Harvard Medical Schoolhttps://nrs.harvard.edu/1/44546852024-03-19T03:54:48Z2024-03-19T03:54:48ZMapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolutionKang, Joyce B.Shen, Amber Z.Gurajala, SaisriramNathan, AparnaRumker, LaurieAguiar, Vitor R. C.Valencia, CristianLagattuta, Kaitlyn A.Zhang, FanJonsson, Anna HelenaYazar, SeyhanAlquicira-Hernandez, JoseKhalili, HamedAnanthakrishnan, Ashwin N.Jagadeesh, KarthikDey, KushalAlbrecht, JenniferApruzzese, WilliamBanda, NirmalBarnas, Jennifer L.Bathon, Joan M.Ben-Artzi, AmiBoyce, Brendan F.Boyle, David L.Bridges, S. LouisBykerk, Vivian P.Campbell, DebbieCarr, Hayley L.Ceponis, ArnoldChicoine, AdamCordle, AndrewCurtis, MichelleDeane, Kevin D.DiCarlo, EdwardDunn, PatrickFiler, AndrewFirestein, Gary S.Forbess, LindsyGeraldino-Pardilla, LauraGoodman, Susan M.Gravallese, Ellen M.Gregersen, Peter K.Guthridge, Joel M.Holers, V. MichaelHorowitz, DianeHughes, Laura B.Ishigaki, KazuyoshiIvashkiv, Lionel B.James, Judith A.Keras, GregoryKorsunsky, IlyaLakhanpal, AmitLederer, James A.Lewis, MylesLi, Zhihan J.Li, YuhongLiao, Katherine P.Mandelin, Arthur M.Mantel, IanMarks, Kathryne E.Maybury, MarkMcDavid, AndrewMcGeachy, Mandy J.Mears, JosephMeednu, NidaMillard, NghiaMoreland, Larry W.Nayar, SabaNerviani, AlessandraOrange, Dana E.Perlman, HarrisPitzalis, CostantinoRangel-Moreno, JavierRaza, KarimReshef, YakirRitchlin, ChristopherRivellese, FeliceRobinson, William H.Sahbudin, IlfitaSingaraju, AnvitaSeifert, Jennifer A.Slowikowski, KamilSmith, Melanie H.Tabechian, DarrenScheel-Toellner, DagmarUtz, Paul J.Watts, Gerald F. M.Wei, KevinWeinand, KathrynWeisenfeld, DanaWeisman, Michael H.Wyse, AaronXiao, QianZhu, ZhuDaly, Mark J.Xavier, Ramnik J.Donlin, Laura T.Anolik, Jennifer H.Powell, Joseph E.Rao, Deepak A.Brenner, Michael B.Gutierrez-Arcelus, MariaLuo, YangSakaue, SaoriRaychaudhuri, Soumyahttps://nrs.harvard.edu/1/373777862024-02-23T19:40:07Z2023-11-30T05:00:00ZMapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution
Kang, Joyce B.; Shen, Amber Z.; Gurajala, Saisriram; Nathan, Aparna; Rumker, Laurie; Aguiar, Vitor R. C.; Valencia, Cristian; Lagattuta, Kaitlyn A.; Zhang, Fan; Jonsson, Anna Helena; Yazar, Seyhan; Alquicira-Hernandez, Jose; Khalili, Hamed; Ananthakrishnan, Ashwin N.; Jagadeesh, Karthik; Dey, Kushal; Albrecht, Jennifer; Apruzzese, William; Banda, Nirmal; Barnas, Jennifer L.; Bathon, Joan M.; Ben-Artzi, Ami; Boyce, Brendan F.; Boyle, David L.; Bridges, S. Louis; Bykerk, Vivian P.; Campbell, Debbie; Carr, Hayley L.; Ceponis, Arnold; Chicoine, Adam; Cordle, Andrew; Curtis, Michelle; Deane, Kevin D.; DiCarlo, Edward; Dunn, Patrick; Filer, Andrew; Firestein, Gary S.; Forbess, Lindsy; Geraldino-Pardilla, Laura; Goodman, Susan M.; Gravallese, Ellen M.; Gregersen, Peter K.; Guthridge, Joel M.; Holers, V. Michael; Horowitz, Diane; Hughes, Laura