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Method: Genetics-driven risk predictions leveraging the Mendelian randomization framework
- Daniel Sens,
- Liubov Shilova,
- Ludwig Gräf,
- Maria Grebenshchikova,
- Bjoern M. Eskofier,
- and Francesco Paolo Casale
Genome Res. September 2024 34: 1276-1285; Published in Advance September 27, 2024, doi:10.1101/gr.279252.124
...health outcomes are limited. To overcome this challenge, we introduce a novel framework, Predictive Risk modeling using Mendelian Randomization (PRiMeR), which utilizes genetic effects as supervisory signals to learn disease risk predictors without relying on longitudinal data. To do so, PRiMeR leverages...
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Method: A spectral component approach leveraging identity-by-descent graphs to address recent population structure in genomic analysis
- Ruhollah Shemirani,
- Gillian M. Belbin,
- Sinead Cullina,
- Christa Caggiano,
- Christopher R. Gignoux,
- Noah Zaitlen,
- and Eimear E. Kenny
Genome Res. March 2026 36: 534-546; Published in Advance December 23, 2025, doi:10.1101/gr.280659.125
...illustrate SPCs’ robustness to ascertainment bias (Supplemental Fig. 12).DiscussionWe introduced SPCs, a graph-based approach that leverages IBD graphs to capture localized, nonlinear fine-scale population structure and transforms them into a continuous representation for statistical genetics analyses...
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Method: Robust and efficient annotation of cell states through gene signature scoring
- Laure Ciernik,
- Agnieszka Kraft,
- Florian Barkmann,
- Josephine Yates,
- and Valentina Boeva
Genome Res. March 2026 36: 630-644; Published in Advance February 18, 2026, doi:10.1101/gr.280926.125
...-type annotation in CRC. The small length of these effective signatures might be owing to the relative ease of distinguishing malignant from nonmalignant cells, that is, that the signatures contain genes with high specificity for the two populations.Further, to test the methods’ robustness to the presence...
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Review: Leveraging the power of long reads for targeted sequencing
- Shruti V. Iyer,
- Sara Goodwin,
- and William Richard McCombie
Genome Res. November 2024 34: 1701-1718; doi:10.1101/gr.279168.124
...-frequency variants in heterogeneous populations. Here, we review currently used and recently developed targeted sequencing strategies that leverage existing long-read technologies to increase the resolution with which we can look at nucleic acids in a variety of biological contexts.There are several applications...
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Research: Genotype imputation from low-coverage data for medical and population genetic analyses
- Simone Andrea Biagini,
- Sara Becelaere,
- Mio Aerden,
- Tatjana Jatsenko,
- Laurens Hannes,
- Philip Van Damme,
- Jeroen Breckpot,
- Koenraad Devriendt,
- Bernard Thienpont,
- Joris Robert Vermeesch,
- Isabelle Cleynen,
- and Toomas Kivisild
Genome Res. September 2025 35: 1929-1941; Published in Advance July 22, 2025, doi:10.1101/gr.280175.124
..., for the population genetic study of genetic ancestry and PGS estimation for medical risk stratification. In tests performed on an individual level, we found that imputation can be achieved with comparable quality using QUILT (Davies et al. 2021) and GLIMPSE2 (Rubinacci et al. 2023). When using ultralow coverage (<0...
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Method: Robust 16S rRNA classification based on a compressed LCA index
- Omar Ahmed,
- Christina Boucher,
- and Ben Langmead
Genome Res. December 2025 35: 2650-2660; Published in Advance August 25, 2025, doi:10.1101/gr.279846.124
...in expectation under a random model we propose here. We implemented these ideas in an open-source tool called Cliffy that performs efficient taxonomic classification of sequencing reads with respect to a compressed taxonomic index. When applied to simulated 16S rRNA reads, Cliffy's read-level accuracy is higher...
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Research: Leveraging the T2T assembly to resolve rare and pathogenic inversions in reference genome gaps
- Kristine Bilgrav Saether,
- Jesper Eisfeldt,
- Jesse D. Bengtsson,
- Ming Yin Lun,
- Christopher M. Grochowski,
- Medhat Mahmoud,
- Hsiao-Tuan Chao,
- Jill A. Rosenfeld,
- Pengfei Liu,
- Marlene Ek,
- Jakob Schuy,
- Adam Ameur,
- Hongzheng Dai,
- Undiagnosed Diseases Network,
- James Paul Hwang,
- Fritz J. Sedlazeck,
- Weimin Bi,
- Ronit Marom,
- Josephine Wincent,
- Ann Nordgren,
- Claudia M.B. Carvalho,
- and Anna Lindstrand
Genome Res. November 2024 34: 1785-1797; Published in Advance November 1, 2024, doi:10.1101/gr.279346.124
..., GRCh38, T2T-CHM13) and a reference agnostic analysis was needed. One of these cases, an INV9 mappable only in de novo assembled lrGS data using T2T-CHM13 disrupts EHMT1 consistent with a Mendelian diagnosis (Kleefstra syndrome 1; MIM#610253). Next, by pairwise comparison between T2T-CHM13, GRCh37...
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Method: Robust chromatin state annotation
- Mehdi Foroozandeh Shahraki,
- Marjan Farahbod,
- and Maxwell W. Libbrecht
Genome Res. March 2024 34: 469-483; Published in Advance March 21, 2024, doi:10.1101/gr.278343.123
...this problem by designing SAGA models that are more robust to data quality.Future studies should enhance our understanding by investigating the impact of the upstream decisions on the reproducibility of downstream annotations: for instance, the choice of SAGA methods (e...
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Research: T2T-CHM13 improves read mapping and detection of clinically relevant genetic variation in the Swedish population
- Daniel Schmitz,
- Adam Ameur,
- and Åsa Johansson
Genome Res. November 2025 35: 2377-2388; Published in Advance September 16, 2025, doi:10.1101/gr.279320.124
...tool, especially for rare diseases, which affect between 3.5% and 5.9% of the population (Nguengang Wakap et al. 2020) and are often caused by a single nucleotide variant (SNV) or a structural variant (SV). However, a minority of the rare disease patients receive a definite diagnosis and often must go...
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Perspective: The impact of long-read sequencing on human population-scale genomics
- Tobias Rausch,
- Tobias Marschall,
- and Jan O. Korbel
Genome Res. April 2025 35: 593-598; doi:10.1101/gr.280120.124
...: 246. doi:10.1186/s13059-019-1828-7 ↵Mastrorosa FK, Miller DE, Eichler EE. 2023. Applications of long-read sequencing to Mendelian genetics. Genome Med 15: 42. doi:10.1186/s13073-023-01194-3 ↵Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A...

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