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      Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep

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          Abstract

          Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual’s genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

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          Most cited references32

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          AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors

          Abstract The Animal Transcription Factor DataBase (AnimalTFDB) is a resource aimed to provide the most comprehensive and accurate information for animal transcription factors (TFs) and cofactors. The AnimalTFDB has been maintained and updated for seven years and we will continue to improve it. Recently, we updated the AnimalTFDB to version 3.0 (http://bioinfo.life.hust.edu.cn/AnimalTFDB/) with more data and functions to improve it. AnimalTFDB contains 125,135 TF genes and 80,060 transcription cofactor genes from 97 animal genomes. Besides the expansion in data quantity, some new features and functions have been added. These new features are: (i) more accurate TF family assignment rules; (ii) classification of transcription cofactors; (iii) TF binding sites information; (iv) the GWAS phenotype related information of human TFs; (v) TF expressions in 22 animal species; (vi) a TF binding site prediction tool to identify potential binding TFs for nucleotide sequences; (vii) a separate human TF database web interface (HumanTFDB) was designed for better utilizing the human TFs. The new version of AnimalTFDB provides a comprehensive annotation and classification of TFs and cofactors, and will be a useful resource for studies of TF and transcription regulation.
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            The ETS-domain transcription factor family.

            ETS-domain transcription-factor networks represent a model for how combinatorial gene expression is achieved. These transcription factors interact with a multitude of co-regulatory partners to elicit gene-specific responses and drive distinct biological processes. These proteins are controlled by a complex series of inter and intramolecular interactions, and signalling pathways impinge on these proteins to further regulate their action.
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              miR-33a/b contribute to the regulation of fatty acid metabolism and insulin signaling.

              Cellular imbalances of cholesterol and fatty acid metabolism result in pathological processes, including atherosclerosis and metabolic syndrome. Recent work from our group and others has shown that the intronic microRNAs hsa-miR-33a and hsa-miR-33b are located within the sterol regulatory element-binding protein-2 and -1 genes, respectively, and regulate cholesterol homeostasis in concert with their host genes. Here, we show that miR-33a and -b also regulate genes involved in fatty acid metabolism and insulin signaling. miR-33a and -b target key enzymes involved in the regulation of fatty acid oxidation, including carnitine O-octaniltransferase, carnitine palmitoyltransferase 1A, hydroxyacyl-CoA-dehydrogenase, Sirtuin 6 (SIRT6), and AMP kinase subunit-α. Moreover, miR-33a and -b also target the insulin receptor substrate 2, an essential component of the insulin-signaling pathway in the liver. Overexpression of miR-33a and -b reduces both fatty acid oxidation and insulin signaling in hepatic cell lines, whereas inhibition of endogenous miR-33a and -b increases these two metabolic pathways. Together, these data establish that miR-33a and -b regulate pathways controlling three of the risk factors of metabolic syndrome, namely levels of HDL, triglycerides, and insulin signaling, and suggest that inhibitors of miR-33a and -b may be useful in the treatment of this growing health concern.
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                Author and article information

                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                27 June 2020
                July 2020
                : 11
                : 7
                : 715
                Affiliations
                [1 ]Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24071 León, Spain; hmarg@ 123456unileon.es (H.M.); beatriz.gutierrez@ 123456unileon.es (B.G.-G.); asuav@ 123456unileon.es (A.S.-V.); cestb@ 123456unileon.es (C.E.-B.)
                [2 ]CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd., St Lucia, Brisbane, Queensland 4067, Australia; toni.reverter-gomez@ 123456csiro.au (A.R.); Pamela.Alexandre@ 123456csiro.au (P.A.A.); laercio.portoneto@ 123456csiro.au (L.R.P.-N.); Yutao.Li@ 123456csiro.au (Y.L.)
                Author notes
                [* ]Correspondence: jjarrs@ 123456unileon.es ; Tel.: +34-987-291-470
                Author information
                https://orcid.org/0000-0001-9226-2902
                https://orcid.org/0000-0002-0649-7033
                https://orcid.org/0000-0002-7726-4288
                https://orcid.org/0000-0001-9158-9946
                https://orcid.org/0000-0002-2425-000X
                https://orcid.org/0000-0001-9058-131X
                Article
                genes-11-00715
                10.3390/genes11070715
                7397207
                32605032
                4cff34c4-4494-477f-92db-4cbc61bc59ce
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 08 June 2020
                : 25 June 2020
                Categories
                Article

                dairy sheep,milk coagulation properties,meta-analysis,gwas,stepwise analysis,pleiotropy,linkage disequilibrium

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