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Heilig R, Eckenberg R, Petit JL, Fonknechten N, Da Silva C, Cattolico L, Levy M, Barbe V, de Berardinis V, Ureta-Vidal A, Pelletier E, Vico V, Anthouard V, Rowen L, Madan A, Qin S, Sun H, Du H, Pepin K, Artiguenave F, Robert C, Cruaud C, Brüls T, Jaillon O, Friedlander L, Samson G, Brottier P, Cure S, Ségurens B, Anière F, Samain S, Crespeau H, Abbasi N, Aiach N, Boscus D, Dickhoff R, Dors M, Dubois I, Friedman C, Gouyvenoux M, James R, Madan A, Mairey-Estrada B, Mangenot S, Martins N, Ménard M, Oztas S, Ratcliffe A, Shaffer T, Trask B, Vacherie B, Bellemere C, Belser C, Besnard-Gonnet M, Bartol-Mavel D, Boutard M, Briez-Silla S, Combette S, Dufossé-Laurent V, Ferron C, Lechaplais C, Louesse C, Muselet D, Magdelenat G, Pateau E, Petit E, Sirvain-Trukniewicz P, Trybou A, Vega-Czarny N, Bataille E, Bluet E, Bordelais I, Dubois M, Dumont C, Guérin T, Haffray S, Hammadi R, Muanga J, Pellouin V, Robert D, Wunderle E, Gauguet G, Roy A, Sainte-Marthe L, Verdier J, Verdier-Discala C, Hillier L, Fulton L, McPherson J, Matsuda F, Wilson R, Scarpelli C, Gyapay G, Wincker P, Saurin W, Quétier F, Waterston R, Hood L, Weissenbach J. Publisher Correction: The DNA sequence and analysis of human chromosome 14. Nature 2023; 620:E17. [PMID: 37491470 DOI: 10.1038/s41586-023-06403-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
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Manry J, Bastard P, Gervais A, Le Voyer T, Rosain J, Philippot Q, Michailidis E, Hoffmann HH, Eto S, Garcia-Prat M, Bizien L, Parra-Martínez A, Yang R, Haljasmägi L, Migaud M, Särekannu K, Maslovskaja J, de Prost N, Tandjaoui-Lambiotte Y, Luyt CE, Amador-Borrero B, Gaudet A, Poissy J, Morel P, Richard P, Cognasse F, Troya J, Trouillet-Assant S, Belot A, Saker K, Garçon P, Rivière JG, Lagier JC, Gentile S, Rosen LB, Shaw E, Morio T, Tanaka J, Dalmau D, Tharaux PL, Sene D, Stepanian A, Mégarbane B, Triantafyllia V, Fekkar A, Heath JR, Franco JL, Anaya JM, Solé-Violán J, Imberti L, Biondi A, Bonfanti P, Castagnoli R, Delmonte OM, Zhang Y, Snow AL, Holland SM, Biggs CM, Moncada-Vélez M, Arias AA, Lorenzo L, Boucherit S, Anglicheau D, Planas AM, Haerynck F, Duvlis S, Ozcelik T, Keles S, Bousfiha AA, El Bakkouri J, Ramirez-Santana C, Paul S, Pan-Hammarström Q, Hammarström L, Dupont A, Kurolap A, Metz CN, Aiuti A, Casari G, Lampasona V, Ciceri F, Barreiros LA, Dominguez-Garrido E, Vidigal M, Zatz M, van de Beek D, Sahanic S, Tancevski I, Stepanovskyy Y, Boyarchuk O, Nukui Y, Tsumura M, Vidaur L, Tangye SG, Burrel S, Duffy D, Quintana-Murci L, Klocperk A, Kann NY, Shcherbina A, Lau YL, Leung D, Coulongeat M, Marlet J, Koning R, Reyes LF, Chauvineau-Grenier A, Venet F, Monneret G, Nussenzweig MC, Arrestier R, Boudhabhay I, Baris-Feldman H, Hagin D, Wauters J, Meyts I, Dyer AH, Kennelly SP, Bourke NM, Halwani R, Sharif-Askari FS, Dorgham K, Sallette J, Sedkaoui SM, AlKhater S, Rigo-Bonnin R, Morandeira F, Roussel L, Vinh DC, Erikstrup C, Condino-Neto A, Prando C, Bondarenko A, Spaan AN, Gilardin L, Fellay J, Lyonnet S, Bilguvar K, Lifton RP, Mane S, Anderson MS, Boisson B, Béziat V, Zhang SY, Andreakos E, Hermine O, Pujol A, Peterson P, Mogensen TH, Rowen L, Mond J, Debette S, de Lamballerie X, Burdet C, Bouadma L, Zins M, Soler-Palacin P, Colobran R, Gorochov G, Solanich X, Susen S, Martinez-Picado J, Raoult D, Vasse M, Gregersen PK, Piemonti L, Rodríguez-Gallego C, Notarangelo LD, Su HC, Kisand K, Okada S, Puel A, Jouanguy E, Rice CM, Tiberghien P, Zhang Q, Casanova JL, Abel L, Cobat A. The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies. Proc Natl Acad Sci U S A 2022; 119:e2200413119. [PMID: 35576468 PMCID: PMC9173764 DOI: 10.1073/pnas.2200413119] [Citation(s) in RCA: 126] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/17/2022] [Indexed: 01/25/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged <70 y and in >4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.
