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140 results on '"Goddard, Michael"'

6. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data

Author

Wainschtein, Pierrick, Jain, Deepti, Zheng, Zhili, Cupples, L Adrienne, Shadyab, Aladdin H, McKnight, Barbara, Shoemaker, Benjamin M, Mitchell, Braxton D, Psaty, Bruce M, Kooperberg, Charles, Liu, Ching-Ti, Albert, Christine M, Roden, Dan, Chasman, Daniel I, Darbar, Dawood, Lloyd-Jones, Donald M, Arnett, Donna K, Regan, Elizabeth A, Boerwinkle, Eric, Rotter, Jerome I, O’Connell, Jeffrey R, Yanek, Lisa R, de Andrade, Mariza, Allison, Matthew A, McDonald, Merry-Lynn N, Chung, Mina K, Fornage, Myriam, Chami, Nathalie, Smith, Nicholas L, Ellinor, Patrick T, Vasan, Ramachandran S, Mathias, Rasika A, Loos, Ruth JF, Rich, Stephen S, Lubitz, Steven A, Heckbert, Susan R, Redline, Susan, Guo, Xiuqing, Chen, Y-D Ida, Laurie, Cecelia A, Hernandez, Ryan D, McGarvey, Stephen T, Goddard, Michael E, Laurie, Cathy C, North, Kari E, Lange, Leslie A, Weir, Bruce S, Yengo, Loic, Yang, Jian, and Visscher, Peter M

Subjects
Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Alleles, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Multifactorial Inheritance, Polymorphism, Single Nucleotide, TOPMed Anthropometry Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Published
2022

7. Assortative mating biases marker-based heritability estimators

Author

Border, Richard, O’Rourke, Sean, de Candia, Teresa, Goddard, Michael E, Visscher, Peter M, Yengo, Loic, Jones, Matt, and Keller, Matthew C

Subjects
Biological Sciences, Genetics, Biological Psychology, Statistics, Mathematical Sciences, Psychology, Algorithms, Bias, Computer Simulation, Female, Genetics, Population, Genome-Wide Association Study, Humans, Likelihood Functions, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Reproduction
Abstract

Many traits are subject to assortative mating, with recent molecular genetic findings confirming longstanding theoretical predictions that assortative mating induces long range dependence across causal variants. However, all marker-based heritability estimators implicitly assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments and likelihood-based estimators are biased in the presence of assortative mating and derive corrected heritability estimators for traits subject to assortment. Finally, we demonstrate that the empirical patterns of estimates across methods and sample sizes for real traits subject to assortative mating are congruent with expected assortative mating-induced biases. For example, marker-based heritability estimates for height are 14% - 23% higher than corrected estimates using UK Biobank data.

