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ADVANCES IN FARM ANIMAL GENOMIC RESOURCES

EDITED BY :

Stéphane Joost, Michael W. Bruford, Ino Curik,

Juha Kantanen, Johannes A. Lenstra, Johann Sölkner,

Göran Andersson, Philippe V. Baret, Nadine Buys, Jutta Roosen, Michèle Tixier-Boichard and Paolo Ajmone Marsan

PUBLISHED IN : Frontiers in Genetics

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ISSN 1664-8714 ISBN 978-2-88919-735-4 DOI 10.3389/978-2-88919-735-4

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The history of livestock started with the domestication of their wild ancestors: a restricted number of species allowed to be tamed and entered a symbiotic relationship with humans. In exchange for food, shelter and protection, they provided us with meat, eggs, hides, wool and draught power, thus contributing considerably to our economic and cultural development. Depending on the species, domestication took place in different areas and periods. After domestication, livestock spread over all inhabited regions of the earth, accompanying human migrations and becoming also trade objects. This required an adaptation to different climates and varying styles of husbandry and resulted in an enormous phenotypic diversity.

Approximately 200 years ago, the situation started to change with the rise of the concept of breed. Animals were selected for the same visible characteristics, and crossing with different phenotypes was reduced. This resulted in the formation of different breeds, mostly genetically isolated from other populations. A few decades ago, selection pressure was increased again with intensive production focusing on a limited range of types and a subsequent loss of genetic

GENOMIC RESOURCES

Images 1-3 taken from: http://www.photolibre.fr (retrieved in 2010), image 4 by Stéphane Joost.

Cover image by Stéphane Joost, EPFL and http://www.photolibre.fr (retrieved in 2010).

Topic Editors:

Stéphane Joost, École Polytechnique Fédérale de Lausanne, Switzerland Michael W. Bruford, Cardiff University, UK

Ino Curik, University of Zagreb, Croatia

Juha Kantanen, Natural Resources Institute Finland, Finland Johannes A. Lenstra, Utrecht University, Netherlands

Johann Sölkner, University of Natural Resources and Life Sciences Vienna, Austria Göran Andersson, Swedish University of Agricultural Sciences, Sweden

Philippe V. Baret, Université catholique de Louvain, Belgium Nadine Buys, KU Leuven, Belgium

Jutta Roosen, Technische Universität München, Germany Michèle Tixier-Boichard, INRA, France

Paolo Ajmone Marsan, Università Cattolica del S. Cuore, Italy

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diversity. For short-term economic reasons, farmers have abandoned traditional breeds. As a consequence, during the 20th century, at least 28% of farm animal breeds became extinct, rare or endangered. The situation is alarming in developing countries, where native breeds adapted to local environments and diseases are being replaced by industrial breeds. In the most marginal areas, farm animals are considered to be essential for viable land use and, in the developing world, a major pathway out of poverty.

Historic documentation from the period before the breed formation is scarce. Thus, reconstruc- tion of the history of livestock populations depends on archaeological, archeo-zoological and DNA analysis of extant populations. Scientific research into genetic diversity takes advantage of the rapid advances in molecular genetics. Studies of mitochondrial DNA, microsatellite DNA profiling and Y-chromosomes have revealed details on the process of domestication, on the diversity retained by breeds and on relationships between breeds. However, we only see a small part of the genetic information and the advent of new technologies is most timely in order to answer many essential questions.

High-throughput single-nucleotide polymorphism genotyping is about to be available for all major farm animal species. The recent development of sequencing techniques calls for new methods of data management and analysis and for new ideas for the extraction of information.

To make sense of this information in practical conditions, integration of geo-environmental and socio-economic data are key elements. The study and management of farm animal genomic resources (FAnGR) is indeed a major multidisciplinary issue.

The goal of the present Research Topic was to collect contributions of high scientific quality relevant to biodiversity management, and applying new methods to either new genomic and bioinformatics approaches for characterization of FAnGR, to the development of FAnGR con- servation methods applied ex-situ and in-situ, to socio-economic aspects of FAnGR conserva- tion, to transfer of lessons between wildlife and livestock biodiversity conservation, and to the contribution of FAnGR to a transition in agriculture (FAnGR and agro-ecology).

Citation: Joost, S., Bruford, M. W., Curik, I., Kantanen, J., Lenstra, J. A., Sölkner, J., Andersson, G., Baret, P. V., Buys, N., Roosen, J., Tixier-Boichard, M., Marsan, P. A., eds. (2016). Advances in Farm Animal Genomic Resources. Lausanne: Frontiers Media. doi: 10.3389/978-2-88919-735-4

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Table of Contents

08 Editorial: Advances in Farm Animal Genomic Resources

Stéphane Joost, Michael W. Bruford and The Genomic-Resources Consortium

Challenges for the conservation of farm animal genomic resources 13 Prospects and challenges for the conservation of farm animal genomic

resources, 2015-2025

Michael W. Bruford, Catarina Ginja, Irene Hoffmann, Stéphane Joost,

Pablo Orozco-terWengel, Florian J. Alberto, Andreia J. Amaral, Mario Barbato, Filippo Biscarini, Licia Colli, Mafalda Costa, Ino Curik, Solange Duruz,