B.; Ishigaki, Kazuyoshi; Ivashkiv, Lionel B.; James, Judith A.; Keras, Gregory; Korsunsky, Ilya; Lakhanpal, Amit; Lederer, James A.; Lewis, Myles; Li, Zhihan J.; Li, Yuhong; Liao, Katherine P.; Mandelin, Arthur M.; Mantel, Ian; Marks, Kathryne E.; Maybury, Mark; McDavid, Andrew; McGeachy, Mandy J.; Mears, Joseph; Meednu, Nida; Millard, Nghia; Moreland, Larry W.; Nayar, Saba; Nerviani, Alessandra; Orange, Dana E.; Perlman, Harris; Pitzalis, Costantino; Rangel-Moreno, Javier; Raza, Karim; Reshef, Yakir; Ritchlin, Christopher; Rivellese, Felice; Robinson, William H.; Sahbudin, Ilfita; Singaraju, Anvita; Seifert, Jennifer A.; Slowikowski, Kamil; Smith, Melanie H.; Tabechian, Darren; Scheel-Toellner, Dagmar; Utz, Paul J.; Watts, Gerald F. M.; Wei, Kevin; Weinand, Kathryn; Weisenfeld, Dana; Weisman, Michael H.; Wyse, Aaron; Xiao, Qian; Zhu, Zhu; Daly, Mark J.; Xavier, Ramnik J.; Donlin, Laura T.; Anolik, Jennifer H.; Powell, Joseph E.; Rao, Deepak A.; Brenner, Michael B.; Gutierrez-Arcelus, Maria; Luo, Yang; Sakaue, Saori; Raychaudhuri, Soumya
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. For example, a T cell HLA-DQA1 eQTL (rs3104371) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
2023-11-30T05:00:00ZDynamic computational phenotyping of human cognitionSchurr, RoeyReznik, DanielHillman, HannaBhui, RahulGershman, Samuel J.https://nrs.harvard.edu/1/373777832024-02-23T19:16:11Z2024-02-08T05:00:00ZDynamic computational phenotyping of human cognition
Schurr, Roey; Reznik, Daniel; Hillman, Hanna; Bhui, Rahul; Gershman, Samuel J.
Computational phenotyping has emerged as a powerful tool for characterizing individual variability across a variety of cognitive domains. An individual's computational phenotype is defined as a set of mechanistically interpretable parameters obtained from fitting computational models to behavioral data. However, the interpretation of these parameters hinges critically on their psychometric properties, which are rarely studied. In order to identify the sources governing the temporal variability of the computational phenotype, we carried out a 12-week longitudinal study using a battery of seven tasks that measure aspects of human learning, memory, perception, and decision making. To examine the influence of state effects, each week participants provided reports tracking their mood, habits and daily activities. We developed a dynamic computational phenotyping framework, which allowed us to tease apart the time-varying effects of practice and internal states such as affective valence and arousal. Our results show that many phenotype dimensions covary with practice and affective factors, indicating that what appears to be unreliability may reflect previously unmeasured structure. These results support a fundamentally dynamic understanding of cognitive variability within an individual.
