14 results match your criteria Gene Expression to Genetical Genomics [Journal]

  • Page 1 of 1

Genetical genomics of growth in a chicken model.

BMC Genomics 2018 01 23;19(1):72. Epub 2018 Jan 23.

AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, 581 83, Linköping, Sweden.

Background: The genetics underlying body mass and growth are key to understanding a wide range of topics in biology, both evolutionary and developmental. Body mass and growth traits are affected by many genetic variants of small effect. This complicates genetic mapping of growth and body mass. Read More

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http://dx.doi.org/10.1186/s12864-018-4441-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5782384PMC
January 2018
3 Reads

Contribution of trans regulatory eQTL to cryptic genetic variation in C. elegans.

BMC Genomics 2017 06 29;18(1):500. Epub 2017 Jun 29.

Laboratory of Nematology, Wageningen University and Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands.

Background: Cryptic genetic variation (CGV) is the hidden genetic variation that can be unlocked by perturbing normal conditions. CGV can drive the emergence of novel complex phenotypes through changes in gene expression. Although our theoretical understanding of CGV has thoroughly increased over the past decade, insight into polymorphic gene expression regulation underlying CGV is scarce. Read More

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http://dx.doi.org/10.1186/s12864-017-3899-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492678PMC
June 2017
7 Reads

Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data.

BMC Genomics 2013 Dec 2;14:845. Epub 2013 Dec 2.

INIA, Mejora Genética Animal, 28040 Madrid, Spain.

Background: Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Read More

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http://dx.doi.org/10.1186/1471-2164-14-845DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4046688PMC
December 2013
11 Reads

Genome-wide analysis of coordinated transcript abundance during seed development in different Brassica rapa morphotypes.

BMC Genomics 2013 Dec 1;14:840. Epub 2013 Dec 1.

Wageningen UR Plant Breeding, Wageningen University and Research Center, Droevendaalsesteeg 1, 6708 PB Wageningen, the Netherlands.

Background: Brassica seeds are important as basic units of plant growth and sources of vegetable oil. Seed development is regulated by many dynamic metabolic processes controlled by complex networks of spatially and temporally expressed genes. We conducted a global microarray gene co-expression analysis by measuring transcript abundance of developing seeds from two diverse B. Read More

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http://dx.doi.org/10.1186/1471-2164-14-840DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4046715PMC
December 2013
30 Reads

Differential adaptation to multi-stressed conditions of wine fermentation revealed by variations in yeast regulatory networks.

BMC Genomics 2013 Oct 4;14:681. Epub 2013 Oct 4.

INRA, UMR1083 Science pour l'Œnologie, 2 Place Viala, Montpellier F-34060, France.

Background: Variation of gene expression can lead to phenotypic variation and have therefore been assumed to contribute the diversity of wine yeast (Saccharomyces cerevisiae) properties. However, the molecular bases of this variation of gene expression are unknown. We addressed these questions by carrying out an integrated genetical-genomic study in fermentation conditions. Read More

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http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2
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http://dx.doi.org/10.1186/1471-2164-14-681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3870980PMC
October 2013
5 Reads

Defense mechanisms against herbivory in Picea: sequence evolution and expression regulation of gene family members in the phenylpropanoid pathway.

BMC Genomics 2011 Dec 16;12:608. Epub 2011 Dec 16.

Department of Forest Sciences, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T1Z4, Canada.

Background: In trees, a substantial amount of carbon is directed towards production of phenolics for development and defense. This metabolic pathway is also a major factor in resistance to insect pathogens in spruce. In such gene families, environmental stimuli may have an important effect on the evolutionary fate of duplicated genes, and different expression patterns may indicate functional diversification. Read More

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http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2
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http://dx.doi.org/10.1186/1471-2164-12-608DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3288119PMC
December 2011
4 Reads

Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism.

BMC Genomics 2011 Nov 4;12:548. Epub 2011 Nov 4.

Laboratoire de Génétique Cellulaire, INRA UMR444, Chemin de Borde Rouge, F-31326 Castanet-Tolosan, France.

Background: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. Read More

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http://dx.doi.org/10.1186/1471-2164-12-548DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3239847PMC
November 2011
7 Reads

Genome-wide expression quantitative trait loci (eQTL) analysis in maize.

BMC Genomics 2011 Jun 30;12:336. Epub 2011 Jun 30.

DuPont Agricultural Biotechnology, Wilmington, DE 19880, USA.