Maja Ferencˇakovic‘, Daniel Fischer, Robert Fitak, Linn F. Groeneveld, Stephen J. G. Hall, Olivier Hanotte, Faiz-ul Hassan, Philippe Helsen, Laura Iacolina, Juha Kantanen, Kevin Leempoel, Johannes A. Lenstra, Paolo Ajmone-Marsan, Charles Masembe, Hendrik-Jan Megens, Mara Miele, Markus Neuditschko, Ezequiel L. Nicolazzi, François Pompanon, Jutta Roosen, Natalia Sevane, Anamarija Smetko,

Anamaria Štambuk, Ian Streeter, Sylvie Stucki, China Supakorn, Luis Telo Da Gama, Michèle Tixier-Boichard, Daniel Wegmann and Xiangjiang Zhan

24 What can livestock breeders learn from conservation genetics and vice versa?

Torsten N. Kristensen, Ary A. Hoffmann, Cino Pertoldi and Astrid V. Stronen 36 Changing values of farm animal genomic resources. from historical breeds to

the Nagoya Protocol Sakari Tamminen

45 Genetic resources and genomics for adaptation of livestock to climate change Paul J. Boettcher, Irene Hoffmann, Roswitha Baumung, Adam G. Drucker,

Concepta McManus, Peer Berg, Alessandra Stella, Linn B. Nilsen, Dominic Moran, Michel Naves and Mary C. Thompson

FAnGR in Africa

49 Characterizing neutral genomic diversity and selection signatures in indigenous populations of Moroccan goats (Capra hircus) using WGS data Badr Benjelloun, Florian J. Alberto, Ian Streeter, Frédéric Boyer, Eric Coissac, Sylvie Stucki, Mohammed BenBati, Mustapha Ibnelbachyr, Mouad Chentouf, Abdelmajid Bechchari, Kevin Leempoel, Adriana Alberti, Stefan Engelen, Abdelkader Chikhi, Laura Clarke, Paul Flicek, Stéphane Joost, Pierre Taberlet, François Pompanon and NextGen Consortium

63 Trypanosomosis: Potential driver of selection in African cattle

Anamarija Smetko, Albert Soudre, Katja Silbermayr, Simone Müller, Gottfried Brem, Olivier Hanotte, Paul J. Boettcher, Alessandra Stella, Gábor Mészáros,

Maria Wurzinger, Ino Curik, Mathias Müller, Jörg Burgstaller and Johann Sölkner

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71 Genomic adaptation of admixed dairy cattle in East Africa Eui-Soo Kim and Max F. Rothschild

81 Population genetic structure, linkage disequilibrium and effective population size of conserved and extensively raised village chicken populations of Southern Africa

Khulekani S. Khanyile, Edgar F. Dzomba and Farai C. Muchadeyi

92 Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel

Sithembile O. Makina, Farai C. Muchadeyi, Este van Marle-Köster, Michael D. MacNeil and Azwihangwisi Maiwashe

The role of social science in the management of FAnGR

100 Comparing decision-support systems in adopting sustainable intensification criteria

Bouda Vosough Ahmadi, Dominic Moran, Andrew P. Barnes and Philippe V. Baret 105 Citizens’ preferences for the conservation of agricultural genetic resources

Eija Pouta, Annika Tienhaara and Heini Ahtiainen

115 Farm animal genetic and genomic resources from an agroecological perspective

Michèle Tixier-Boichard, Etienne Verrier, Xavier Rognon and Tatiana Zerjal 118 Utilization of farm animal genetic resources in a changing agro-ecological

environment in the Nordic countries

Juha Kantanen, Peter Løvendahl, Erling Strandberg, Emma Eythorsdottir, Meng-Hua Li, Anne Kettunen-Præbel, Peer Berg and Theo Meuwissen

Demographic events and diversity in cattle

128 Genomic data as the “hitchhiker’s guide” to cattle adaptation: Tracking the milestones of past selection in the bovine genome

Yuri T. Utsunomiya, Ana M. Pérez O’Brien, Tad S. Sonstegard, Johann Sölkner and José F. Garcia

141 Revisiting demographic processes in cattle with genome-wide population genetic analysis

Pablo Orozco-terWengel, Mario Barbato, Ezequiel Nicolazzi, Filippo Biscarini,

Marco Milanesi, Wyn Davies, Don Williams, Alessandra Stella, Paolo Ajmone-Marsan and Michael W. Bruford

156 Microsatellite genotyping of medieval cattle from central Italy suggests an old origin of Chianina and Romagnola cattle

Maria Gargani, Lorraine Pariset, Johannes A. Lenstra, Elisabetta De Minicis, European Cattle Genetic Diversity Consortium and Alessio Valentini

162 Hybrid origin of European commercial pigs examined by an in-depth haplotype analysis on chromosome 1

Mirte Bosse, Ole Madsen, Hendrik-Jan Megens, Laurent A. F. Frantz, Yogesh Paudel, Richard P. M. A. Crooijmans and Martien A. M. Groenen

171 SNeP: A tool to estimate trends in recent effective population size trajectories using genome-wide SNP data

Mario Barbato, Pablo Orozco-terWengel, Miika Tapio and Michael W. Bruford

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178 Challenges and opportunities in genetic improvement of local livestock breeds Filippo Biscarini, Ezequiel L. Nicolazzi, Alessandra Stella, Paul J. Boettcher and Gustavo Gandini

185 Recent advances in understanding the genetic resources of sheep breeds locally-adapted to the UK uplands: Opportunities they offer for sustainable productivity

