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INVITED REVIEWS |
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* Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg 24061; Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing 48824; Department of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23, Sweden; and Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, BMC, SE-75 124, Uppsala, Sweden
1 Corresponding author: pbsiegel{at}vt.edu
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ABSTRACT |
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 TOP ABSTRACT HISTORICAL PERSPECTIVESMOLECULAR GENETICS TO GENOME...THE CHICKEN: A MODEL...REFERENCES |
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Key Words: domestication • animal model • genome sequence • genome mapping • quantitative trait loci
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HISTORICAL PERSPECTIVES |
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TOPABSTRACTHISTORICAL PERSPECTIVESMOLECULAR GENETICS TO GENOME...THE CHICKEN: A MODEL...REFERENCES |
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Punnett (1923) dedicated his book, Heredity in Poultry, "To William Bateson whose experiments with poultry offered the first demonstration of Mendelian heredity in the animal kingdom" (dedication page). Bateson, a long-time colleague of Punnett, had almost 2 decades earlier, in reports to the Evolution Committee of the Royal Society, demonstrated complementary gene action (comb type) using the chicken as a model (Bateson and Punnett, 1905–1908). In his classic paper, Jull (1927) begins with, "It is a far cry from the time that man first heard the crow of the wild cock of the bamboo jungles of India to the cackle of the highly domestic hen upon celebrating her production of 1,000 or more eggs" (page 379). Jull’s paper, plus those of Hashime Murayama and Harry Lewis in that April issue of National Geographic, are relevant to our current concerns with possible loss of biological diversity. We would also be remiss in not citing the insights of Smith and Daniel (1975) in their lucid history on the role and use of chickens from ancient times.
There is a dynamic between chicken breeding and chicken genetics, with the latter providing the biological foundation for the former. Although genetics is a 20th-century science, as Smith and Daniel (1975) point out, there is a long history of breeding chickens for religious and ceremonial reasons, expression of mutants, sport, and food. Whether the goal was to increase the length of tail feathers, crow, or shank, selection of a parent for the next generation was based on its phenotype for the trait in question. Although meiosis and mitosis were not understood or even described, selection at the phenotypic level was frequently enhanced by information on relationships among individuals (e.g., sibs, parent-offspring). Thus, although modes of inheritance and Darwinian thoughts on domestication were not to be understood for decades or even centuries later, genetics was being applied without knowledge of the specific mechanisms. Decades after the rediscovery of Mendelism, debates persisted among geneticists on continuous and discontinuous variation (Falconer, 1992). Even today, chicken breeding is far from an exact science, with chance part of the paradigm.
Depending on the quantitative-qualitative mode of inheritance as well as thresholds, the degree of phenotypic expression of traits varies. Moreover, it is essential to distinguish between the properties of the individual and of the population. Among the most important of such distinctions is that, barring mutation, the genotype of a chicken is fixed at no more than 2 alleles per locus, whereas populations allow for much greater diversity. The emergence of molecular techniques discussed subsequently in this paper will enlighten our understanding of the genotype-phenotype connection. Since the early years following the rediscovery of Mendelism, quantitative procedures and research with mutants have been used to further our understanding of modes of inheritance. Today, with information at the molecular level, opportunities for the study of genetic mechanisms as such and how they may be influenced by the background genome are greatly enhanced, as addressed in subsequent sections of this paper.
During the 20th century, quantum changes occurred in the breeding of chickens, much of which can be attributed to an understanding and application of the genetics of chickens. These concepts and their application at various points in time have been addressed in several books (Lamon and Slocum, 1927; Hutt, 1949; Lerner, 1958; Crawford, 1990; Stevens, 1991; Muir and Aggrey, 2003). The emergence of the evaluation and application of quantitative and molecular genetic theory has, in the last 50+ yr, been dramatic. The computer, PCR, automated sequencing, the Internet, and jet aircraft are among the technological breakthroughs that removed some of the drudgery from breeding and enhanced global cooperation among scientists.
Historically, advances in the genetics of the chicken have followed what may be called repeated incremental progression. Namely, there is cumulative change generation after generation. Genetic and nongenetic factors may result in changes; however, it is the genetic aspects that facilitate the sustainability of the changes. The tools used by the geneticist are part of the process—not the process.