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Su Y, Yuan D, Chen DG, Ng RH, Wang K, Choi J, Li S, Hong S, Zhang R, Xie J, Kornilov SA, Scherler K, Pavlovitch-Bedzyk AJ, Dong S, Lausted C, Lee I, Fallen S, Dai CL, Baloni P, Smith B, Duvvuri VR, Anderson KG, Li J, Yang F, Duncombe CJ, McCulloch DJ, Rostomily C, Troisch P, Zhou J, Mackay S, DeGottardi Q, May DH, Taniguchi R, Gittelman RM, Klinger M, Snyder TM, Roper R, Wojciechowska G, Murray K, Edmark R, Evans S, Jones L, Zhou Y, Rowen L, Liu R, Chour W, Algren HA, Berrington WR, Wallick JA, Cochran RA, Micikas ME, Wrin T, Petropoulos CJ, Cole HR, Fischer TD, Wei W, Hoon DSB, Price ND, Subramanian N, Hill JA, Hadlock J, Magis AT, Ribas A, Lanier LL, Boyd SD, Bluestone JA, Chu H, Hood L, Gottardo R, Greenberg PD, Davis MM, Goldman JD, Heath JR. Multiple early factors anticipate post-acute COVID-19 sequelae. Cell 2022; 185:881-895.e20. [PMID: 35216672 PMCID: PMC8786632 DOI: 10.1016/j.cell.2022.01.014] [Citation(s) in RCA: 629] [Impact Index Per Article: 209.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/14/2021] [Accepted: 01/19/2022] [Indexed: 01/14/2023]
Abstract
Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
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Manry J, Bastard P, Gervais A, Le Voyer T, Rosain J, Philippot Q, Michailidis E, Hoffmann HH, Eto S, Garcia-Prat M, Bizien L, Parra-Martínez A, Yang R, Haljasmägi L, Migaud M, Särekannu K, Maslovskaja J, de Prost N, Tandjaoui-Lambiotte Y, Luyt CE, Amador-Borrero B, Gaudet A, Poissy J, Morel P, Richard P, Cognasse F, Troya J, Trouillet-Assant S, Belot A, Saker K, Garçon P, Rivière JG, Lagier JC, Gentile S, Rosen L, Shaw E, Morio T, Tanaka J, Dalmau D, Tharaux PL, Sene D, Stepanian A, Mégarbane B, Triantafyllia V, Fekkar A, Heath J, Franco J, Anaya JM, Solé-Violán J, Imberti L, Biondi A, Bonfanti P, Castagnoli R, Delmonte O, Zhang Y, Snow A, Holland S, Biggs C, Moncada-Vélez M, Arias A, Lorenzo L, Boucherit S, Anglicheau D, Planas A, Haerynck F, Duvlis S, Nussbaum R, Ozcelik T, Keles S, Bousfiha A, El Bakkouri J, Ramirez-Santana C, Paul S, Pan-Hammarstrom Q, Hammarstrom L, Dupont A, Kurolap A, Metz C, Aiuti A, Casari G, Lampasona V, Ciceri F, Barreiros L, Dominguez-Garrido E, Vidigal M, Zatz M, van de Beek D, Sahanic S, Tancevski I, Stepanovskyy Y, Boyarchuk O, Nukui Y, Tsumura M, Vidaur L, Tangye S, Burrel S, Duffy D, Quintana-Murci L, Klocperk A, Kann N, Shcherbina A, Lau YL, Leung D, Coulongeat M, Marlet J, Koning R, Reyes L, Chauvineau-Grenier A, Venet F, Monneret G, Nussenzweig M, Arrestier R, Boudhabhay I, Baris-Feldman H, Hagin D, Wauters J, Meyts I, Dyer A, Kennelly S, Bourke N, Halwani R, Sharif-Askari F, Dorgham K, Sallette J, Mehlal-Sedkaoui S, AlKhater S, Rigo-Bonnin R, Morandeira F, Roussel L, Vinh D, Erikstrup C, Condino-Neto A, Prando C, Bondarenko A, Spaan A, Gilardin L, Fellay J, Lyonnet S, Bilguvar K, Lifton R, Mane S, Anderson M, Boisson B, Béziat V, Zhang SY, Andreakos E, Hermine O, Pujol A, Peterson P, Mogensen TH, Rowen L, Mond J, Debette S, deLamballerie X, Burdet C, Bouadma L, Zins M, Soler-Palacin P, Colobran R, Gorochov G, Solanich X, Susen S, Martinez-Picado J, Raoult D, Vasse M, Gregersen P, Rodríguez-Gallego C, Piemonti L, Notarangelo L, Su H, Kisand K, Okada S, Puel A, Jouanguy E, Rice C, Tiberghien P, Zhang Q, Casanova JL, Abel L, Cobat A. The risk of COVID-19 death is much greater and age-dependent with type I IFN autoantibodies. RESEARCH SQUARE 2022:rs.3.rs-1225906. [PMID: 35043109 PMCID: PMC8764723 DOI: 10.21203/rs.3.rs-1225906/v1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
SARS-CoV-2 infection fatality rate (IFR) doubles with every five years of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ~20% of deceased patients across age groups. In the general population, they are found in ~1% of individuals aged 20-70 years and in >4% of those >70 years old. With a sample of 1,261 deceased patients and 34,159 uninfected individuals, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to non-carriers. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRD was 17.0[95% CI:11.7-24.7] for individuals under 70 years old and 5.8[4.5-7.4] for individuals aged 70 and over, whereas, for autoantibodies neutralizing both molecules, the RRD was 188.3[44.8-774.4] and 7.2[5.0-10.3], respectively. IFRs increased with age, from 0.17%[0.12-0.31] for individuals <40 years old to 26.7%[20.3-35.2] for those ≥80 years old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84%[0.31-8.28] to 40.5%[27.82-61.20] for the same two age groups, for autoantibodies neutralizing both molecules. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, particularly those neutralizing both IFN-α2 and -ω. Remarkably, IFR increases with age, whereas RRD decreases with age. Autoimmunity to type I IFNs appears to be second only to age among common predictors of COVID-19 death.
