Animal Reproduction (AR)
https://www.animal-reproduction.org/article/5b71d6be0e8825271e8068aa
Animal Reproduction (AR)
Conference Paper

Application of integrative genomics and systems biology to conventional and in vitro reproductive traits in cattle

Gianluca Mazzoni, Hanne S. Pedersen, Gerson A. de Oliveira Junior, Pamela Alexandre, Eduardo M. Razza, Henrik Callesen, Poul Hyttel, Marcelo F.G. Nogueira, Jose Bento S. Ferraz, Haja N. Kadarmideen

Downloads: 0
Views: 1292

Abstract

Assisted reproductive technologies (ARTs) have a strong impact on breeding especially when coupled with genomic selection (GS). The routine implementation of in vitro production (IVP) and GS of embryos before embryo transfer (ET) in breeding companies is not yet possible. Improvement of oocyte donor and embryo recipient quality is needed to make realistic a commercialization of these procedures in the near future. A better understanding of both biological mechanisms and molecular markers associated to IVPET related traits is necessary to improve the prediction of donor and recipient cow quality for IVP procedures. The huge amount of data generated from high throughput technologies has a tremendous impact in the search for biomarkers of complex traits. This paper reviews integrative genomics and systems biology approaches as applied to both Bos indicus and Bos taurus cattle reproduction by both conventional and ARTs such as OPU-IVP. The integration of systems biology information across different biological layers generates a complete view of the different molecular networks that control complex traits and can provide a strong contribution to the understanding of traits related to ARTs.

Keywords

systems biology, IVP, reproduction, cattle, biomarkers, data integration.

References

Amstalden M, Cardoso R, Alves B, Williams G. 2014. Reproduction symposium: hypothalamic neuropeptides and the nutritional programming of puberty in heifers. J Anim Sci, 92:3211-3222.

Aronson J. 2005. Biomarkers and surrogate endpoints. Br J Clin Pharmacol, 59:491-494.

Balboula AZ, Yamanaka K-I, Sakatani M, Kawahara M, Hegab A, Zaabel S, Takahashi M. 2013. Cathepsin B activity has a crucial role in the developmental competence of bovine cumulus–oocyte complexes exposed to heat shock during in vitro maturation. Reproduction, 146:407-417.

Bauersachs S, Ulbrich S, Gross K, Schmidt S, Meyer H, Einspanier R, Wenigerkind H, Vermehren M, Blum H, Sinowatz F. 2005. Gene expression profiling of bovine endometrium during the oestrous cycle: detection of molecular pathways involved in functional changes. J Mol Endocrinol, 34:889-908.

Bauersachs S, Ulbrich SE, Gross K, Schmidt SE, Meyer HH, Wenigerkind H, Vermehren M, Sinowatz F, Blum H, Wolf E. 2006. Embryo-induced transcriptome changes in bovine endometrium reveal species-specific and common molecular markers of uterine receptivity. Reproduction, 132:319-331.

Bauersachs S, Ulbrich SE, Zakhartchenko V, Minten M, Reichenbach M, Reichenbach H-D, Blum H, Spencer T.E, Wolf E. 2009. The endometrium responds differently to cloned versus fertilized embryos. Proc Natl Acad Sci, 106:5681-5686.

Binelli M, Scolari SC, Pugliesi G, Van Hoeck V, Gonella-Diaza AM, Andrade SC, Gasparin GR, Coutinho LL. 2015. The transcriptome signature of the receptive bovine uterus determined at early gestation. PloS One, 10:e0122874. Brazhnik P, de la Fuente A, Mendes P. 2002. Gene networks: how to put the function in genomics. Trends Biotechnol, 20:467-472.

Breiman L. 2001. Random forests. Mach Learn, 45:5- 32.

Buchner DA, Nadeau JH. 2015. Contrasting genetic architectures in different mouse reference populations used for studying complex traits. Genome Res, 25:775- 791.

Chuang H-Y, Hofree M, Ideker T. 2010. A decade of systems biology. Annu Rev Cell Dev Biol, 26:721-744. Cookson W, Liang L, Abecasis G, Moffatt M, Lathrop M. 2009. Mapping complex disease traits with global gene expression. Nat Rev Genet, 10:184-194.

De Wit A, Wurth Y, Kruip T. 2000. Effect of ovarian phase and follicle quality on morphology and developmental capacity of the bovine cumulus-oocyte complex. J Anim Sci, 78:1277-1283.

Dixon AL, Liang L, Moffatt MF, Chen W, Heath S, Wong KC, Taylor J, Burnett E, Gut I, Farrall M. 2007. A genome-wide association study of global gene expression. Nat Genet, 39:1202-1207.

Feng W-G, Sui H-S, Han Z-B, Chang Z-L, Zhou P, Liu D-J, Bao S, Tan J-H. 2007. Effects of follicular atresia and size on the developmental competence of bovine oocytes: a study using the well-in-drop culture system. Theriogenology, 67:1339-1350.