Published
2022

9. A saturated map of common genetic variants associated with human height

Author

Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U., Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D., Graham, Sarah E., Mukamel, Ronen E., Spracklen, Cassandra N., Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H., Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E., Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S., Akiyama, Masato, Allison, Matthew A., Alvarez, Marcus, Andersen, Mette K., Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F., Bollepalli, Sailalitha, Bonnycastle, Lori L., Bork-Jensen, Jette, Bradfield, Jonathan P., Bradford, Yuki, Braund, Peter S., Brody, Jennifer A., Burgdorf, Kristoffer S., Cade, Brian E., Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E. Warwick, Degenhard, Frauke, Delgado, Graciela E., Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B., Engmann, Jorgen E., Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D., Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E., Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P., Goel, Anuj, Gordon, Scott D., Gorski, Mathias, Grove, Jakob, Guo, Xiuqing, Gustafsson, Stefan, Haessler, Jeffrey, Hansen, Thomas F., Havulinna, Aki S., Haworth, Simon J., He, Jing, Heard-Costa, Nancy, Hebbar, Prashantha, Hindy, George, Ho, Yuk-Lam A., Hofer, Edith, Holliday, Elizabeth, Horn, Katrin, Hornsby, Whitney E., Hottenga, Jouke-Jan, Huang, Hongyan, Huang, Jie, Huerta-Chagoya, Alicia, Huffman, Jennifer E., Hung, Yi-Jen, Huo, Shaofeng, Hwang, Mi Yeong, Iha, Hiroyuki, Ikeda, Daisuke D., Isono, Masato, Jackson, Anne U., Jäger, Susanne, Jansen, Iris E., Johansson, Ingegerd, Jonas, Jost B., Jonsson, Anna, Jørgensen, Torben, Kalafati, Ioanna-Panagiota, Kanai, Masahiro, Kanoni, Stavroula, Kårhus, Line L., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kawaguchi, Takahisa, Kember, Rachel L., Kentistou, Katherine A., Kim, Han-Na, Kim, Young Jin, Kleber, Marcus E., Knol, Maria J., Kurbasic, Azra, Lauzon, Marie, Le, Phuong, Lea, Rodney, Lee, Jong-Young, Leonard, Hampton L., Li, Shengchao A., Li, Xiaohui, Li, Xiaoyin, Liang, Jingjing, Lin, Honghuang, Lin, Shih-Yi, Liu, Jun, Liu, Xueping, Lo, Ken Sin, Long, Jirong, Lores-Motta, Laura, Luan, Jian’an, Lyssenko, Valeriya, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamakou, Vasiliki, Mangino, Massimo, Manichaikul, Ani, Marten, Jonathan, Mattheisen, Manuel, Mavarani, Laven, McDaid, Aaron F., Meidtner, Karina, Melendez, Tori L., Mercader, Josep M., Milaneschi, Yuri, Miller, Jason E., Millwood, Iona Y., Mishra, Pashupati P., Mitchell, Ruth E., Møllehave, Line T., Morgan, Anna, Mucha, Soeren, Munz, Matthias, Nakatochi, Masahiro, Nelson, Christopher P., Nethander, Maria, Nho, Chu Won, Nielsen, Aneta A., Nolte, Ilja M., Nongmaithem, Suraj S., Noordam, Raymond, Ntalla, Ioanna, Nutile, Teresa, Pandit, Anita, Christofidou, Paraskevi, Pärna, Katri, Pauper, Marc, Petersen, Eva R. B., Petersen, Liselotte V., Pitkänen, Niina, Polašek, Ozren, Poveda, Alaitz, Preuss, Michael H., Pyarajan, Saiju, Raffield, Laura M., Rakugi, Hiromi, Ramirez, Julia, Rasheed, Asif, Raven, Dennis, Rayner, Nigel W., Riveros, Carlos, Rohde, Rebecca, Ruggiero, Daniela, Ruotsalainen, Sanni E., Ryan, Kathleen A., Sabater-Lleal, Maria, Saxena, Richa, Scholz, Markus, Sendamarai, Anoop, Shen, Botong, Shi, Jingchunzi, Shin, Jae Hun, Sidore, Carlo, Sitlani, Colleen M., Slieker, Roderick C., Smit, Roelof A. J., Smith, Albert V., Smith, Jennifer A., Smyth, Laura J., Southam, Lorraine, Steinthorsdottir, Valgerdur, Sun, Liang, Takeuchi, Fumihiko, Tallapragada, Divya