Equine Genomics E-Book

Bhanu P. Chowdhary

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 736

Veröffentlichungsjahr: 2013

Beschreibung

Equine Genomics Equine genetics has long been studied as a means of improving traits such as performance capabilities and coat color in horses. Dramatic advances in genomics and high-throughput DNA analysis technologies have significantly increased our understanding of the molecular biology of growth, development, and disease. Equine Genomics focuses on the significant advances in genome-mapping and genomic technologies and their application to the improvement of equine traits of economic significance. Equine Genomics provides broad-ranging coverage of advances in genome science as applied to horses. The opening chapters provide strong foundational information on defining the equine genome, the development of genetic linkage, physical and comparative maps, as well as whole genome sequences. The following several chapters then look at the underlying genetics of key traits, such as reproduction, coat color, performance, and a variety of key diseases impacting horses. The final chapter looks at equine mitochondrial DNA and its implication on equid evolution and genetic diversity. A timely and vitally important resource, Equine Genomics, is an essential title for animal scientists, genomic researchers, veterinary scientists, equine breeders, and industry personnel.

Leseprobe

Contents

Cover

Title Page

Copyright

Dedication

Contributors

Preface

Chapter 1: Defining the equine genome: The nuclear genome and the mitochondrial genome

Nuclear Genome of the Horse

Mitochondrial Genome of the Horse

Acknowledgments

References

Chapter 2: Genetic linkage maps

Introduction

Genetic Linkage Maps

Polymorphic Genetic Markers

Reference Pedigrees

Horse Genetic Linkage Maps

The Selection of Microsatellite Mapping Panels for the Dissection of Inherited Conditions in the Horse

The Continuing Usefulness of the Equine Linkage Map

References

Chapter 3: Physical and comparative maps

Introduction

Horse Chromosomes

Gene Mapping in Horses – Historical Background

Cytogenetic Map

Somatic Cell Hybrid (SCH) Panels and Synteny Mapping

Radiation Hybrid (RH) Panels and RH Mapping

Comparative Map

References

Chapter 4: The Y-Chromosome

Introduction

Cytogenetics

Molecular Probes

Genes

Maps

The Pseudoautosomal Region (PAR)

Disorders

Polymorphism and Population Studies

Y chromosome in Other Equids and Perissodactyls

Concluding Remarks

Acknowledgments

References

Chapter 5: Unexpected structural features of the equine major histocompatibility complex

Organization and Gene Content of the Model MHC

Some MHC Genes Are Highly Polymorphic

The Molecular Map of the Equine Leucocyte Antigen Complex

RT-PCR

Chromatin Modifications Associated with Transcription

Summary

References

Chapter 6: Assembly and analysis of the equine genome sequence

Introduction

Sequencing a Genome

Features of the Equine Genome Assembly

Comparison with Genetic Maps

Repetitive Elements

Synteny with Humans

Special Centromeres

Genes

A Single Nucleotide Polymorphism Map

Genomic Attributes of Equine Breeds

Summary

Acknowledgments

References

Chapter 7: Genomic tools and resources: Development and applications of an equine SNP genotyping array

Introduction

Development of an Equine SNP Genotyping Array

Equine SNP50 Beadchip Design and Validation in the Domestic Horse

Utility of the Equine SNP50 Beadchip for Genome-Wide Mapping Strategies

Utility of the Beadchip for Mapping Simple Traits within Breeds

Use of the Equine SNP50 Beadchip for Mapping of Complex Traits in the Horse

Mapping across Breeds

Utility of the Equine SNP50 Beadchip for Population Genetic Analysis in the Horse

Utility of the Equine SNP50 Beadchip in Extant Perissodactyla

Design of a Second-Generation Equine SNP Genotyping Array

References

Chapter 8: Functional genomics

Introduction: From Genotype to Phenotype

Functional Impact of the Genome

The Transcriptome

The Proteome

Networks

Capturing Biological Understanding from Functional Genomics

Conclusion

References

Chapter 9: Coat color genomics

Introduction

Base Colors (Black, Chestnut, Bay, and Seal Brown)

Dilutions (Cream, Pearl, Champagne, Silver, Dun, and Lavender Foal)

