Implementing Data-Flow Fusion DSL on Clojure

This paper presents a new optimization tech-nique for programming language Clojure based on the stan-dard fusion technique that merges list operations into a simplified loop.Short-cut fusions, foldr/build fusion, and stream fusions are standard fusion techniques used in a functional programming.Moreover, a recent fusion technique proposed by Lippmeier. Data flow fusion [7] can fuse loops containing several data consumers over stream operators on Haskell. However, this isonly for Haskell. Clojure\u27s transducers [2] are factory func-tions generating abstract list objects. The functions generated by them wait evaluation as a lazy evaluation partially.We introduce data-flow fusion macros into Clojure as a dynamic typing mechanism and show the difference of data flow fusion between that of Clojure and Haskell.We focus on Clojure which is a functional programming language with attracting features of dynamic typing, Lisp macros, partial lazy evaluation, and running on the Java Virtual Machine (JVM). Our macro compiles S-expression of Clojure to Clojure code and Java class file. Our ideas are implemented as a domain specific language, which has strong points of the pro-vision of a simple interface for loop fusion, and independence from the implementation of a Clojure Compiler.We discuss the advantages and disadvantages of data-flow fusion macro from experimental results and adaptability of our macro

Identification of key yeast species and microbe–microbe interactions impacting larval growth of Drosophila in the wild

自然界で動物の成長を支える共生微生物叢 --中心的な役割を担う共生酵母・細菌の同定--. 京都大学プレスリリース. 2023-12-28.Microbiota consisting of various fungi and bacteria have a significant impact on the physiological functions of the host. However, it is unclear which species are essential to this impact and how they affect the host. This study analyzed and isolated microbes from natural food sources of Drosophila larvae, and investigated their functions. Hanseniaspora uvarum is the predominant yeast responsible for larval growth in the earlier stage of fermentation. As fermentation progresses, Acetobacter orientalis emerges as the key bacterium responsible for larval growth, although yeasts and lactic acid bacteria must coexist along with the bacterium to stabilize this host–bacterial association. By providing nutrients to the larvae in an accessible form, the microbiota contributes to the upregulation of various genes that function in larval cell growth and metabolism. Thus, this study elucidates the key microbial species that support animal growth under microbial transition

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection