Evin Padhi

All Publications

• Decoding common and rare noncoding variant effects across cellular and developmental contexts. Nature genetics Marderstein, A. R., Kundu, S., Padhi, E. M., Deshpande, S., Wang, A., Robb, E., Sun, Y., Yun, C. M., Pomales-Matos, D., Xie, Y., Chang, S. H., Chin, I. M., Shah, A. J., Gardell, Z. A., Corces, M. R., Nachun, D., Jessa, S., Kundaje, A., Montgomery, S. B. 2026

  Abstract

  Interpreting how noncoding variants act in specific cell types across human development is a major challenge. Here we generated 3 billion predictions from deep learning sequence models of chromatin accessibility across diverse fetal and adult cellular contexts. These prioritized functional variants and revealed a dichotomy: common variants are more cell-type-specific, whereas ultra-rare variants had larger and broader effects across cell types, with the strongest evidence of purifying selection in fetal neurons. Leveraging these insights, we developed FLARE (Functional Lasso Analysis of Regulatory Evolution), which integrates evolutionary constraint to prioritize noncoding variants with extreme regulatory effects. FLARE provided a general framework for studying regulatory variation, from de novo mutations in childhood disorders to rare variants underlying outlier adult brain expression and common variants enriched for schizophrenia heritability. Together, these results demonstrate how integrating single-cell chromatin accessibility, population genetics and deep learning can identify regulatory variants that influence human development and disease.

  View details for DOI 10.1038/s41588-026-02619-6

  View details for PubMedID 42298188

  View details for PubMedCentralID 7237642

• Genomics-Informed Approach Identifies Which Cell Types Regulate the Metabolome. Bioinformatics (Oxford, England) Krupkin, H., Padhi, E. M., Nachun, D., Kain, J., Long, J. Z., Montgomery, S. B. 2026

  Abstract

  Metabolism occurs in a cell type-specific manner, but which cells regulate metabolite levels remains unclear. Here, we integrate some of the largest metabolite quantitative trait loci datasets, TOPMed and UK Biobank, with one of the most extensive single-cell RNA sequencing resources, Tabula Sapiens. This integration allows us to identify cell types that regulate metabolites body-wide. We find hepatocytes are the primary regulatory cell type for most metabolites, associating with 385/410 (94%) metabolites for whom an association is found. Additionally, our multi-gene approach reveals more metabolite associations with beta cells compared to those identified using a single-gene approach. For example, we identify novel metabolite-cell type associations, such as the association between phenylpropanoic acid and beta cells, this metabolite that was previously thought to be regulated by the microbiome.

  View details for DOI 10.1093/bioinformatics/btag330

  View details for PubMedID 42213079

• GREGoR: accelerating genomics for rare diseases. Nature Dawood, M., Heavner, B., Wheeler, M. M., Ungar, R. A., LoTempio, J., Wiel, L., Berger, S., Bernstein, J. A., Chong, J. X., Délot, E. C., Eichler, E. E., Lupski, J. R., Shojaie, A., Talkowski, M. E., Wagner, A. H., Wei, C. L., Wellington, C., Wheeler, M. T., Carvalho, C. M., Gibbs, R. A., Gifford, C. A., May, S., Miller, D. E., Rehm, H. L., Samocha, K. E., Sedlazeck, F. J., Vilain, E., O'Donnell-Luria, A., Posey, J. E., Chadwick, L. H., Bamshad, M. J., Montgomery, S. B. 2025; 647 (8089): 331-342

  Abstract

  Rare diseases are collectively common, affecting approximately 1 in 20 individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in next-generation sequencing, development of new computational and functional genomics approaches to prioritize genes and variants and increased global sharing of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Furthermore, all data generated, currently representing over 7,500 individuals from over 3,000 families, are rapidly made available to researchers worldwide through the Analysis, Visualization and Informatics Lab-space (AnVIL) to catalyse global efforts to develop approaches for genetic diagnoses in rare diseases. Most of these families have undergone previous clinical genetic testing but remained unsolved, with most being exome-negative. Here we describe the collaborative research framework, datasets and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.