White Spotting and Depigmentation Patterns (Frame, Tobiano, Sabino, Dominant White, Leopard Complex, Gray, Roan, and White face and leg markings)

References

Chapter 10: Genomics of skin disorders

Introduction

Skin Diseases with Identified Mutations

Skin Diseases with Suspected Heritable Basis

Skin/Hair Color Phenotypes

Hair Phenotypes

Conclusion

References

Chapter 11: Genomics of muscle disorders

Introduction

Hyperkalemic Periodic Paralysis

Malignant Hyperthermia

Glycogen Branching Enzyme Deficiency

Polysaccharide Storage Myopathy Type 1

Polysaccharide Storage Myopathy Type 2

Recurrent Exertional Rhabdomyolysis

Conclusions and Future Directions

References

Chapter 12: Genomics of skeletal disorders

Osteochondrosis

Navicular Disease

Conclusions

References

Chapter 13: Genomics of reproduction and fertility

Introduction

Cytogenetics of Reproduction

Molecular Genetics of Reproduction

Functional Genomics of Reproduction

Summary and Future Prospects

Acknowledgments

References

Chapter 14: Genetics of equine neurologic disease

Introduction

Neurologic Disorders with Known Mutations

Neurologic Disorders with Ongoing Mapping Efforts

Conclusion

References

Chapter 15: Molecular genetic testing and karyotyping in the horse

Introduction

Genetic Tests for Individual Identification and Parentage Analysis

Genetic Tests for Genetic Diseases

Genetic Tests for Phenotypic Traits

Future Developments in Molecular Genetic Testing

Karyotyping Services Available for the Horse

Molecular Genetic Testing and Equine Cytogenetic Resources

References

Chapter 16: Genomics of laminitis

Introduction

Functional Genomics of Laminitis

Whole Genome Transcriptional Profiling

Contribution of Genomics to the Therapy of Laminitis

References

Chapter 17: Genomics of performance

Introduction

Heritability of Athletic Performance

Athletic Performance Genes Encoded by the Nuclear Genome

Mitochondrial DNA and Athletic Performance in Thoroughbreds

Detection of Genomic Regions under Selection in the Thoroughbred Genome

DNA Sequence Variation and Athletic Performance Traits in the Thoroughbred

Identification of the Myostatin Gene (MSTN) – the “Speed” Gene – as a Major Locus Affecting Race Distance Aptitude

A Genome-Wide Association Study (GWAS) for Optimum Race Distance in the Thoroughbred

Functional Genomics and Proteomics

Global Gene Expression Changes: Microarrays and Other Highly Parallel Gene Expression Approaches

Genetic Testing for Thoroughbred Performance Potential

Acknowledgments

References

Chapter 18: Genomics of the circadian clock

Introduction

Introduction to Circadian Biology

The Mammalian Clockwork Mechanism

Hierarchy of Master and Peripheral Clocks

Equine Peripheral Clocks

Circadian Regulation of Performance

Immune-Circadian Interaction

Circadian Desynchrony

Discussion

Bibliography

Chapter 19: Mitochondrial genome: Clues about the evolution of extant equids and genomic diversity of horse breeds

Introduction

Evolution of the Family Equidae

Przewalski's Horse and Horse Domestication

History of Horse Breeds

Adaptation in Horse Breeds

References

Index

This edition first published 2013 © 2013 by John Wiley & Sons, Inc.

Wiley-Blackwell is an imprint of John Wiley & Sons, formed by the merger of Wiley's global Scientific, Technical and Medical business with Blackwell Publishing.

Editorial Offices2121 State Avenue, Ames, Iowa 50014-8300, USA The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK 9600 Garsington Road, Oxford, OX4 2DQ, UK

For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley-blackwell.

Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by Blackwell Publishing, provided that the base fee is paid directly to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For those organizations that have been granted a photocopy license by CCC, a separate system of payments has been arranged. The fee codes for users of the Transactional Reporting Service are ISBN-13: 978-0-8138-1563-3/2013.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book.

