Structural variations (SVs) are important contributors to the genetics of numerous human diseases. However, their role in Alzheimer’s disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. Here, we analyzed whole-genome sequencing data from the Alzheimer’s Disease Sequencing Project (ADSP, N=16,905 subjects) and identified 400,234 (168,223 high-quality) SVs. We found a significant burden of deletions and duplications in AD cases (OR=1.05, P =0.03), particularly for singletons (OR=1.12, P =0.0002) and homozygous events (OR=1.10, P <0.0004). On AD genes, the ultra-rare SVs, including protein-altering SVs in ABCA7 , APP , PLCG2 , and SORL1 , were associated with AD (SKAT-O P =0.004). Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, e.g., a deletion (chr2:105731359-105736864) in complete LD (R ² =0.99) with rs143080277 (chr2:105749599) in NCK2 . We also identified 16 SVs associated with AD and 13 SVs associated with AD-related pathological/cognitive endophenotypes. Our findings demonstrate the broad impact of SVs on AD genetics. Search Terms: Alzheimer’s disease, Structural variation, Copy number variation

Background: The 17q21.31 region with various structural forms characterized by the H1/H2 haplotypes and three large copy number variations (CNVs) represents the strongest risk locus in progressive supranuclear palsy (PSP).Objective: To investigate the association between CNVs and structural forms on 17q.21.31 with the risk of PSP.Methods: Utilizing whole genome sequencing data from 1684 PSP cases and 2392 controls, the three large CNVs (α, β, and γ) and structural forms within 17q21.31 were identified and analyzed for their association with PSP.Results: We found that the copy number of γ was associated with increased PSP risk (odds ratio [OR] = 1.10, P = 0.0018). From H1β1γ1 (OR = 1.21) and H1β2γ1 (OR = 1.24) to H1β1γ4 (OR = 1.57), structural forms of H1 with additional copies of γ displayed a higher risk for PSP. The frequency of the risk sub‐haplotype H1c rises from 1% in individuals with two γ copies to 88% in those with eight copies. Additionally, γ duplication up‐regulates expression of ARL17B, LRRC37A/LRRC37A2, and NSFP1, while down‐regulating KANSL1. Single‐nucleus RNA‐seq of the dorsolateral prefrontal cortex analysis reveals γ duplication primarily up‐regulates LRRC37A/LRRC37A2 in neuronal cells.Conclusions: The copy number of γ is associated with the risk of PSP after adjusting for H1/H2, indicating that the complex structure at 17q21.31 is an important consideration when evaluating the genetic risk of PSP. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The angiosperm seed represents a critical evolutionary breakthrough that has been shown to propel the reproductive success and radiation of flowering plants. Seeds promote the rapid diversification of angiosperms by establishing postzygotic reproductive barriers, such as hybrid seed inviability. While prezygotic barriers to reproduction tend to be transient, postzygotic barriers are often permanent and therefore can play a pivotal role in facilitating speciation. This property of the angiosperm seed is exemplified in the Mimulus genus. In order to further the understanding of the gene regulatory mechanisms important in the Mimulus seed, we performed gene regulatory network (GRN) inference analysis by using time-series RNA-seq data from developing hybrid seeds from a viable cross between Mimulus guttatus and Mimulus pardalis. GRN inference has the capacity to identify active regulatory mechanisms in a sample and highlight genes of potential biological importance. In our case, GRN inference also provided the opportunity to uncover active regulatory relationships and generate a reference set of putative gene regulations. We deployed two GRN inference algorithms—RTP-STAR and KBoost—on three different subsets of our transcriptomic dataset. While the two algorithms yielded GRNs with different regulations and topologies when working with the same data subset, there was still significant overlap in the specific gene regulations they inferred, and they both identified potential novel regulatory mechanisms that warrant further investigation.

Copy number variants (CNVs) are DNA gains or losses involving >50 base pairs. Assessing CNV effects on disease risk requires consideration of several factors. First, there are no natural definitions for CNV loci. Second, CNV effects can depend on dosage and length. Third, CNV effects can be more accurately estimated when all CNV events in a genomic region are analyzed together to assess their joint effects. We propose a new framework for association analysis that directly models an individual’s entire CNV profile within a genomic region. This framework represents an individual’s CNVs using a CNV profile curve to capture variations in CNV length and dosage and to bypass the need to predefine CNV loci. CNV effects are estimated at each genome position, making the results comparable across different studies. To jointly estimate the effects of all CNVs, we use a Lasso penalty to select CNVs associated with the trait and integrate a weighted L2-fusion penalty to encourage similar effects of adjacent CNVs when supported by the data. Simulations show that the proposed model can more effectively identify causal CNVs while maintaining false positive rates comparable to baseline methods and yield more precise effect-size estimates across different settings. When applied to CNV derived from whole genome sequencing data of the Alzheimer’s Disease Sequencing Project, the proposed methods identify additional CNVs associated with Alzheimer’s Disease (AD). These identified CNVs overlap with several known AD-risk genes and are significantly enriched by biological processes related to neuron structures and functions crucial in AD development.