Sri Priyanka, Taylor, Kent D., Tayo, Bamidele O., Tcheandjieu, Catherine, Terzikhan, Natalie, Tesolin, Paola, Teumer, Alexander, Theusch, Elizabeth, Thompson, Deborah J., Thorleifsson, Gudmar, Timmers, Paul R. H. J., Trompet, Stella, Turman, Constance, Vaccargiu, Simona, van der Laan, Sander W., van der Most, Peter J., van Klinken, Jan B., van Setten, Jessica, Verma, Shefali S., Verweij, Niek, Veturi, Yogasudha, Wang, Carol A., Wang, Chaolong, Wang, Lihua, Wang, Zhe, Warren, Helen R., Bin Wei, Wen, Wickremasinghe, Ananda R., Wielscher, Matthias, Wiggins, Kerri L., Winsvold, Bendik S., Wong, Andrew, Wu, Yang, Wuttke, Matthias, Xia, Rui, Xie, Tian, Yamamoto, Ken, Yang, Jingyun, Yao, Jie, Young, Hannah, Yousri, Noha A., Yu, Lei, Zeng, Lingyao, Zhang, Weihua, Zhang, Xinyuan, Zhao, Jing-Hua, Zhao, Wei, Zhou, Wei, Zimmermann, Martina E., Zoledziewska, Magdalena, Adair, Linda S., Adams, Hieab H. H., Aguilar-Salinas, Carlos A., Al-Mulla, Fahd, Arnett, Donna K., Asselbergs, Folkert W., Åsvold, Bjørn Olav, Attia, John, Banas, Bernhard, Bandinelli, Stefania, Bennett, David A., Bergler, Tobias, Bharadwaj, Dwaipayan, Biino, Ginevra, Bisgaard, Hans, Boerwinkle, Eric, Böger, Carsten A., Bønnelykke, Klaus, Boomsma, Dorret I., Børglum, Anders D., Borja, Judith B., Bouchard, Claude, Bowden, Donald W., Brandslund, Ivan, Brumpton, Ben, Buring, Julie E., Caulfield, Mark J., Chambers, John C., Chandak, Giriraj R., Chanock, Stephen J., Chaturvedi, Nish, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Ching-Yu, Christophersen, Ingrid E., Ciullo, Marina, Cole, John W., Collins, Francis S., Cooper, Richard S., Cruz, Miguel, Cucca, Francesco, Cupples, L. Adrienne, Cutler, Michael J., Damrauer, Scott M., Dantoft, Thomas M., de Borst, Gert J., de Groot, Lisette C. P. G. M., De Jager, Philip L., de Kleijn, Dominique P. V., Janaka de Silva, H., Dedoussis, George V., den Hollander, Anneke I., Du, Shufa, Easton, Douglas F., Elders, Petra J. M., Eliassen, A. Heather, Ellinor, Patrick T., Elmståhl, Sölve, Erdmann, Jeanette, Evans, Michele K., Fatkin, Diane, Feenstra, Bjarke, Feitosa, Mary F., Ferrucci, Luigi, Ford, Ian, Fornage, Myriam, Franke, Andre, Franks, Paul W., Freedman, Barry I., Gasparini, Paolo, Gieger, Christian, Girotto, Giorgia, Goddard, Michael E., Golightly, Yvonne M., Gonzalez-Villalpando, Clicerio, Gordon-Larsen, Penny, Grallert, Harald, Grant, Struan F. A., Grarup, Niels, Griffiths, Lyn, Gudnason, Vilmundur, Haiman, Christopher, Hakonarson, Hakon, Hansen, Torben, Hartman, Catharina A., Hattersley, Andrew T., Hayward, Caroline, Heckbert, Susan R., Heng, Chew-Kiat, Hengstenberg, Christian, Hewitt, Alex W., Hishigaki, Haretsugu, Hoyng, Carel B., Huang, Paul L., Huang, Wei, Hunt, Steven C., Hveem, Kristian, Hyppönen, Elina, Iacono, William G., Ichihara, Sahoko, Ikram, M. Arfan, Isasi, Carmen R., Jackson, Rebecca D., Jarvelin, Marjo-Riitta, Jin, Zi-Bing, Jöckel, Karl-Heinz, Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Kähönen, Mika, Kamatani, Yoichiro, Kang, Kui Dong, Kaprio, Jaakko, Kardia, Sharon L. R., Karpe, Fredrik, Kato, Norihiro, Kee, Frank, Kessler, Thorsten, Khera, Amit V., Khor, Chiea Chuen, Kiemeney, Lambertus A. L. M., Kim, Bong-Jo, Kim, Eung Kweon, Kim, Hyung-Lae, Kirchhof, Paulus, Kivimaki, Mika, Koh, Woon-Puay, Koistinen, Heikki A., Kolovou, Genovefa D., Kooner, Jaspal S., Kooperberg, Charles, Köttgen, Anna, Kovacs, Peter, Kraaijeveld, Adriaan, Kraft, Peter, Krauss, Ronald M., Kumari, Meena, Kutalik, Zoltan, Laakso, Markku, Lange, Leslie A., Langenberg, Claudia, Launer, Lenore J., Le