Limit of Liability/Disclaimer of Warranty: While the publisher and author(s) have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. It is sold on the understanding that the publisher is not engaged in rendering professional services and neither the publisher nor the author shall be liable for damages arising herefrom. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

Library of Congress Cataloging-in-Publication Data

Equine genomics / editor, Bhanu P. Chowdhary, Texas A&M University, College Station, Texas, USA. pages cm Includes bibliographical references and index. ISBN 978-0-8138-1563-3 (hardback : alk. paper) 1. Horses–Genetics. 2. Domestic animals–Genome mapping. I. Chowdhary, Bhanu P., editor of compilation. SF291.E64 2013 636.1′0821–dc23 2012038413

A catalogue record for this book is available from the British Library.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Cover design by Modern Alchemy LLC

This is dedicated to all contributing authors for enthusiastically sharing their knowledge and discoveries and my beloved parents, Mohini and Pranveer Singh, for their love, support, and encouragement throughout my learning.

Contributors

Monica AlemanUniversity of California, Davis, California, USADanika L. BannasvchUniversity of California, Davis, California, USAJim K. BelknapCollege of Veterinary Medicine, The Ohio State University, Columbus, Ohio, USARebecca R. BelloneThe University of Tampa, Tampa, Florida, USACandice L. Brinkmeyer-Langford Texas A&M University, College Station, Texas, USASamantha A. BrooksCornell University, Ithaca, New York, USABhanu P. ChowdharyTexas A&M University, College Station, Texas, USAStephen J. ColemanUniversity of Kentucky, Lexington, Kentucky, USAPranab J. DasTexas A&M University, College Station, Texas, USAOttmar DistlUniversity of Veterinary Medicine Hannover, Hanover, GermanyCarrie J. FinnoUniversity of California, Davis, California, USAEmmeline W. HillSchool of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin, IrelandLisa M. KatzSchool of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin, IrelandGabriella LindgrenSwedish University of Agricultural Sciences, Uppsala, SwedenDavid E. MacHughSchool of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin, IrelandJames N. MacLeodUniversity of Kentucky, Lexington, Kentucky, USAKateryna D. MakovaDepartment of Biology, Pennsylvania State University, University Park, Pennsylvania, USAMolly McCueUniversity of Minnesota, St. Paul, Minnesota, USAJim MickelsonUniversity of Minnesota, St. Paul, Minnesota, USAMichael J. MienaltowskiUniversity of Kentucky, Lexington, Kentucky, USABarbara A. MurphySchool of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin, IrelandNandina PariaTexas A&M University, College Station, Texas, USAM. C. T. PenedoCornell University, Ithaca, New York, USATerje RaudseppTexas A&M University, College Station, Texas, USAOliver A. RyderGenetics Division, San Diego Zoo Institute for Conservation Research, Escondido, California, USALoren C. SkowTexas A&M University, College Station, Texas, USACynthia C. SteinerGenetics Division, San Diego Zoo Institute for Conservation Research, Escondido, California, USAJune SwinburneAnimal Health Trust, Newmarket, United KingdomStephanie J. ValbergUniversity of Minnesota, St. Paul, Minnesota, USAClaire M. WadeThe University of Sydney, New South Wales, AustraliaStephen D. WhiteUniversity of California, Davis, California, USAAmy E. YoungUniversity of California, Davis, California, USA

Preface

Equine Genomics largely summarizes a range of accelerated research activities conducted by equine geneticists and researchers during the past two decades. I was privileged to have been closely involved with some of the key activities and was fortunate to have witnessed the progression of several exciting ones. I can classify the two decades into two distinct eras, each of which uniquely contributed to the advancement in equine genetics. The first decade laid the foundation for a much needed knowledgebase of the equine genome, while the second built on its progress and slowly but steadily allowed us to start reaping the benefits. So, who deserves kudos for this progress? In my view, it is due to the extraordinary combined effort of several entities that enables us to read about genetics underlying about 40 equine diseases and more than 20 phenotypes in this book. Twenty years ago, the possibility of this level of achievement was unthinkable. While sitting in a researcher's chair, it would be easy for me to glorify the work of my colleagues worldwide and attribute the success to them. However, in all honesty, the credit goes much beyond this small, yet dedicated, group. The progressive community of horse owners, the scientifically demanding yet generous funding agencies -- federal, state, and private -- the ever approachable and helping clinicians, the increasingly open-minded breed associations, the highly supportive foundations, and the unrelenting horse enthusiasts worldwide have played a vital role in converting the ``unthinkable'' into ``possible''. Despite being a rather small community compared to researchers of other species, it is this extraordinary support, cooperation, and collaboration that allowed us to make this enviable advancement. In essence, the group has made strides, and the horse is better off with a healthier future. This book is a timely tribute to all of them.

