Mutations in phospholipase C eta-1 (PLCH1) are associated with holoprosencephaly

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.

Concepts in Multifactorial Etiology of Developmental Disorders: Gene-Gene and Gene-Environment Interactions in Holoprosencephaly

Many common developmental disorders are thought to arise from a complex set of genetic and environmental risk factors. These factors interact with each other to affect the strength and duration of key developmental signaling pathways, thereby increasing the possibility that they fail to achieve the thresholds required for normal embryonic patterning. One such disorder, holoprosencephaly (HPE), serves as a useful model system in understanding various forms of multifactorial etiology. Genomic analysis of HPE cases, epidemiology, and mechanistic studies of animal models have illuminated multiple potential ways that risk factors interact to produce adverse developmental outcomes. Among these are: 1) interactions between driver and modifier genes; 2) oligogenic inheritance, wherein each parent provides predisposing variants in one or multiple distinct loci; 3) interactions between genetic susceptibilities and environmental risk factors that may be insufficient on their own; and 4) interactions of multiple genetic variants with multiple non-genetic risk factors. These studies combine to provide concepts that illuminate HPE and are also applicable to additional disorders with complex etiology, including neural tube defects, congenital heart defects, and oro-facial clefting.