Functional Genomics Overview

Principles

Definition

Functional genomics is an academic field that investigates the function of genes, their regulatory elements, and gene products, and their interactions, often employing high-throughput experimental and computational methods to understand how the genome contributes to biological processes and phenotypes.

Ontological type

Core Methods

Key Applications

Data Integration

Key developments

Key Figures

High-Throughput Profiling era

Patrick O. Brown [1] was associated with Harvard University [3] and University of California, San Francisco [4] during this era. Brown [1] played a pivotal role in advancing functional genomics through comprehensive identification of cell cycle–regulated genes of Saccharomyces cerevisiae by microarray hybridization [6] and through the use of a cDNA microarray to analyze gene expression patterns in human cancer [7], which established genome-wide expression profiling as a quantitative readout and enabled cross-tissue and disease-state comparisons. David Botstein [2] held appointments at Massachusetts Institute of Technology [5] and University of California, San Francisco [4] during this era. Botstein [2] contributed to this era by leading large-scale transcriptional profiling, exemplified by the yeast cell-cycle gene study using microarrays [6], which provided scalable transcriptional readouts and seeded systems-level interpretations across tissues and diseases.

Pathway-Centric Transcriptomics era

Eric S. Lander [1] is a central figure in this Pathway-Centric Transcriptomics era, with affiliations at Harvard University [3] and the Massachusetts Institute of Technology [4] shaping the field. His key contributions include the Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles [5], which introduced a pathway-focused method that enabled robust interpretation of genome-wide data and established a foundation for pathway-level hypotheses in the era. Todd R. Golub [2] is likewise embedded in this era through ties to Harvard University [3] and the Massachusetts Institute of Technology [4], reflecting the era's emphasis on integrative functional genomics. His contribution centers on the Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs [6], which extends pathway-aware interpretation to transcript architecture and isoform-level analyses, aligning with the era's trajectory.

Single-Cell Multi-Omics era

Gordon K. Smyth [1] is associated with The University of Melbourne [3] and the University of Zurich [4] during this era, reflecting cross-institutional leadership in the Single-Cell Multi-Omics period. His key contribution, exemplified by limma for differential expression analyses of RNA-sequencing and microarray studies [5], provided a robust, scalable framework for cross-platform regulatory inference that underpins cellular-resolution analyses in single-cell multi-omics. Charity W. Law [2] is associated with The University of Melbourne [3] and the University of Zurich [4] in this era. Her co-authorship of the limma paper [5] delivered foundational differential expression tools that enable robust interpretation of regulatory programs at single-cell resolution across tissues, aligning with the era's emphasis on integrative multi-omics to map pathways and cell types.