As a group we are, and must remain to be, mindful that the real work on such discoveries has just begun. Fruits that next need to be picked will be more difficult to reach (as the lower most are already picked). Innovation, creativity, and teamwork will continue to be the mantras for our progress in the coming decades, as will be support from a more determined, vocal, and generous group of advocates who will ensure that ample funding for equine genetics research is readily available. New priority areas in equine genetics research will become more time consuming and challenging and will hence require additional funding. Moreover, many equine diseases, if not all, will be probed through the ``genetics'' lens. This is a reality, and the sooner the entire equine community embraces this concept, the better off we will be during coming years.

In all honesty, no project is fun unless it poses challenges. As much as challenges energize me, I soon found myself pulled in several directions after having started this project. Three things did not let me fail: the enthusiasm and support of the contributing authors, never exhausting patience of the Wiley crew Justin Jeffryes and Anna Ehler, and lastly Terje Raudsepp, who was always there to help with every ``next step'' along the road. Without them, this book would not have been possible.

I hope a wide spectrum of readers will find Equine Genomics informative and enjoyable. It is the first attempt to compile and present all research developments in this field. Despite its ``scientifically inclined'' tone, all horse enthusiasts will find something that they can relate to, understand, and use. Knowledge in any field is never finite. Having said that, take this book as a sincere attempt from all of us to share with you what we know in the field of Equine Genomics. There will always be more to report as we progress, which we will!

Bhanu P. Chowdhary, BVSc&AH, MVSc. VMD (PhD) Professor and Associate Dean for Research and Graduate Studies

2

Genetic linkage maps

June Swinburne and Gabriella Lindgren

Introduction

From the first meeting of the International Equine Gene Mapping Workshop in Lexington, Kentucky, in October 1995 until the sequencing of the horse genome in 2007 (http://www.broadinstitute.org/mammals/horse; Wade et al., 2009), the primary activity of the equine genetics academic research community was the development of integrated maps of the horse genome. Together with somatic cell hybrid, radiation hybrid, and physical/cytogenetic maps based on fluorescence in situ hybridization (FISH), the generation of genetic linkage maps was critical to achieve this goal. The primary driving force for these endeavors was to map genetic variants that underlie disease, reproduction, growth, and other interesting traits such as coat color. Knowing the genetic basis for these traits would allow for informed breeding decisions to reduce the levels of disease or select for desired characteristics. Furthermore, it would enable investigation of the population structure of horse breeds and their relationship to other equids and also contribute to the greater understanding of the evolution of the mammalian genome. Additionally, linkage maps would provide scaffolding for the assembly of the horse genome sequence. Even subsequent to the release of the horse genome sequence and the development of a single nucleotide polymorphism (SNP) microarray, the utility of the linkage maps continues. This is evidenced by recent publications about the use of genetic linkage analysis to map various congenital disorders and diseases (Mittmann et al., 2010; Swinburne et al., 2009; Zeitz et al., 2009; Lampe et al., 2009; Andersson et al., 2008). The continuing usefulness of the equine linkage map will be described later in this chapter.

Genetic Linkage Maps

Chromosomes are inherited intact from one generation to the next except where rearrangements caused by recombination events – or crossovers – occur during gamete formation. The further apart the two loci are, the more likely it is that a recombination event will take place between them. Linkage maps provide a representation of this genetic separation between loci on chromosomes – in other words, higher frequencies of recombination are represented by greater distances on the linkage map. A genetic map therefore illustrates which markers belong to the same linkage group, their relative order, and the distance between them. The distance along the map is measured in centiMorgans (cM); 1 cM is defined as a 1% probability that the two positions will be separated by recombination in one generation. Since recombination rates vary widely across the genome, genetic distance is not directly related to physical distance; in regions of high recombination, known as recombination hot spots, the genetic distance will widen relative to the physical distance, and vice versa. On average, however, 1 cM is equal to 1 megabase (Mb).

Linkage maps therefore illustrate the likelihood of markers being inherited together, whereas physical maps provide a straightforward representation of distance in base-pairs. These maps are complementary to one another.