Dianna Bowles

190 A case study on strains of Buša cattle structured into a metapopulation to show the potential for use of single-nucleotide polymorphism genotyping in the management of small, cross-border populations of livestock breeds and varieties

Elli T. Broxham, Waltraud Kugler and Ivica Medugorac

192 Genomic analysis for managing small and endangered populations: A case study in Tyrol Grey cattle

Gábor Mészáros, Solomon A. Boison, Ana M. Pérez O’Brien, Maja Ferencˇakovic‘, Ino Curik, Marcos V. Barbosa Da Silva, Yuri T. Utsunomiya, Jose F. Garcia and Johann Sölkner

204 Characterization of genetic diversity and gene mapping in two Swedish local chicken breeds

Anna M. Johansson and Ronald M. Nelson

212 Morphological and genetic characterization of an emerging Azorean horse breed: The Terceira Pony

Maria S. Lopes, Duarte Mendonça, Horst Rojer, Verónica Cabral, Sílvia X. Bettencourt and Artur da Câmara Machado

219 Fecal egg counts for gastrointestinal nematodes are associated with a polymorphism in the MHC-DRB1 gene in the Iranian Ghezel sheep breed Rahman Hajializadeh Valilou, Seyed A. Rafat, David R. Notter, Djalil Shojda, Gholamali Moghaddam and Ahmad Nematollahi

Approaches and tools for breeding programs

231 An interpretive review of selective sweep studies in Bos taurus cattle

populations: Identification of unique and shared selection signals across breeds Beatriz Gutiérrez-Gil, Juan J. Arranz and Pamela Wiener

251 Artificial selection with traditional or genomic relationships: Consequences in coancestry and genetic diversity

Silvia Teresa Rodríguez-Ramilo, Luis Alberto García-Cortés and María Ángeles Rodríguez de Cara

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

Duy N. Do, Anders B. Strathe, Tage Ostersen, Sameer D. Pant and Haja N. Kadarmideen

272 Changes in variance explained by top SNP windows over generations for three traits in broiler chicken

Breno de Oliveira Fragomeni, Ignacy Misztal, Daniela Lino Lourenco, Ignacio Aguilar, Ronald Okimoto and William M. Muir

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279 Genetic differentiation of Mexican Holstein cattle and its relationship with Canadian and U.S. Holsteins

Adriana García-Ruiz, Felipe de J. Ruiz-López, Curtis P. Van Tassell, Hugo H. Montaldo and Heather J. Huson

286 Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes

Ludmilla B. Zavarez, Yuri T. Utsunomiya, Adriana S. Carmo, Haroldo H. R. Neves, Roberto Carvalheiro, Maja Ferencˇakovic‘, Ana M. Pérez O’Brien, Ino Curik, John B. Cole, Curtis P. Van Tassell, Marcos V. G. B. da Silva, Tad S. Sonstegard, Johann Sölkner and José F. Garcia

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Edited and reviewed by:

Guilherme J. M. Rosa, University of Wisconsin, USA

*Correspondence:

Stéphane Joost stephane.joost@epfl.ch

http://genomic-resources.epfl.ch

Specialty section:

This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics Received:14 September 2015 Accepted:04 November 2015 Published:24 November 2015 Citation:

Joost S, Bruford MW and The Genomic-Resources Consortium (2015) Editorial: Advances in Farm Animal Genomic Resources.

Front. Genet. 6:333.

doi: 10.3389/fgene.2015.00333

Editorial: Advances in Farm Animal Genomic Resources

Stéphane Joost1*, Michael W. Bruford2, 3and The Genomic-Resources Consortium

1Laboratory of Geographic Information Systems, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,2School of Biosciences, Cardiff University, Cardiff, UK,

3Sustainable Places Research Institute, Cardiff University, Cardiff, UK

Keywords: genomic resources, conservation of genomic diversity, data integration, GIS, next generation sequencing, social sciences, disease resistance, sustainable breeding

Livestock conservation is changing rapidly in light of policy developments, climate change, and diversifying market demands. The last decade has seen a step change in technology and analytical approaches available to define and manage Farm Animal Genetic Resources (FAnGR).

However, these rapid changes pose challenges for FAnGR management in terms of technological continuity, analytical capacity, and integrative methodologies. Indeed, high-throughput single- nucleotide polymorphism genotyping is available for all major farm animal species and beyond the technological challenge to deal with these large molecular datasets, their integration with geo- environmental and socio-economic information is key to making sense of the data in practical conditions.

In this context, a 4-year (2010–2014) European Science Foundation (http://www.esf.org) Research Networking Programme “Advances in Farm Animal Genomic Resources” (Genomic- Resources) proposed an action dedicated to the education of young scientists in cutting edge approaches to the characterization, analysis, evaluation, management, and conservation of FAnGR.

The RNP funded three summer schools (Italy, Croatia, Austria), three workshops (Switzerland, Iceland, Finland), two conferences (Belgium, United Kingdom), and 26 exchange grants. These actions directly connected a community of 350 researchers to develop activities with the goal to meet two major challenges: (i) training in the use of novel methods able to manage and analyse high-throughput molecular data, and (ii) promoting collaboration between the animal science and social science communities to more efficiently manage FAnGR.