  View details for DOI 10.1038/s41586-025-09613-8

  View details for PubMedID 41224980

  View details for PubMedCentralID 9119004

• Transcriptome-wide outlier approach identifies individuals with minor spliceopathies. American journal of human genetics Arriaga, T. M., Mendez, R., Ungar, R. A., Bonner, D. E., Matalon, D. R., Lemire, G., Goddard, P. C., Padhi, E. M., Miller, A. M., Nguyen, J. V., Ma, J., Smith, K. S., Scott, S. A., Liao, L., Ng, Z., Marwaha, S., Bademci, G., Bivona, S. A., Tekin, M., Bernstein, J. A., Montgomery, S. B., O'Donnell-Luria, A., Wheeler, M. T., Ganesh, V. S. 2025

  Abstract

  RNA sequencing has improved the diagnostic yield of individuals with rare diseases. Current analyses predominantly focus on identifying outliers in single genes that can be attributed to cis-acting variants within the gene locus. This approach overlooks causal variants with trans-acting effects on splicing transcriptome wide, such as variants impacting spliceosome function. We present a transcriptomics-first method to diagnose individuals with rare diseases by examining transcriptome-wide patterns of splicing outliers. Using splicing outlier detection methods (FRASER and FRASER2), we characterized splicing outliers from whole blood for 385 individuals from the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) and Undiagnosed Diseases Network (UDN) consortia. We examined all individuals for excess intron retention outliers in minor intron-containing genes (MIGs). Minor introns, which account for 0.5% of all introns in the human genome, are removed by small nuclear RNAs (snRNAs) in the minor spliceosome. This approach identified five individuals with excess intron retention outliers in MIGs, all of whom were found to harbor rare, bi-allelic variants in minor spliceosome snRNAs. Four individuals had rare, compound heterozygous variants in RNU4ATAC, which aided the reclassification of four variants. Additionally, one individual had rare, highly conserved, compound heterozygous variants in RNU6ATAC that may disrupt the formation of the catalytic spliceosome, suggesting it is a gene associated with Mendelian disease. These results demonstrate that examining RNA-sequencing data for transcriptome-wide signatures can increase the diagnostic yield of individuals with rare diseases, provide variant-to-function interpretation of spliceopathies, and uncover gene-disease associations.

  View details for DOI 10.1016/j.ajhg.2025.08.018

  View details for PubMedID 40975062

• Interactions Between Dietary Metabolites and Regulatory Risk Variants for Human Colon Cancer. bioRxiv : the preprint server for biology Fabo, T. N., Meyers, R. M., Padhi, E., Kellman, L. N., Zhao, Y., Kundu, S., Reynolds, D. L., Chen, Z., Yang, X., Ko, L., Elfaki, I., Montgomery, S. B., Khavari, P. A. 2025

  Abstract

  Interactions between genetic variants and environmental factors influence malignancy risk, including for colorectal cancer (CRC). Prevalent CRC susceptibility loci reside predominantly in noncoding regulatory DNA where they may interact with dietary influences to dysregulate expression of specific genes predisposing to neoplasia. The impacts of CRC protective and risk dietary metabolites, butyrate and deoxycholic acid, were thus studied on the transcription-directing activity of 3703 regulatory CRC-associated variants via massively parallel reporter assays (MPRA) in human colonic cells. 1595 variant-dietary metabolite interactions were identified, pointing to dysregulation of MED13L, NKD2, and several modulators of Wnt/β-catenin signaling in potential CRC gene-environment interactions (GxE). Opposing impacts of butyrate and deoxycholic acid were also uncovered, indicating dietary influences may converge on common CRC risk loci and nominating FOSL1 and SP1 as mediators of these opposing responses. Coupling MPRA to relevant environmental factors offers an approach to extend insight into GxE in common human cancers.