There are two essential components for generating linkage maps. Each of these components is described separately in the following sections. First, a large number of polymorphic markers, usually microsatellites, are required. Second, suitable reference pedigrees are necessary. The generation of a linkage map then requires the genotyping of the individuals from the pedigrees with each of the polymorphic markers. Linkage mapping software is then used to identify groups of markers that originate on the same chromosome and therefore exhibit significant linkage – hence linkage groups – by calculating logarithm of the odds (LOD) scores for each pair. LOD scores of over 3 are considered statistical evidence of linkage. A multipoint analysis is then performed on each linkage group to identify the most likely order of markers and the distance between them; these are based on the assumption that the most parsimonious order – that is, the order which necessitates the fewest crossover events – will be the most likely. Finally, each linkage group is assigned to a chromosome; this is traditionally achieved using FISH. In the generation of the linkage maps described below, each of these have utilized the software CRIMAP (Lander & Green, 1987) and MULTIMAP (Matise et al., 1994) to generate the linkage groups and perform the multipoint analysis.

Although the idea behind linkage mapping is quite simple, there are a number of pitfalls to be aware of and to accommodate for. For example, over long chromosomal distances it is possible that there will be two crossovers that could lead to recombinants being scored as non-recombinants. Therefore, recombination frequencies are not additive. Another problem is the phenomenon of interference; in positive interference a crossover has the effect of reducing the probability of a second crossover in its vicinity. Some mapping functions take interference into account whereas others do not. A number of mapping functions have been derived depending on the degree of interference assumed (Kosambi, 1944). Increasing the number of genetic markers will make the map more accurate with respect to these anomalies.

The genotyping of sufficient numbers of markers and sufficient numbers of individuals required to construct a linkage map only became possible with the advent of efficient methods for genotyping in the late 1980s–early 1990s. At this time great efforts were made to generate the first linkage maps of livestock and domesticated species such as pig, cattle, sheep, and dog based on microsatellites (Ellegren et al., 1993; Beever et al., 1994; Crawford et al., 1995; Werner et al., 1999).

Polymorphic Genetic Markers

The first essential components required for the construction of linkage maps are genetic markers that demonstrate polymorphism. Traditionally linkage maps have been constructed using microsatellite markers due to their ease of identification in the absence of genome sequence, and their increased numbers of alleles compared to SNPs. Microsatellites consist of tandem repeats where the repeat units occur immediately adjacent to one another and vary from 1-6 base pairs in length. The different alleles can be distinguished using molecular techniques such as polymerase chain reaction (PCR) followed by electrophoresis, the higher numbers of alleles providing increased power for mapping. In addition, microsatellites are abundant and widely dispersed throughout the genome. Dinucleotide microsatellites have mainly been used in the horse; a likely explanation for this is that several research groups reported that they found it easier to isolate dinucleotide repeats than trinucleotide repeats in this species. The first horse microsatellites were identified by Ellegren et al. (1992). At present there are more than 24,000 microsatellite submissions to GenBank (http://www.ncbi.nlm.nih.gov/genbank/), which are identified using a search for (“Equus caballus”[Organism] OR horse [Organism]) AND microsatellite [All Fields]) (queried August 13, 2010). The majority of these has been submitted subsequent to the release of the genome sequence and illustrate the ease with which microsatellites can now be identified and located in the genome in an automated fashion.

Although highly polymorphic microsatellites are powerful markers for linkage mapping, these are increasingly being replaced by SNPs. The advantages of SNP arrays include fast, efficient, and highly parallel genotyping. Additionally their genotyping and analysis is more easily automated, is cheaper, and has a lower error rate. The lack of informativeness for biallelic SNPs, compared to highly polymorphic microsatellites, is offset by their dense and uniform distribution throughout the genome. Typically tens of thousands of SNPs are genotyped in a genome-wide scan, compared to several hundreds of microsatellites. SNP availability is not a limiting factor, as one SNP is found on average every 1,050 bases in the horse genome (Wade et al., 2009). However, microsatellite scans still provide an inexpensive low-resolution approach that can be performed by most basically equipped laboratories, in contrast to SNP genotyping that requires expensive equipment.