Background: Expression QTL analyses have shed light on transcriptional regulation in numerous species of plants, animals, and yeasts. These microarray-based analyses identify regulators of gene expression as either cis-acting factors that regulate proximal genes, or trans-acting factors that function through a variety of mechanisms to affect transcript abundance of unlinked genes.

Results: A hydroponics-based genetical genomics study in roots of a Zea mays IBM2 Syn10 double haploid population identified tens of thousands of cis-acting and trans-acting eQTL. Read More

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http://dx.doi.org/10.1186/1471-2164-12-336DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141675PMC
June 2011
5 Reads

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice.

BMC Genomics 2010 Dec 19;11:713. Epub 2010 Dec 19.

Department of Pharmacology, Physiology and Toxicology, Joan C, Edwards School of Medicine, Marshall University, Huntington, WV 25755, USA.

Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. Read More

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http://dx.doi.org/10.1186/1471-2164-11-713DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3022919PMC
December 2010
6 Reads

From QTL to candidate gene: genetical genomics of simple and complex traits in potato using a pooling strategy.

BMC Genomics 2010 Mar 8;11:158. Epub 2010 Mar 8.

Wageningen UR Plant Breeding, Wageningen University and Research Centre, PO Box 386, 6700 AJ Wageningen, the Netherlands.

Background: Utilization of the natural genetic variation in traditional breeding programs remains a major challenge in crop plants. The identification of candidate genes underlying, or associated with, phenotypic trait QTLs is desired for effective marker assisted breeding. With the advent of high throughput -omics technologies, screening of entire populations for association of gene expression with targeted traits is becoming feasible but remains costly. Read More

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http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2
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http://dx.doi.org/10.1186/1471-2164-11-158DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2843620PMC
March 2010
8 Reads

Cis sequence effects on gene expression.

BMC Genomics 2007 Aug 29;8:296. Epub 2007 Aug 29.

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA.

Background: Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics) provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects) in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. Read More

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http://dx.doi.org/10.1186/1471-2164-8-296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2077339PMC
August 2007
6 Reads

Genetical genomics: use all data.

BMC Genomics 2007 Mar 12;8:69. Epub 2007 Mar 12.

Departament of Food and Animal Science, Veterinary School, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.

Background: Genetical genomics is a very powerful tool to elucidate the basis of complex traits and disease susceptibility. Despite its relevance, however, statistical modeling of expression quantitative trait loci (eQTL) has not received the attention it deserves. Based on two reasonable assertions (i) a good model should consider all available variables as potential effects, and (ii) gene expressions are highly interconnected, we suggest that an eQTL model should consider the rest of expression levels as potential regressors, in addition to the markers. Read More

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http://dx.doi.org/10.1186/1471-2164-8-69DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1828729PMC
March 2007
6 Reads

Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint x Flint maize recombinant inbred line population.

BMC Genomics 2007 Jan 18;8:22. Epub 2007 Jan 18.

Technical University of Munich, Am Hochanger 2, 85350 Freising, Germany.

Background: Cell-wall digestibility is the major target for improving the feeding value of forage maize. An understanding of the molecular basis for cell-wall digestibility is crucial towards breeding of highly digestible maize.

Results: 865 candidate ESTs for cell-wall digestibility were selected according to the analysis of expression profiles in 1) three sets of brown-midrib isogenic lines in the genetic background of inbreds 1332 (1332 and 1332 bm3), 5361 (5361 and 5361 bm3), and F2 (F2, F2 bm1, F2 bm2, and F2 bm3), 2) the contrasting extreme lines of FD (Flint x Dent, AS08 x AS 06), DD1 (Dent x Dent, AS11 x AS09), and DD2 (Dent x Dent, AS29 x AS30) mapping populations, and 3) two contrasting isogenic inbreds, AS20 and AS21. Read More

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http://dx.doi.org/10.1186/1471-2164-8-22DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1785377PMC
January 2007
12 Reads

Human mucin genes assigned to 11p15.5: identification and organization of a cluster of genes.

Genomics 1996 Dec;38(3):340-52

Unité INSERM No. 377, Lille, France.

Four distinct genes that encode mucins have previously been mapped to chromosome 11p15.5. Three of these genes (MUC2, MUC5AC, and MUC6) show a high level of genetically determined polymorphism and were analyzed in the CEPH families. Read More

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http://dx.doi.org/10.1006/geno.1996.0637DOI Listing
December 1996
3 Reads
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