In addition to the activities described above, Genomic-Resources has, in this issue ofFrontiers in Genetics, fostered scientific contributions applying new methods to genomic and bioinformatics approaches for characterization of FAnGR, enhancing ex-situand in-situFAnGR conservation methods, promoting socio-economic elements of FAnGR conservation, transferring lessons between wildlife and livestock biodiversity conservation and has evaluated the contribution of FAnGR to a transition in agriculture (agro-ecology). The 31 articles can be broadly attributed to six different topic areas.

The first topic area contains general papers dealing with the identification of questions of highest priority for FAnGR research during the coming decade (Bruford et al., 2015), the common management challenges shared by livestock breeds and threatened natural populations (Kristensen et al., 2015), the transformation of FAnGR from economic, ecological, and scientific into political entities (Tamminen, 2015), and on the impact of climate change on genetic resources, which constitute the livelihoods of around 1 billion people worldwide (Boettcher et al., 2015).

The latter paper links to a section of papers dedicated to Africa, a continent where livestock genetic resources are particularly endangered and where climate change poses a major threat.

The need to increase short-term productivity is prompting the substitution of local breeds by cosmopolitan ones, with the consequence of breeders becoming dependent on expensive external inputs (Colli et al., 2014) instead of making greater use of the well-adapted livestock already

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Joost et al. Editorial: Advances in FAnGR

living in Africa (Hanotte et al., 2010). Here Benjelloun et al.

(2015) characterize neutral genomic diversity and selection signatures in local Moroccan goat populations illustrating the use of whole genome sequence data. To the South, in Burkina Faso, Trypanosomosis transmitted by tsetse-flies is a cause of productivity reduction in cattle. To better understand resistance to the disease, Smetko et al. (2015) compare levels of zebu and taurine admixture in genomic regions possibly involved in trypanotolerance. Eastwards, in Kenya,Kim and Rothschild (2014)analyze the ancestry of local cattle admixed with imported breeds including Guernsey, Norwegian Red, and Holstein to provide useful information for dairy breeding. In Malawi, Zimbabwe, and South Africa, Khanyile et al. (2015) focus on village chicken production and investigated the genetic structure and diversity in more than 300 individuals with a High-density SNP assay to extract valuable information useful for indigenous animal genetic resources management. Finally, in South Africa Makina et al. (2014)investigate genetic diversity and population structure among six cattle breeds using a whole genome SNP panel to examine the possible valuable distinctiveness of indigenous South African breeds likely to cope with climate change.

To stress the important role of social science and its links with animal science in FAnGR management, Genomic-Resources encouraged interaction between the fields (see http://www.

genresandpit.eu/) and solicited contributions to this special issue to illustrate the inputs of these disciplines. Key contributions within this scope constitute part of section 3. Ahmadi et al.

(2015)highlight the role of decision support systems—used for FAnGR prioritization for example—to integrate technical and social aspects of farming practices. The social dimension of FAnGR conservation is also exemplified by citizen’s willingness to pay for conservation programs according to their preferences for native breeds, as shown by Pouta et al. (2014). Section 3 is complemented by papers dealing with agro-ecology. As argued byTixier-Boichard et al. (2015), the application of agro- ecology to livestock production requires a change of scale in breed management, and represents a social rather than a genetic challenge. Then, concerned with the physical dimension of agro- ecology, Kantanen et al. (2015) review the main changes in Nordic agro-climatic conditions caused in part by livestock production, stressing the importance of animals’ ability to adapt.

The fourth section is dedicated to the analysis of demographic events that have shaped cattle diversity.Utsunomiya et al. (2015) track the milestones of past selection in the bovine genome, Orozco-terWengel et al. (2015) revisit demographic processes in cattle with genome-wide data, and Gargani et al. (2015) show how DNA from archeological remains can be used to interpret the history of ancient populations and their supposed relationship with Chianina and Romagnola, two modern central- Italian breeds.Bosse et al. (2015)investigate different events in the history of the domestication of the Eurasian wild boar (Sus scrofa), comparing the genomes of European commercial pigs to their wild ancestors. The section closes with a description of SNeP, a tool to estimate changes in effective population size using genome-wide SNP data which can improve our understanding of population demography in the recent past (Barbato et al., 2015).

The next section in the special issue focuses on local breeds.

It is introduced by two mini-review papers on the relevance of genetic improvement for these breeds (Biscarini et al., 2015), and on the opportunity represented by locally-adapted livestock breeds in the United Kingdom as valuable reservoirs of adaptive fitness to face productivity issues under changing climate (Bowles, 2015). Also highlighting the characteristics of local breeds,Broxham et al. (2015)describe the BushaLive project targeting the autochthonous Buša cattle of the Balkans. The use of genomic analysis to manage small endangered populations (Mészáros et al., 2015), the determination of comb color in two Swedish local chicken breeds (Johansson and Nelson, 2015), the genetic characterization of the Terceira Pony from the Azores (Lopes et al., 2015), and resistance to gastrointestinal nematodes in the Iranian Ghezel sheep (Valilou et al., 2015) comprise the other research papers presented in this section.

The final section combines research on tools and approaches used in the context of (industrial) breeding programs.Gutiérrez- Gil et al. (2015)compile a review of studies with more than 1000 selection signatures in mainly beef and dairy breeds, and propose a characterization of these selective sweeps. The other contributions illustrate different applications related to estimated breeding value (Rodríguez-Ramilo et al., 2015), genomic selection (Do et al., 2014; Fragomeni Bde et al., 2014), and genetic differentiation (García-Ruiz et al., 2015).