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Bastard P, Gervais A, Le Voyer T, Rosain J, Philippot Q, Manry J, Michailidis E, Hoffmann HH, Eto S, Garcia-Prat M, Bizien L, Parra-Martínez A, Yang R, Haljasmägi L, Migaud M, Särekannu K, Maslovskaja J, de Prost N, Tandjaoui-Lambiotte Y, Luyt CE, Amador-Borrero B, Gaudet A, Poissy J, Morel P, Richard P, Cognasse F, Troya J, Trouillet-Assant S, Belot A, Saker K, Garçon P, Rivière JG, Lagier JC, Gentile S, Rosen LB, Shaw E, Morio T, Tanaka J, Dalmau D, Tharaux PL, Sene D, Stepanian A, Megarbane B, Triantafyllia V, Fekkar A, Heath JR, Franco JL, Anaya JM, Solé-Violán J, Imberti L, Biondi A, Bonfanti P, Castagnoli R, Delmonte OM, Zhang Y, Snow AL, Holland SM, Biggs C, Moncada-Vélez M, Arias AA, Lorenzo L, Boucherit S, Coulibaly B, Anglicheau D, Planas AM, Haerynck F, Duvlis S, Nussbaum RL, Ozcelik T, Keles S, Bousfiha AA, El Bakkouri J, Ramirez-Santana C, Paul S, Pan-Hammarström Q, Hammarström L, Dupont A, Kurolap A, Metz CN, Aiuti A, Casari G, Lampasona V, Ciceri F, Barreiros LA, Dominguez-Garrido E, Vidigal M, Zatz M, van de Beek D, Sahanic S, Tancevski I, Stepanovskyy Y, Boyarchuk O, Nukui Y, Tsumura M, Vidaur L, Tangye SG, Burrel S, Duffy D, Quintana-Murci L, Klocperk A, Kann NY, Shcherbina A, Lau YL, Leung D, Coulongeat M, Marlet J, Koning R, Reyes LF, Chauvineau-Grenier A, Venet F, Monneret G, Nussenzweig MC, Arrestier R, Boudhabhay I, Baris-Feldman H, Hagin D, Wauters J, Meyts I, Dyer AH, Kennelly SP, Bourke NM, Halwani R, Sharif-Askari NS, Dorgham K, Sallette J, Sedkaoui SM, AlKhater S, Rigo-Bonnin R, Morandeira F, Roussel L, Vinh DC, Ostrowski SR, Condino-Neto A, Prando C, Bonradenko A, Spaan AN, Gilardin L, Fellay J, Lyonnet S, Bilguvar K, Lifton RP, Mane S, Anderson MS, Boisson B, Béziat V, Zhang SY, Vandreakos E, Hermine O, Pujol A, Peterson P, Mogensen TH, Rowen L, Mond J, Debette S, de Lamballerie X, Duval X, Mentré F, Zins M, Soler-Palacin P, Colobran R, Gorochov G, Solanich X, Susen S, Martinez-Picado J, Raoult D, Vasse M, Gregersen PK, Piemonti L, Rodríguez-Gallego C, Notarangelo LD, Su HC, Kisand K, Okada S, Puel A, Jouanguy E, Rice CM, Tiberghien P, Zhang Q, Cobat A, Abel L, Casanova JL. Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths. Sci Immunol 2021; 6:eabl4340. [PMID: 34413139 PMCID: PMC8521484 DOI: 10.1126/sciimmunol.abl4340] [Citation(s) in RCA: 371] [Impact Index Per Article: 92.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 08/16/2021] [Indexed: 01/16/2023]
Abstract
Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/mL, in plasma diluted 1 to 10) of IFN-α and/or -ω are found in about 10% of patients with critical COVID-19 pneumonia, but not in subjects with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or -ω (100 pg/mL, in 1/10 dilutions of plasma) in 13.6% of 3,595 patients with critical COVID-19, including 21% of 374 patients > 80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1,124 deceased patients (aged 20 days-99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected subjects from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or -ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of subjects carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals <70 years, 2.3% between 70 and 80 years, and 6.3% >80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over-80s, and total fatal COVID-19 cases.
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Su Y, Chen D, Yuan D, Lausted C, Choi J, Dai CL, Voillet V, Duvvuri VR, Scherler K, Troisch P, Baloni P, Qin G, Smith B, Kornilov SA, Rostomily C, Xu A, Li J, Dong S, Rothchild A, Zhou J, Murray K, Edmark R, Hong S, Heath JE, Earls J, Zhang R, Xie J, Li S, Roper R, Jones L, Zhou Y, Rowen L, Liu R, Mackay S, O'Mahony DS, Dale CR, Wallick JA, Algren HA, Zager MA, Wei W, Price ND, Huang S, Subramanian N, Wang K, Magis AT, Hadlock JJ, Hood L, Aderem A, Bluestone JA, Lanier LL, Greenberg PD, Gottardo R, Davis MM, Goldman JD, Heath JR. Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19. Cell 2020; 183:1479-1495.e20. [PMID: 33171100 PMCID: PMC7598382 DOI: 10.1016/j.cell.2020.10.037] [Citation(s) in RCA: 406] [Impact Index Per Article: 81.2] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 09/16/2020] [Accepted: 10/22/2020] [Indexed: 12/29/2022]
Abstract
We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.