To digress at this point may be instructive, as we remind ourselves that the chicken is a biological organism that has genetic attributes resulting from natural selection that initially favored its domestication. Included among these is a social structure that allowed large social groups of males with females; promiscuity; precocial young, in which the hen accepted its hatchlings quickly; general dietary habits; limited agility; and adaptation to a range of environments (Hale, 1969). The degree of expression of these characteristics varies depending on whether the fowl are observed in the feral state or in captivity (McBride et al., 1969). Domestication is a continuing process that involves human intervention through artificial selection (i.e., breeding programs). If we view human intervention in a broad context, then inventions such as the trap nest, the incubator, and electricity allowed for developing breeding programs based on an understanding of the inheritance that precluded the relevance of incubation behavior and parent-offspring relationships. This history of genetic and phenotypic plasticity has enhanced the popularity of the chicken as a source of food and a model organism in the research community. Adaptability to a wide range of environments facilitated the emergence of the chicken as the leading domesticated avian species. Beebe (1926) writes of the Jungle Fowl, "To the human race, this is the most important wild bird living on earth, for it represents the ancestor of all varieties of the domestic fowl. It ranges from the border of Kashmir to Singapore, and is found in the wildest regions, as well as close to native villages..." (page XXXi). The chicken thrives as a scavenger in rural environments, where its eggs are a valuable source of food. It adapts quickly to a range of intensive husbandries (both farm and laboratory), in which it is fed specific diets. The global spread of the chicken via the domestication process has been reviewed in numerous publications (West and Zhou, 1989; Crawford, 1990; Stevens, 1991).
The Recent Past
The past several decades have seen a dramatic transition in poultry genetics, both in the commercial arena of breeding and in research focus. Industrial production has facilitated replacement of the dual-purpose chicken by stocks bred specifically for meat or for eggs. These breeding programs are in the hands of a few multinational organizations with considerable capital, highly trained staffs, large populations, and programs based on a foundation from a strong, publicly supported research base in chicken genetics and genetics. Erosion of this base will have serious consequences, not only in the context of new scientific discovery, but in the training of the next generation of chicken geneticists.
The development of 2 specific entities, the chicken for meat production and the chicken for egg production, has resulted from acceptance of quantitative concepts involving additive and nonadditive genetic variation and negative genetic and phenotypic relationships between growth and reproduction. Realization of this incompatibility and that the purebred was not sacred were seminal, because it meant that a chicken meat industry could develop that was no longer a by-product of the egg industry. Furthermore, progress in understanding the genetics of the chicken facilitated breeding programs that could utilize nonadditive genetic variation via mating schemes that capitalize on nonadditive gene action. Although today’s commercial chicken may appear to be different from its Jungle Fowl ancestor, in an evolutionary context, wild and domestic chickens are still closely related, and they cross freely.
Earlier, we wrote of the long, publicly supported research foundation that enhanced the sophistication of chicken genetics and breeding. One example is the chicken gene mapping reviewed later in this paper, as well as development of experimental lines and mutant stocks (http://animalscience.ucdavis.edu/AvianResources/). At present, chicken breeders estimate genotypes for quantitative traits from information on phenotypes. Although we can now map and assay the genotype with great precision, the path to the phenotype can be distant and complex, with interacting networks of pleiotropic genes facilitating dynamic genotypic and phenotypic plasticity. The map, which remains a work in progress, means an exciting future for studies that combine quantitative and molecular techniques.
There are concerns that intense selection for egg production or meat production may exhaust genetic variation for these traits. This concern for plateaus is not new, and proactive papers on genetic reasons for such plateaus for egg production are in the literature (Dickerson, 1955; Clayton, 1972). Although these early concerns of plateaus in egg production became moot with procedures for identifying leucosis shedders from breeding populations (Spencer et al., 1979), physiological and genetic limits should not be lightly regarded. Today, human intervention is necessary to control feed intake of meat stocks. Skeletal and metabolic issues exist for meat and egg stocks. Yet, genetic variation exists for the primary economic traits. Why? Small molecular changes in genes may introduce variability in populations (Hill, 2005) as well as selection-induced genetic variation (Eitan and Soller, 2004; Carlborg et al., 2006). In the case of the latter, the hypothesis is that as selection proceeds to change the genetic background, new sets of genes come into play as sources of variation.
Chicken genetics has a long history of accomplishment, both in contributing new knowledge as well as in meeting the global demand for food. The challenge now is to achieve an orderly incorporation and implementation of the chicken genome into a paradigm that complements both science and application. The context and potential of this challenge are presented in subsequent sections of this paper.