This research topic has provided a valuable set of papers taking stock of the current advances in farm animal genomic resources worldwide. However, it inevitably lacks contributions in some areas, such as incorporation of Geographic Information Systems (GIS) to integrate complementary data on population genetics, animal husbandry practices, socio-economic and environmental characteristics (Joost et al., 2010) needed to enable the “landscape approach” advocated (Boettcher et al., 2015), and featuring in several of the top 20 questions in farm animal genomics research (Bruford et al. 2015, Table 1, questions #4, #12, #13 and #14). While the integrative function they provide is likely to identify potentially valuable genetic material (Hanotte et al., 2010), GIS and related approaches remain underexploited in FAnGR management.

AUTHOR CONTRIBUTION

SJ initiated the research topic and chaired the corresponding European Science Foundation project, SJ and MB wrote and revised the manuscript, members of the Genomic-Resources consortium managed the ESF project and participated in the editorial process of this research topic.

ACKNOWLEDGMENTS

GENOMIC-RESOURCES was supported by: Fonds zur Förderung der wissenschaftlichen Forschung (FWF), FWF Austrian Science Fund, Austria; Fonds National de la Recherche Scientifique (FNRS), Belgium; Fonds voor Wetenschappelijk Onderzoek-Vlaanderen (FWO), The Research Foundation, Flanders, Belgium; Nacionalna zaklada za znanost, visoko školstvo i tehnologijski razvoj Republike Hrvatske, Croatian

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Science Foundation, Republic of Croatia; Suomen Akatemia, Biotieteiden ja ympäristön tutkimuksen toimikunta, Academy of Finland, Research Council for Biosciences and Environment, Finland; Deutsche Forschungsgemeinschaft (DFG), German Research Foundation, Germany; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), The Netherlands Organisation for Scientific Research, The Netherlands;

Norges Forskningsråd, The Research Council of Norway, Norway; Forskningsrådet för miljö, areella näringar och samhällsbyggande, Swedish Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS), Sweden;

Schweizerischer Nationalfonds (SNF), Swiss National Science Foundation, Switzerland; Biotechnology and Biological Sciences Research Council (BBSRC), United Kingdom.

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Joost, Bruford and The Genomic-Resources Consortium. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice.

No use, distribution or reproduction is permitted which does not comply with these terms.

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FARM ANIMAL GENOMIC RESOURCES

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HYPOTHESIS AND THEORY published: 21 October 2015 doi: 10.3389/fgene.2015.00314

Edited by:

Peter Dovc, University of Ljubljana, Slovenia Reviewed by:

Juan Steibel, Michigan State University, USA John B. Cole, United States Department of Agriculture, USA

*Correspondence:

Michael W. Bruford brufordmw@cardiff.ac.uk

Specialty section:

This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics Received:26 May 2015 Accepted:05 October 2015 Published:21 October 2015

Prospects and challenges for the

conservation of farm animal genomic resources, 2015-2025

Michael W. Bruford1, 2*, Catarina Ginja3, 4, Irene Hoffmann5, Stéphane Joost6, Pablo Orozco-terWengel1, Florian J. Alberto7, Andreia J. Amaral8, Mario Barbato1, Filippo Biscarini9, Licia Colli10, Mafalda Costa1, Ino Curik11, Solange Duruz6, Maja Feren ˇcakovi ´c11, Daniel Fischer12, Robert Fitak13, Linn F. Groeneveld14, Stephen J. G. Hall15, Olivier Hanotte16, Faiz-ul Hassan16, 17, Philippe Helsen18, Laura Iacolina19, Juha Kantanen12, 20, Kevin Leempoel6, Johannes A. Lenstra21, Paolo Ajmone-Marsan10, Charles Masembe22, Hendrik-Jan Megens23, Mara Miele24, Markus Neuditschko25, Ezequiel L. Nicolazzi9, François Pompanon7, Jutta Roosen26, Natalia Sevane27, Anamarija Smetko28, Anamaria Štambuk29, Ian Streeter30,

Sylvie Stucki6, China Supakorn16, 31, Luis Telo Da Gama32, Michèle Tixier-Boichard33, Daniel Wegmann34and Xiangjiang Zhan35, 36

1School of Biosciences, Cardiff University, Cardiff, UK,2Sustainable Places Research Institute, Cardiff University, Cardiff, UK,

3Faculdade de Ciências, Centro de Ecologia, Evolução e Alterações Ambientais (CE3C), Universidade de Lisboa, Lisboa, Portugal,4Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO-InBIO), Universidade do Porto, Campus Agrário de Vairão, Portugal,5Food and Agriculture Organization of the United Nations, Animal Genetic Resources Branch, Animal Production and Health Division, Rome, Italy,6Laboratory of Geographic Information Systems (LASIG), School of Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,7Laboratoire d’Ecologie Alpine, Université Grenoble Alpes, Grenoble, France,8Faculty of Sciences, BioISI- Biosystems and Integrative Sciences Institute, University of Lisbon, Campo Grande, Portugal,9Parco Tecnologico Padano, Lodi, Italy,10BioDNA Centro di Ricerca sulla Biodiversità a sul DNA Antico, Istituto di Zootecnica, Università Cattolica del Sacro Cuore di Piacenza, Italy,

