‡ Indicates co-first or co-corresponding authorship
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Gamarra N, Chittenden C, Sundararajan K, Schwartz JP, Lundqvist S, Robles D, Dixon-Luinenburg O, Marcus J, Maslan A, Franklin JM, Streets A, Straight AF, Altemose N (2025). DiMeLo-cito: a one-tube protocol for mapping protein-DNA interactions reveals CTCF bookmarking in mitosis. bioRxiv, 2025.03.11.642717. https://doi.org/10.1101/2025.03.11.642717
Existing protocols for probing specific protein-DNA interactions genome-wide, such as CUT&RUN or DiMeLo-seq, involve lossy wash steps that can compromise sample quality and yield. To address this, we invented an efficient one-pot protocol for performing DiMeLo-seq, by making key reagent optimizations and by replacing wash steps with affinity-based depletions. This advance also eliminates the need for a nuclear envelope to contain chromatin during wash steps, enabling us to interrogate chromatin state in mitotic cells, in which the nuclear envelope is disassembled. In doing so, we resolved a disagreement in the field by uncovering strong evidence that the 3D genome architecture protein CTCF remains bound to DNA in mitosis.
Dubocanin D, Kalygina A, Franklin JM, Chittenden C, Vollger M, Neph S, Stergachis AB, Altemose N (2025). Integrating single-molecule sequencing and deep learning to predict haplotype-specific 3D chromatin organization in a Mendelian condition. bioRxiv, 2025.02.26.640261. https://doi.org/10.1101/2025.02.26.640261
Each chromosome must fold up in 3D space to fit inside the cell, and the way it does this can affect how genes are turned on and off, sometimes in ways that lead to inborn diseases. Measuring this 3D organization across the genome with existing DNA sequencing technologies can be challenging and costly, making it difficult to study how changes in 3D organization contribute to disease. To address this, we developed a machine learning model that can accurately predict 3D genome organization from a single long-read multi-omic sequencing experiment called Fiber-seq, which is simpler and cheaper to perform on patient samples than the equivalent short-read sequencing experiments. Our approach will make 3D genome analysis accessible for a wide range of basic research and clinical applications, accelerating the discovery of genotype-phenotype relationships in human disease.
Franklin JM, Dubocanin D, Chittenden C, Barillas A, Lee RJ, Ghosh RP, Gerton JL, Guan K-L‡, Altemose N‡ (2024).
Human Satellite 3 DNA encodes megabase-scale transcription factor binding platforms. bioRxiv, 2024.10.22.616524. https://doi.org/10.1101/2024.10.22.616524
Among the most mysterious regions of the human genome are highly repetitive satellite DNAs that do not participate in centromere function, including Human Satellite 3 (HSat3), which makes up roughly 2% of the genome and is made up of arrays as large as 30 Mb. To better understand the potential functions of these regions, we performed a systematic computational screen for novel HSat3-binding factors. Our work revealed that HSat3 arrays contain high densities of transcription factor (TF) motifs that are bound by factors related to multiple, highly conserved signaling pathways. By performing careful follow-up experiments on one of these factors, we discovered a novel and unexpected regulatory axis connecting satellite DNA, the Hippo Pathway, and ribogenesis. More broadly, this work demonstrates that satellite DNA arrays can act as enormous transcription factor binding platforms for dozens of different pathways, opening up a new field for further discovery.
Salinas-Luypaert C, Dubocanin D, Lee RJ, Ruiz LA, Gamba R, Grison M, Velikovsky L, Angrisani A, Scelfo A, Xu Y, Dumont M, Barra V, Wilhelm T, Velasco G, Losito M, Wardenaar R, Francastel C, Foijer F, Kops GJPL, Miga KH, Altemose N‡, Fachinetti D‡ (2025). DNA methylation influences human centromere positioning and function. Nature Genetics (accepted)
One of the major discoveries from the T2T Consortium’s assemblies across human centromeric repeat arrays was that centromere proteins only localize to a small region within each array, and this region tends to have low DNA methylation, while the rest of the array has very high DNA methylation. However, it has remained unknown whether this correlation between centromere protein localization and DNA hypomethylation is causal or important for centromere function. To address this, we specifically perturbed the methylation state of centromeres by targeting them with DNA demethylases and DNA methyltransferases, then we performed DiMeLo-seq to measure centromere protein localization. We found that hypomethylation of entire centromeric repeat arrays led to increased binding of centromere proteins, while hypermethylation of centromeres led to reduced centromere protein binding. Both perturbations increased chromosomal segregation errors and reduced cell proliferation rate. These results confirm that DNA methylation causally influences human centromere positioning and function, providing fundamental insights and raising new questions about the epigenetic maintenance of human centromere identity.
Altemose N (2022). [Review]
A classical revival: Human satellite DNAs enter the genomics era. Seminars in Cell and Developmental Biology, 128, 2-14.
https://doi.org/10.1016/j.semcdb.2022.04.012 [open-access preprint available]
The classical human satellite DNAs, which constitute roughly 3% of the genome, were among the first human DNA sequences to be isolated and characterized at the dawn of molecular biology, but they were among the last to be included in the human genome reference assembly. This review outlines the history and state of the field of human satellite DNA biology, with a view toward future studies unlocked by the potential of long-read sequencing technologies.