Marchand, Loic, Lee, Hyejin, Lee, Nanette R., Lehtimäki, Terho, Li, Huaixing, Li, Liming, Lieb, Wolfgang, Lin, Xu, Lind, Lars, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Loeffler, Markus, London, Barry, Lubitz, Steven A., Lye, Stephen J., Mackey, David A., Mägi, Reedik, Magnusson, Patrik K. E., Marcus, Gregory M., Vidal, Pedro Marques, Martin, Nicholas G., März, Winfried, Matsuda, Fumihiko, McGarrah, Robert W., McGue, Matt, McKnight, Amy Jayne, Medland, Sarah E., Mellström, Dan, Metspalu, Andres, Mitchell, Braxton D., Mitchell, Paul, Mook-Kanamori, Dennis O., Morris, Andrew D., Mucci, Lorelei A., Munroe, Patricia B., Nalls, Mike A., Nazarian, Saman, Nelson, Amanda E., Neville, Matt J., Newton-Cheh, Christopher, Nielsen, Christopher S., Nöthen, Markus M., Ohlsson, Claes, Oldehinkel, Albertine J., Orozco, Lorena, Pahkala, Katja, Pajukanta, Päivi, Palmer, Colin N. A., Parra, Esteban J., Pattaro, Cristian, Pedersen, Oluf, Pennell, Craig E., Penninx, Brenda W. J. H., Perusse, Louis, Peters, Annette, Peyser, Patricia A., Porteous, David J., Posthuma, Danielle, Power, Chris, Pramstaller, Peter P., Province, Michael A., Qi, Qibin, Qu, Jia, Rader, Daniel J., Raitakari, Olli T., Ralhan, Sarju, Rallidis, Loukianos S., Rao, Dabeeru C., Redline, Susan, Reilly, Dermot F., Reiner, Alexander P., Rhee, Sang Youl, Ridker, Paul M., Rienstra, Michiel, Ripatti, Samuli, Ritchie, Marylyn D., Roden, Dan M., Rosendaal, Frits R., Rotter, Jerome I., Rudan, Igor, Rutters, Femke, Sabanayagam, Charumathi, Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sanghera, Dharambir K., Sattar, Naveed, Schmidt, Börge, Schmidt, Helena, Schmidt, Reinhold, Schulze, Matthias B., Schunkert, Heribert, Scott, Laura J., Scott, Rodney J., Sever, Peter, Shiroma, Eric J., Shoemaker, M. Benjamin, Shu, Xiao-Ou, Simonsick, Eleanor M., Sims, Mario, Singh, Jai Rup, Singleton, Andrew B., Sinner, Moritz F., Smith, J. Gustav, Snieder, Harold, Spector, Tim D., Stampfer, Meir J., Stark, Klaus J., Strachan, David P., ‘t Hart, Leen M., Tabara, Yasuharu, Tang, Hua, Tardif, Jean-Claude, Thanaraj, Thangavel A., Timpson, Nicholas J., Tönjes, Anke, Tremblay, Angelo, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Tusié-Luna, Maria-Teresa, Uitterlinden, Andre G., van Dam, Rob M., van der Harst, Pim, Van der Velde, Nathalie, van Duijn, Cornelia M., van Schoor, Natasja M., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Völzke, Henry, Wacher-Rodarte, Niels H., Walker, Mark, Wang, Ya Xing, Wareham, Nicholas J., Watanabe, Richard M., Watkins, Hugh, Weir, David R., Werge, Thomas M., Widen, Elisabeth, Wilkens, Lynne R., Willemsen, Gonneke, Willett, Walter C., Wilson, James F., Wong, Tien-Yin, Woo, Jeong-Taek, Wright, Alan F., Wu, Jer-Yuarn, Xu, Huichun, Yajnik, Chittaranjan S., Yokota, Mitsuhiro, Yuan, Jian-Min, Zeggini, Eleftheria, Zemel, Babette S., Zheng, Wei, Zhu, Xiaofeng, Zmuda, Joseph M., Zonderman, Alan B., Zwart, John-Anker, Chasman, Daniel I., Cho, Yoon Shin, Heid, Iris M., McCarthy, Mark I., Ng, Maggie C. Y., O’Donnell, Christopher J., Rivadeneira, Fernando, Thorsteinsdottir, Unnur, Sun, Yan V., Tai, E. Shyong, Boehnke, Michael, Deloukas, Panos, Justice, Anne E., Lindgren, Cecilia M., Loos, Ruth J. F., Mohlke, Karen L., North, Kari E., Stefansson, Kari, Walters, Robin G., Winkler, Thomas W., Young, Kristin L., Loh, Po-Ru, Yang, Jian, Esko, Tõnu, Assimes, Themistocles L., Auton, Adam, Abecasis, Goncalo R., Willer, Cristen J., Locke, Adam E., Berndt, Sonja I., Lettre, Guillaume, Frayling, Timothy M., Okada, Yukinori, Wood, Andrew R., Visscher, Peter M., and Hirschhorn, Joel N.

