Results 61 to 70 of about 3,463,080 (339)

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Nature Genetics
Multi-ancestry genome-wide association meta-analysis of major depression identifies new risk loci, assesses the transferability of risk loci across ancestry groups, and improves fine-mapping resolution and prioritization of candidate effector genes. Most
Xiangrui Meng, Georgina Navoly, O. Giannakopoulou, D. Levey, Dora Koller, G. Pathak, N. Koen, Kuang Lin, Mark J. Adams, Miguel E. Rentería, Yanzhe Feng, J. Gaziano, D. Stein, Heather J. Zar, Megan L. Campbell, D. A. Heel, B. Trivedi, S. Finer, A. McQuillin, N. Bass, V. K. Chundru, Hilary C. Martin, Q. Huang, M. Valkovskaya, Chia-Yi Chu, Susan Kanjira, Po-Hsiu Kuo, Hsi- Chen, Shih-Jen Tsai, Yu-Li Liu, K. Kendler, Roseann E. Peterson, Na Cai, Yu Fang, Srijan Sen, Laura J. Scott, Margit Burmeister, R. Loos, Michael H. Preuss, Ky'Era V. Actkins, Lea K. Davis, Monica Uddin, Agaz H. Wani, Derek Wildman, Allison E Aiello, R. Ursano, Ronald C. Kessler, M. Kanai, Y. Okada, S. Sakaue, Jill A. Rabinowitz, Brion S. Maher, George Uhl, William Eaton, C. S. Cruz-Fuentes, G. Martínez-Levy, A. Campos, I. Millwood, Zhengmin Chen, Liming Li, Sylvia Wassertheil-Smoller, Yunxuan Jiang, C. Tian, Nicholas G. Martin, B. Mitchell, Enda M. Byrne, S. Awasthi, J. Coleman, S. Ripke, T. Sofer, R. Walters, Andrew M. McIntosh, R. Polimanti, Erin C. Dunn, Murray B. Stein, J. Gelernter, C. Lewis, K. Kuchenbaecker, Pgc Mdd working group, China Kadoorie Biobank (CKB) Collab Group, the 23andMe Research Team, Genes Health Research Team, Biobank Japan Project   +82 more
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Fine mapping of two grain chalkiness QTLs sensitive to high temperature in rice

Rice, 2021
Background Grain chalkiness is one of important factors affected rice grain quality. It is known that chalkiness is affected by the high temperature during the seed filling period.
Weifeng Yang, Jiayan Liang, Qingwen Hao, Xin Luan, Quanya Tan, Shiwan Lin, Hai-tao Zhu, Guifu Liu, Zupei Liu, Suhong Bu, Shaokui Wang, Guiquan Zhang   +11 more
semanticscholar   +1 more source

Fine‐scale mapping using Hardy–Weinberg disequilibrium [PDF]

Annals of Human Genetics, 2001
Hardy–Weinberg disequilibrium (HWD) among affected individuals has recently been proposed for fine‐scale mapping of disease susceptibility genes. We investigate the statistical properties of several available HWD measures and develop a new HWD measure J for fine‐scale mapping.
R, Jiang, J, Dong, D, Wang, F Z, Sun
openaire   +2 more sources

Mapping and Preliminary Analysis of ABORTED MICROSPORES (AMS) as the Candidate Gene Underlying the Male Sterility (MS-5) Mutant in Melon (Cucumis melo L.)

Frontiers in Plant Science, 2017
Melon is an important agricultural and economic vegetable crop worldwide. The genetic male sterility mutant (ms-5) has a recessive nuclear gene that controls the male sterility germplasm.
Yunyan Sheng, Yunyan Sheng, Yudan Wang, Shiqi Jiao, Yazhong Jin, Peng Ji, Feishi Luan   +6 more
doaj   +1 more source

The flashfm approach for fine-mapping multiple quantitative traits

Nature Communications, 2021
Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for ...
N. Hernandez, J. Soenksen, P. Newcombe, Mannila Sandhu, I. Barroso, C. Wallace, J. Asimit   +6 more
semanticscholar   +1 more source

Fine mapping of an immunoglobulin gene activator. [PDF]

Molecular and Cellular Biology, 1984
It has recently been shown that the promoter of a kappa immunoglobulin gene is activated for transcription by a downstream sequence element. Here we mapped the activating element to a resolution of about 20 base pairs by constructing a series of deletions in the cloned kappa gene.
C, Queen, J, Stafford
openaire   +2 more sources

Identification of an SCPL Gene Controlling Anthocyanin Acylation in Carrot (Daucus carota L.) Root

Frontiers in Plant Science, 2020
Anthocyanins are natural health promoting pigments that can be produced in large quantities in some purple carrot cultivars. Decoration patterns of anthocyanins, such as acylation, can greatly influence their stability and biological properties and use ...
Julien Curaba, Hamed Bostan, Pablo F. Cavagnaro, Pablo F. Cavagnaro, Douglas Senalik, Douglas Senalik, Molla Fentie Mengist, Yunyang Zhao, Philipp W. Simon, Philipp W. Simon, Massimo Iorizzo, Massimo Iorizzo   +11 more
doaj   +1 more source

Overview of the MHC fine mapping data [PDF]

Diabetes, Obesity and Metabolism, 2009
Aim:  The aim of this study was to perform quality control (QC) and initial family‐based association analyses on the major histocompatibility complex (MHC) single nucleotide polymorphism (SNP) and microsatellite marker data for the MHC Fine Mapping Workshop through the Type 1 Diabetes Genetics Consortium (T1DGC).
W M, Brown, J, Pierce, J E, Hilner, L H, Perdue, K, Lohman, L, Li, R B, Venkatesh, S, Hunt, J C, Mychaleckyj, P, Deloukas   +9 more
openaire   +2 more sources

Encoding and Selecting Coarse-Grain Mapping Operators with Hierarchical Graphs

, 2018
Coarse grain (CG) molecular dynamics (MD) can simulate systems inaccessible to fine grain (FG) MD simulations. A CG simulation decreases the degrees of freedom by mapping atoms from an FG representation into agglomerate CG particles. The FG to CG mapping
Chakraborty, Maghesree, White, Andrew D., Xu, Chenliang   +2 more
core   +1 more source

Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Nature Communications, 2020
The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants’ effect on gene expressions in native chromatin context via direct ...
Qingbo S. Wang, David R. Kelley, J. Ulirsch, M. Kanai, Shuvom Sadhuka, R. Cui, C. Albors, Nathan Cheng, Y. Okada, Koichi Yuji Yoichi Takayuki Yoshinori Yoichiro Kaori Akik Matsuda Yamanashi Furukawa Morisaki Murakami Kamat, K. Matsuda, Yuji Yamanashi, Y. Furukawa, T. Morisaki, Yoshinori Murakami, Y. Kamatani, K. Muto, A. Nagai, Wataru Obara, Ken Yamaji, Kazuhisa Takahashi, S. Asai, Yasuo Takahashi, Takao Suzuki, N. Sinozaki, H. Yamaguchi, S. Minami, S. Murayama, K. Yoshimori, S. Nagayama, D. Obata, Masahiko Higashiyama, A. Masumoto, Y. Koretsune, F. Aguet, K. Ardlie, D. MacArthur, H. Finucane   +37 more
semanticscholar   +1 more source