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Deciphering the functional effects of noncoding genetic variants stands as a fundamental challenge in human genetics. Traditional approaches, such as Genome-Wide Association Studies (GWAS), Transcriptome-Wide Association Studies (TWAS), and Quantitative Trait Loci (QTL) studies, are constrained by obscured the underlying molecular-level mechanisms, making it challenging to unravel the genetic basis of complex traits. The advent of Next-Generation Sequencing (NGS) technologies has enabled context-specific genome-wide measurements, encompassing gene expression, chromatin accessibility, epigenetic marks, and transcription factor binding sites, to be obtained across diverse cell types and tissues, paving the way for decoding genetic variation effects directly from DNA sequences only. Thede novopredictions of functional effects are pivotal for enhancing our comprehension of transcriptional regulation and its disruptions caused by the plethora of noncoding genetic variants linked to human diseases and traits. This review provides a systematic overview of the state-of-the-art models and algorithms for genetic variant effect predictions, including traditional sequence-based models, Deep Learning models, and the cutting-edge Foundation Models. It delves into the ongoing challenges and prospective directions, presenting an in-depth perspective on contemporary developments in this domain. 

Abstract In women, excess androgen causes polycystic ovary syndrome (PCOS), a common fertility disorder with comorbid metabolic dysfunctions including diabetes, obesity, and nonalcoholic fatty liver disease. Using a PCOS mouse model, this study shows that chronic high androgen levels cause hepatic steatosis while hepatocyte-specific androgen receptor (AR)-knockout rescues this phenotype. Moreover, through RNA-sequencing and metabolomic studies, we have identified key metabolic genes and pathways affected by hyperandrogenism. Our studies reveal that a large number of metabolic genes are directly regulated by androgens through AR binding to androgen response element sequences on the promoter region of these genes. Interestingly, a number of circadian genes are also differentially regulated by androgens. In vivo and in vitro studies using a circadian reporter [Period2::Luciferase (Per2::LUC)] mouse model demonstrate that androgens can directly disrupt the hepatic timing system, which is a key regulator of liver metabolism. Consequently, studies show that androgens decrease H3K27me3, a gene silencing mark on the promoter of core clock genes, by inhibiting the expression of histone methyltransferase, Ezh2, while inducing the expression of the histone demethylase, JMJD3, which is responsible for adding and removing the H3K27me3 mark, respectively. Finally, we report that under hyperandrogenic conditions, some of the same circadian/metabolic genes that are upregulated in the mouse liver are also elevated in nonhuman primate livers. In summary, these studies not only provide an overall understanding of how hyperandrogenism associated with PCOS affects liver gene expression and metabolism but also offer insight into the underlying mechanisms leading to hepatic steatosis in PCOS.