- HiNT: a computational method for detecting copy number variations and translocations from Hi-C dataSu Wang, Soohyun Lee, Chong Chu, Dhawal Jain, Peter Kerpedjiev, Geoffrey M. Nelson, Jennifer M. Walsh, Burak H. Alver, and Peter J. ParkGenome Biology, Mar 2020
The three-dimensional conformation of a genome can be profiled using Hi-C, a technique that combines chromatin conformation capture with high-throughput sequencing. However, structural variations often yield features that can be mistaken for chromosomal interactions. Here, we describe a computational method HiNT (Hi-C for copy Number variation and Translocation detection), which detects copy number variations and interchromosomal translocations within Hi-C data with breakpoints at single base-pair resolution. We demonstrate that HiNT outperforms existing methods on both simulated and real data. We also show that Hi-C can supplement whole-genome sequencing in structure variant detection by locating breakpoints in repetitive regions.
- Widespread macromolecular interaction perturbations in human genetic disordersNidhi Sahni, Song Yi, Mikko Taipale, Juan I. Fuxman Bass, Jasmin Coulombe-Huntington, Fan Yang, Jian Peng, Jochen Weile, Georgios I. Karras, Yang Wang, István A. Kovács, Atanas Kamburov, Irina Krykbaeva, Mandy H. Lam, George Tucker, Vikram Khurana, Amitabh Sharma, Yang-Yu Liu, Nozomu Yachie, Quan Zhong, Yun Shen, Alexandre Palagi, Adriana San-Miguel, Changyu Fan, Dawit Balcha, Amelie Dricot, Daniel M. Jordan, Jennifer M. Walsh, Akash A. Shah, Xinping Yang, Ani K. Stoyanova, Alex Leighton, Michael A. Calderwood, Yves Jacob, Michael E. Cusick, Kourosh Salehi-Ashtiani, Luke J. Whitesell, Shamil Sunyaev, Bonnie Berger, Albert-László Barabási, Benoit Charloteaux, David E. Hill, Tong Hao, Frederick P. Roth, Yu Xia, Albertha J. M. Walhout, Susan Lindquist, and Marc VidalCell, Apr 2015
How disease-associated mutations impair protein activities in the context of biological networks remains mostly undetermined. Although a few renowned alleles are well characterized, functional information is missing for over 100,000 disease-associated variants. Here we functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays. The majority of disease-associated alleles exhibit wild-type chaperone binding profiles, suggesting they preserve protein folding or stability. While common variants from healthy individuals rarely affect interactions, two-thirds of disease-associated alleles perturb protein-protein interactions, with half corresponding to "edgetic" alleles affecting only a subset of interactions while leaving most other interactions unperturbed. With transcription factors, many alleles that leave protein-protein interactions intact affect DNA binding. Different mutations in the same gene leading to different interaction profiles often result in distinct disease phenotypes. Thus disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.
- A Proteome-Scale Map of the Human Interactome NetworkThomas Rolland, Murat Taşan, Benoit Charloteaux, Samuel J. Pevzner, Quan Zhong, Nidhi Sahni, Song Yi, Irma Lemmens, Celia Fontanillo, Roberto Mosca, Atanas Kamburov, Susan D. Ghiassian, Xinping Yang, Lila Ghamsari, Dawit Balcha, Bridget E. Begg, Pascal Braun, Marc Brehme, Martin P. Broly, Anne-Ruxandra Carvunis, Dan Convery-Zupan, Roser Corominas, Jasmin Coulombe-Huntington, Elizabeth Dann, Matija Dreze, Amélie Dricot, Changyu Fan, Eric Franzosa, Fana Gebreab, Bryan J. Gutierrez, Madeleine F. Hardy, Mike Jin, Shuli Kang, Ruth Kiros, Guan Ning Lin, Katja Luck, Andrew MacWilliams, Jörg Menche, Ryan R. Murray, Alexandre Palagi, Matthew M. Poulin, Xavier Rambout, John Rasla, Patrick Reichert, Viviana Romero, Elien Ruyssinck, Julie M. Sahalie, Annemarie Scholz, Akash A. Shah, Amitabh Sharma, Yun Shen, Kerstin Spirohn, Stanley Tam, Alexander O. Tejeda, Shelly A. Wanamaker, Jean-Claude Twizere, Kerwin Vega, Jennifer Walsh, Michael E. Cusick, Yu Xia, Albert-László Barabási, Lilia M. Iakoucheva, Patrick Aloy, Javier De Las Rivas, Jan Tavernier, Michael A. Calderwood, David E. Hill, Tong Hao, Frederick P. Roth, and Marc VidalCell, Nov 2014Publisher: Elsevier
- High-resolution spectroscopic study of extremely metal-poor star candidates from the SkyMapper surveyHeather R. Jacobson, Anna Frebel, José M. Peña, Jennifer M. Walsh, Qinsi Yu, Stefan Keller, Martin Asplund, Michael S. Bessell, Gary S. Da Costa, Anna F. Marino, John E. Norris, Brian P. Schmidt, Patrick Tisserand, David Yong, Andrew R. Casey, and Karin LindAstrophysical Journal, Jul 2015
The SkyMapper Southern Sky Survey is carrying out a search for the most metal-poor stars in the Galaxy. It identifies candidates by way of its unique filter set which allows for estimation of stellar atmospheric parameters. The set includes a narrow filter centered on the Ca ii K 3933 Å line, enabling a robust estimate of stellar metallicity. Promising candidates are then confirmed with spectroscopy. We present the analysis of Magellan Inamori Kyocera Echelle high-resolution spectroscopy of 122 metal-poor stars found by SkyMapper in the first two years of commissioning observations. Forty-one stars have [Fe/H]⩽−3.0. Nine have [Fe/H]⩽−3.5, with three at [Fe/H]∼−4. A 1D LTE abundance analysis of the elements Li, C, Na, Mg, Al, Si, Ca, Sc, Ti, Cr, Mn, Co, Ni, Zn, Sr, Ba, and Eu shows these stars have [X/Fe] ratios typical of other halo stars. One star with low [X/Fe] values appears to be “Fe-enhanced,” while another star has an extremely large [Sr/Ba] ratio: \textgreater2. Only one other star is known to have a comparable value. Seven stars are “CEMP-no” stars ([C/Fe]\textgreater0.7, [Ba/Fe]\textless0). 21 stars exhibit mild r-process element enhancements (0.3⩽[Eu/Fe]\textless1.0), while four stars have [Eu/Fe]⩾1.0. These results demonstrate the ability to identify extremely metal-poor stars from SkyMapper photometry, pointing to increased sample sizes and a better characterization of the metal-poor tail of the halo metallicity distribution function in the future.
- HiNT: a computational method for detecting copy number variations and translocations from Hi-C dataGenome Biology, Mar 2020
- Widespread macromolecular interaction perturbations in human genetic disordersCell, Apr 2015
- A Proteome-Scale Map of the Human Interactome NetworkCell, Nov 2014Publisher: Elsevier
- High-resolution spectroscopic study of extremely metal-poor star candidates from the SkyMapper surveyAstrophysical Journal, Jul 2015