Published
2022
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11. Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility

Author

Forutan, Mehrnush, primary, Engle, Bailey N., additional, Chamberlain, Amanda J., additional, Ross, Elizabeth M., additional, Nguyen, Loan T., additional, D’Occhio, Michael J., additional, Snr, Alf Collins, additional, Kho, Elise A., additional, Fordyce, Geoffry, additional, Speight, Shannon, additional, Goddard, Michael E., additional, and Hayes, Ben J., additional

Published
2024
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21. The extracellular heparan sulfatase SULF2 limits myeloid IFNβ signaling and Th17 responses in inflammatory arthritis.

Author

Swart, Maarten, Redpath, Andia N., Ogbechi, Joy, Cardenas, Ryan, Topping, Louise, Compeer, Ewoud B., Goddard, Michael, Chanalaris, Anastasios, Williams, Richard, Brewer, Daniel S., Smart, Nicola, Monaco, Claudia, and Troeberg, Linda

Subjects
JOINT diseases, HEPARAN sulfate, BONE marrow, GROWTH factors, T helper cells, TYPE I interferons
Abstract

Heparan sulfate (HS) proteoglycans are important regulators of cellular responses to soluble mediators such as chemokines, cytokines and growth factors. We profiled changes in expression of genes encoding HS core proteins, biosynthesis enzymes and modifiers during macrophage polarisation, and found that the most highly regulated gene was Sulf2, an extracellular HS 6-O-sulfatase that was markedly downregulated in response to pro-inflammatory stimuli. We then generated Sulf2+/− bone marrow chimeric mice and examined inflammatory responses in antigen-induced arthritis, as a model of rheumatoid arthritis. Resolution of inflammation was impaired in myeloid Sulf2+/− chimeras, with elevated joint swelling and increased abundance of pro-arthritic Th17 cells in synovial tissue. Transcriptomic and in vitro analyses indicated that Sulf2 deficiency increased type I interferon signaling in bone marrow-derived macrophages, leading to elevated expression of the Th17-inducing cytokine IL6. This establishes that dynamic remodeling of HS by Sulf2 limits type I interferon signaling in macrophages, and so protects against Th17-driven pathology. [ABSTRACT FROM AUTHOR]

Published
2024
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22. A common regulatory haplotype doubles lactoferrin concentration in milk

Author

Lopdell, Thomas J., primary, Trevarton, Alexander J., additional, Moody, Janelle, additional, Prowse-Wilkins, Claire, additional, Knowles, Sarah, additional, Tiplady, Kathryn, additional, Chamberlain, Amanda J., additional, Goddard, Michael E., additional, Spelman, Richard J., additional, Lehnert, Klaus, additional, Snell, Russell G., additional, Davis, Stephen R., additional, and Littlejohn, Mathew D., additional

Published
2024
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23. The extracellular heparan sulfatase SULF2 limits myeloid IFNβ signaling and Th17 responses in inflammatory arthritis

Author

Swart, Maarten, primary, Redpath, Andia, additional, Ogbechi, Joy, additional, Cardenas, Ryan, additional, Topping, Louise, additional, Compeer, Ewoud B., additional, Goddard, Michael, additional, Chanalaris, Anastasios, additional, Williams, Richard, additional, Brewer, Daniel S., additional, Smart, Nicola, additional, Monaco, Claudia, additional, and Troeberg, Linda, additional

Published
2024
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24. Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations.

Author

Ghoreishifar, Mohammad, Chamberlain, Amanda J., Xiang, Ruidong, Prowse-Wilkins, Claire P., Lopdell, Thomas J., Littlejohn, Mathew D., Pryce, Jennie E., and Goddard, Michael E.

Subjects
GENE expression, LOCUS (Genetics), LINKAGE disequilibrium, NUCLEOTIDE sequence, IMMUNOPRECIPITATION, SUPPORT vector machines
Abstract

