iiinova — where your digital self keeps evolving

Jumpei Ito @jampei2.bsky.social · 06/09/2026

Our lab (Viral Informatics Lab, RIMD, U. Osaka) pursues "AI for Viral Infectious Diseases": viral evolution, viral protein modeling for vaccine optimization, and AI to efficiently search for viruses that could cause the next pandemic. (9/10) sites.google.com/view/virus-i...

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

Arnon Plianchaisuk performed all analyses. The work began at our former affiliation, Division of Systems Virology, IMSUT, University of Tokyo (Kei Sato lab). We thank Spyros Lytras, Hiroyuki Hikida, Yoichiro Nakatani, Emma Harding and Aris Katzourakis for their feedback. (8/10)

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

Gene gain and duplication were also strongly constrained by genome architecture. In most lineages, expansion was concentrated at both genome termini; in the most expanded lineages, amplification reached even the normally highly conserved central region. (5/10)

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

The poxvirus gene repertoire has evolved through a complex process of gain, duplication and loss. Across diverse lineages we found a consistent tendency toward expansion, marking its evolution as expansion-biased birth-and-death dynamics. (4/10)

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

Poxvirus genome size showed a strong linear relationship with the number of encoded viral genes. In other words, coding capacity increased proportionally with genome size. (3/10)

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

Unlike most viruses, poxviruses carry genomes of several hundred kb with hundreds of genes. Across 59 genomes we integrated gene gain, loss and duplication, horizontal transfer from hosts, and synteny to reconstruct how the repertoire evolved. (2/10)

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

New preprint! We show that poxvirus gene repertoires are shaped by expansion-biased birth-and-death dynamics and genome architectural constraints. Led by Arnon Plianchaisuk (@chainorato) in our lab. Please share! (1/10) www.biorxiv.org/content/10.6...

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

阪大微研ウイルス情報科学（伊東研）は「AI for Viral Infectious Diseases」を掲げ、ウイルス進化研究、ワクチン最適化に向けたウイルスタンパク質モデリング、次のパンデミックを起こし得るウイルスを効率的に探索するAI技術の開発に取り組んでいます（9/10） sites.google.com/view/virus-i...

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

解析はすべてArnon Plianchaisuk先生が実施しました。本研究は前職の東大医科研システムウイルス学分野（佐藤佳研究室）で開始したものです。Spyros Lytras先生、疋田弘之先生、中谷洋一郎先生、Emma F. Harding先生、Aris Katzourakis先生から貴重なご助言をいただきました（8/10）

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

また、遺伝子の獲得や重複はゲノム構造に強く制約されていました。多くの系統ではレパトアの拡大がゲノム両末端に集中する一方、特に大きく拡大した系統では、通常は高度に保存される中央領域にまで遺伝子増幅が及んでいました（5/10）

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

poxvirusの遺伝子レパトアは、獲得・重複・喪失からなる複雑な過程を経て進化してきました。さらに、様々な系統で一貫して拡大する傾向がみられ、その進化は「拡大に偏ったbirth-and-death dynamics」に特徴づけられます（4/10）

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

poxvirusのゲノムサイズは、コードするウイルス遺伝子数と強い線形関係を示しました。すなわち、ゲノムが大きいほどコード可能な遺伝子数（coding capacity）も比例して増加することが明らかになりました（3/10）

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

大部分のウイルスがゲノムの小ささを特徴とするのとは対照的に、poxvirusは数百kbの巨大なゲノムと数百の遺伝子を持ちます。本研究では59種のゲノムを対象に、遺伝子の獲得・喪失・重複、宿主からの水平伝播、シンテニーを統合的に解析し、遺伝子レパトアの進化ダイナミクスを再構築しました（2/10）

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Jumpei Ito @jampei2.bsky.social · 06/09/2026

【拡散希望】プレプリントを公開しました！poxvirusが「拡大に偏ったbirth-and-death dynamics」と「ゲノム構造に制約された遺伝子増幅」により遺伝子レパトアを増大させてきたことを示しました。当研究室のArnon Plianchaisuk先生@chainoratoが主導した研究です（1/10） www.biorxiv.org/content/10.6...

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

This work was driven by three outstanding young researchers: Luca led ISG Profiler, Hiroaki led ISG-VIP, and Kyoko conducted large-scale virus discovery and characterization together with me. I sincerely thank them for their exceptional efforts (13/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

These chaphamaparvoviruses were frequently detected in the livers of chickens and wild birds, and infected samples showed viral hepatitis-like transcriptomic signatures, suggesting a potential role in avian hepatitis (10/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

Notably, geNomad failed to detect viruses of the recently characterized and highly diverse genus Chaphamaparvovirus, whereas our method identified many, including highly divergent viral species (9/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

Importantly, our approach detected many viral infections missed by the widely used tool geNomad. These were enriched for highly divergent viruses with low sequence similarity to known viruses, highlighting the strength of our strategy for novel virus discovery (8/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

Using this pre-screening strategy, we analyzed ~40k animal RNA-seq data sets released in 2024 and identified ~2,441 infections across diverse species, including 385 infections by novel viruses (7/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

ISG-VIP showed a positive prediction rate of ~8% and a recall of ~0.45. When used as a pre-screening step, it reduces the number of samples subjected to computationally intensive virome analysis to 8%, while still capturing ~45% of viral infections (6/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

In this study, we developed ISG Profiler for rapid ISG quantification from RNA-seq data and ISG-VIP for infection prediction. The framework applies to diverse avian and mammalian species, including those without reference genomes, and processes each sample in ~4 minutes (5/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

Upon viral infection, interferon-stimulated genes (ISGs) are induced as part of the innate immune response. This response is broadly conserved across vertebrates and observed for diverse viruses, making ISG expression a robust indicator of infection (4/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

Many human infectious diseases arise through zoonotic transmission of animal viruses. To prepare for future outbreaks, it is essential to comprehensively analyze large-scale RNA-seq data from wildlife and livestock to identify previously unknown pathogenic viruses (2/n).

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Jumpei Ito @jampei2.bsky.social · 18/03/2026

[Please RT] Our new preprint is out! By rapidly quantifying interferon-stimulated genes (ISGs) expression across 220k RNA-seq data sets from diverse animals, we comprehensively identified “hidden viral infections” in wildlife and livestock (1/n). www.biorxiv.org/content/10.6...

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