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MOLECULAR GENETICS TO GENOME SEQUENCE |
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TOPABSTRACTHISTORICAL PERSPECTIVESMOLECULAR GENETICS TO GENOME...THE CHICKEN: A MODEL...REFERENCES |
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phage vectors (Maniatis et al., 1978), it became possible to isolate single-copy chicken genes, using as probes either purified chicken cDNA or homologous sequences previously cloned from other species (Dodgson et al., 1979; Perler et al., 1980). Hundreds of individual chicken genes were isolated this way, among them proto-oncogenes, hormonally regulated genes, and tissue-specific genes. Most often, chicken genes were isolated to provide evolutionary comparisons to mammalian genes or gene families (Perler et al., 1980). The effect on poultry science was modest, because it was unclear how these discoveries, interesting though they may be, could be applied to breeding and management.
The Linkage-Map Era
Although classical chicken genetics dates back to the early 1900s, linkage mapping was handicapped by the limited number of easily observable, single-gene phenotypes and the generations of breeding necessary to develop appropriate populations segregating for multiple traits. The seminal paper of Botstein et al. (1980) demonstrated that random changes in DNA sequence could be used as a phenotype, thereby opening the way to exploit the full genetic diversity of any mating pair for mapping. Efforts were begun in the late 1980s at Compton (CT; Bumstead and Palyga, 1992) and East Lansing (EL; Crittenden et al., 1993) to generate DNA marker-based maps of the chicken genome. The CT population parents were from 2 White Leghorn (WL) lines. The EL population was modeled on the interspecific backcross approach developed earlier for mouse mapping (Copeland and Jenkins, 1991). After comparing several options, a single male from the inbred UCD001 Red Jungle Fowl line was mated to a single female from the highly inbred UCD003 WL line. This wide cross was designed to enhance the efficiency of identifying DNA polymorphisms between the parental genomes. Although this proved true, it’s now obvious that even 2 WL chickens exhibit more than enough DNA polymorphisms for a good map (International Chicken Polymorphism Map Consortium, 2004). A key factor in the advance of chicken genomics (with comparatively limited resources) has been the worldwide sharing of both data and resources. This sharing was particularly important at this early stage. The CT and EL populations were jointly assigned as international "reference mapping" populations, and DNA panels from both were available to anyone. As a result, map development was inherently cooperative, in that each marker placed by any laboratory added to the quality and value of everyone’s data. Later, a third chicken mapping population was generated in an effort led by Groenen et al. (2000). Although the Wageningen population DNA is not publicly available, the number of informative meioses examined was much higher in this family, so it proved crucial for the accurate placement of framework markers (Groenen et al., 2000).
Initially, the predominant DNA marker used in the chicken was the RFLP. However, RFLP were relatively tedious to develop and, especially, to genotype, leading to relatively low coverage and excessive numbers of linkage groups in the early maps. "Fingerprint" markers are quick, inexpensive, and do not require DNA sequence information for their development (but have several disadvantages, as well; Dodgson et al., 1997), so these were used to enhance map coverage and merge smaller linkage groups (Levin et al., 1994a,b; Herbergs et al., 1999; Knorr et al., 1999). As large-scale sequencing and machine-based genotyping became within reach of at least some poultry genetics laboratories, there was a growing move toward microsatellite markers (Haberfeld et al., 1991; Crooijmans et al., 1993; Khatib et al., 1993; Moran, 1993; Cheng and Crittenden, 1994). Microsatellites make up an especially polymorphic, PCR-based marker set, easily transferred to resource populations segregating for QTL of interest. Although microsatellites are still in wide use, today virtually all segregating DNA polymorphisms can be used as markers, and single nucleotide polymorphisms (SNP) have become increasingly popular. Single nucleotide polymorphisms, especially those within chicken protein-coding regions (coding SNP), have been genotyped for over a decade (Bumstead et al., 1994; Smith et al., 1997). Their locations within specific genes allow for alignment of chicken linkage maps with genes mapped in other species ("comparative mapping"). Extensive sequence data and modern SNP-typing techniques make them the current marker of choice. The linkage-mapping phase culminated in a "consensus" chicken linkage map (Groenen et al., 2000) based on all 3 reference populations. Thereafter, this map grew slowly, while efforts shifted toward QTL analysis, physical mapping, or both until recent massively parallel SNP-typing projects greatly expanded the map and integrated it intimately with the chicken genome sequence.
The maps of mammalian livestock species have been greatly augmented by radiation hybrid (RH) mapping in which the requisite chromosome breaks are induced by radiation rather than meiosis. For technical reasons, use-able RH mapping panels for the chicken were difficult to generate. A useful chicken RH panel was finally developed by Morisson et al. (2002), and it is now providing critical data for refining the genome sequence assembly.