11Faculty of Agriculture, University of Zagreb, Zagreb, Croatia,12Natural Resources Institute Finland (Luke), Green

Technology, Jokioinen, Finland,13Institut für Populationsgenetik, Vetmeduni, Vienna, Austria,14NordGen -The Nordic Genetic Resource Center, Ås, Norway,15Livestock Diversity Ltd., Lincoln, UK,16School of Life Sciences, University of Nottingham, Nottingham, UK,17Department of Animal Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan,18Centre for Research and Conservation, Royal Zoological Society of Antwerp, Antwerp, Belgium,19Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark,20Department of Biology, University of Eastern Finland, Kuopio, Finland,

21Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherland,22Institute of the Environment and Natural Resources, Makerere University, Kampala, Uganda,23Animal Breeding and Genomics Centre, Wageningen University, Wageningen, Netherlands,24School of Planning and Geography, Cardiff University, Cardiff, UK,25Agroscope, Swiss National Stud Farm, Avenches, Switzerland,26TUM School of Management, Technische Universität München, Munich, Germany,

27Department of Animal Production, Veterinary Faculty, Universidad Complutense de Madrid, Madrid, Spain,28Croatian Agricultural Agency, Zagreb, Croatia,29Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia,

30European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK,31School of Agricultural Technology, Walailak University, Tha Sala, Thailand,32Centre of Research in Animal Health (CIISA) – Faculty of Veterinary Medicine, University of Lisbon, Lisbon, Portugal,33INRA, AgroParisTech, UMR GABI, Jouy-en-Josas, France,34Department of Biology, University of Fribourg, Fribourg, Switzerland,35Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China,36Cardiff University – Institute of Zoology, Joint Laboratory for Biocomplexity Research, Beijing, China

Livestock conservation practice is changing rapidly in light of policy developments, climate change and diversifying market demands. The last decade has seen a step change in technology and analytical approaches available to define, manage and conserve Farm Animal Genomic Resources (FAnGR). However, these rapid changes pose challenges for FAnGR conservation in terms of technological continuity, analytical capacity and integrative methodologies needed to fully exploit new, multidimensional data. The final conference of the ESF Genomic Resources program aimed to address

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these interdisciplinary problems in an attempt to contribute to the agenda for research and policy development directions during the coming decade. By 2020, according to the Convention on Biodiversity’s Aichi Target 13, signatories should ensure that

“…the genetic diversity of …farmed and domesticated animals and of wild relatives …is maintained, and strategies have been developed and implemented for minimizing genetic erosion and safeguarding their genetic diversity.” However, the real extent of genetic erosion is very difficult to measure using current data. Therefore, this challenging target demands better coverage, understanding and utilization of genomic and environmental data, the development of optimized ways to integrate these data with social and other sciences and policy analysis to enable more flexible, evidence-based models to underpin FAnGR conservation. At the conference, we attempted to identify the most important problems for effective livestock genomic resource conservation during the next decade. Twenty priority questions were identified that could be broadly categorized into challenges related to methodology, analytical approaches, data management and conservation. It should be acknowledged here that while the focus of our meeting was predominantly around genetics, genomics and animal science, many of the practical challenges facing conservation of genomic resources are societal in origin and are predicated on the value (e.g., socio-economic and cultural) of these resources to farmers, rural communities and society as a whole. The overall conclusion is that despite the fact that the livestock sector has been relatively well-organized in the application of genetic methodologies to date, there is still a large gap between the current state-of-the-art in the use of tools to characterize genomic resources and its application to many non-commercial and local breeds, hampering the consistent utilization of genetic and genomic data as indicators of genetic erosion and diversity. The livestock genomic sector therefore needs to make a concerted effort in the coming decade to enable to the democratization of the powerful tools that are now at its disposal, and to ensure that they are applied in the context of breed conservation as well as development.

Keywords: farm animal genetic resources, livestock genetic resources, genomic diversity, livestock population prioritization, effective conservation policy

INTRODUCTION

Understanding current technical, infrastructural and policy challenges and assessing the likely benefits of overcoming them in the future is essential for any field of scientific endeavor and especially those with clear societal consequences and potential benefits. In this context, the concept of horizon scanning has been developed and applied annually in the field of biodiversity conservation since 2009 (Sutherland and Woodroof, 2009), using a variety of systematic and semi-systematic methods to mine trending issues from web engines and social media and by analyzing focused questionnaires. Similar approaches have also been taken to identify emerging issues in agriculture (Pretty et al., 2010) and related fields such as soil science, food systems and pollination (Dicks et al., 2013; Ingram et al., 2013; Adewopo et al., 2014). Such exercises have identified a number of issues of relevance to the conservation of FAnGR, such as genetic control of invasive species (Sutherland et al., 2014) and sustainable intensification of high yielding agriculture (Sutherland et al., 2015). In 2010, Pretty et al.’s article pinpointing the “Top

100 questions of importance to the future of global agriculture”

identified genetic issues in crop improvement (e.g., gains in improvement that could result from breeding for stress tolerance) but identified no such pressing agendas for livestock genomic resources. Since Cardellino and Boyazoglu (2009) no attempt has been published to identify research priorities for FAnGR conservation, despite genetic erosion (sensu Aichi Target 13) continuing apace (e.g., Berthouly-Salazar et al., 2012; FAO, 2015a) and the step-change that has occurred in molecular breed characterization since the routine implementation of livestock Single Nucleotide Polymorphism (SNP) arrays. To fill this gap, a central activity of the Final Conference of the European Science Foundation’s Genomic Resources program, held at Cardiff University June 17th–19th 2014 was to pick out a series of pressing questions that could form part of a research and policy agenda for FAnGR conservation for the next decade. While not following the standard systematic approaches adopted by conventional Horizon Scanning exercises, all 43 attendees of this focused meeting took part in the exercise, including scientists and policy-makers from South and East Asia, North America, Europe

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Bruford et al. Challenges in livestock conservation

and Africa involved in a range of disciplines from genomics to animal breeding, genetic resource management, economic and social sciences and global agricultural policy development.