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Qin S, Zhou Y, Gray L, Kusebauch U, McEvoy L, Antoine DJ, Hampson L, Park KB, Campbell D, Caballero J, Glusman G, Yan X, Kim TK, Yuan Y, Wang K, Rowen L, Moritz RL, Omenn GS, Pirmohamed M, Hood L. Identification of Organ-Enriched Protein Biomarkers of Acute Liver Injury by Targeted Quantitative Proteomics of Blood in Acetaminophen- and Carbon-Tetrachloride-Treated Mouse Models and Acetaminophen Overdose Patients. J Proteome Res 2016; 15:3724-3740. [PMID: 27575953 DOI: 10.1021/acs.jproteome.6b00547] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Organ-enriched blood proteins, those produced primarily in one organ and secreted or exported to the blood, potentially afford a powerful and specific approach to assessing diseases in their cognate organs. We demonstrate that quantification of organ-enriched proteins in the blood offers a new strategy to find biomarkers for diagnosis and assessment of drug-induced liver injury (and presumably the assessment of other liver diseases). We used selected reaction monitoring (SRM) mass spectrometry to quantify 81 liver-enriched proteins plus three aminotransferases (ALT1, AST1, and AST2) in plasma of C57BL/6J and NOD/ShiLtJ mice exposed to acetaminophen or carbon tetrachloride. Plasma concentrations of 49 liver-enriched proteins were perturbed significantly in response to liver injury induced by one or both toxins. We validated four of these toxin-responsive proteins (ALDOB, ASS1, BHMT, and GLUD1) by Western blotting. By both assays, these four proteins constitute liver injury markers superior to currently employed markers such as ALT and AST. A similar approach was also successful in human serum where we had analyzed 66 liver-enriched proteins in acetaminophen overdose patients. Of these, 23 proteins were elevated in patients; 15 of 23 overlapped with the concentration-increased proteins in the mouse study. A combination of 5 human proteins, AGXT, ALDOB, CRP, FBP1, and MMP9, provides the best diagnostic performance to distinguish acetaminophen overdose patients from controls (sensitivity: 0.85, specificity: 0.84, accuracy: 85%). These five blood proteins are candidates for detecting acetaminophen-induced liver injury using next-generation diagnostic devices (e.g, microfluidic ELISA assays).
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Brownstein CA, Beggs AH, Homer N, Merriman B, Yu TW, Flannery KC, DeChene ET, Towne MC, Savage SK, Price EN, Holm IA, Luquette LJ, Lyon E, Majzoub J, Neupert P, McCallie D, Szolovits P, Willard HF, Mendelsohn NJ, Temme R, Finkel RS, Yum SW, Medne L, Sunyaev SR, Adzhubey I, Cassa CA, de Bakker PIW, Duzkale H, Dworzyński P, Fairbrother W, Francioli L, Funke BH, Giovanni MA, Handsaker RE, Lage K, Lebo MS, Lek M, Leshchiner I, MacArthur DG, McLaughlin HM, Murray MF, Pers TH, Polak PP, Raychaudhuri S, Rehm HL, Soemedi R, Stitziel NO, Vestecka S, Supper J, Gugenmus C, Klocke B, Hahn A, Schubach M, Menzel M, Biskup S, Freisinger P, Deng M, Braun M, Perner S, Smith RJH, Andorf JL, Huang J, Ryckman K, Sheffield VC, Stone EM, Bair T, Black-Ziegelbein EA, Braun TA, Darbro B, DeLuca AP, Kolbe DL, Scheetz TE, Shearer AE, Sompallae R, Wang K, Bassuk AG, Edens E, Mathews K, Moore SA, Shchelochkov OA, Trapane P, Bossler A, Campbell CA, Heusel JW, Kwitek A, Maga T, Panzer K, Wassink T, Van Daele D, Azaiez H, Booth K, Meyer N, Segal MM, Williams MS, Tromp G, White P, Corsmeier D, Fitzgerald-Butt S, Herman G, Lamb-Thrush D, McBride KL, Newsom D, Pierson CR, Rakowsky AT, Maver A, Lovrečić L, Palandačić A, Peterlin B, Torkamani A, Wedell A, Huss M, Alexeyenko A, Lindvall JM, Magnusson M, Nilsson D, Stranneheim H, Taylan F, Gilissen C, Hoischen A, van Bon B, Yntema H, Nelen M, Zhang W, Sager J, Zhang L, Blair K, Kural D, Cariaso M, Lennon GG, Javed A, Agrawal S, Ng PC, Sandhu KS, Krishna S, Veeramachaneni V, Isakov O, Halperin E, Friedman E, Shomron N, Glusman G, Roach JC, Caballero J, Cox HC, Mauldin D, Ament SA, Rowen L, Richards DR, San Lucas FA, Gonzalez-Garay ML, Caskey CT, Bai Y, Huang Y, Fang F, Zhang Y, Wang Z, Barrera J, Garcia-Lobo JM, González-Lamuño D, Llorca J, Rodriguez MC, Varela I, Reese MG, De La Vega FM, Kiruluta E, Cargill M, Hart RK, Sorenson JM, Lyon GJ, Stevenson DA, Bray BE, Moore BM, Eilbeck K, Yandell M, Zhao H, Hou L, Chen X, Yan X, Chen M, Li C, Yang C, Gunel M, Li P, Kong Y, Alexander AC, Albertyn ZI, Boycott KM, Bulman DE, Gordon PMK, Innes AM, Knoppers BM, Majewski J, Marshall CR, Parboosingh JS, Sawyer SL, Samuels ME, Schwartzentruber J, Kohane IS, Margulies DM. An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge. Genome Biol 2014; 15:R53. [PMID: 24667040 PMCID: PMC4073084 DOI: 10.1186/gb-2014-15-3-r53] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Accepted: 03/25/2014] [Indexed: 12/30/2022] Open
Abstract
Background There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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Abstract
The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called 'big science' - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project.
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Roach JC, Glusman G, Smit AF, Huff CD, Hubley R, Shannon PT, Rowen L, Pant KP, Goodman N, Bamshad M, Shendure J, Drmanac R, Jorde LB, Hood L, Galas DJ. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 2010; 328:636-9. [PMID: 20220176 PMCID: PMC3037280 DOI: 10.1126/science.1186802] [Citation(s) in RCA: 745] [Impact Index Per Article: 49.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of approximately 1.1 x 10(-8) per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.