2024-02-08T05:00:00ZGenomic data in the All of Us Research ProgramBick, Alexander G.Metcalf, Ginger A.Mayo, Kelsey R.Lichtenstein, LeeRura, ShimonCarroll, Robert J.Musick, AnjeneLinder, Jodell E.Jordan, I. KingNagar, Shashwat DeepaliSharma, ShivamMeller, RobertBasford, MelissaBoerwinkle, EricCicek, Mine S.Doheny, Kimberly F.Eichler, Evan E.Gabriel, StaceyGibbs, Richard A.Glazer, DavidHarris, Paul A.Jarvik, Gail P.Philippakis, AnthonyRehm, Heidi L.Roden, Dan M.Thibodeau, Stephen N.Topper, ScottBlegen, Ashley L.Wirkus, Samantha J.Wagner, Victoria A.Meyer, Jeffrey G.Cicek, Mine S.Muzny, Donna M.Venner, EricMawhinney, Michelle Z.Griffith, Sean M. L.Hsu, ElvinLing, HuaAdams, Marcia K.Walker, KimberlyHu, JianhongDoddapaneni, HarshaKovar, Christie L.Murugan, MullaiDugan, ShannonKhan, ZiadBoerwinkle, EricLennon, Niall J.Austin-Tse, ChristinaBanks, EricGatzen, MichaelGupta, NamrataHenricks, EmmaLarsson, KatieMcDonough, SheliHarrison, Steven M.Kachulis, ChristopherLebo, Matthew S.Neben, Cynthia L.Steeves, MarcieZhou, Alicia Y.Smith, Joshua D.Frazar, Christian D.Davis, Colleen P.Patterson, Karynne E.Wheeler, Marsha M.McGee, SeanLockwood, Christina M.Shirts, Brian H.Pritchard, Colin C.Murray, Mitzi L.Vasta, ValeriaLeistritz, DruRichardson, Matthew A.Buchan, Jillian G.Radhakrishnan, AparnaKrumm, NiklasEhmen, Brenna W.Schwartz, SophieAster, M. Morgan T.Cibulskis, KristianHaessly, AndreaAsch, RebeccaCremer, AuroraDegatano, KyleeShergill, AkumGauthier, Laura D.Lee, Samuel K.Hatcher, AaronGrant, George B.Brandt, Genevieve R.Covarrubias, MiguelBanks, EricAble, AshleyGreen, Ashley E.Carroll, Robert J.Zhang, JenniferCondon, Henry R.Wang, YuanyuanDillon, Moira K.Albach, C. H.Baalawi, WailChoi, Seung HoanWang, XinRosenthal, Elisabeth A.Ramirez, Andrea H.Lim, SoknyNambiar, SiddharthaOzenberger, BradleyWise, Anastasia L.Lunt, ChrisGinsburg, Geoffrey S.Denny, Joshua C.https://nrs.harvard.edu/1/373777822024-02-23T19:09:32Z2024-02-19T05:00:00ZGenomic data in the All of Us Research Program
Bick, Alexander G.; Metcalf, Ginger A.; Mayo, Kelsey R.; Lichtenstein, Lee; Rura, Shimon; Carroll, Robert J.; Musick, Anjene; Linder, Jodell E.; Jordan, I. King; Nagar, Shashwat Deepali; Sharma, Shivam; Meller, Robert; Basford, Melissa; Boerwinkle, Eric; Cicek, Mine S.; Doheny, Kimberly F.; Eichler, Evan E.; Gabriel, Stacey; Gibbs, Richard A.; Glazer, David; Harris, Paul A.; Jarvik, Gail P.; Philippakis, Anthony; Rehm, Heidi L.; Roden, Dan M.; Thibodeau, Stephen N.; Topper, Scott; Blegen, Ashley L.; Wirkus, Samantha J.; Wagner, Victoria A.; Meyer, Jeffrey G.; Cicek, Mine S.; Muzny, Donna M.; Venner, Eric; Mawhinney, Michelle Z.; Griffith, Sean M. L.; Hsu, Elvin; Ling, Hua; Adams, Marcia K.; Walker, Kimberly; Hu, Jianhong; Doddapaneni, Harsha; Kovar, Christie L.; Murugan, Mullai; Dugan, Shannon; Khan, Ziad; Boerwinkle, Eric; Lennon, Niall J.; Austin-Tse, Christina; Banks, Eric; Gatzen, Michael; Gupta, Namrata; Henricks, Emma; Larsson, Katie; McDonough, Sheli; Harrison, Steven M.; Kachulis, Christopher; Lebo, Matthew S.; Neben, Cynthia L.; Steeves, Marcie; Zhou, Alicia Y.; Smith, Joshua D.; Frazar, Christian D.; Davis, Colleen P.; Patterson, Karynne E.; Wheeler, Marsha M.; McGee, Sean; Lockwood, Christina M.; Shirts, Brian H.; Pritchard, Colin C.; Murray, Mitzi L.; Vasta, Valeria; Leistritz, Dru; Richardson, Matthew A.; Buchan, Jillian G.; Radhakrishnan, Aparna; Krumm, Niklas; Ehmen, Brenna W.; Schwartz, Sophie; Aster, M. Morgan