Altemose N, Logsdon GA, Bzikadze AV, Sidhwani P, Langley SA, Caldas GV, Hoyt SJ, Uralsky L, Ryabov FD, Shew CJ, Sauria MEG, Borchers M, Gershman A, Mikheenko A, Shepelev VA, Dvorkina T, Kunyavskaya O, Vollger MR, Rhie A, McCartney AM, Asri M, Lorig-Roach R, Shafin K, Lucas JK, Aganezov S, Olson D, Gomes de Lima L, Potapova T, Hartley GA, Haukness M, Kerpedjiev P, Gusev F, Tigyi K, Brooks S, Young A, Nurk S, Koren S, Salama SR, Paten B, Rogaev EI, Streets A, Karpen GH, Dernburg A, F, Sullivan BA, Straight AF, Wheeler TJ, Gerton JL, Eichler EE, Phillippy AM, Timp W, Dennis MY, O’Neill RJ, Zook JM, Schatz MC, Pevzner PA, Diekhans M, Langley CH, Alexandrov IA, Miga KH (2021).
Complete genomic and epigenetic maps of human centromeres. Science, 375, eabl4178.
https://doi.org/10.1126/science.abl4178 [free to read]
Altemose N, Maslan A, Rios-Martinez C, Lai A, White JA, Streets A (2020).
μDamID: a microfluidic approach for joint imaging and sequencing of protein-DNA interactions in single cells. Cell Systems, 11, 1-13.
https://doi.org/10.1016/j.cels.2020.08.015 [open access, transparent review]
Li R‡, Bitoun E‡, Altemose N‡, Davies RW, Davies B, Myers SR (2019).
A high-resolution map of non-crossover events reveals impacts of genetic diversity on mammalian meiotic recombination. Nature Communications, 10, 1-15.
https://doi.org/10.1038/s41467-019-11675-y [open access, transparent review]
Altemose N, Noor N, Bitoun E, Tumian A, Imbeault M, Chapman R, Aricescu AR, Myers SR (2017).
A map of human PRDM9 binding provides evidence for novel behaviors of PRDM9 and other zinc-finger proteins in meiosis. eLife, 6, e28383.
https://doi.org/10.7554/eLife.28383 [open access, transparent review]
Davies B‡, Hatton E‡, Altemose N, Hussin JG, Pratto F, Zhang G, Hinch AG, Moralli D, Biggs D, Diaz R, Preece C, Li R, Brick K, Green CM, Camerini-Otero RD, Myers SR, and Donnelly P (2016).
Re-engineering the zinc fingers of PRDM9 reverses hybrid sterility in mice. Nature, 530(7589), 171–176.
https://doi.org/10.1038/nature16931 [free to read on PubMed Central]
Altemose N, Hayden KE, Maggioni M, Willard HF (2014).
Genomic characterization of large heterochromatic gaps in the human genome assembly. PLoS Computational Biology, 10(5), e1003628.
https://doi.org/10.1371/journal.pcbi.1003628 [open access]
Lu X, Keo V, Cheng I, Xie W, Gritsina G, Wang J, Lu L, Shiau C-K, He Y, Jin Q, Jin P, Yue F, Sanda MG, Corces VG, Altemose N, Gao R, Zhao JC, Yu J (2025). NKX2-1 drives neuroendocrine transdifferentiation of prostate cancer via epigenetic and 3D chromatin remodeling. Nature Genetics, https://doi.org/10.1038/s41588-025-02265-4
Tang J‡, Weiser NE‡, Wang G‡, Chowdhry S, Curtis EJ, Zhao Y, Wong I T-L, Marinov GK, Li R, Hanoian P, Tse E, Hansen R, Plum J, Steffy A, Mulutinovic S, Meyer T, Luebeck J, Wang Y, Zhang S, Altemose N, Curtis C, Greenleaf WJ, Bafna V, Benkovic SJ, Pinkerton AB, Kasibhatia S, Hassig CA, Mischel PS, Chang HY (2024). Enhancing transcription–replication conflict targets ecDNA-positive cancers. Nature, 635, 210–218, https://doi.org/10.1038/s41586-024-07802-5 [open-access preprint available]
Maslan A, Altemose N, Marcus J, Mishra R, Brennan LD, Sundararajan K, Karpen G, Straight AF, Streets A (2024). Mapping protein-DNA interactions with DiMeLo-seq. Nature Protocols, https://doi.org/10.1038/s41596-024-01032-9 [open-access preprint available]
Rhie A‡, Nurk S‡, Cechova M‡, Hoyt SJ‡, Taylor DJ‡, Altemose N, The Telomere-To-Telomere Consortium (80 authors), Phillippy AM (2023). The complete sequence of a human Y chromosome. Nature, https://doi.org/10.1038/s41586-023-06457-y [open-access preprint available]
Nurk S‡, Koren S‡, Rhie A‡, Rautiainen M‡, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, The Telomere-To-Telomere Consortium (74 authors), Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM (2022). The complete sequence of a human genome. Science, 375, eabj6987, https://doi.org/10.1126/science.abj6987 [free to read]