Reference Pedigrees

The construction of genetic linkage maps for animals such as the horse, where suitable reference families are difficult and expensive to generate, is challenging. The late maturity, long gestation period, and singleton pregnancies all conspire against the generation of ideal reference pedigrees; these would consist of numerous full-sibling offspring, three generations, and a high level of heterozygosity. In such situations a number of large half-sibling families have typically been used instead. These are generated by the mating of several sires to numerous dams; such family structures are widespread in production animals where prolific sires are common, and resources are not required to generate pedigrees specifically for linkage mapping. The drawbacks of half-sibling families are that the X chromosome cannot be mapped due to recombination being observed only in the male, large numbers of offspring must be genotyped to achieve sufficient power, and the pedigrees generally represent within-breed matings with a consequent lower-marker heterozygosity. Such pedigrees have been used successfully, however, to develop linkage maps in cattle (Beever et al., 1994; Ma et al., 1996), goat (Vaiman et al., 1996), and sheep (Crawford et al., 1995).

In cows, alternative approaches have also been available; it has been possible to super-ovulate cows followed by the transference of multiple embryos into synchronized recipient cows to generate large full-sibling families (Barendse et al., 1994). In the horse, however, superovulation still proves challenging (review in Scherzer et al., 2008).

Horse Genetic Linkage Maps

During the 1990s, three mapping resources were used in the horse for linkage mapping, and these are now described. The first two used large half-sibling families, and the third utilized reproductive techniques to generate full-sibling pedigrees. In addition, the available maps were merged to form a combined map.

The Uppsala map

The Uppsala map was the first low-density male autosomal linkage map of the horse genome (Lindgren et al., 1998). The reference material consisted of eight paternal half-sibling families of which four families were Icelandic horses and four were Standardbreds. These were two-generation panels with 263 offspring in total. The linkage map was generated by genotyping 140 polymorphic markers, 100 of which were arranged into 25 linkage groups on 18 different autosomes. The genetic markers used included 121 microsatellite markers, 8 protein polymorphisms, 5 restriction fragment length polymorphisms (RFLPs), 3 blood group polymorphisms, 2 PCR-RFLPs, and 1 single strand conformation polymorphism (SSCP). About one-third of the microsatellite markers had been physically mapped to chromosomes by in situ hybridization (e.g., Breen et al., 1997; Godard et al., 1997). These markers allowed twenty-two of the linkage groups to be assigned to chromosomes. The average distance between linked markers was 12.6 cM and the total map distance within linkage groups was 679 cM.

The International Horse Reference Family Panel (IHRFP) map

This linkage map was generated as an international collaborative effort and published in two stages. Phase I (Guérin et al., 1999) described the genotyping of 12 paternal half-sibling families consisting of 448 individuals, which were genotyped with 161 markers. The half-sibling families originated in the United States, Europe, and Australasia and were each comprised of 21 to 52 offspring. They represented hot-blooded, warm-blooded, draft, and pony breeds. Significant linkage was detected for 124 markers, of which 95 were unambiguously ordered with an average spacing of 14.2 cM. The markers were assembled into 29 linkage groups and 28 of these could be assigned to 26 of the 31 autosomes via either FISH or synteny mapping using a cell hybrid panel. The total map length was 936 cM.

In Phase II (Guérin et al., 2003), an additional family was added, and a further 55 individuals, and the number of markers genotyped was increased to 344. Heterozygosity in the stallions varied from 46% (a Thoroughbred family) to 66% (a Shetland pony cross family). Significant linkage was detected for 310 markers, with 257 of these unambiguously ordered with an average spacing of 10.1 cM. The markers were assembled into 34 linkage groups, which were assigned to all 31 of the autosomes. The total map length was 2262 cM.

The Newmarket map

Alternative approaches initiated by Dr. Matthew Binns were employed by Swinburne et al. (2000, 2006) to generate a reference family that would avoid the drawbacks of large half-sibling reference pedigrees. Specifically the planned family structure would avoid the need to genotype large numbers of individuals and would enable the mapping of the horse X chromosome (ECAX). The generation of such a pedigree required the use of reproductive techniques that were available locally at the Equine Fertility Unit in Newmarket, United Kingdom, led by Professor Twink Allen. The procedures utilized were, first, the nonsurgical removal of equine conceptuses (Allen & Bracher 1992), and second, the generation of monozygotic twins via embryo micromanipulation (Allen & Pashen 1984). The resulting family was referred to as the Newmarket horse reference family.