Physical Mapping
Even when a chicken genome sequence seemed, at best, a distant prospect, it was clear that a recombinant DNA clone-based physical map was both feasible and desirable. Physical maps align markers according to the length of DNA between them and provide landmarks for the assignment and orientation of linkage groups to specific chromosomes. Eventually, local integration of physical and genetic maps are required for map-based cloning and identification of QTL alleles. Furthermore, a comparative physical map, aligned by homologous gene sequences between the chicken and human genomes, would aid in applying the results of human biology to the study of the chicken and vice-versa.
The key elements in recombinant DNA-based physical maps are large insert clone libraries. By the late 1990s, bacterial artificial chromosomes (BAC) had become the vectors of choice, due to being more resistant to DNA rearrangements during the cloning process and because BAC DNA can be purified more readily and in high throughput fashion. Zoorob, Auffray, and colleagues constructed an early chicken BAC library (Morisson et al., 1998) that, however, wasn’t widely distributed. Crooijmans et al. (2000) and Lee et al. (2003) constructed BAC libraries that were heavily utilized for both physical mapping and sequence assembly. After the chicken genome sequencing project began, Pieter de Jong and colleagues (Children’s Hospital of Oakland Research Institute, CA) were recruited to generate an additional BAC library (CHORI-261) with larger DNA inserts (Wallis et al., 2004).
Most common physical maps are based on BAC contigs, in which sets of overlapping BAC inserts are aligned to cover long (millions of base pairs) regions of the genome. Each overlapping (contiguous) insert set is termed a BAC contig. Ideally, each chromosome (or, at least, each chromosome arm, as centromeres are often difficult to map or sequence) would be covered by a single BAC contig. However, generally this is not feasible, except for small or very intensively studied genomes. Bacterial artificial chromosome overlaps primarily are determined by computer analysis of fingerprints obtained by digesting individual BAC with 1 or more restriction enzymes and separating the many fragments by size. Various combinations of restriction enzymes, fragment-labeling methods, and fragment-separation techniques have been used. Any 2 overlapping BAC will share some, but not all, of the same fragments in a fingerprint. If enough BAC fingerprints (>5 to 6x coverage of the haploid genome) are obtained, computer analysis can be used to align BAC contigs that cover almost all of the genome. High throughput hybridization techniques (Ross et al., 1999) are also used to merge contigs that cannot be united by fingerprint data alone and to align BAC contigs with linkage maps, RH maps, and genome sequence data, as well as to build comparative maps. Initial BAC contig mapping for the chicken was carried out mostly in the Groenen laboratory in Wageningen (Aerts et al., 2003) and by a USDA Cooperative State Research, Education, and Extension Service-supported project at Texas A&M (College Station) and Michigan State (Ren et al., 2003).
Sequencing the Chicken Genome
By the end of the 20th century, it was becoming clear that the draft human genome sequence would soon be complete (International Human Genome Sequencing Consortium, 2001) and that this would be followed by a "finished" human genome and a high-quality mouse genome sequence in surprisingly short order. The National Human Genome Research Institute (NHGRI; Bethesda, MD), by then heavily invested in DNA sequencers (both machines and humans), began looking for other genomes to analyze. About this time, 1 of the authors (J. B. Dodgson) was asked by the NHGRI and then by the Washington University Genome Sequencing Center (WUGSC; St. Louis, MO) to provide existing chicken BAC libraries (Lee et al., 2003) to help "feed" the WUGSC fingerprinting pipeline. Thus, BAC fingerprints were obtained both at Texas A & M with USDA-Cooperative State Research, Education, and Extension Service support (Ren et al., 2003) and at the WUGSC (Wallis et al., 2004). Soon there was also a need to keep the DNA sequence pipelines running at capacity. On July 9 to 10, 2001, the NHGRI held a workshop entitled "Developing Guidelines for Choosing New Genomic Sequencing Targets" (Pennisi, 2001), at which Richard Frahm, of the USDA National Animal Genome Research Program, spoke in favor of including at least 1 domestic food animal among the targets. Shortly thereafter, interest in the chicken genome was expressed at the 10th International Strategy Meeting on Human Genome Sequencing (Hangzhou, China). Bin Liu of the Beijing Genomics Institute (BGI; China) and Nat Bumstead for the UK Biotechnology and Biological Sciences Research Council (Swindon) took the lead in negotiating support for a chicken genome project. This was discussed further at the first Meeting of the Chicken Genome Consortium in Manchester, UK, that December and at the Plant, Animal and Microbial Genome X meeting in January 2002. The NHGRI administrators independently issued a request for "white papers" proposing to sequence new genomes that would be of general interest to National Institutes of Health-supported scientists with a Febuary 10, 2002, deadline. A proposal to generate a draft (6x coverage) sequence of the chicken genome was submitted by McPherson et al. (2002) and was subsequently conferred "high priority" by the NHGRI. The strong support of the WUGSC, the efforts already in progress to generate a BAC contig map for the chicken, and the support of numerous scientists who were using the chicken as a model organism for health-related research were critical toward making chicken the first domestic animal genome to be sequenced. When the NHGRI and WUGSC jointly decided to sequence the chicken genome on their own, BGI chose to do "sample" (one-fourth genome) sequencing of a broiler, layer (White Leghorn), and Silkie genome to provide a dense SNP map (International Chicken Polymorphism Map Consortium, 2004).