METHODS AND RESULTS

During the course of the conference, attendees were asked to contribute up to five questions of highest priority for research, infrastructure and policy development during the coming decade. Eighty-six suggestions were received. The issue identified with highest frequency (18 times) was the need for

“next generation phenotyping” (i.e., high-throughput methods to collect and summarize detailed phenotypic data from domestic animals). A summary of the top 20 questions is found in Table 1, a subset of which are presented below (some are amalgamated). All responses were categorized into four major groups, “Methodological Challenges,” “Analytical Challenges,”

“Data Management,” and “Conservation Management and Prioritization.” Four working groups were convened to cover these categories and their findings are presented below.

Methodological Challenges

Next Generation Phenotyping

The need for high-resolution phenotypic data to be collected for in-depth characterization of FAnGR was identified, especially in light of the rapid advances that have been made in molecular breed characterization. Developing methods for phenotypic characterization was also identified byCardellino and Boyazoglu (2009)following from FAO recommendations (FAO, 2007a) and has clearly remained an under-explored research area. However, with the richness of molecular data increasing dramatically since 2009, the mismatch between molecular and phenotypic data is widening for all except highly commercial transboundary breeds and lines with genomic breeding values. Inherent in high-resolution breed characterization is a need to define key phenotypic traits and characteristics (particularly those potentially involved in local adaptation) based on guidelines that can be used as common measures for such studies with stringent field protocols for their collection. FAO published guidelines on phenotypic characterization (FAO, 2012a). In this way more comparable data can be generated, and breed characterization can have a more functional basis, especially with the urgent need to understand breed characteristics in the face of climate change (Hoffmann, 2010). Also an improved description of the specific production environment and epidemiological history in which populations of a breed are kept would allow better comparison of phenotypes and performances (e.g.,FAO, 2009).

Since breed characterization can be a costly exercise, especially for remote regions of the world, as many phenotypic traits as possible should be collected following well documented and reproducible procedures, a process that calls for the need for standardized methods to measure/collect data and ultimately for training of people on how to do it. Where possible, data should be made publicly available through a repository such as FAO’s global Domestic Animal Diversity Information System DAD-IS (http://dad.fao.org) for comparative purposes. The establishment of a working group to define guidelines, protocols and tools for collecting such data under the auspices of the FAO, International

Society for Animal Genetics or the International Committee for Animal Recording (www.icar.org) would accelerate this process.

Omics Data and Association Studies

The dramatic acceleration in genome sequencing means that all domesticated species and their few remaining wild relatives will become genome-enabled in the coming decade (e.g., Qiu et al., 2012; Wu et al., 2014). Reference genomes provide the basis for development of genome-wide assays for variation in less commonly farmed and/or more regionally distributed livestock species and populations using SNP arrays, as have been developed and made available for commercial livestock in the past 5 years (e.g.,Matukumalli et al., 2009). The choice of SNPs for inclusion in arrays for less commercial populations may be expected to focus on a wider array of traits than for commercial/transboundary breeds, such as those related to local adaptation, disease resistance, drought tolerance and niche product characters, but in practice this could be hampered by a lack of reliable phenotypic data. To enable SNP arrays to be developed in a rapid, cost effective and widely applicable manner, the identification of common reference genomes and test panels of individuals for array development and diversity studies is key.

However, it is important to note that with the rapidly falling cost of whole genome resequencing (e.g.,Lee et al., 2013; Zhang et al., 2015) using next generation technologies and the availability of even lower cost genotyping by sequencing (GBS:De Donato et al., 2013) being available, the problem of ascertainment bias can be mitigated against since they allow the identification and direct estimation of SNP diversity for FAnGR populations, breeds or species at reasonable prices. Indeed these methods are sufficiently cost-effective now, that they can be in principle used as standard assaying approaches, with a cost in the low tens of dollars for GBS now feasible for analysis of tens of thousands of SNPs.

A major issue identified for genome-wide association studies (GWAS) is experimental design including, but not confined to, sample size considerations (Kadarmideen, 2014) and the availability of different SNP genotyping arrays for some species and their compatibility or lack thereof (Nicolazzi et al., 2015). Characterization of environmental parameters in extensive production systems is another key challenge for GWAS but may be assisted by the application of E(environment)WAS methodologies as applied in humans (e.g., Patel et al., 2010). Additionally, understanding the role of the epigenome and its role in environment-dependent phenotypic diversity and plasticity is becoming an increasing focus in livestock genetics (e.g., Jammes and Renard, 2010; Magee et al., 2011, 2014). Ultimately, the integration of genomic, epigenomic, transcriptomic, and environmental data will be required if meaningful large-scale studies are to be successful in identifying selection and conservation targets in heterogeneous environments (Jones et al., 2013; Wu et al., 2014) and in scrutinizing the biological basis for adaptation, resilience, and even animal improvement.