The equine conceptus is unusual in its late implantation, which does not occur until 37 days post-conception. The embryo is easily recoverable via uterine lavage using videoendoscopy until this time, and will yield 3–5 mg DNA on extraction. Using this technique, in conjunction with drugs to induce estrus, up to five full-sibling embryos were obtained from each of the four mares per season. To increase the numbers of full-sibling embryos, the mares employed consisted of two pairs of monozygotic twins. Only one stallion was used on all four mares. The embryos from each pair of twins were therefore genetically full-sibling, and each full-sibling family was half-sibling with respect to the other. Over 5 seasons, 61 embryos were produced and used subsequently for genotyping. Interestingly, five pairs of dizygotic twin embryos were recovered. The structure of this pedigree is illustrated in Figure 2.1.

Figure 2.1 Pedigree structure of the Newmarket horse reference family used to generate the Newmarket map (Swinburne et al., 2006). Two pairs of monozygotic twin mares were covered by a single stallion to generate two families of full-sibling horse embryos. Females are depicted by circles and males are depicted by squares. All twin embryos retrieved were found to be dizygotic in origin. The breeds used in this pedigree were: Arabian, Thoroughbred, Welsh Cob, European Warmblood, and Icelandic Horse.

A third generation was also genotyped, as samples from five of the six grandparents were also available. This allowed the generation of a linkage map for ECAX as recombination in the mares could also be assayed. The founding animals represented a number of breeds, namely Arabian, Thoroughbred, Welsh Cob, European Warmblood, and Icelandic Horse, thereby maximizing the chances of heterozygosity. Only 17.1% of markers tested were homozygous across both halves of this pedigree and were therefore uninformative for mapping. Drawbacks to this family were that no phenotypes were available for the embryos, and so could not be mapped, in contrast to the half-sibling families.

The maps resulting from genotyping on this reference family have been published in two stages. The first stage (Swinburne et al., 2000) described the genotyping of all 61 F2 embryos, together with the parental and grandparental individuals, with 353 microsatellites and 6 SNPs. These were placed into 42 linkage groups of which 37 could be anchored to the physical map. The X chromosome and all autosomes except ECA28 had linkage groups assigned to them. The average spacing between the markers was 10.5 cM, and the total map length was 1780 cM.

The subsequent publication (Swinburne et al., 2006) described the genotyping of 734 microsatellites and 8 SNPs. These were assigned to 32 linkage groups, one for each of the 31 autosomes and one for ECAX. Each of these groups was assigned to a chromosome and oriented by virtue of FISH-mapped markers. The total length of this sex-averaged genetic map was 2,772 cM, with the average distance between markers being 3.7 cM. This map length is very close to the predicted length of 2,720 cM estimated from chiasma counts in horses (Scott & Long 1980). Figure 2.2 presents these 32 linkage maps as seen in Swinburne et al. (2006). In addition, the linkage maps are aligned with the contemporary RH map as described in Chowdhary et al. (2003). Alignments were also made to the human genome by in silico mapping, that is, comparing the unique flanking sequence of each microsatellite with the human genome sequence using BLAST; half of those markers tested identified significant and unique matches to the human genome. In a recent study (Mittmann et al., 2010), in which the order of these markers was compared with the horse genome assembly EquCab2.0 (http://www.broadinstitute.org/mammals/horse), only two discrepancies were found: marker order of TYK601 and COR020 was switched, and COR062 was incorrectly positioned on ECA19.

Figure 2.2 The Newmarket map (Swinburne et al., 2006). Sex-averaged genetic linkage maps of the horse autosomes and female-specific map of the X chromosome are shown as grey bars in the center of each figure. The positions of markers along the chromosome are shown in centiMorgans (cM) to the left. Framework markers are shown in bold italics. Markers that could not be ordered with a threshold of LOD > 1 are shown to the right in vertical text. The adjacent vertical line describes their probable location with their most likely position indicated by a short horizontal line. The contemporary RH map is shown to the far right (Chowdhary et al., 2003). Grey bars to the far left indicate proposed segments of conserved synteny between the horse linkage map and the human genome sequence. The identity of the human chromosome is shown adjacent to the bars. The position of match with the human chromosome is shown in megabases. The maps were orientated by reference to FISH mapped markers and genes (Chowdhary et al., 2003).

