GENERATIVE GENOMICS

Why?

Comparative Genomics has traditionally aimed to discover homologous genes and proteins from the perspective of their evolutionary relationships through alignment-based procedures. However, orphan genes have revealed the potential limitation of analyzing their origin determination. Nevertheless, the origins of orphan genes have been explored from an evolutionary perspective under the assumption that they arose either through mutational transformations of ancestral genes or as de novo genes derived from non-coding sequences. But this approach alone cannot identify the phenotypes of species-specific genes and founder genes that are the basis of descendant gene lineages.

How?

Thus, we need to extend the search for the origins of orphan genes beyond simple homology searches. We define Generative Genes considering the emergence conditions of orphan genes and their context. The functions of generative genes can be classified into two categories: Species- & Taxon-Specific Generative Genes and Founding Generative Genes that were inherited by diverse descendants [1].
To validate the functions of species-specific (and taxon-specific) Generative Genes, we need to map these genes to unique species-specific (and uniquely common taxon-specific) phenotypic traits. The unique traits may be identified by contrasting very closely related species. The one-to-many and many-to-one relationships between generative genes and phenotypic traits can be integrated into the Generative Genomic AI model. This model will provide a new method for annotating genes.
To validate the functions of founding generative genes, we need to examine the nature of orphan genes at their stage of emergence. The homology should be tested in comparison with the genes available at that time. As a founder gene, the consequence of inheritance should be identified as a network of well-conserved genes.

[1] D. Tautz and T. Domazet-Loso, “The Evolutionary Origin of Orphan Genes,” Nature Reviews Genetics, Vol. 12, pp. 692–702 (2011)

ILLUSTRATIVE RESEARCH TOPICS

To advance the objectives of Generative Genomics and examine its implications for health science, we propose to investigate the following research issues, as illustrated (but not limited to) by the five topics below. We believe these topics present valuable opportunities for researchers studying orphan genes and de novo genes.

1) ORIGINS OF ORPHAN GENES AND GENERATIVE GENES

• Standard procedures of identifying orphan genes: Sensitivity of e-values and interspecies comparison
• Conditions for the identification of founder orphan genes
• Necessary and sufficient conditions for validating the emergence of de novo genes and transformed genes
• Identification of orphan genes and generative genes across various species

2) GENERATIVE GENOMICS

• Conceptual distinction of Generative Genomics
• Development of automated platforms for identification of generative genes, built upon BLAST, DIAMOND and regulatory network tools
• Design of annotation methods for generative genes by mapping them to multi-layered species-specific and taxon-specific phenotypic traits
• Identification of founder genes and the gene networks of their descendants

3) GENERATIVE TREE OF LIFE WITH GENERATIVE GENES

• Association of generative genes with unique phenotypic traits in the phylogenetic Tree of Life, leading to the construction of the Generative Tree of Life
• Distinction between the ambiguous concepts of reproductive ancestors and classification taxa
• Definition of reproductive species as the unit of the generative tree of life
• Identification of the founding generative genes and the network structure of inherited genes in the Generative Tree of Life

4) AI MODELS FOR GENERATIVE GENOMICS

• Build an AI model that maps one-to-many and many-to-one relationships between generative genes and species- & taxon-specific phenotypic traits
• Integration of the generative genes and the founder genes network with existing annotation databases
• Development of Generative AI models for Generative Genomics research
• Integration of the Generative Genomic AI models with multi-omics databases

5) GENERATIVE GENOMICS IN DISEASE PATHWAY ANALYSIS

• Generative Genomic AI model for the molecular pathway analysis of diseases
• Discovery of diseases specific generative genes in humans and other species
• Treatment methods for diseases that originate from generative genes
• Pathological studies associated with generative genes in diverse organisms

Program Committee

• Chair: Jae Kyu Lee (Chair Professor, Xi’an Jiaotong University, China; Professor Emeritus, Korea Advanced Institute of Science and Technology, Korea)
• Co-chair: Diethard Tautz (Professor Dr., Director of Max Planck Institute for Evolutionary Biology; Emeritus Scientific Member, Germany)
• Co-chair: Ming Chen (Professor and Director of Bioinformatics Lab, College of Life Science, Zhejiang University, China)
• Thomas C. G. Bosch (Professor Dr. Dr.h.c, Senior Research Professor, Zoological Institute Kiel University)
• Dae Kyun Chung (Professor and Dean, College of Life Sciences, Kyung Hee University)
• Kyong-Tai Kim (Chair Professor and Director of Generative Genomics Lab, Handong Global University; Professor Emeritus, POSTECH)
• Wooju Kim (Professor and Director of AI Technology Research Center, Yonsei University)
• Ah-Ram Kim (Professor of Life Science & Applied AI, Handong Global University)
• Taesung Park (Professor and Director of Bioinformatics and Biostatistics Lab, Seoul National University)
• Yungang Xu (Professor of Bioinformatics and Computational Biology, Xi’an Jiaotong University)
• Chuck Yoo (Professor of Computer Science, Korea University; Former Vice President of Research, Korea University)