Non-autosomal Inheritance

Non-autosomal inheritance (Y-chromosomal, X-chromosomal, and mitochondrial) is a comparatively neglected area of

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TABLE 1 | Summary of the Top 20 questions in farm animal genomics research identified by the participants of the Cardiff symposium.

Question #

1. Next generation phenotyping The mismatch between molecular and phenotypic data has increased dramatically. Which key phenotypic traits should be used as common measures for diversity studies to define breed characteristics in the face of climate change?

2. Genome-wide SNP assays The identification of common reference genomes and test panels of individuals for SNP array development in less commercial and/or local populations is key. Which strategy shall be used to enable SNP arrays to be developed in a rapid, cost effective and widely applicable manner?

3. Reference genomes Which common reference genomes and test panels of individuals should be used for array development and diversity studies?

4. E(environment)WAS How to characterize environmental parameters in extensive production systems?

5. Epigenetics How can epigenomic information be integrated with phenotypic and genomic data to scrutinize the biological basis for adaptation and plasticity/resilience in livestock populations?

6. Male-mediated genetic diversity Which methodological approach can be applied to promote reliable assembly of the Y-chromosome, still lacking for many livestock species, as well as to develop polymorphic Y-chromosome markers?

7. Ancient DNA and paleoenvironmental analyses

Which strategies should be followed to collect zooarchaeological specimens from critical geographic sites and promote the analysis of ancient genomes?

8. Conservation of genomic diversity How to design a management program that evaluates genomic regions for conservation?

9. Polygenic adaptive and economic traits Haplotypes vs. SNPs: in which situations do one or the other provide a more efficient unit of diversity in QTL regions?

10. Microsatellites (STRs) vs. SNPs How to integrate data from the STRs and SNPs, and how to manage the transition from STR- to SNP-based characterization of FAnGR?

11. GW diversity statistics Which combination of parameters will be required to adequately summarize genome diversity?

12. Data management How can links between major FAnGR databases be promoted to be able to federate resources and act as an educational central point?

13. Data availability Which format should be used to make NGS, phenotyping and GIS data publicly available, and how can industry contribute toward population and maintenance of such database?

14. Participatory projects How can participatory projects, including citizen science, for example, the use of smart-phone technologies be encouraged to enable data collection on FAnGR at a large scale?

15. Prioritization for conservation Why are prioritization methods not being applied by policy makers and managers and is there a lack of dissemination or penetrance?

16. Genomic prioritization How to implement genomic approaches systematically in conservation prioritization to include genes important in functionally valuable traits?

17. Utilization in practice How to reconcile the cost of genomic analysis vs. the economic returns on genotyped stock to allow for a wider use of genomic data to assist conservation, production and management of FAnGR? What is the demand and willingness to pay within the sector?

18. Systematic collection How to ensure that genetic and genomic data are collected sufficiently systematically to be applied to new indicators?

19. Defining goals Which indicators can be applied to most efficiently monitor genetic trends in domestic populations?

20. Strategic approach How will the latest advances in ‘omics technology contribute to achieve the ultimate goal of halting the loss of biodiversity of FAnGR?

Frequencies are not included for each question and the questions are not listed in rank order.

research in livestock conservation. While studies of non- autosomal genetic markers have been extensively used in studies of evolutionary history, both singly and combined (e.g., Götherström et al., 2005; Meadows and Kijas, 2008;

Svensson and Götherström, 2008; Pereira et al., 2009; Ramírez et al., 2009; Ginja et al., 2010; Groeneveld et al., 2010), their exploitation in genomic studies has been somewhat overlooked in comparison to autosomal markers in many livestock species. This oversight is surprising given the well- documented links between mitochondrial sequence variation and fitness in human populations (e.g.,Wallace, 2005) and the increasingly recognized role that Y-chromosomal variation plays in male fertility in livestock (e.g.,Chang et al., 2013; Yue et al., 2014). Technical challenges have long been acknowledged with finding polymorphic markers on the Y-chromosome in mammals and W-chromosome in birds, however such markers, although elusive, have been shown to provide novel insights into livestock

diversity when available (e.g.,Edwards et al., 2011; Wallner et al., 2013), and should be used as a matter of course to provide a male/female perspective on livestock genomic diversity.

Ancient DNA Studies

Although firmly established as a major route into a deeper understanding of livestock evolution and diversity (e.g.,Larson et al., 2010), ancient DNA (aDNA) studies have been hampered by a number of constraints. These include limited access to samples from geographic areas where (local) domestication may have taken place (e.g., Africa, Near East, Asia, South America), limited data sharing among those groups working on samples from critical sites (but see Arbuckle et al., 2014) and limited success rates, especially for genome-wide studies. Nonetheless, recently developed methodological and bioinformatics tools allowed for increased accuracy in the analysis of high-throughput ancient DNA data and even the characterization of complete

Hình ảnh

TABLE 1 | Summary of the Top 20 questions in farm animal genomics research identified by the participants of the Cardiff symposium.
FIGURE 1 | Estimated numbers of domestic animal breeds at risk worldwide (FAO Livestock report, 2005).
TABLE 1 | The historical changes in the value system for animal genetic resources.
FIGURE 2 | Phylogenetic network based on the mitochondrial HVI segment of the control region
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