The International Equine Gene Mapping Workshop (IEGMW) linkage map; the merging of contemporary linkage maps

In an attempt to produce a comprehensive linkage map that would bring together linkage mapping data available at that time, the IEGMW produced a merged map (Penedo et al., 2005). A further 359 microsatellites were genotyped on the IHRFP (Guérin et al., 2003), and this was merged with the Uppsala map (Lindgren et al., 1998) and the Phase I Newmarket map (Swinburne et al., 2000), together with data from a further two half-sibling families. Since the majority of this data originated from half-sibling families, only recombination occurring in the sires was included in the analyses. In total, 766 markers were assigned to linkage groups, with only 59 markers not displaying significant linkage to another marker. The map spans a total of 3,740 cM, with an average of 6.3 cM between markers; it may be that genotyping error – which was estimated at 0.6% – has artificially inflated the map length.

The Selection of Microsatellite Mapping Panels for the Dissection of Inherited Conditions in the Horse

Once substantial linkage maps became available, efforts turned to the selection of well-spaced panels of markers for gene mapping purposes. An important contribution to this choice was the development of horse/human comparative maps to identify the likely positions of genes. Various aspects of comparative mapping are discussed in other chapters, but an important component was the use of in silico mapping to locate horse microsatellites with respect to the human genome (Farber & Medrano 2004; Swinburne et al., 2006; Tozaki et al., 2007). Specifically this involved the sequence comparison of unique microsatellite-flanking sequence to the human genome sequence using BLAST-like alignment tool (BLAT). Some of the comparative mapping performed during this period is illustrated in Figure 2.2.

Microsatellite genome scan panels include multiplex sets of microsatellite markers that are evenly spread over the genome. Sets of markers that amplify robustly under similar PCR conditions are put together for multiplex PCR. Sets of markers that do not PCR-amplify well together are sometimes combined post-PCR before fragment separation. Microsatellite markers in the same set that have a similar fragment size are labeled with different fluorescent dyes. Panels of markers have been developed by a number of research groups; for example, a panel of 316 markers was developed by the Veterinary Genetics Laboratory, University of California, Davis (http://www.vgl.ucdavis.edu/genomic/GenomeScanPanel.pdf). More recently, with the advantage of reference to the genome sequence, Mittmann et al. (2010) identified a highly polymorphic microsatellite scan panel of 322 evenly spaced markers that covers all autosomes and ECAX.

The Continuing Usefulness of the Equine Linkage Map

Despite the recent sequencing of the horse genome and subsequent development of a SNP microarray, the utility of microsatellite panels as a first step in identifying the approximate location of a genetic variant of interest is still apparent. Further, information from the equine linkage map was used to assemble the genome sequence of this species.

For monogenic trait mapping

Genetic linkage maps can be used to identify genes or chromosome regions that regulate various phenotypic traits. Both monogenic traits, controlled by a single gene, and polygenic traits, controlled by an unknown number of genes and often environmental factors, can be studied. As described in previous sections, linkage mapping entails following the segregation of alleles in families to establish whether or not the alleles at one locus co-segregate with alleles at other loci. To be able to do this, it is necessary to determine the parental origin of each allele in the progeny. A trait can be mapped using linkage analysis by genotyping a pedigree in which this trait is segregating using a genome-wide marker panel. Markers that are inherited together (i.e., co-segregating) with the trait are genetically linked to a gene that influences that trait, and thereby indicate its approximate chromosome location. This method, known as linkage mapping, has relatively low resolution and generally results in the identification of large regions (megabases) that require further investigation by fine mapping.

The ultimate aim is to identify the gene responsible for the trait and ideally the causative mutation. To this end the critical region can be reduced in size by haplotype mapping, where more individuals of the same breed – or if possible, other breeds – are genotyped for markers in the region. Ultimately the re-sequencing of affected and control animals would be performed to search the reduced critical interval for candidate mutations. Further confirmatory studies could involve the evaluation of candidate mutations by investigating their biological function within cells.