Background: Genome sequence variants affecting complex traits (quantitative trait loci, QTL) are enriched in functional regions of the genome, such as those marked by certain histone modifications. These variants are believed to influence gene expression. However, due to the linkage disequilibrium among nearby variants, pinpointing the precise location of QTL is challenging. We aimed to identify allele-specific binding (ASB) QTL (asbQTL) that cause variation in the level of histone modification, as measured by the height of peaks assayed by ChIP-seq (chromatin immunoprecipitation sequencing). We identified DNA sequences that predict the difference between alleles in ChIP-seq peak height in H3K4me3 and H3K27ac histone modifications in the mammary glands of cows. Results: We used a gapped k-mer support vector machine, a novel best linear unbiased prediction model, and a multiple linear regression model that combines the other two approaches to predict variant impacts on peak height. For each method, a subset of 1000 sites with the highest magnitude of predicted ASB was considered as candidate asbQTL. The accuracy of this prediction was measured by the proportion where the predicted direction matched the observed direction. Prediction accuracy ranged between 0.59 and 0.74, suggesting that these 1000 sites are enriched for asbQTL. Using independent data, we investigated functional enrichment in the candidate asbQTL set and three control groups, including non-causal ASB sites, non-ASB variants under a peak, and SNPs (single nucleotide polymorphisms) not under a peak. For H3K4me3, a higher proportion of the candidate asbQTL were confirmed as ASB when compared to the non-causal ASB sites (P < 0.01). However, these candidate asbQTL did not enrich for the other annotations, including expression QTL (eQTL), allele-specific expression QTL (aseQTL) and sites conserved across mammals (P > 0.05). Conclusions: We identified putatively causal sites for asbQTL using the DNA sequence surrounding these sites. Our results suggest that many sites influencing histone modifications may not directly affect gene expression. However, it is important to acknowledge that distinguishing between putative causal ASB sites and other non-causal ASB sites in high linkage disequilibrium with the causal sites regarding their impact on gene expression may be challenging due to limitations in statistical power. [ABSTRACT FROM AUTHOR]

Published
2024
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31. LEVERAGING FUNCTIONAL GENOMIC ANNOTATIONS AND GENOME COVERAGE TO IMPROVE POLYGENIC PREDICTION OF COMPLEX TRAITS WITHIN AND BETWEEN ANCESTRIES

Author

Zeng, Jian, primary, Zheng, Zhili, additional, Liu, Shouye, additional, Sidorenko, Julia, additional, Yengo, Loic, additional, Turley, Patrick, additional, Ani, Alireza, additional, Wang, Rujia, additional, Nolte, Ilja, additional, Snieder, Harold, additional, Yang, Jian, additional, Wray, Naomi, additional, Goddard, Michael, additional, and Visscher, Peter, additional

Published
2023
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32. Integrating genome-wide association and expression quantitative trait loci (eQTL) analyses identifies genes affecting fertility in cattle and suggests a common set of genes regulating fertility in mammals

Author

Forutan, Mehrnush, primary, Engle, Bailey, additional, Chamberlain, Amanda, additional, Ross, Elizabeth, additional, Nguyen, Loan, additional, D’Occhio, Michael, additional, Snr, Alf Collins, additional, Kho, Elise, additional, Fordyce, Geoffry, additional, Speight, Shannon, additional, Goddard, Michael, additional, and Hayes, Ben, additional

Published
2023
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33. Lipoproteins act as vehicles for lipid antigen delivery and activation of invariant natural killer T cells

Author

Engelen, Suzanne E., primary, Ververs, Francesca A., additional, Markovska, Angela, additional, Lagerholm, B. Christoffer, additional, Kraaijenhof, Jordan M., additional, Yousif, Laura I.E., additional, Zurke, Yasemin-Xiomara, additional, Gulersonmez, Can M.C., additional, Kooijman, Sander, additional, Goddard, Michael, additional, van Eijkeren, Robert J., additional, Jervis, Peter J., additional, Besra, Gurdyal S., additional, Haitjema, Saskia, additional, Asselbergs, Folkert W., additional, Kalkhoven, Eric, additional, Ploegh, Hidde L., additional, Boes, Marianne, additional, Cerundolo, Vincenzo, additional, Hovingh, G.K., additional, Salio, Mariolina, additional, Stigter, Edwin C.A., additional, Rensen, Patrick C.N., additional, Monaco, Claudia, additional, and Schipper, Henk S., additional

Published
2023
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35. Supplementary Material from Inflammatory-Related Genetic Variants in Non–Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment

Author

Masson-Lecomte, Alexandra, primary, López de Maturana, Evangelina, primary, Goddard, Michael E., primary, Picornell, Antoni, primary, Rava, Marta, primary, González-Neira, Anna, primary, Márquez, Mirari, primary, Carrato, Alfredo, primary, Tardon, Adonina, primary, Lloreta, Josep, primary, Garcia-Closas, Montserrat, primary, Silverman, Debra, primary, Rothman, Nathaniel, primary, Kogevinas, Manolis, primary, Allory, Yves, primary, Chanock, Stephen J., primary, Real, Francisco X., primary, and Malats, Núria, primary

Published
2023
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37. Lipoproteins act as vehicles for lipid antigen delivery and activation of invariant natural killer T-cells