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Dishaw LJ, Mueller MG, Gwatney N, Cannon JP, Haire RN, Litman RT, Amemiya CT, Ota T, Rowen L, Glusman G, Litman GW. Genomic complexity of the variable region-containing chitin-binding proteins in amphioxus. BMC Genet 2008; 9:78. [PMID: 19046437 PMCID: PMC2632668 DOI: 10.1186/1471-2156-9-78] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2008] [Accepted: 12/01/2008] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND The variable region-containing chitin-binding proteins (VCBPs) are found in protochordates and consist of two tandem immunoglobulin variable (V)-type domains and a chitin-binding domain. We previously have shown that these polymorphic genes, which primarily are expressed in the gut, exhibit characteristics of immune genes. In this report, we describe VCBP genomic organization and characterize adjacent and intervening genetic features which may influence both their polymorphism and complex transcriptional repertoire. RESULTS VCBP genes 1, 2, 4, and 5 are encoded in a single contiguous gene-rich chromosomal region and VCBP3 is encoded in a separate locus. The VCBPs exhibit extensive haplotype variation, including copy number variation (CNV), indel polymorphism and a markedly elevated variation in repeat type and density. In at least one haplotype, inverted repeats occur more frequently than elsewhere in the genome. Multi-animal cDNA screening, as well as transcriptional profilingusing a novel transfection system, suggests that haplotype-specific transcriptional variants may contribute to VCBP genetic diversity. CONCLUSION The availability of the Branchiostoma floridae genome (Joint Genome Institute, Brafl1), along with BAC and PAC screening and sequencing described here, reveal that the relatively limited number of VCBP genes present in the amphioxus genome exhibit exceptionally high haplotype variation. These VCBP haplotypes contribute a diverse pool of allelic variants, which includes gene copy number variation, pseudogenes, and other polymorphisms, while contributing secondary effects on gene transcription as well.
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David-Fung ES, Butler R, Buzi G, Yui MA, Diamond RA, Anderson MK, Rowen L, Rothenberg EV. Transcription factor expression dynamics of early T-lymphocyte specification and commitment. Dev Biol 2008; 325:444-67. [PMID: 19013443 DOI: 10.1016/j.ydbio.2008.10.021] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2008] [Accepted: 10/17/2008] [Indexed: 12/15/2022]
Abstract
Mammalian T lymphocytes are a prototype for development from adult pluripotent stem cells. While T-cell specification is driven by Notch signaling, T-lineage commitment is only finalized after prolonged Notch activation. However, no T-lineage specific regulatory factor has been reported that mediates commitment. We used a gene-discovery approach to identify additional candidate T-lineage transcription factors and characterized expression of >100 regulatory genes in early T-cell precursors using realtime RT-PCR. These regulatory genes were also monitored in multilineage precursors as they entered T-cell or non-T-cell pathways in vitro; in non-T cells ex vivo; and in later T-cell developmental stages after lineage commitment. At least three major expression patterns were observed. Transcription factors in the largest group are expressed at relatively stable levels throughout T-lineage specification as a legacy from prethymic precursors, with some continuing while others are downregulated after commitment. Another group is highly expressed in the earliest stages only, and is downregulated before or during commitment. Genes in a third group undergo upregulation at one of three distinct transitions, suggesting a positive regulatory cascade. However, the transcription factors induced during commitment are not T-lineage specific. Different members of the same transcription factor family can follow opposite trajectories during specification and commitment, while factors co-expressed early can be expressed in divergent patterns in later T-cell development. Some factors reveal new regulatory distinctions between alphabeta and gammadelta T-lineage differentiation. These results show that T-cell identity has an essentially complex regulatory basis and provide a detailed framework for regulatory network modeling of T-cell specification.
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Hood L, Rowen L, Galas DJ, Aitchison JD. Systems biology at the Institute for Systems Biology. BRIEFINGS IN FUNCTIONAL GENOMICS AND PROTEOMICS 2008; 7:239-48. [PMID: 18579616 DOI: 10.1093/bfgp/eln027] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Systems biology represents an experimental approach to biology that attempts to study biological systems in a holistic rather than an atomistic manner. Ideally this involves gathering dynamic and global data sets as well as phenotypic data from different levels of the biological information hierarchy, integrating them and modeling them graphically and/or mathematically to generate mechanistic explanations for the emergent systems properties. This requires that the biological frontiers drive the development of new measurement and visualization technologies and the pioneering of new computational and mathematical tools-all of which requires a cross-disciplinary environment composed of biologists, chemists, computer scientists, engineers, mathematicians, physicists, and physicians speaking common discipline languages. The Institute for Systems Biology has aspired to pioneer and seamlessly integrate each of these concepts.
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Tydell CC, David-Fung ES, Moore JE, Rowen L, Taghon T, Rothenberg EV. Molecular dissection of prethymic progenitor entry into the T lymphocyte developmental pathway. THE JOURNAL OF IMMUNOLOGY 2007; 179:421-38. [PMID: 17579063 DOI: 10.4049/jimmunol.179.1.421] [Citation(s) in RCA: 78] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Notch signaling activates T lineage differentiation from hemopoietic progenitors, but relatively few regulators that initiate this program have been identified, e.g., GATA3 and T cell factor-1 (TCF-1) (gene name Tcf7). To identify additional regulators of T cell specification, a cDNA library from mouse Pro-T cells was screened for genes that are specifically up-regulated in intrathymic T cell precursors as compared with myeloid progenitors. Over 90 genes of interest were identified, and 35 of 44 tested were confirmed to be more highly expressed in T lineage precursors relative to precursors of B and/or myeloid lineage. To a remarkable extent, however, expression of these T lineage-enriched genes, including zinc finger transcription factor, helicase, and signaling adaptor genes, was also shared by stem cells (Lin(-)Sca-1(+)Kit(+)CD27(-)) and multipotent progenitors (Lin(-)Sca-1(+)Kit(+)CD27(+)), although down-regulated in other lineages. Thus, a major fraction of these early T lineage genes are a regulatory legacy from stem cells. The few genes sharply up-regulated between multipotent progenitors and Pro-T cell stages included those encoding transcription factors Bcl11b, TCF-1 (Tcf7), and HEBalt, Notch target Deltex1, Deltex3L, Fkbp5, Eva1, and Tmem131. Like GATA3 and Deltex1, Bcl11b, Fkbp5, and Eva1 were dependent on Notch/Delta signaling for induction in fetal liver precursors, but only Bcl11b and HEBalt were up-regulated between the first two stages of intrathymic T cell development (double negative 1 and double negative 2) corresponding to T lineage specification. Bcl11b was uniquely T lineage restricted and induced by Notch/Delta signaling specifically upon entry into the T lineage differentiation pathway.