The "chicken" genome that was sequenced was actually that of a single female bird of the UCD001 inbred Red Jungle Fowl line, initially developed by Abplanalp (1992). As noted above, the UCD001 Red Jungle Fowl and UCD003 WL lines were chosen for the EL reference mapping backcross (Crittenden et al., 1993). When the BAC libraries of Lee et al. (2003) were constructed, UCD001 DNA from a single female was used, because, at that time, many of the consensus linkage-map markers were dominant amplified fragment-length polymorphism, random amplification of polymorphic DNA, and complement receptor 1 markers, for which the mapped polymorphism was only known in the UCD001 parental genome. When it came time for the WUGSC to construct sequencing libraries, they requested DNA from the same bird that was used to make these BAC libraries. Subsequently, DNA from this individual was also used to make the CHORI-261, larger insert BAC library. Both fingerprinting and sequencing benefit from using DNA from a single inbred individual, because heterozygous polymorphisms that could be confused with sequencing errors or finger-print differences are minimized. In retrospect, a UCD003 inbred WL hen would have been at least as satisfactory. However, the Jungle Fowl bird used can be viewed as a "wild type" chicken and has served as a good base to which comparisons have been made to broiler, layer, and exotic chicken genomes (International Chicken Polymorphism Map Consortium, 2004). Choice of a female genome provided coverage of both the chicken Z and W chromosomes, but at the cost of covering each of these only half as well as the autosomes. Again, in retrospect, a good argument could be made for using a male genome to get full coverage of the more gene-rich Z. As it is, additional targeted efforts will be required for a high-quality assembly of both the Z and the W sequences.
The actual data-collection phase of chicken genome sequencing proceeded with remarkable speed. The WUGSC finished fingerprinting BAC by the end of 2002 and moved on to construct the sequencing (small insert) libraries. Bulk sequencing was done mostly from April to August of 2003, with some additional data collected through the end of that year. The initial sequence assembly was posted online on March 1, 2004. The detailed analysis of the sequence and manuscript preparation began in February of 2004, with the manuscript being submitted to Nature on July 19, 2004, and, after a substantial revision (mostly shortening), it was published on December 9, 2004 (International Chicken Genome Sequencing Consortium, 2004). The same issue included the results of the BGI SNP sample sequencing (International Chicken Polymorphism Map Consortium, 2004) and a second generation BAC contig map of the genome (Wallis et al., 2004). It should be emphasized that this was a "draft" sequence that included numerous gaps and rare, but significant, assembly errors. A second, improved "build" of the genome is to appear in April 2006 that incorporates some additional sequence data and new SNP and RH map data. A proposal for "genome refinement" for the chicken was submitted (Warren et al., 2005), and this effort should be underway, if not completed, by the publication of this review. Even then gaps will remain, especially in highly repetitive, uncloneable, or both regions of the genome.
The initial conclusions based on the chicken sequence are described in detail in the Nature publication (International Chicken Genome Sequencing Consortium, 2004) and a series of companion papers in Genome Research (Abril et al., 2005; Axelsson et al., 2005; Bourque et al., 2005; Hubbard et al., 2005; Kellner et al., 2005; Ovcharenko et al., 2005a,b; Paulsen et al., 2005; Wicker et al., 2005; Yokomine et al., 2005), with implications of the sequence for the poultry industry discussed later. Suffice it to say that having a genome sequence makes the chicken a "member of the club" of species in which molecular genetic research can be conducted using the full power of modern genomics technology. As argued elsewhere (Dodgson, 2003), it also offers the prospect of "connecting poultry science, not just to all of animal science, but to all of biology" (page 295) and the hope of bringing scientists primarily interested in the chicken as a food animal into closer contact and collaboration with those who study it as a model organism. Dramatic glimpses have already been provided into the remarkable genetic diversity that remains even in populations of chickens (commercial and experimental) that have been subjected to many generations of intensive selection. This diversity would have been very difficult to predict in advance. The possibilities now exist for new and deeper insights into the molecular nature of the QTL, which is just beginning to emerge from its previous "black box" status. Certainly, the sequence should make one optimistic for both continued progress in breeding more productive chickens and in doing better poultry science in the coming decades.