Fernando R, Garrick D. 2012. GenSel: user manual for a portfolio of genomic selection related analyses. Ames, IA: Iowa State University Animal Breeding &Genetics. 24 pp.

Forde N, Lonergan P. 2012. Transcriptomic analysis of the bovine endometrium: what is required to establish uterine receptivity to implantation in cattle? J Reprod Dev, 58:189-195.

Friedman N, Linial M, Nachman I, Pe'er D. 2000. Using Bayesian networks to analyze expression data. J Comput Biol, 7:601-620.

Gilbert I, Robert C, Vigneault C, Blondin P, Sirard M-A. 2012. Impact of the LH surge on granulosa cell transcript levels as markers of oocyte developmental competence in cattle. Reproduction, 143:735-747.

Girard A, Dufort I, Douville G, Sirard M-A. 2015. Global gene expression in granulosa cells of growing, plateau and atretic dominant follicles in cattle. Reproductive Biology and Endocrinology, 13:17. doi: 10.1186/s12958-015-0010-7.

Hatzirodos N, Hummitzsch K, Irving-Rodgers HF, Harland ML, Morris SE, Rodgers RJ. 2014a.

Transcriptome profiling of granulosa cells from bovine ovarian follicles during atresia. BMC Genomics, 15:40. doi: 10.1186/1471-2164-15-40.

Hatzirodos N, Irving-Rodgers HF, Hummitzsch K, Harland ML, Morris SE, Rodgers RJ. 2014b. Transcriptome profiling of granulosa cells of bovine ovarian follicles during growth from small to large antral sizes. BMC Genomics, 15:24. doi: 10.1186/1471- 2164-15-24.

Heleil B, Kuzmina T, Alm H, Scotti O, Tuchscherer A, Torner H. 2010. Involvement of granulosa cells in realization of prolactin effects on the developmental competence of bovine oocytes matured in vitro. J Am Sci, 6:796-805.

Horvath S, 2011. Weighted Network Analysis: applications in genomics and systems biology. New York, NY Springer Science & Business Media. 421 pp.

Jiang J-Y, Xiong H, Cao M, Xia X, Sirard M-A, Tsang BK. 2010. Mural granulosa cell gene expression associated with oocyte developmental competence. J Ovarian Res, 3:6. doi: 10.1186/1757-2215-3-6.

Kadarmideen HN, Watson-Haigh NS, Andronicos NM. 2011. Systems biology of ovine intestinal parasite resistance: disease gene modules and biomarkers. Mol Biosyst, 7:235-246.

Kadarmideen HN. 2014. Genomics to systems biology in animal and veterinary sciences: progress, lessons and opportunities. Livest Sci, 166:232-248.

Kadarmideen H, Mazzoni G, Watanabe Y, Strøbech L, Baruselli P, Meirelles F, Callesen H, Hyttel P, Ferraz J, Nogueira M. 2015. Genomic selection of in vitro produced and somatic cell nuclear transfer embryos for rapid genetic improvement in cattle production. Anim Reprod, 12, 389-396.

Killeen AP, Morris DG, Kenny DA, Mullen MP, Diskin MG, Waters SM. 2014. Global gene expression in endometrium of high and low fertility heifers during the mid-luteal phase of the estrous cycle. BMC Genomics, 15:234. doi: 10.1186/1471-2164-15-234.

Kitano H. 2002. Systems biology: a brief overview. Science, 295:1662-1664.

Lu P, Vogel C, Wang R, Yao X, Marcotte EM. 2007. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat Biotechnol, 25:117-124.

Mansouri-Attia N, Sandra O, Aubert J, Degrelle S, Everts RE, Giraud-Delville C, Heyman Y, Galio L, Hue I, Yang X. 2009. Endometrium as an early sensor of in vitro embryo manipulation technologies. Proc Natl Acad Sci, 106:5687-5692.

Matoba S, Bender K, Fahey AG, Mamo S, Brennan L, Lonergan P, Fair T. 2014. Predictive value of bovine follicular components as markers of oocyte developmental potential. Reprod Fertil Dev, 26:337- 345.

Mazzoni G, Kogelman LJ, Suravajhala P, Kadarmideen HN. 2015. Systems genetics of complex diseases using RNA-sequencing methods. Int J Biosci Biochem Bioinforma, 5:264.

Mazzoni G, Salleh SM, Freude K, Pedersen HS, Stroebech L, Callesen H, Hyttel P, Kadarmideen HN. 2017. Identification of potential biomarkers in donor cows for in vitro embryo production by granulosa cell transcriptomics. PloS One, 12:e0175464.

McCulloch WS, Pitts W. 1943. A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys, 5:115-133.

Minten MA, Bilby TR, Bruno RG, Allen CC, Madsen CA, Wang Z, Sawyer JE, Tibary A, Neibergs HL, Geary TW. 2013. Effects of fertility on gene expression and function of the bovine endometrium. PLoS One, 8:e69444.

