Quantitative genetics, version 3.0: where have we gone since 1987 and where are we headed?

Area of Science:

• Quantitative genetics and genomics
• Statistical genetics
• Population genetics

Background:

• Over the past 20 years, quantitative genetics has seen major advancements driven by genomics, computation, and statistics.
• Key developments include the use of molecular markers for quantitative trait loci (QTL) mapping, association studies, and marker-assisted selection.

Observation:

• Phenotyping has emerged as the primary bottleneck in molecular quantitative genetics, surpassing genotyping.
• Advances in statistical methods, particularly Markov Chain Monte Carlo (MCMC) and mixed models, have been crucial for analyzing large marker datasets.
• The integration of population and quantitative genetics, utilizing coalescence theory, has enhanced association mapping and demographic history inference.

Findings:

• The field is moving towards analyzing higher-dimensional and more complex traits, including those indexed over multiple variables, graphs, and dynamical networks.
• Interfacing quantitative genetics with physiological and developmental models is a critical future direction for understanding gene-phenotype relationships and predicting environmental impacts.
• Addressing the dimensional constraints of complex traits and avoiding errors from treating them as univariate is essential for future research.

Implications:

• Future research will likely involve developing methods for high-dimensional trait analysis and integrating genetic data with mechanistic models.
• The field requires a continued focus on robust statistical and computational tools to handle increasingly complex biological data.
• Ensuring the integration of breeding expertise with molecular biology is vital for the practical application of genetic advancements in agriculture and animal science.