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Zody MC, Garber M, Sharpe T, Young SK, Rowen L, O'Neill K, Whittaker CA, Kamal M, Chang JL, Cuomo CA, Dewar K, FitzGerald MG, Kodira CD, Madan A, Qin S, Yang X, Abbasi N, Abouelleil A, Arachchi HM, Baradarani L, Birditt B, Bloom S, Bloom T, Borowsky ML, Burke J, Butler J, Cook A, DeArellano K, DeCaprio D, Dorris L, Dors M, Eichler EE, Engels R, Fahey J, Fleetwood P, Friedman C, Gearin G, Hall JL, Hensley G, Johnson E, Jones C, Kamat A, Kaur A, Locke DP, Madan A, Munson G, Jaffe DB, Lui A, Macdonald P, Mauceli E, Naylor JW, Nesbitt R, Nicol R, O'Leary SB, Ratcliffe A, Rounsley S, She X, Sneddon KMB, Stewart S, Sougnez C, Stone SM, Topham K, Vincent D, Wang S, Zimmer AR, Birren BW, Hood L, Lander ES, Nusbaum C. Analysis of the DNA sequence and duplication history of human chromosome 15. Nature 2006; 440:671-5. [PMID: 16572171 DOI: 10.1038/nature04601] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2005] [Accepted: 01/26/2006] [Indexed: 11/09/2022]
Abstract
Here we present a finished sequence of human chromosome 15, together with a high-quality gene catalogue. As chromosome 15 is one of seven human chromosomes with a high rate of segmental duplication, we have carried out a detailed analysis of the duplication structure of the chromosome. Segmental duplications in chromosome 15 are largely clustered in two regions, on proximal and distal 15q; the proximal region is notable because recombination among the segmental duplications can result in deletions causing Prader-Willi and Angelman syndromes. Sequence analysis shows that the proximal and distal regions of 15q share extensive ancient similarity. Using a simple approach, we have been able to reconstruct many of the events by which the current duplication structure arose. We find that most of the intrachromosomal duplications seem to share a common ancestry. Finally, we demonstrate that some remaining gaps in the genome sequence are probably due to structural polymorphisms between haplotypes; this may explain a significant fraction of the gaps remaining in the human genome.
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Cameron RA, Rowen L, Nesbitt R, Bloom S, Rast JP, Berney K, Arenas-Mena C, Martinez P, Lucas S, Richardson PM, Davidson EH, Peterson KJ, Hood L. Unusual gene order and organization of the sea urchin hox cluster. JOURNAL OF EXPERIMENTAL ZOOLOGY PART B-MOLECULAR AND DEVELOPMENTAL EVOLUTION 2006; 306:45-58. [PMID: 16116652 DOI: 10.1002/jez.b.21070] [Citation(s) in RCA: 96] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
While the highly consistent gene order and axial colinear patterns of expression seem to be a feature of vertebrate hox gene clusters, this pattern may be less well conserved across the rest of the bilaterians. We report the first deuterostome instance of an intact hox cluster with a unique gene order where the paralog groups are not expressed in a sequential manner. The finished sequence from BAC clones from the genome of the sea urchin, Strongylocentrotus purpuratus, reveals a gene order wherein the anterior genes (Hox1, Hox2 and Hox3) lie nearest the posterior genes in the cluster such that the most 3' gene is Hox5. (The gene order is 5'-Hox1, 2, 3, 11/13c, 11/13b, 11/13a, 9/10, 8, 7, 6, 5-3'.) The finished sequence result is corroborated by restriction mapping evidence and BAC-end scaffold analyses. Comparisons with a putative ancestral deuterostome Hox gene cluster suggest that the rearrangements leading to the sea urchin gene order were many and complex.
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Roach JC, Glusman G, Rowen L, Kaur A, Purcell MK, Smith KD, Hood LE, Aderem A. The evolution of vertebrate Toll-like receptors. Proc Natl Acad Sci U S A 2005; 102:9577-82. [PMID: 15976025 PMCID: PMC1172252 DOI: 10.1073/pnas.0502272102] [Citation(s) in RCA: 847] [Impact Index Per Article: 42.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The complete sequences of Takifugu Toll-like receptor (TLR) loci and gene predictions from many draft genomes enable comprehensive molecular phylogenetic analysis. Strong selective pressure for recognition of and response to pathogen-associated molecular patterns has maintained a largely unchanging TLR recognition in all vertebrates. There are six major families of vertebrate TLRs. This repertoire is distinct from that of invertebrates. TLRs within a family recognize a general class of pathogen-associated molecular patterns. Most vertebrates have exactly one gene ortholog for each TLR family. The family including TLR1 has more species-specific adaptations than other families. A major family including TLR11 is represented in humans only by a pseudogene. Coincidental evolution plays a minor role in TLR evolution. The sequencing phase of this study produced finished genomic sequences for the 12 Takifugu rubripes TLRs. In addition, we have produced >70 gene models, including sequences from the opossum, chicken, frog, dog, sea urchin, and sea squirt.
