Gene Expression to Genetical Genomics

10.4137/ggg ◽  
2018 ◽  
Keyword(s):  
Gene Expression ◽  
Genetical Genomics

scholarly journals Genetical Genomics: Combining Gene Expression with Marker Genotypes in Poultry

2007 ◽  
Vol 86 (7) ◽  
pp. 1501-1509 ◽  
Author(s):  
D.J. de Koning ◽  
C.P. Cabrera ◽  
C.S. Haley
Keyword(s):  
Gene Expression ◽  
Genetical Genomics

scholarly journals Genetical genomics: combining genetics with gene expression analysis

2005 ◽  
Vol 14 (suppl_2) ◽  
pp. R163-R169 ◽  
Author(s):  
Jun Li ◽  
Margit Burmeister
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Genetical Genomics

Inferring Gene Regulatory Networks from Genetical Genomics Data

2010 ◽  
pp. 79-107 ◽  
Author(s):  
Bing Liu ◽  
Ina Hoeschele ◽  
Alberto de la Fuente
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Network Inference ◽  
Dna Marker ◽  
Search Space ◽  
Genetical Genomics ◽  
Gene Regulatory Network Inference ◽  
Gene Regulatory

In this chapter, we review the current state of Gene Regulatory Network inference based on ‘Genetical Genomics’ experiments (Brem & Kruglyak, 2005; Brem, Yvert, Clinton & Kruglyak, 2002; Jansen, 2003; Jansen & Nap, 2001; Schadt et al., 2003) as a special case of causal network inference in ‘Systems Genetics’ (Threadgill, 2006). In a Genetical Genomics experiment, a segregating or genetically randomized population is DNA marker genotyped and gene-expression profiled on a genomewide scale. The genotypes are regarded as natural, multifactorial perturbations resulting in different gene-expression ‘phenotypes’, and causal relationships can therefore be established between the measured genotypes and the gene-expression phenotypes. In this chapter, we review different computational approaches to Gene Regulatory Network inference based on the joint analysis of DNA marker and expression data and additionally of DNA sequence information if available. This includes different methods for expression QTL mapping, selection of regulator-target pairs, construction of an encompassing network, which strongly constrains the network search space, and pairwise and multivariate methods for Gene Regulatory Network inference, such as Bayesian Networks and Structural Equation Modeling.

A Genetical Genomics Methodology to Identify Genetic Markers of a Bovine Fertility Phenotype Based on CYP19A1 Gene Expression

2015 ◽  
pp. 9 ◽  
Author(s):  
Isabelle Dufort ◽  
Nicolas Guillemin ◽  
Marc-Andre Sirard
Keyword(s):  
Gene Expression ◽  
Genetic Markers ◽  
Genetical Genomics ◽  
Bovine Fertility

scholarly journals Mapping Determinants of Gene Expression Plasticity by Genetical Genomics in C. elegans

PLoS Genetics ◽  
2005 ◽  
Vol preprint (2006) ◽  
pp. e222 ◽  
Author(s):  
Yang Li ◽  
Olga Alda Alvarez ◽  
Evert W Gutteling ◽  
Marcel Tijsterman ◽  
Jingyuan Fu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetical Genomics ◽  
C Elegans

scholarly journals Mapping Determinants of Gene Expression Plasticity by Genetical Genomics in C. elegans

PLoS Genetics ◽  
2006 ◽  
Vol 2 (12) ◽  
pp. e222 ◽  
Author(s):  
Yang Li ◽  
Olga Alda Álvarez ◽  
Evert W. Gutteling ◽  
Marcel Tijsterman ◽  
Jingyuan Fu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetical Genomics ◽  
C Elegans
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