  View details for DOI 10.1101/2025.09.05.674475

  View details for PubMedID 40964363

  View details for PubMedCentralID PMC12439979

• The Somatic Mosaicism across Human Tissues Network. Nature Coorens, T. H., Oh, J. W., Choi, Y. A., Lim, N. S., Zhao, B., Voshall, A., Abyzov, A., Antonacci-Fulton, L., Aparicio, S., Ardlie, K. G., Bell, T. J., Bennett, J. T., Bernstein, B. E., Blanchard, T. G., Boyle, A. P., Buenrostro, J. D., Burns, K. H., Chen, F., Chen, R., Choudhury, S., Doddapaneni, H. V., Eichler, E. E., Evrony, G. D., Faith, M. A., Fazzio, T. G., Fulton, R. S., Garber, M., Gehlenborg, N., Germer, S., Getz, G., Gibbs, R. A., Hernandez, R. G., Jin, F., Korbel, J. O., Landau, D. A., Lawson, H. A., Lennon, N. J., Li, H., Li, Y., Loh, P. R., Marth, G., McConnell, M. J., Mills, R. E., Montgomery, S. B., Natarajan, P., Park, P. J., Satija, R., Sedlazeck, F. J., Shao, D. D., Shen, H., Stergachis, A. B., Underhill, H. R., Urban, A. E., VonDran, M. W., Walsh, C. A., Wang, T., Wu, T. P., Zong, C., Lee, E. A., Vaccarino, F. M. 2025; 643 (8070): 47-59

  Abstract

  From fertilization onwards, the cells of the human body acquire variations in their DNA sequence, known as somatic mutations. These postzygotic mutations arise from intrinsic errors in DNA replication and repair, as well as from exposure to mutagens. Somatic mutations have been implicated in some diseases, but a fundamental understanding of the frequency, type and patterns of mutations across healthy human tissues has been limited. This is primarily due to the small proportion of cells harbouring specific somatic variants within an individual, making them more challenging to detect than inherited variants. Here we describe the Somatic Mosaicism across Human Tissues Network, which aims to create a reference catalogue of somatic mutations and their clonal patterns across 19 different tissue sites from 150 non-diseased donors and develop new technologies and computational tools to detect somatic mutations and assess their phenotypic consequences, including clonal expansions. This strategy enables a comprehensive examination of the mutational landscape across the human body, and provides a comparison baseline for somatic mutation in diseases. This will lead to a deep understanding of somatic mutations and clonal expansions across the lifespan, as well as their roles in health, in ageing and, by comparison, in diseases.

  View details for DOI 10.1038/s41586-025-09096-7

  View details for PubMedID 40604182

  View details for PubMedCentralID 9402379

• Predicting expression-altering promoter mutations with deep learning. Science (New York, N.Y.) Jaganathan, K., Ersaro, N., Novakovsky, G., Wang, Y., James, T., Schwartzentruber, J., Fiziev, P., Kassam, I., Cao, F., Hawe, J., Cavanagh, H., Lim, A., Png, G., McRae, J., Banerjee, A., Kumar, A., Ulirsch, J., Zhang, Y., Aguet, F., Wainschtein, P., Sundaram, L., Salcedo, A., Kyriazopoulou Panagiotopoulou, S., Aghamirzaie, D., Padhi, E., Weng, Z., Dong, S., Smedley, D., Caulfield, M., O'Donnell-Luria, A., Rehm, H. L., Sanders, S. J., Kundaje, A., Montgomery, S. B., Ross, M. T., Farh, K. K. 2025: eads7373

  Abstract

  Only a minority of patients with rare genetic diseases are currently diagnosed by exome sequencing, suggesting that additional unrecognized pathogenic variants may reside in non-coding sequence. Here, we describe PromoterAI, a deep neural network that accurately identifies non-coding promoter variants which dysregulate gene expression. We show that promoter variants with predicted expression-altering consequences produce outlier expression at both RNA and protein levels in thousands of individuals, and that these variants experience strong negative selection in human populations. We observe that clinically relevant genes in rare disease patients are enriched for such variants and validate their functional impact through reporter assays. Our estimates suggest that promoter variation accounts for 6% of the genetic burden associated with rare diseases.

