeline, we are able to overcome the significant individual variation exhibited by Marmosets to obtain routine and high quality maps to a common atlas framework. This will facilitate the systematic assembly of a mesoscale connectivity matrix together with unprecedented 3D reconstructions of brain-wide projection patterns in a primate brain. While component instruments or protocols may be available from previous work, we believe that this is the first detailed systems-level presentation of the methodology required for high-throughput neuroanatomy in a model primate.

neuroscience↗

bioRxiv2017

The genetic architecture of the network underlying flowering time variation in Arabidopsis thaliana

Flowering time is a key adaptive trait in plants and is tightly controlled by a complex regulatory network that responds to seasonal signals. In a rapidly changing climate, understanding the genetic basis of flowering time variation is important for both agriculture and ecology. Genetic mapping has revealed many genetic variants affecting flowering time, but the effects on the gene regulatory networks in population-scale are still largely unknown. We dissected flowering time networks using multi-layered Swedish population data from Arabidopsis thaliana, consisting of flowering time and transcriptome collected under constant 10{degrees}C growth temperature in addition to full genome sequence data. Our analysis identified multiple alleles of the key flowering time gene FLOWERING LOCUS C (FLC) as the primary determinant of the network underlying flowering time variation under our condition. Genetic variation of FLC affects multiple-pathways through known flowering-time genes including FLOWERING LOCUS T (FT), and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1). We demonstrated that an extremely simple single-locus model of FLC involving allelic variation and expression explains almost a half of flowering time variation, with 60% of the effect being mediated through FLC expression. Furthermore, the accuracy of the model fitted at 10{degrees}C is almost unchanged at 16{degrees}C.

genetics↗

bioRxiv2017

Mapping The Malaria Parasite Drug-Able Genome Using In Vitro Evolution And Chemogenomics

Chemogenetic characterization through in vitro evolution combined with whole genome analysis is a powerful tool to discover novel antimalarial drug targets and identify drug resistance genes. Our comprehensive genome analysis of 262 Plasmodium falciparum parasites treated with 37 diverse compounds reveals how the parasite evolves to evade the action of small molecule growth inhibitors. This detailed data set revealed 159 gene amplifications and 148 nonsynonymous changes in 83 genes which developed during resistance acquisition. Using a new algorithm, we show that gene amplifications contribute to 1/3 of drug resistance acquisition events. In addition to confirming known multidrug resistance mechanisms, we discovered novel multidrug resistance genes. Furthermore, we identified promising new drug target-inhibitor pairs to advance the malaria elimination campaign, including: thymidylate synthase and a benzoquinazolinone, farnesyltransferase and a pyrimidinedione, and a dipeptidylpeptidase and an arylurea. This deep exploration of the P. falciparum resistome and drug-able genome will guide future drug discovery and structural biology efforts, while also advancing our understanding of resistance mechanisms of the deadliest malaria parasite.\n\nOne Sentence SummaryWhole genome sequencing reveals how Plasmodium falciparum evolves resistance to diverse compounds and identifies new antimalarial drug targets.

genomics↗