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Rowen L, Williams E, Glusman G, Linardopoulou E, Friedman C, Ahearn ME, Seto J, Boysen C, Qin S, Wang K, Kaur A, Bloom S, Hood L, Trask BJ. Interchromosomal segmental duplications explain the unusual structure of PRSS3, the gene for an inhibitor-resistant trypsinogen. Mol Biol Evol 2005; 22:1712-20. [PMID: 15901841 DOI: 10.1093/molbev/msi166] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Homo sapiens possess several trypsinogen or trypsinogen-like genes of which three (PRSS1, PRSS2, and PRSS3) produce functional trypsins in the digestive tract. PRSS1 and PRSS2 are located on chromosome 7q35, while PRSS3 is found on chromosome 9p13. Here, we report a variation of the theme of new gene creation by duplication: the PRSS3 gene was formed by segmental duplications originating from chromosomes 7q35 and 11q24. As a result, PRSS3 transcripts display two variants of exon 1. The PRSS3 transcript whose gene organization most resembles PRSS1 and PRSS2 encodes a functional protein originally named mesotrypsinogen. The other variant is a fusion transcript, called trypsinogen IV. We show that the first exon of trypsinogen IV is derived from the noncoding first exon of LOC120224, a chromosome 11 gene. LOC120224 codes for a widely conserved transmembrane protein of unknown function. Comparative analyses suggest that these interchromosomal duplications occurred after the divergence of Old World monkeys and hominids. PRSS3 transcripts consist of a mixed population of mRNAs, some expressed in the pancreas and encoding an apparently functional trypsinogen and others of unknown function expressed in brain and a variety of other tissues. Analysis of the selection pressures acting on the trypsinogen gene family shows that, while the apparently functional genes are under mild to strong purifying selection overall, a few residues appear under positive selection. These residues could be involved in interactions with inhibitors.
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Smink LJ, Helton EM, Healy BC, Cavnor CC, Lam AC, Flamez D, Burren OS, Wang Y, Dolman GE, Burdick DB, Everett VH, Glusman G, Laneri D, Rowen L, Schuilenburg H, Walker NM, Mychaleckyj J, Wicker LS, Eizirik DL, Todd JA, Goodman N. T1DBase, a community web-based resource for type 1 diabetes research. Nucleic Acids Res 2005; 33:D544-9. [PMID: 15608258 PMCID: PMC540049 DOI: 10.1093/nar/gki095] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
T1DBase (http://T1DBase.org) is a public website and database that supports the type 1 diabetes (T1D) research community. The site is currently focused on the molecular genetics and biology of T1D susceptibility and pathogenesis. It includes the following datasets: annotated genome sequence for human, rat and mouse; information on genetically identified T1D susceptibility regions in human, rat and mouse, and genetic linkage and association studies pertaining to T1D; descriptions of NOD mouse congenic strains; the Beta Cell Gene Expression Bank, which reports expression levels of genes in beta cells under various conditions, and annotations of gene function in beta cells; data on gene expression in a variety of tissues and organs; and biological pathways from KEGG and BioCarta. Tools on the site include the GBrowse genome browser, site-wide context dependent search, Connect-the-Dots for connecting gene and other identifiers from multiple data sources, Cytoscape for visualizing and analyzing biological networks, and the GESTALT workbench for genome annotation. All data are open access and all software is open source.
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Roginski RS, Mohan Raj BK, Birditt B, Rowen L. The human GRINL1A gene defines a complex transcription unit, an unusual form of gene organization in eukaryotes. Genomics 2005; 84:265-76. [PMID: 15233991 DOI: 10.1016/j.ygeno.2004.04.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2003] [Accepted: 04/07/2004] [Indexed: 11/18/2022]
Abstract
Sequencing of genomic DNA and cloned transcripts from the 200-kb human GRINL1A gene on chromosome 15 revealed a complex gene structure comprising at least 28 exons. In one gene model, transcription begins at exon 1 and ends at exon 15b. Another gene model begins transcription at exon 20 and terminates at exon 23, 24, or 28. In a third gene model, transcription begins at exon 1 and ends at exon 23, thus conjoining two apparently discrete genes into a third combined gene. Exon 15 can function as a terminating exon or as an alternatively spliced internal exon, or it can be skipped altogether. Exons 11, 14, 15a, 16, 17, 18, 19, 20a, and 20f are found only in transcripts that do not terminate at exon 15b. Combined transcripts that convert two genes into a third provide evidence for an unusual form of gene organization and expression that we call the complex transcription unit (CTU). Organization of exons into a CTU increases the extractable information content of a segment of genomic DNA and constitutes a potentially significant mechanism for augmenting the proteome of a genome.
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Glusman G, Kaur A, Hood L, Rowen L. An enigmatic fourth runt domain gene in the fugu genome: ancestral gene loss versus accelerated evolution. BMC Evol Biol 2004; 4:43. [PMID: 15527507 PMCID: PMC533870 DOI: 10.1186/1471-2148-4-43] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2004] [Accepted: 11/04/2004] [Indexed: 11/10/2022] Open
Abstract
Background The runt domain transcription factors are key regulators of developmental processes in bilaterians, involved both in cell proliferation and differentiation, and their disruption usually leads to disease. Three runt domain genes have been described in each vertebrate genome (the RUNX gene family), but only one in other chordates. Therefore, the common ancestor of vertebrates has been thought to have had a single runt domain gene. Results Analysis of the genome draft of the fugu pufferfish (Takifugu rubripes) reveals the existence of a fourth runt domain gene, FrRUNT, in addition to the orthologs of human RUNX1, RUNX2 and RUNX3. The tiny FrRUNT packs six exons and two putative promoters in just 3 kb of genomic sequence. The first exon is located within an intron of FrSUPT3H, the ortholog of human SUPT3H, and the first exon of FrSUPT3H resides within the first intron of FrRUNT. The two gene structures are therefore "interlocked". In the human genome, SUPT3H is instead interlocked with RUNX2. FrRUNT has no detectable ortholog in the genomes of mammals, birds or amphibians. We consider alternative explanations for an apparent contradiction between the phylogenetic data and the comparison of the genomic neighborhoods of human and fugu runt domain genes. We hypothesize that an ancient RUNT locus was lost in the tetrapod lineage, together with FrFSTL6, a member of a novel family of follistatin-like genes. Conclusions Our results suggest that the runt domain family may have started expanding in chordates much earlier than previously thought, and exemplify the importance of detailed analysis of whole-genome draft sequence to provide new insights into gene evolution.