  View details for DOI 10.1126/science.ads7373

  View details for PubMedID 40440429

• Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart. bioRxiv : the preprint server for biology Marderstein, A. R., Kundu, S., Padhi, E. M., Deshpande, S., Wang, A., Robb, E., Sun, Y., Yun, C. M., Pomales-Matos, D., Xie, Y., Nachun, D., Jessa, S., Kundaje, A., Montgomery, S. B. 2025

  Abstract

  Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

  View details for DOI 10.1101/2025.02.18.638922

  View details for PubMedID 40027628

  View details for PubMedCentralID PMC11870466

• The human and non-human primate developmental GTEx projects NATURE Coorens, T. H. H., Guillaumet-Adkins, A., Kovner, R., Linn, R. L., Roberts, V. H. J., Sule, A., Van Hoose, P. M., the dGTEx Consortium, T. 2025; 637 (8046): 557-564

  Abstract

  Many human diseases are the result of early developmental defects. As most paediatric diseases and disorders are rare, children are critically underrepresented in research. Functional genomics studies primarily rely on adult tissues and lack critical cell states in specific developmental windows. In parallel, little is known about the conservation of developmental programmes across non-human primate (NHP) species, with implications for human evolution. Here we introduce the developmental Genotype-Tissue Expression (dGTEx) projects, which span humans and NHPs and aim to integrate gene expression, regulation and genetics data across development and species. The dGTEx cohort will consist of 74 tissue sites across 120 human donors from birth to adulthood, and developmentally matched NHP age groups, with additional prenatal and adult animals, with 126 rhesus macaques (Macaca mulatta) and 72 common marmosets (Callithrix jacchus). The data will comprise whole-genome sequencing, extensive bulk, single-cell and spatial gene expression profiles, and chromatin accessibility data across tissues and development. Through community engagement and donor diversity, the human dGTEx study seeks to address disparities in genomic research. Thus, dGTEx will provide a reference human and NHP dataset and tissue bank, enabling research into developmental changes in expression and gene regulation, childhood disorders and the effect of genetic variation on development.

  View details for DOI 10.1038/s41586-024-08244-9

  View details for Web of Science ID 001402006100024

  View details for PubMedID 39815096

  View details for PubMedCentralID PMC12013525

• Transcriptome-wide outlier approach identifies individuals with minor spliceopathies. medRxiv : the preprint server for health sciences Arriaga, M. T., Mendez, R., Ungar, R. A., Bonner, D. E., Matalon, D. R., Lemire, G., Goddard, P. C., Padhi, E. M., Miller, A. M., Nguyen, J. V., Ma, J., Smith, K. S., Scott, S. A., Liao, L., Ng, Z., Marwaha, S., Bademci, G., Bivona, S. A., Tekin, M., Bernstein, J. A., Montgomery, S. B., O'Donnell-Luria, A., Wheeler, M. T., Ganesh, V. S. 2025