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THE CHICKEN: A MODEL FOR UNDERSTANDING BIOLOGY |
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TOPABSTRACTHISTORICAL PERSPECTIVESMOLECULAR GENETICS TO GENOME...THE CHICKEN: A MODEL...REFERENCES |
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Major advances in biology during the last 150 yr include Darwin’s theory of evolution by natural selection, Mendel’s theory on inheritance, the theory on quantitative genetics pioneered by Fisher, Haldane and Wright, the development of molecular genetics, and, more recently, genomics. Chickens have played an important role in several of these major advances. For instance, Bateson (1902) used chickens to first demonstrate Mendelian inheritance of traits in animals. Selection programs and cross-breeding experiments in chickens have played an important role for testing and further developing theories in quantitative genetics. Furthermore, some of the pioneering experiments in developmental biology (Cohen and Levi-Montalcini, 1956; Brown et al., 2003), virology (Rous, 1911; Vogt, 1997), immunology (Cooper et al., 1966), and oncology (Stéhelin et al., 1976) were done using the chicken, just to name a few of those subsequently recognized with Nobel Prizes. The next important step in biology is to use the genome sequences to improve our understanding of all aspects of biology, from development to the genetic basis of evolutionary adaptation. We now have near complete gene lists in many species, and we are starting to accumulate data on the expression patterns of all genes and the transcript diversity they generate. However, for most genes, our understanding of their function is still absent or fragmentary. Furthermore, although the causes of many inherited disorders that exhibit simple inheritance have been resolved, our understanding of the genetic basis for multifactorial traits and disorders is very incomplete. Similarly, the genetic basis for the normal phenotypic diversity that exists in outbred populations is poorly understood. We, thus, would like to improve our understanding of genotype-phenotype relationships; which genes contribute to a certain phenotype and how the genes act and interact. The chicken again could play an important role in this next step in biology.
The chicken has several merits as a model for understanding biology:
The classical approach to understanding gene function is to utilize mutants with altered phenotypes. Today, large efforts are being made to expand the collection of mutations in experimental organisms. This can be accomplished by targeted approaches such as knock-out experiments or by random approaches such as large-scale N-ethyl-N-nitrosourea (ENU)-induced mutagenesis. In this context, it is an anomaly why there is not greater interest in exploiting the genetic diversity that already exists in the chicken. On the contrary, it has been difficult to maintain stocks of chickens that have been established as a result of decades of research (Delany, 2006). The following examples of genetic diversity in chickens can serve as useful resources to understand biology.
Classical Monogenic Traits.
Many such traits have been described, and, in some cases, the underlying gene has already been determined. For instance, it is known that sex-linked dwarfism is caused by mutations in the growth-hormone receptor gene (Burnside et al., 1991) and that dominant white color is caused by a mutation in PMEL17, encoding a protein with a crucial function in the eumelanosome (Kerje et al., 2004). However, many classical monogenic traits remain to be studied. For instance, there are several interesting mutations that affect the shape of the comb (Hutt, 1949). These must be due to alterations in the developmental program forming the shape and size of the comb. Another example is bone color in chickens, which is determined by 2 major loci (Smyth, 1996). The sex-linked Id locus determines the presence or absence of dermal melanin in the skin, probably by controlling the migration of melanocytes. The autosomal W locus determines whether yellow carotenoids are deposited in the skin. Different genotypic combinations at these loci determine whether the chicken has dark, white, yellow, or greenish legs. It will be of interest to find out which genes are controlling this phenotype and whether the same loci are important for explaining the rich diversity in leg color among other bird species or in skin color among humans.
Interesting Resource Populations.