T.; Cibulskis, Kristian; Haessly, Andrea; Asch, Rebecca; Cremer, Aurora; Degatano, Kylee; Shergill, Akum; Gauthier, Laura D.; Lee, Samuel K.; Hatcher, Aaron; Grant, George B.; Brandt, Genevieve R.; Covarrubias, Miguel; Banks, Eric; Able, Ashley; Green, Ashley E.; Carroll, Robert J.; Zhang, Jennifer; Condon, Henry R.; Wang, Yuanyuan; Dillon, Moira K.; Albach, C. H.; Baalawi, Wail; Choi, Seung Hoan; Wang, Xin; Rosenthal, Elisabeth A.; Ramirez, Andrea H.; Lim, Sokny; Nambiar, Siddhartha; Ozenberger, Bradley; Wise, Anastasia L.; Lunt, Chris; Ginsburg, Geoffrey S.; Denny, Joshua C.
Comprehensively mapping the genetic basis of human disease across diverse individuals is a longstanding goal for the field of human genetics.1-4 The All of Us Research Program is a longitudinal cohort aiming to enroll a diverse group of at least one million individuals across the United States to accelerate biomedical research and improve human health.5,6 Here we describe the program’s genomics data release of 245,388 clinical grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities historically underrepresented in biomedical research and 46% are individuals from underrepresented racial and ethnic minorities. All of Us identified >1 billion genetic variants, including >151 million previously unreported genetic variants, >1.8 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both European and African ancestry participants. Summary level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench via a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.
2024-02-19T05:00:00ZSingle-neuronal elements of speech production in humansKhanna, Arjun R.Munoz Miranda, WilliamKim, Young J.Kfir, YoavPaulk, Angelique C.Jamali, MohsenCai, JingMustroph, MartinaCaprara, IreneHardstone, RichardMeszena, DomokosZuckerman, AbigailSchweitzer, JeffreyCash, SydneyWilliams, Ziv M.https://nrs.harvard.edu/1/373777812024-02-23T18:57:00Z2024-01-31T05:00:00ZSingle-neuronal elements of speech production in humans
Khanna, Arjun R.; Munoz Miranda, William; Kim, Young J.; Kfir, Yoav; Paulk, Angelique C.; Jamali, Mohsen; Cai, Jing; Mustroph, Martina; Caprara, Irene; Hardstone, Richard; Meszena, Domokos; Zuckerman, Abigail; Schweitzer, Jeffrey; Cash, Sydney; Williams, Ziv M.
Humans are capable of generating extraordinarily diverse articulatory movement combinations in order to produce meaningful speech. This ability to orchestrate specific phonetic sequences, their syllabification and inflection over sub-second timescales allows us to produce thousands of word-sounds and is a core component of language 1,2. The basic cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh density Neuropixels recordings in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events prior to utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also reliably predicted the phonetic, syllabic and morphological components of upcoming words and displayed a temporally ordered dynamic. Taken collectively, we show how these cells were spatially organized and how their activity patterns transitioned from articulation planning to production in real-time. We also demonstrate how they tracked the composition of phonemes during perception, and how they distinguished processes specifically related to speaking from listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and a cellular process that can support the production of natural speech.
2024-01-31T05:00:00Z