Literature DB >> 19045837

Genetical systems biology in livestock: application to gonadotrophin releasing hormone and reproduction.

H N Kadarmideen1.   

Abstract

Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology.

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Year:  2008        PMID: 19045837     DOI: 10.1049/iet-syb:20070072

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  11 in total

1.  A genome-wide approach to screen for genetic variants in broilers (Gallus gallus) with divergent feed conversion ratio.

Authors:  Tejas M Shah; Namrata V Patel; Anand B Patel; Maulik R Upadhyay; Amitbikram Mohapatra; Krishna M Singh; Sunil D Deshpande; Chaitanya G Joshi
Journal:  Mol Genet Genomics       Date:  2016-05-12       Impact factor: 3.291

2.  Identification of differentially expressed known and novel miRNAs in broodiness of goose.

Authors:  Fang Chen; Jinjun Li; Hao Zhang; Jing Xu; Zhengrong Tao; Junda Shen; Jianliang Shen; Lizhi Lu; ChunMei Li
Journal:  Mol Biol Rep       Date:  2014-01-28       Impact factor: 2.316

3.  FunctSNP: an R package to link SNPs to functional knowledge and dbAutoMaker: a suite of Perl scripts to build SNP databases.

Authors:  Stephen J Goodswen; Cedric Gondro; Nathan S Watson-Haigh; Haja N Kadarmideen
Journal:  BMC Bioinformatics       Date:  2010-06-09       Impact factor: 3.169

4.  Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data.

Authors:  Haja N Kadarmideen; Nathan S Watson-Haigh
Journal:  Bioinformation       Date:  2012-09-21

5.  Genetic effects of polymorphisms in candidate genes and the QTL region on chicken age at first egg.

Authors:  Haiping Xu; Hua Zeng; Chenglong Luo; Dexiang Zhang; Qian Wang; Liang Sun; Lishan Yang; Min Zhou; Qinghua Nie; Xiquan Zhang
Journal:  BMC Genet       Date:  2011-04-15       Impact factor: 2.797

6.  Genetic architecture of gene expression in ovine skeletal muscle.

Authors:  Lisette J A Kogelman; Keren Byrne; Tony Vuocolo; Nathan S Watson-Haigh; Haja N Kadarmideen; James W Kijas; Hutton V Oddy; Graham E Gardner; Cedric Gondro; Ross L Tellam
Journal:  BMC Genomics       Date:  2011-12-15       Impact factor: 3.969

7.  Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake.

Authors:  Duy N Do; Anders B Strathe; Tage Ostersen; Sameer D Pant; Haja N Kadarmideen
Journal:  Front Genet       Date:  2014-09-09       Impact factor: 4.599

Review 8.  The Importance of Endophenotypes to Evaluate the Relationship between Genotype and External Phenotype.

Authors:  Marinus F W Te Pas; Ole Madsen; Mario P L Calus; Mari A Smits
Journal:  Int J Mol Sci       Date:  2017-02-22       Impact factor: 5.923

9.  Pre- and early-postnatal nutrition modify gene and protein expressions of muscle energy metabolism markers and phospholipid Fatty Acid composition in a muscle type specific manner in sheep.

Authors:  Lei Hou; Anna H Kongsted; Seyed M Ghoreishi; Tasnim K Takhtsabzy; Martin Friedrichsen; Lars I Hellgren; Haja N Kadarmideen; Allan Vaag; Mette O Nielsen
Journal:  PLoS One       Date:  2013-06-06       Impact factor: 3.240

10.  Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs.

Authors:  Duy Ngoc Do; Tage Ostersen; Anders Bjerring Strathe; Thomas Mark; Just Jensen; Haja N Kadarmideen
Journal:  BMC Genet       Date:  2014-02-17       Impact factor: 2.797

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