Results 11 to 20 of about 7,493,012 (309)

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits [PDF]

, 2014
A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications.
Labouriau, Rodrigo, Madsen, Per, Maia, Rafael Pimentel   +2 more
core   +2 more sources

Levels of genetic polymorphism: marker loci versus quantitative traits [PDF]

, 1998
Species are the units used to measure ecological diversity and alleles are the units of genetic diversity. Genetic variation within and among species has been documented most extensively using allozyme electrophoresis.
Butlin R. K., Butlin R. K., Meyer J., Muller H. J., Neems R. M., Nei M., Ward R. D., Watt W. B., Watt W. B., Wu C-I.   +9 more
core   +3 more sources

QUANTITATIVE GENETICS OF HETEROCHRONY [PDF]

Evolution, 1987
A model of quantitative-genetic variation in developmental processes is introduced and analyzed. The model is of a bifurcating sequence of events in which traits develop from the same tissue until a transition occurs, after which they develop partially independently.
openaire   +2 more sources

Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast. [PDF]

, 2016
Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion that most genetic variance in populations is additive.
Bloom, Joshua S, Carlborg, Örjan, Forsberg, Simon KG, Kruglyak, Leonid, Sadhu, Meru J   +4 more
core   +3 more sources

Genetic parameters of meat quality traits in two pig breeds measured by rapid methods

Animal, 2010
To study genetic variation in meat quality traits measured by rapid methods, data were recorded between 2005 and 2008 on samples of M. longissimus dorsi (LD) in Landrace (n = 3838) and Duroc (n = 2250) pigs included in the Norwegian pig breeding scheme ...
E. Gjerlaug-Enger, L. Aass, J. Ødegård, O. Vangen   +3 more
doaj   +1 more source

Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses

Genetics Selection Evolution, 2020
Background Sequencing data enable the detection of causal loci or single nucleotide polymorphisms (SNPs) highly linked to causal loci to improve genomic prediction.
Aoxing Liu, Mogens Sandø Lund, Didier Boichard, Emre Karaman, Bernt Guldbrandtsen, Sebastien Fritz, Gert Pedersen Aamand, Ulrik Sander Nielsen, Goutam Sahana, Yachun Wang, Guosheng Su   +10 more
doaj   +1 more source

The Opportunities and Challenges of Integrating Population Histories Into Genetic Studies for Diverse Populations: A Motivating Example From Native Hawaiians

Frontiers in Genetics, 2021
There is a well-recognized need to include diverse populations in genetic studies, but several obstacles continue to be prohibitive, including (but are not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and
Charleston W. K. Chiang, Charleston W. K. Chiang   +1 more
doaj   +1 more source

The Genetic Basis of Mutation Rate Variation in Yeast. [PDF]

, 2018
Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis ...
Bloom, Joshua S, Gou, Liangke, Kruglyak, Leonid   +2 more
core   +1 more source

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Nature Genetics, 2021
Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using ...
U. Võsa, A. Claringbould, H. Westra, M. Bonder, Patrick Deelen, B. Zeng, H. Kirsten, A. Saha, Roman Kreuzhuber, S. Yazar, H. Brugge, R. Oelen, Dylan H. de Vries, M. V. D. van der Wijst, S. Kasela, N. Pervjakova, I. Alves, M. Favé, M. Agbessi, M. Christiansen, R. Jansen, I. Seppälä, L. Tong, A. Teumer, K. Schramm, G. Hemani, J. Verlouw, H. Yaghootkar, Reyhan Sönmez Flitman, A. Brown, V. Kukushkina, A. Kalnapenkis, S. Rüeger, E. Porcu, J. Kronberg, J. Kettunen, Bernett Lee, Futao Zhang, Ting Qi, J. A. Hernandez, W. Arindrarto, F. Beutner, Julia Dmitrieva, Mahmoud Elansary, Benjamin P. Fairfax, M. Georges, B. Heijmans, A. Hewitt, M. Kähönen, Yungil Kim, J. Knight, P. Kovacs, K. Krohn, Shuang Li, M. Loeffler, U. Marigorta, Hailang Mei, Y. Momozawa, M. Müller-Nurasyid, M. Nauck, M. Nivard, B. Penninx, J. Pritchard, O. Raitakari, O. Rotzschke, E. Slagboom, C. Stehouwer, M. Stumvoll, P. Sullivan, P. ’. ’t Hoen, J. Thiery, A. Tönjes, J. van Dongen, M. van Iterson, J. Veldink, U. Völker, R. Warmerdam, C. Wijmenga, M. Swertz, A. Andiappan, G. Montgomery, S. Ripatti, M. Perola, Z. Kutalik, E. Dermitzakis, S. Bergmann, T. Frayling, J. V. van Meurs, H. Prokisch, H. Ahsan, B. Pierce, T. Lehtimäki, D. Boomsma, B. Psaty, Sina A. Gharib, P. Awadalla, L. Milani, W. Ouwehand, K. Downes, O. Stegle, A. Battle, P. Visscher, Jian Yang, M. Scholz, J. Powell, G. Gibson, T. Esko, L. Franke   +107 more
semanticscholar   +1 more source

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models

Genetics, 2016
Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions.
P. de Villemereuil, H. Schielzeth, Shinichi Nakagawa, M. Morrissey   +3 more
semanticscholar   +1 more source