Author

Infection & Immunity, CTI Boes, CDL Cluster Speciële Diagnostiek, Circulatory Health, Team Medisch, Zorg en O&O, Child Health, CMM Groep Burgering, Cancer, Cardiologie patientenzorg, Engelen, Suzanne E, Ververs, Francesca A, Markovska, Angela, Lagerholm, B Christoffer, Kraaijenhof, Jordan M, Yousif, Laura Ie, Zurke, Yasemin-Xiomara, Gulersonmez, Can Mc, Kooijman, Sander, Goddard, Michael, van Eijkeren, Robert J, Jervis, Peter J, Besra, Gurdyal S, Haitjema, Saskia, Asselbergs, Folkert W, Kalkhoven, Eric, Ploegh, Hidde L, Boes, Marianne, Cerundolo, Vincenzo, Hovingh, G Kees, Salio, Mariolina, Stigter, Edwin Ca, Rensen, Patrick Cn, Monaco, Claudia, Schipper, Henk S, Infection & Immunity, CTI Boes, CDL Cluster Speciële Diagnostiek, Circulatory Health, Team Medisch, Zorg en O&O, Child Health, CMM Groep Burgering, Cancer, Cardiologie patientenzorg, Engelen, Suzanne E, Ververs, Francesca A, Markovska, Angela, Lagerholm, B Christoffer, Kraaijenhof, Jordan M, Yousif, Laura Ie, Zurke, Yasemin-Xiomara, Gulersonmez, Can Mc, Kooijman, Sander, Goddard, Michael, van Eijkeren, Robert J, Jervis, Peter J, Besra, Gurdyal S, Haitjema, Saskia, Asselbergs, Folkert W, Kalkhoven, Eric, Ploegh, Hidde L, Boes, Marianne, Cerundolo, Vincenzo, Hovingh, G Kees, Salio, Mariolina, Stigter, Edwin Ca, Rensen, Patrick Cn, Monaco, Claudia, and Schipper, Henk S

Published
2023

39. Use of dry-matter intake recorded at multiple time periods during lactation increases the accuracy of genomic prediction for dry-matter intake and residual feed intake in dairy cattle

Author

Bolormaa, Sunduimijid, primary, Haile-Mariam, Mekonnen, additional, Marett, Leah C., additional, Miglior, Filippo, additional, Baes, Christine F., additional, Schenkel, Flavio S., additional, Connor, Erin E., additional, Manzanilla-Pech, Coralia I. V., additional, Wall, Eileen, additional, Coffey, Mike P., additional, Goddard, Michael E., additional, MacLeod, Iona M., additional, and Pryce, Jennie E., additional

Published
2023
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40. Additional file 4 of Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle

Author

Prowse-Wilkins, Claire P., Lopdell, Thomas J., Xiang, Ruidong, Vander Jagt, Christy J., Littlejohn, Mathew D., Chamberlain, Amanda J., and Goddard, Michael E.

Abstract

Additional file 4: Supplementary Table 6. The frequencies of the top 10 predicted transcription factor (TF) classes from the JASPAR 2018 CORE database. Supplementary Table 7. The frequencies of the top six predicted promotor element classes from the JASPAR 2018 POLII database.

Published
2023
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41. Additional file 2 of Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle

Author

Prowse-Wilkins, Claire P., Lopdell, Thomas J., Xiang, Ruidong, Vander Jagt, Christy J., Littlejohn, Mathew D., Chamberlain, Amanda J., and Goddard, Michael E.

Abstract

Additional file 2: Supplementary Table 2. The number of genes or exons with a heterozygous SNP (tSNP), the number of genes or exons with multiple tSNP and the number of genes or exons where the tSNP phenotypes within were significantly different (p

Published
2023
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42. Additional file 3 of Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle

Author

Prowse-Wilkins, Claire P., Lopdell, Thomas J., Xiang, Ruidong, Vander Jagt, Christy J., Littlejohn, Mathew D., Chamberlain, Amanda J., and Goddard, Michael E.

Abstract

Additional file 3: Supplementary Table 4. The number of peak-exon pairs with shared allele-specific QTL variants as well as the distance between peak-exon pairs and the average number of times a peak was associated with an exon and vice versa. Supplementary Table 5. The number of peak-exon pairs with shared traditional QTL as well as the distance between peak-exon pairs and the average number of times a peak was associated with an exon and vice versa.

Published
2023
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43. Ooi et al (2023) - Supplementary materials.docx

Author

Ooi, Ee Cheng, XIANG, RUIDONG, Chamberlain, Amanda, and GODDARD, MICHAEL

Subjects
Animal production not elsewhere classified
Abstract

Supplementary materials for a published paper: Archetypal clustering reveals physiological mechanisms linking milk yield and fertility in dairy cattle.