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Graveley BR, Kaur A, Gunning D, Zipursky SL, Rowen L, Clemens JC. The organization and evolution of the dipteran and hymenopteran Down syndrome cell adhesion molecule (Dscam) genes. RNA (NEW YORK, N.Y.) 2004; 10:1499-506. [PMID: 15383675 PMCID: PMC1370636 DOI: 10.1261/rna.7105504] [Citation(s) in RCA: 67] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The Drosophila melanogaster Down syndrome cell adhesion molecule (Dscam) gene encodes an axon guidance receptor and can generate 38,016 different isoforms via the alternative splicing of 95 variable exons. Dscam contains 10 immunoglobulin (Ig), six Fibronectin type III, a transmembrane (TM), and cytoplasmic domains. The different Dscam isoforms vary in the amino acid sequence of three of the Ig domains and the TM domain. Here, we have compared the organization of the Dscam gene from three members of the Drosophila subgenus (D. melanogaster, D. pseudoobscura, and D. virilis), the mosquito Anopheles gambiae, and the honeybee Apis mellifera. Each of these organisms contains numerous alternative exons and can potentially synthesize tens of thousands of isoforms. Interestingly, most of the alternative exons in one species are more similar to one another than to the corresponding alternative exons in the other species. These observations provide strong evidence that many of the alternative exons have arisen by reiterative exon duplication and deletion events. In addition, these findings suggest that the expression of a large Dscam repertoire is more important for the development and function of the insect nervous system than the actual sequence of each isoform.
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Daza-Vamenta R, Glusman G, Rowen L, Guthrie B, Geraghty DE. Genetic divergence of the rhesus macaque major histocompatibility complex. Genome Res 2004; 14:1501-15. [PMID: 15289473 PMCID: PMC509259 DOI: 10.1101/gr.2134504] [Citation(s) in RCA: 172] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The major histocompatibility complex (MHC) is comprised of the class I, class II, and class III regions, including the MHC class I and class II genes that play a primary role in the immune response and serve as an important model in studies of primate evolution. Although nonhuman primates contribute significantly to comparative human studies, relatively little is known about the genetic diversity and genomics underlying nonhuman primate immunity. To address this issue, we sequenced a complete rhesus macaque MHC spanning over 5.3 Mb, and obtained an additional 2.3 Mb from a second haplotype, including class II and portions of class I and class III. A major expansion of from six class I genes in humans to as many as 22 active MHC class I genes in rhesus and levels of sequence divergence some 10-fold higher than a similar human comparison were found, averaging from 2% to 6% throughout extended portions of class I and class II. These data pose new interpretations of the evolutionary constraints operating between MHC diversity and T-cell selection by contrasting with models predicting an optimal number of antigen presenting genes. For the clinical model, these data and derivative genetic tools can be implemented in ongoing genetic and disease studies that involve the rhesus macaque.
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Xie T, Rowen L, Aguado B, Ahearn ME, Madan A, Qin S, Campbell RD, Hood L. Analysis of the gene-dense major histocompatibility complex class III region and its comparison to mouse. Genome Res 2004; 13:2621-36. [PMID: 14656967 PMCID: PMC403804 DOI: 10.1101/gr.1736803] [Citation(s) in RCA: 80] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
In mammals, the Major Histocompatibility Complex class I and II gene clusters are separated by an approximately 700-kb stretch of sequence called the MHC class III region, which has been associated with susceptibility to numerous diseases. To facilitate understanding of this medically important and architecturally interesting portion of the genome, we have sequenced and analyzed both the human and mouse class III regions. The cross-species comparison has facilitated the identification of 60 genes in human and 61 in mouse, including a potential RNA gene for which the introns are more conserved across species than the exons. Delineation of global organization, gene structure, alternative splice forms, protein similarities, and potential cis-regulatory elements leads to several conclusions: (1) The human MHC class III region is the most gene-dense region of the human genome: >14% of the sequence is coding, approximately 72% of the region is transcribed, and there is an average of 8.5 genes per 100 kb. (2) Gene sizes, number of exons, and intergenic distances are for the most part similar in both species, implying that interspersed repeats have had little impact in disrupting the tight organization of this densely packed set of genes. (3) The region contains a heterogeneous mixture of genes, only a few of which have a clearly defined and proven function. Although many of the genes are of ancient origin, some appear to exist only in mammals and fish, implying they might be specific to vertebrates. (4) Conserved noncoding sequences are found primarily in or near the 5'-UTR or the first intron of genes, and seldom in the intergenic regions. Many of these conserved blocks are likely to be cis-regulatory elements.
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Gan TI, Rowen L, Nesbitt R, Roe BA, Wu H, Hu P, Yao Z, Kim UJ, O'Sickey T, Bina M. Genomic organization of human TCF12 gene and spliced mRNA variants producing isoforms of transcription factor HTF4. Cytogenet Genome Res 2003; 98:245-8. [PMID: 12826747 DOI: 10.1159/000071042] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2003] [Accepted: 01/13/2003] [Indexed: 11/19/2022] Open
Abstract
The human TCF12 gene, mapping to 15q21, encodes the helix-loop-helix transcription factor 4 (HTF4). A detailed analysis of this genomic region established the organization of the TCF12 gene. The gene includes 21 exons and is significantly larger than an average human gene. Preceding the second exon, two alternative acceptor sites for mRNA splicing yield two distinguishable transcripts (HTF4a and HTF4b) which differ in their 5' untranslated region but share identical coding sequences. Differential utilization of exon 15 in the TCF12 gene may reflect a mechanism producing a cell-type-specific protein (HTF4c). In addition, intron 5 in the TCF12 gene corresponds to the region involved in a translocation, t(9;15)(q22;q21), that results in a form of extraskeletal myxoid chondrosarcoma.
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