On the nature and measurement of variational bias: a developmental perspective

Natural selection cannot work with imaginary phenotypes, only those realized by developmental systems. The observed diversity of life on Earth occupies only a subset of conceivable forms in the absence of selection. This is because of the non-linear and discrete nature of genotype-to-phenotype maps as an outcome of the developmental system. Despite that, it is widely accepted in population and quantitative genetic modelings that the phenotypic production from random mutations is isotropic and uniform. Conventional methods linking genetic variants and phenotypic variation often assume that the origin of phenotypic variation is purely due to genetic and environmental factors. Here, in this thesis, I adopt a developmental causation view which proposes that patterns of variation may emerge as an inherent consequence guided by physico-chemical principles and that part of the nature can not be fully reducible to genetic factors. The distribution of phenotypic variants that arise from genetic and environmental variation is influenced by the developmental processes that transform the embryonic phenotype into the adult form. This developmental process is subject to constraints that stem from the structure, character, composition, or dynamics of development. We term such a constraint as developmental bias. Despite the prevalence of developmental bias, detecting and testing its role remains a challenge. To address this gap, in the thesis, I propose frameworks and showcase examples aimed at identifying developmental bias and testing its implications in shaping phenotypic evolution. Specifically, I answer three questions: (1) How does the central conponent of nonlinear genotype-to-phentype map --- transcriptional regulation --- bias the analyses of gene-gene interactions? (2) How to disentangle the contribution of developmental bias in trait-trait interdependencies? (3) How expression variability affects gene retention and gene expression evolution following gene and genome duplication.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Cai, Haoran

Advisor dc:contributor.advisor

• Des Marais, David

Statement dc:rights

• Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-nd/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/158887

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/158887