There exist many chicken lines that can be used for genetic studies of genotype-phenotype relationships. First, there are many lines that have been selected for production purposes. In the Western world these can be divided into broilers and layers. Unfortunately, many of these lines are maintained by private companies, and they may not be available for research. Second, there is a rich diversity of local breeds across the world with chickens adapted to different environmental conditions and production systems. Finally, there are many lines that have been established for research purposes. Examples of such lines include the obese strain that develops autoimmune thyroiditis, the UCD-200 line that develops autoimmune scleroderma, and the Smyth line that exhibits autoimmune vitiligo (Wick et al., 2006). Each of these lines appears to provide an outstanding animal model mimicking the corresponding disease in humans. Quantitative trait loci experiments with the aim to identify the genes underlying these disorders are underway (in the laboratory of L. Andersson, unpublished data). Another excellent example is the high-growth and low-growth selection lines that have been developed by one of us (in the laboratory of P. B. Siegel) by divergent selection solely on BW at 8 wk of age for almost 50 generations (Dunnington and Siegel, 1996). These lines show a staggering 9-fold difference in BW at selection age, and several correlated responses have been documented. The 2 lines differ in appetite, fat deposition, behavior, and immune response traits. An extensive QTL mapping project is beginning to unravel the genetic basis for the remarkable selection response in the 2 lines. Standard single-QTL analyses reveals about 15 QTL affecting BW and body composition but no QTL for antibody response or the incidence of anorexia, despite striking differences for the 2 latter traits between the parental lines (Jacobsson et al., 2005; Park et al., 2006). The results suggest that each individual locus affecting growth explains only a small portion of the residual phenotypic variance. However, a more in-depth analysis reveals that epistatic interactions among QTL have played a major role in this selection experiment (Carlborg et al., 2006). This implies that genetic variance is released during selection; that is, the phenotypic effects of individual loci are altered as the gene frequencies of interacting QTL change. This finding provides a possible explanation for the enigmatic observation that continuous, long-term selection responses can be obtained without the exhaustion of genetic variance. This research is another example in which a chicken model has improved our understanding of an important biological question. Further analyses of these selection lines have the potential to give valuable insight into the genetic control of appetite and growth.
New Spontaneous Mutations.
As argued above, the huge population size of the chicken is a potential resource that can be used to pick up interesting new mutations for genetic studies. An example of this is the obese strain of chicken that develops autoimmune thyroiditis. This phenotype was first observed by Cole (1966) in a few birds in a large flock of White Leghorns. He then rather quickly established a line with a high incidence of disease. Another interesting case is the smoky plumage color mutation (Kerje et al., 2004). This mutation arose spontaneously in a line of White Leghorns that express dominant white. Smoky partially restores color, and it can be considered to be a suppressor mutation that partially blocks the action of the dominant white mutation. Kerje et al. (2004) were able to show that Smoky is caused by a second mutation in the same gene (PMEL17) as that causing dominant white. These mutations will be very useful for explaining the enigmatic function of this protein (Theos et al., 2005).
Strategies for Exploring Genotype-Phenotype Relationships
The classical approach to map genes controlling phenotypic traits is to carry out cross-breeding experiments between lines that are fixed or close to fixation for alleles controlling the traits. This may involve lines that differ for a single trait of interest showing a monogenic or polygenic inheritance. One may also cross 2 lines that differ for many phenotypic traits that can be investigated in the same population. An example of the latter is a cross between a broiler and a layer line. The critical question is to find an optimal design that allows the identification of the genes underlying the phenotypic trait. These designs are described and discussed in detail in a companion paper in this series (Soller et al., 2006) but will be mentioned briefly here. For a simple monogenic trait, it may be sufficient to use a small pedigree comprising 30 to 50 backcross or intercross progeny. This should be sufficient for low-resolution mapping that may allow the identification of a candidate gene that can be resequenced for the identification of mutations. Putative causative mutations subsequently may be verified by demonstrating a complete concordance between genotype and phenotype across breeds (Kerje et al., 2004) or by functional experiments. However, if no obvious candidate gene is identified, it may be wise to expand the size of the pedigree considerably to allow a refined localization and reduce the size of the interval under consideration. This is particularly important when the underlying mutation occurs in noncoding DNA.
When dealing with polygenic traits it is essential to generate a sufficiently large pedigree (500 intercross progeny or more) to obtain reasonable power and to allow more sophisticated statistical analysis of the data. However, the major challenge in a QTL experiment is not to detect QTL but to identify the genes underlying a QTL (Andersson and Georges, 2004). This is because there is not a 1-to-1 relationship between genotype and phenotype, as exists for a simple monogenic trait. One option to obtain a more precise localization of a QTL is to perform selective backcrossing. In such experiments, one first identifies animals carrying recombinant chromosomes and uses backcrossing and progeny testing to determine the QTL status of recombinant chromosomes with great confidence. Another option is to maintain advance intercross lines (Darvasi, 1998) that are used to break up the strong linkage that is generated by the initial crossing experiment. A new QTL scan can be carried out at a subsequent generation, and the map position of the QTL will be much improved. A third approach is to use identical-by-descent mapping across breeds, if there are reasons to believe that the same QTL allele may be present in more than 1 breed. This approach can be very powerful because it takes advantage of historical recombination events. A key issue is to determine the QTL status of each haplotype with great confidence. Risks of failure with this strategy include the possibility that the similarity in map position across breeds may be caused by different genes with similar phenotypic effects or different alleles at the same locus. In those cases, no shared haplotypes will be detected across breeds.