Published
2023
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46. Interferon regulatory factor-5-dependent CD11c+ macrophages contribute to the formation of rupture–prone atherosclerotic plaques

Author

Edsfeldt, Andreas, primary, Swart, Maarten, additional, Singh, Pratibha, additional, Dib, Lea, additional, Sun, Jiangming, additional, Cole, Jennifer E, additional, Park, Inhye, additional, Al-Sharify, Dania, additional, Persson, Ana, additional, Nitulescu, Mihaela, additional, Borges, Patricia Das Neves, additional, Kassiteridi, Christina, additional, Goddard, Michael E, additional, Lee, Regent, additional, Volkov, Petr, additional, Orho-Melander, Marju, additional, Maegdefessel, Lars, additional, Nilsson, Jan, additional, Udalova, Irina, additional, Goncalves, Isabel, additional, and Monaco, Claudia, additional

Published
2022
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48. Bayesian genome-wide analysis of cattle traits using variants with functional and evolutionary significance.

Author

Ruidong Xiang, Breen, Ed J., Prowse-Wilkins, Claire P., Chamberlain, Amanda J., and Goddard, Michael E.

Abstract

Context. Functional genomics studies have highlighted genomic regions with regulatory and evolutionary significance. Such information independent of association analysis may benefit fine-mapping and genomic selection of economically important traits. However, systematic evaluation of the use of functional information in mapping, and genomic selection of cattle traits, is lacking. Also, single-nucleotide polymorphisms (SNPs) from the high-density (HD) panel are known to tag informative variants, but the performance of genomic prediction using HD SNPs together with variants supported by different functional genomics is unknown. Aims. We selected six sets of functionally important variants and modelled each set together with HD SNPs in Bayesian models to map and predict protein, fat and milk yield as well as mastitis, somatic cell count and temperament of dairy cattle. Methods. Two models were used, namely (1) BayesR, which includes priors of four distribution of variant effects, and (2) BayesRC, which includes additional priors of different functional classes of variants. Bayesian models were trained in three breeds of 28 000 cows of Holstein, Jersey and Australian Red and predicted into 2600 independent bulls. Key results. Adding functionally important variants significantly increased the enrichment of genetic variance explained for mapped variants, suggesting improved genome-wide mapping precision. Such improvement was significantly higher when the same set of variants was modelled by BayesRC than by BayesR. Combining functional variant sets with HD SNPs improves genomic prediction accuracy in the majority of the cases and such improvement was more common and stronger for non-Holstein breeds and traits such as mastitis, somatic cell count and temperament. In contrast, adding a large number of random sequence variants to HD SNPs reduces mapping precision and has a worse or similar prediction accuracy, compared with using HD SNPs alone to map or predict. While BayesRC tended to have better genomic prediction accuracy than did BayesR, the overall difference in prediction accuracy between the two models was insignificant. Conclusions. Our findings demonstrated the usefulness of functional data in genomic mapping and prediction. Implications. We have highlighted the need for effective tools exploiting complex functional datasets to improve genomic prediction. [ABSTRACT FROM AUTHOR]

Published
2021
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50. Genome-wide fine-mapping improves identification of causal variants.

Author

Wu Y, Zheng Z, Thibaut L, Goddard ME, Wray NR, Visscher PM, and Zeng J

Abstract

Fine-mapping refines genotype-phenotype association signals to identify causal variants underlying complex traits. However, current methods typically focus on individual genomic segments without considering the global genetic architecture. Here, we demonstrate the advantages of performing genome-wide fine-mapping (GWFM) and develop methods to facilitate GWFM. In simulations and real data analyses, GWFM outperforms current methods in error control, mapping power and precision, replication rate, and trans-ancestry phenotype prediction. For 48 well-powered traits in the UK Biobank, we identify causal variants that collectively explain 17% of the SNP-based heritability, and predict that fine-mapping 50% of that would require 2 million samples on average. We pinpoint a known causal variant, as proof-of-principle, at FTO for body mass index, unveil a hidden secondary variant with evolutionary conservation, and identify new missense causal variants for schizophrenia and Crohn's disease. Overall, we analyse 600 complex traits with 13 million SNPs, highlighting the efficacy of GWFM with functional annotations., Competing Interests: Competing Interests The authors declare no competing interests. Additional Declarations: There is NO Competing Interest

Published
2024
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