More than 10 years have passed since the first free-living organism genome was sequenced. Since then, the pace of the genome sequencing projects has been getting faster and faster, and the number of the sequenced genomes is soon reaching the 1,000 mark. This fact would mean that, by taking advantage of the abundant genomic data from the wide range of organisms, now we can reconstruct the evolutionary history of the genomes and investigate how the extant species' genomes have been organized through evolution until today.

In this thesis, first, I present a novel, effective and efficient method for estimating the whole gene sets of the ancient species by utilizing abundant genomic data from hundreds of species.

To reconstruct plausible evolutionary history, rates of gene gain/loss should be estimated by considering the high level of heterogeneity: for example, genome duplication and parasitization, respectively, result in high rates of gene gain and loss. However, gene-content evolution reconstruction methods that consider this heterogeneity and that are both effective in estimating the rates of gene gain and loss and sufficiently efficient to analyze abundant genomic data had not been developed. The present method comprises analytically integrable modeling of gene-content evolution, analytical formulation of expectation-maximization, and efficient calculation of marginal likelihood using an inside-outside-like algorithm. Simulation tests on the scale of hundreds of genomes showed that both the gene gain/loss rates and evolutionary history were effectively estimated within a few days of computational time. Subsequently,this algorithm was applied to an actual data set of nearly 200 genomes to reconstruct the heterogeneous gene-content evolution across the three domains of life. The reconstructed history, which contained several features consistent with biological observations, showed that the trends of gene-content evolution were not only drastically different between prokaryotes and eukaryotes, but were highly variable within each form of life. The results suggest that heterogeneity should be considered in studies of the evolution of gene content, genomes, and biological systems.

Second, I show the results of the application of the present method to the evolution of metabolic pathways of prokaryotes.

The evolutionary history of biological pathways is of general interest especially in this post-genomic era,because it may provide clues for understanding how complex systems encoded on genomes have been organized. To explain how pathways can evolve de novo, some noteworthy models have been proposed until today. However, direct reconstruction of pathway evolutionary history both on a genomic scale and at the depth of the tree of life has suffered from artificial effects in estimating the gene content of ancestral species. Thus I applied the present algorithm that effectively reconstructs gene-content evolution without these artificial effects to this problem, to provide a definitive version of the pathway evolutionary history. The carefully reconstructed history, which was based on the metabolic pathways of 160 prokaryotic species, confirmed that pathways have grown actively and not just through the random acquisition of individual genes. The pathway acquisition took place in short time, probably eliminating the difficulty in holding function less genes during the course of the pathway evolution. This rapid evolution was due to massive horizontal gene transfers as gene groups, a part of which was probably operon transfers, which would convey existing pathways but not be able to generate novel pathways. To this end, I analyzed how these pathways originally appeared in the ancient era, and found that the ancient acquisition of pathways occurred significantly contemporaneously across distant phylogenetic clades. As a possible model that explains this observation, I propose that novel pathway evolution may be facilitated by bidirectional horizontal gene transfers in prokaryotic communities, which model would complement the existing pathway-evolution models.

ゲノムの解読は哺乳類そして脊椎動物の場合には依然として難しく時間もかかるが、原核生物などゲノムサイズが小規模の場合は容易になってきている。現在では数百生物種のゲノム配列情報が利用可能である。この資源を活用すれば祖先生物種の遺伝子セットを精密に推定することが期待される。ただし推定は単純ではない。なぜなら、進化は一定した変異率により単調に進行するのではなく、ゲノム重複や遺伝子水平伝搬など急激な非単調な変化が進化のドライビングフォースとなることが知られているからである。したがって非単調的進化をうまく取り入れた理論を構成する必要がある。

岩崎は、系統樹上の各枝における遺伝子の獲得/欠失速度の急激な変化を表現できるモデルを作成し、最尤法および期待値最大化法により推定するアプローチを提案している。例えば、ゲノム重複や寄生生活への移行により遺伝子数の急激な増加や減少がしばしば起こることに代表されるようなゲノムの非単調な進化過程をモデル化したものである。本手法を実際のゲノムデータに適用しその進化解析を行うことで、ゲノムは時に急激な変化を経つつ進化してきたことを確認するとともに、生物種横断的にゲノムの進化解析を行う場合に本手法のような工夫を行うことの必要性を示唆している。この方法で推定した遺伝子セットは急速な変化をうまく描出しており、他の独立な推定とも一致する場合が多く、世界的にも評価されている。

最近は一歩進んで、遺伝子セット進化の理論を応用して、代謝パスウェイの進化過程の再構築にも岩崎は取り組んでいる。160種の原核生物ゲノムデータに適用し、代謝パスウェイの進化過程の再構築・解析を行った。その結果、パスウェイは個々の遺伝子の獲得以上に活発に進化してきたこと、この活発な進化は遺伝子グループとしての遺伝子水平伝播によることを確認している。さらに、その中でも初期のパスウェイ獲得は異なる系統群間で同時代的に起こったことを明らかにし、パスウェイの獲得が原核生物コミュニティ内での遺伝子水平伝播によって促進されるというモデルを提案している。

これら一連の研究は、現在利用可能なゲノム情報を上手に利用して、あたらしい進化像を提案している点で評価できる。論文は平易な英語でわかりやすく書かれている。

なお、本論文は、指導教員である高木利久との共同研究であるが、論文提出者が主体となって分析及び検証を行ったもので、論文提出者の寄与が十分であると判断する。

したがって、博士(科学)の学位を授与できると認める。