The detection of selective sweeps can be a very powerful approach to identify chromosomal regions that have been under strong selection. A selective sweep is the process in which 1 favorable allele goes to fixation within a population and, as a consequence, genetic variation is lost in the surrounding region due to hitchhiking (Andersson and Georges, 2004). It is expected that selective sweeps are a common phenomenon in domestic animals due to the strong directional selection that recently has been imposed on these species by human intervention. A prime example of such a selective sweep is at the IGF2 locus in domestic pigs selected for lean growth (Van Laere et al., 2003). It is shown that the selection for the causative mutation in IGF2 intron 3 leads to a high degree of homozygosity in a region of about 10 kb flanking the causative mutation among breeds intensively selected for high muscle development. The existence of footprints of selective sweeps in the chicken genome has not yet been examined widely, but 1 example is at the dominant white locus encoding the PMEL17 protein. Kerje et al. (2004) determined the entire gene sequence of 4.1 kb (including all exons and all introns) among different lines of chickens. They failed to detect a single nucleotide difference between 2 lines both carrying the dominant white allele, whereas multiple differences were found compared with lines with the wild-type allele. Many more selective sweeps must exist in the chicken, but the data indicate that the regions affected are rather small (International Chicken Polymorphism Map Consortium, 2004), which is both bad and good news. It means that it will be difficult to detect such regions, but once they are found, only a comparatively small region will need to be searched for the causative mutation(s). A very dense SNP map, perhaps 1 SNP/10 kb, is therefore needed to provide a good chance of detecting selective sweeps. The ultimate solution will be to resequence the entire genome of different lines of chickens. A powerful experiment would be to sequence 10 birds from each line of interest, each to 2x coverage. This would result in sampling 20 chromosomes per line and should generate, on average, 20 sequence reads for each nucleotide position per line throughout the chicken genome. Careful bioinformatic analysis of such data should be able to detect selective sweeps, and one could compare several lines with a similar phenotype (e.g., different broilers) to examine shared regions. The cost for DNA sequencing needs to decrease by about 2 orders of magnitude before such a dream project could become a reality. However, the progress of sequencing technology is rapid, so this possibility lies within the foreseeable future (Church, 2006).
Applications in the Breeding Industry
The industry is already using MAS, to some extent, in their breeding programs. This can be used to increase the frequency of favorable alleles or to eliminate unfavorable alleles. For instance, breeders can now use a DNA test for dominant white if they would like to ensure that their line breeds true for color. An emerging opportunity is to use genomic selection as a method to predict the total genetic value of an animal based on data from genome-wide dense marker maps (Meuwissen et al., 2001). This is becoming feasible due to the huge collection of SNP available in the chicken and the reduced cost of high-throughput SNP typing. With this approach, breeders can estimate the effect of QTL haplotypes without any need to understand the underlying molecular nature of the QTL. They may also be able to estimate modes of action and possibly interactions for each haplotype and use this to improve their breeding program.
In a long-term perspective, the ability to improve the genetic constitution of chicken lines by transgenic technology may eventually become the most important practical application of molecular genetics. Not only is such technology critical to the use of the chicken as a model organism (Dodgson, 2003), it may be essential to verify candidate QTL alleles and to sort out the interactions between QTL and the genetic background. Furthermore, the wealth of knowledge in biology that is currently accumulating, not only from research on chickens but with all organisms, will lead to new opportunities to genetically modify chickens in ways that are of value to agriculture. Most important, the benefits obtainable must be sufficient to outweigh consumer resistance, as they have been, in at least some countries, for crop plants. It appears that disease resistance provides an excellent example of an area in which this technology can have great benefit. For instance, if we could learn more about the biology of influenza infection in birds, it may be possible to genetically engineer chickens to be highly resistant to this disease, a very important achievement that should reduce a major animal welfare problem and a risk to human health.
Received for publication June 30, 2006. Accepted for publication July 10, 2006.
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