This study investigates the genetic architecture of white-matter structural connectivity using genome-wide association studies (GWAS) of 206 tractography-derived measures from 26,333 UK Biobank participants. The research identifies 30 genome-wide significant variants, implicating genes involved in myelination, neurite elongation and guidance, neural cell proliferation and differentiation, neuronal migration, cytoskeletal organization, and brain metal transport. These variants show four broad spatial patterns of association with structural connectivity, including strong associations with corticothalamic and interhemispheric connectivity. Structural connectivity measures are highly polygenic, with a median of 9.1% of common variants estimated to have non-zero effects on each measure, and exhibit signatures of negative selection. Structural connectivity measures have significant genetic correlations with various neuropsychiatric and cognitive traits, indicating that connectivity-altering variants influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in oligodendrocytes, microglia, inhibitory neurons, astrocytes, and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. The study highlights pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, supporting the relevance of this genetic control to healthy brain function. The findings suggest that structural connectivity is highly polygenic and under negative selection, with a significant genetic correlation with various neuropsychiatric and cognitive traits. The study also notes limitations, including the use of tractography to infer structural connectivity, which may not directly measure connectivity, and the potential for age-related changes in structural connectivity to affect cognitive measures. The results emphasize the importance of further research to uncover the genetic basis of structural connectivity and its implications for brain health and disease.This study investigates the genetic architecture of white-matter structural connectivity using genome-wide association studies (GWAS) of 206 tractography-derived measures from 26,333 UK Biobank participants. The research identifies 30 genome-wide significant variants, implicating genes involved in myelination, neurite elongation and guidance, neural cell proliferation and differentiation, neuronal migration, cytoskeletal organization, and brain metal transport. These variants show four broad spatial patterns of association with structural connectivity, including strong associations with corticothalamic and interhemispheric connectivity. Structural connectivity measures are highly polygenic, with a median of 9.1% of common variants estimated to have non-zero effects on each measure, and exhibit signatures of negative selection. Structural connectivity measures have significant genetic correlations with various neuropsychiatric and cognitive traits, indicating that connectivity-altering variants influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in oligodendrocytes, microglia, inhibitory neurons, astrocytes, and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. The study highlights pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, supporting the relevance of this genetic control to healthy brain function. The findings suggest that structural connectivity is highly polygenic and under negative selection, with a significant genetic correlation with various neuropsychiatric and cognitive traits. The study also notes limitations, including the use of tractography to infer structural connectivity, which may not directly measure connectivity, and the potential for age-related changes in structural connectivity to affect cognitive measures. The results emphasize the importance of further research to uncover the genetic basis of structural connectivity and its implications for brain health and disease.