Mitko K, Ulbrich SE, Wenigerkind H, Sinowatz F, Blum H, Wolf E, Bauersachs S. 2008. Dynamic changes in messenger RNA profiles of bovine endometrium during the oestrous cycle. Reproduction, 135:225-240.

Montojo J, Zuberi K, Rodriguez H, Kazi F, Wright G, Donaldson SL, Morris Q, Bader GD. 2010. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics, 26:2927- 2928.

Moor R, Trounson A, 1977. Hormonal and follicular factors affecting maturation of sheep oocytes in vitro and their subsequent developmental capacity. J Reprod Fertil, 49:101-109.

Morota G, Peñagaricano F, Petersen J, Ciobanu DC, Tsuyuzaki K, Nikaido I. 2015. An application of MeSH enrichment analysis in livestock. Anim Genet, 46:381-387.

Nica AC, Dermitzakis ET. 2013. Expression quantitative trait loci: present and future. Phil Trans R Soc B, 368:20120362.

Nivet A-L, Vigneault C, Blondin P, Sirard M-A. 2013. Changes in granulosa cells' gene expression associated with increased oocyte competence in bovine. Reproduction, 145:555-565.

Orozco-Lucero E, Sirard M. 2014. Molecular markers of fertility in cattle oocytes and embryos: progress and challenges. Anim Reprod, 11:183-194.

Ponsuksili S, Murani E, Schwerin M, Schellander K, Wimmers K. 2010. Identification of expression QTL (eQTL) of genes expressed in porcine M. longissimus dorsi and associated with meat quality traits. BMC Genomics, 11:572. doi: 10.1186/1471-2164-11-572.

Ponsuksili S, Murani E, Schwerin M, Schellander K, Tesfaye D, Wimmers K. 2012. Gene expression and DNA-methylation of bovine pretransfer endometrium depending on its receptivity after in vitro-produced embryo transfer. PloS One, 7:e42402.

Saadi HAS, Vigneault C, Sargolzaei M, Gagné D, Fournier É, de Montera B, Chesnais J, Blondin P, Robert C. 2014. Impact of whole-genome amplification on the reliability of pre-transfer cattle embryo breeding value estimates. BMC Genomics, 15:889. doi: 10.1186/1471-2164-15-889.

Salilew-Wondim D, Hölker M, Rings F, Ghanem N, Ulas-Cinar M, Peippo J, Tholen E, Looft C, Schellander K, Tesfaye D. 2010. Bovine pretransfer endometrium and embryo transcriptome fingerprints as predictors of pregnancy success after embryo transfer. Physiol Genomics, 42:201-218.

Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Selbach M. 2011. Global quantification of mammalian gene expression control. Nature, 473:337-342.

Simianer H. 2016. Genomic and other revolutions: why some technologies are quickly adopted and others are not. Anim Front, 6:53-58.

Suravajhala P, Kogelman LJ, Kadarmideen HN. 2016. Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare. Genet Sel Evol, 48:38.

Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP. 2015. STRING v10: protein– protein interaction networks, integrated over the tree of life. Nucleic Acids Res, 43, D447-D452.

Tsuyuzaki K, Morota G, Ishii M, Nakazato T, Miyazaki S, Nikaido I. 2015. MeSH ORA framework: R/Bioconductor packages to support MeSH overrepresentation analysis. BMC Bioinformatics, 16:45. doi: 10.1186/s12859-015-0453-z.

Wang H, Misztal I, Aguilar I, Legarra A, Muir W. 2012. Genome-wide association mapping including phenotypes from relatives without genotypes. Genet Res, 94:73-83.

Wang L, Michoel T. 2016. Detection of regulator genes and eQTLs in gene networks. In: Systems Biology in Animal Production and Health. Cham, Switzerland: Springer. vol. 1, pp. 1-23.

Westra H-J, Franke L. 2014. From genome to function by studying eQTLs. Biochim Biophys Acta, , 1842:1896-1902.

Wurth Y, Kruip TA. 1992. Bovine embryo production in vitro after selection of the follicles and oocytes. In: Proceedings of the 12th International Congress on Animal Reproduction, The Hague, The Netherlands. The Hague: ICAR. pp. 387-389.

Zeron Y, Ocheretny A, Kedar O, Borochov A, Sklan D, Arav A. 2001. Seasonal changes in bovine fertility: relation to developmental competence of oocytes, membrane properties and fatty acid composition of follicles. Reproduction, 121:447-454.

Zhang ZH, Jhaveri DJ, Marshall VM, Bauer DC, Edson J, Narayanan RK, Robinson GJ, Lundberg AE, Bartlett PF, Wray NR. 2014. A comparative study of techniques for differential expression analysis on RNA-Seq data. PloS One, 9:e103207.

Zhao W, Langfelder P, Fuller T, Dong J, Li A, Hovarth S. 2010. Weighted gene coexpression network analysis: state of the art. J Biopharm Stat, 20:281-300.

5b71d6be0e8825271e8068aa animreprod Articles
Links & Downloads

Anim Reprod

Share this page
Page Sections