Gershman A, Sauria MEG, Guitart X, Vollger MR, Hook PW, Hoyt SJ, Jain M, Shumate A, Razaghi R, Koren S, Altemose N, Caldas GV, Logsdon GA, Rhie A, Eichler EE, Schatz MC, O’Neill RJ, Phillippy AM, Miga KH, Timp W (2022). Epigenetic patterns in a complete human genome. Science, 375, eabj5089, https://doi.org/10.1126/science.abj5089 [free to read]
Hoyt SJ, Storer JM, Hartley GA, Grady PGS, Gershman A, de Lima LG, Limouse C, Halabian R, Wojenski L, Rodriguez M, Altemose N, Rhie A, Core LJ, Gerton JL, Makalowski W, Olson D, Rosen J, Smit AFA, Straight AF, Vollger MR, Wheeler TJ, Schatz MC, Eichler EE, Phillippy AM, Timp W, Miga KH, O’Neill RJ (2022). From telomere to telomere: The transcriptional and epigenetic state of human repeat elements. Science, 375, eabk3112, https://doi.org/10.1126/science.abk3112 [free to read]
Gupta A, Shamsi F, Altemose N, Dorlhiac GF, Cypess AM, White AP, Yosef N, Patti ME, Tseng Y-H, Streets A (2022). Characterization of transcript enrichment and detection bias in single-nuclei RNA-seq for mapping of distinct human adipocyte lineages. Genome Research, 32, 242-257, https://doi.org/10.1101/gr.275509.121 [open-access preprint available]
Grist S, Geldert A, Gopal A, Su A, Balch H, Herr A, Rampazzi S, Smullin S, Starr N, Rempel D, Agarwal P, Altemose N, Chen T, Hu G, Tung M, Pillarisetti A, Robinowitz D, Shless J (2021). Current understanding of ultraviolet-C decontamination of N95 filtering facepiece respirators. Applied Biosafety, eprint. https://doi.org/10.1089/apb.20.0051 [open access]
Nakatsuka N, Patterson N, Patsopoulos N, De Jager P, Altemose N, Tandon A, Beecham AH, McCauley JL, Isobel N, Hauser S, Hafler DA, Oksenberg JR, Reich D (2020). Two genetic variants explain the association of European ancestry with multiple sclerosis risk in African-Americans. Scientific Reports, 10, 16902. https://doi.org/10.1038/s41598-020-74035-7 [open access]
Lai A, Altemose N, White JA, Streets AM (2019). On-ratio PDMS bonding for multilayer microfluidic device fabrication. Journal of Micromechanics and Microengineering, 29(10), 107001. https://doi.org/10.1088/1361-6439/ab341e [open-access preprint available]
Williams AL, Genovese G, Dyer T, Altemose N, Truax K, Jun G, Patterson N, Myers SR, Curran JE, Duggirala R, Blangero J, Reich D, Przeworski M, on behalf of the T2D-GENES Consortium (2015). Non-crossover gene conversions show strong GC bias and unexpected clustering in humans. eLife 4. https://doi.org/10.7554/eLife.04637 [open access]
Hinch AG, Altemose N, Noor N, Donnelly P, Myers SR (2014). Recombination in the human pseudoautosomal region PAR1. PLoS Genetics 10(7), e1004503–e1004503. https://doi.org/10.1371/journal.pgen.1004503 [open access]
Miga KH, Newton Y, Jain M, Altemose N, Willard HF, Kent WJ (2014). Centromere reference models for human chromosomes X and Y satellite arrays. Genome Research 24(4), 697–707. https://doi.org/10.1101/gr.159624.113 [open access]
Genovese G, Handsaker R, Li H, Altemose N, Lindgren AM, Chambert K, Pasaniuc B, Price AL, Reich D, Morton CC, Pollak MR, Wilson JG, McCarroll SA (2013). Using population admixture to help complete maps of the human genome. Nature Genetics 45, 406-414. https://doi.org/10.1038/ng.2565 [free to read on PubMed Central]
Carty BL, Dubocanin D, Murillo-Pineda M, Dumont M, Volpe E, Mikulski P, Humes J, Whittingham O, Fachinetti D, Giunta S, Altemose N, Jansen LET (2025). [Preprint] Heterochromatin boundaries maintain centromere position, size and number. bioRxiv, 2025.02.03.635667, https://doi.org/10.1101/2025.02.03.635667
Mahlke MA, Lumerman L, Nath P, Chittenden C, Hoyt S, Koeppel J, Xu Y, Raphael R, Zaffina K, Hook PW, Timp W, Miga KH, Campbell PJ, O’Neill R, Altemose N, Nechemia-Arbely Y (2025). [Preprint] Epigenetically dynamic human centromeres are maintained within a stable DNA methylation signature. bioRxiv, 2025.02.03.636285, https://doi.org/10.1101/2025.02.03.636285