  Abstract

  RNA-sequencing has improved the diagnostic yield of individuals with rare diseases. Current analyses predominantly focus on identifying outliers in single genes that can be attributed to cis-acting variants within or near that gene. This approach overlooks causal variants with trans-acting effects on splicing transcriptome-wide, such as variants impacting spliceosome function. We present a transcriptomics-first method to diagnose individuals with rare diseases by examining transcriptome-wide patterns of splicing outliers. Using splicing outlier detection methods - FRASER and FRASER2 - we identified splicing outliers from whole blood for 390 individuals from the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) and Undiagnosed Diseases Network (UDN) consortia. We examined all samples for excess intron retention events in minor intron containing genes. Minor introns, which make up about 0.5% of all introns in the human genome, are removed by small nuclear RNAs (snRNAs) in the minor spliceosome. This approach identified five cases with excess intron retention events in minor intron containing genes, all of which were found to harbor rare, biallelic variants in the minor spliceosome snRNAs. Four had rare, compound heterozygous variants in RNU4ATAC. These results led to the reclassification of four variants. Additionally, one case had rare, highly conserved, compound heterozygous variants in RNU6ATAC that may disrupt the formation of the catalytic spliceosome, suggesting a novel disease-gene candidate. These results demonstrate that examining RNA-sequencing data for known transcriptome-wide signatures can increase the diagnostic yield of individuals with rare diseases, provide variant-to-functional interpretation of spliceopathies, and potentially uncover novel disease genes.

  View details for DOI 10.1101/2025.01.02.24318941

  View details for PubMedID 39802771

  View details for PubMedCentralID PMC11722475

• Single-cell multi-omics map of human fetal blood in Down syndrome. Nature Marderstein, A. R., De Zuani, M., Moeller, R., Bezney, J., Padhi, E. M., Wong, S., Coorens, T. H., Xie, Y., Xue, H., Montgomery, S. B., Cvejic, A. 2024

  Abstract

  Down syndrome predisposes individuals to haematological abnormalities, such as increased number of erythrocytes and leukaemia in a process that is initiated before birth and is not entirely understood1-3. Here, to understand dysregulated haematopoiesis in Down syndrome, we integrated single-cell transcriptomics of over 1.1 million cells with chromatin accessibility and spatial transcriptomics datasets using human fetal liver and bone marrow samples from 3 fetuses with disomy and 15 fetuses with trisomy. We found that differences in gene expression in Down syndrome were dependent on both cell type and environment. Furthermore, we found multiple lines of evidence that haematopoietic stem cells (HSCs) in Down syndrome are 'primed' to differentiate. We subsequently established a Down syndrome-specific map linking non-coding elements to genes in disomic and trisomic HSCs using 10X multiome data. By integrating this map with genetic variants associated with blood cell counts, we discovered that trisomy restructured regulatory interactions to dysregulate enhancer activity and gene expression critical to erythroid lineage differentiation. Furthermore, as mutations in Down syndrome display a signature of oxidative stress4,5, we validated both increased mitochondrial mass and oxidative stress in Down syndrome, and observed that these mutations preferentially fell into regulatory regions of expressed genes in HSCs. Together, our single-cell, multi-omic resource provides a high-resolution molecular map of fetal haematopoiesis in Down syndrome and indicates significant regulatory restructuring giving rise to co-occurring haematological conditions.

  View details for DOI 10.1038/s41586-024-07946-4

  View details for PubMedID 39322663

  View details for PubMedCentralID 2480572

• Deciphering the impact of genomic variation on function. Nature 2024; 633 (8028): 47-57

  Abstract

  Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.

  View details for DOI 10.1038/s41586-024-07510-0

  View details for PubMedID 39232149

  View details for PubMedCentralID 7405896

• Beyond the exome: What's next in diagnostic testing for Mendelian conditions. American journal of human genetics Wojcik, M. H., Reuter, C. M., Marwaha, S., Mahmoud, M., Duyzend, M. H., Barseghyan, H., Yuan, B., Boone, P. M., Groopman, E. E., Délot, E. C., Jain, D., Sanchis-Juan, A., Starita, L. M., Talkowski, M., Montgomery, S. B., Bamshad, M. J., Chong, J. X., Wheeler, M. T., Berger, S. I., O'Donnell-Luria, A., Sedlazeck, F. J., Miller, D. E. 2023; 110 (8): 1229-1248

  Abstract

  Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

  View details for DOI 10.1016/j.ajhg.2023.06.009

  View details for PubMedID 37541186