Quantitative Trait Loci (QTL) Morris Soller Ehud Lipkin The Hebrew University of Jerusalem, Jerusalem, Israel INTRODUCTION Most traits of agricultural importance, such as growth rate and body composition, milk yield and composition, and egg number and quality show a continuous distribu- tion of quantitative trait measurements in a population. Such traits are termed quantitative traits, in contrast to Mendelian traits, which typically are found in a limited number of qualitatively different forms in a population (e.g., presence or absence of horns, brown or black coat color). Genetic variation in a quantitative trait is generally attributed to allelic variation at a number of genes, in contrast to the one or two genes generally found sufficient to explain genetic variation in a Mendelian trait. Moreover, quantitative trait expression is much affected by environmental variables, again in contrast to Mende- lian traits, which are generally little affected by environment. Consequently, for quantitative traits, the relationship between genotype and phenotype is complex, and the genotype of an individual cannot be inferred from its phenotype or that of its relatives. Instead, the various genes affecting a quantitative trait are individuated by mapping them to specific chromosomal locations (loci). For this reason, the term quantitative trait loci, or QTL, was proposed for the individual mapped genetic factors affecting quantitative trait value. Mapping the QTL responsible for genetic variation in traits of agricultural importance, and using the map locations to identify the actual genes involved, is a major challenge for animal genetics. Success will pro- vide powerful tools for understanding the physiology of trait variation, and for genetic improvement of ani- mal stocks. QTL MAPPING QTL mapping means locating the specific chromosomal regions in which QTL are found. This is achieved by locating the QTL with respect to a standard set of Mendelian loci that have been previously mapped using standard genetic or physical gene-mapping procedures. These reference loci are termed genetic markers, since they identify (mark) specific chromosomal locations. Consequently, showing that a QTL is found in the near vicinity of a specific marker (termed ‘‘linked’’ to the marker) is equivalent to mapping the QTL to the location of the marker. Thus, a prior requirement for QTL mapping is the availability of a comprehensive marker map. Such maps, based on DNA-level polymorphic loci, are now available for all of the major farm animals. At present, QTL can only be mapped by using genetic (as opposed to physical) mapping procedures. Genetic mapping procedures start with an individual that is heterozygous for the marker and for the linked QTL. The genetic distance between a marker and a QTL then stands in direct proportion to the number of recombinant gene combinations (haplotypes) among the progeny of the doubly heterozygous individual, i.e., when a QTL and marker are tightly linked, recombinant haplotypes will be rare. The way in which the proportion of recombinant haplotypes among the progeny of an individual is inferred for a QTL and a linked marker is best explained by example, using the basic half-sib sire-family QTL mapping design. Let M be a marker locus and Q a nearby linked QTL, with alleles M and m and Q and q, respectively, where allele Q is a positive allele that increases trait value, and allele q is a negative allele that decreases trait value (italics denote genes, and bold type denotes alleles). Consider a sire having haplotypes MQ and mq on a pair of homologous chromosomes carrying these genes. Let r denote the total proportion of daughters that received recombinant haplotypes Mq or mQ from their sire, and (1Àr) the total proportion of daughters that received the parental haplotypes, MQ or mq. Then, the following table shows the proportion of daughters carrying each of the four transmitted sire haplotypes. Daughter type Sire haplotype Relative proportion among all daughters Parental MQ 0.5(1 Àr) Recombinant Mq 0.5 r Recombinant mQ 0.5 r Parental mq 0.5(1 Àr) The progeny of the sire that receive the M marker allele from their sire will be of two types: MQ and Mq. 760 Encyclopedia of Animal Science DOI: 10.1081/E EAS 120019780 Copyright D 2005 by Marcel Dekker, Inc. All rights reserved. Thus, they will receive a mixture of Q and q alleles, in relative proportion (1Àr):r.IfM is close to Q, r will be small. Consequently, among these progeny, there will be a preponderance of Q alleles having positive effects on trait value. The opposite holds for progeny that re- ceive the m marker allele from the sire; among these daughters, there will be a preponderance of q alleles having negative effects on trait value. The net result is that, on average, the progeny carrying the M marker allele are expected to show a higher trait value than the progeny carrying the m marker allele, the expected difference (D-value) being greater the closer M and Q are to one another, while D = 0 when marker and QTL are on different chromosomes or far removed on the same chromosome. In practice, the location of the markers in linkage to QTL is not known in advance; hence the experiment is carried out as a genome scan, in which D-values are calculated for a complete set of markers spanning the entire genome. A typical scan may involve 70 to 150 markers. In single-marker mapping, a QTL in a given chromosomal region is assigned the location of the marker that shows the greatest D-value. In interval mapping, information on all markers in a chromosomal region is used to obtain the most likely position of the QTL using advanced statistical procedures of maximum likelihood estimation and least squares regression mapping. OTHER MAPPING DESIGNS The granddaughter design is a variant of the half-sib design, widely used in dairy cattle QTL mapping. In this design, the half-sib family consists of the progeny-tested sons of an elite sire. The phenotype of the sons is given by the average production records of their daughters. This is a convenient design to implement because semen samples of the sire and his sons can be used as a source of DNA; semen samples of all progeny-tested sires in the United States are routinely collected in a special repository maintained by the U.S. Department of Agriculture (USDA) and made available to qualified scientists for QTL mapping. Progeny test data on the sire and his sons are also widely available through the USDA sire evaluation service. Backcross and F2 designs are imple- mented when mapping QTL responsible for trait differ- ences between two populations that differ widely in trait value (such as broiler and layer chickens, disease-resistant and susceptible breeds of cattle). When the mapping population is very large and a large number of markers are followed, selective DNA pooling can reduce the genotyp- ing load ten- to one-hundredfold. CONFIDENCE INTERVAL OF QTL MAP LOCATION AND HIGH-RESOLUTION MAPPING OF QTL QTL mapping gives the most likely point location for the QTL, accompanied by a confidence interval, which is an interval along the chromosome to both sides of the point location within which the QTL could actually reside. The width of this interval defines the map resolution of the experiment. In many QTL mapping experiments, the confidence interval is very large, from one-quarter to one- half of the entire chromosome. The confidence interval can be reduced by increasing the sample size and the density of marker spacing, and by application of specialized multilocus and multitrait mapping procedures. Advanced intercross lines can also be used to improve map resolution in experimental and farm populations. LINKAGE DISEQUILIBRIUM (LD) MAPPING AND IDENTICAL BY DESCENT (IBD) MAPPING When marker and QTL are very close together, or when the marker is within the DNA sequence of the gene itself, a situation may arise in which there is an excess of some haplotypes and a deficiency of others across the population as a whole. This condition, termed linkage disequilibrium (LD), can be uncovered by an association test, which compares average trait value of the different genotypes at a marker across the population as a whole. Finding marker QTL LD indicates that the marker involved is very close to the QTL. Linkage disequilibrium can be generated by the random accumulation of small changes in frequency of the various marker QTL haplotypes over many generations. Identical by descent (IBD) mapping is based on the assumption that the mutation that produced a specific positive or negative QTL allele was a unique event that took place in a single ancestor chromosome, and will hence be in association with the specific marker alleles found in the haplotype of the ancestor chromosome within which the mutation arose. Thus, IBD mapping can lead to the very gene underlying the QTL. RESULTS OF QTL MAPPING: NUMBER AND EFFECTS OF QTL When all QTL mapping studies in a farm animal species are considered together and appropriate extrapolations are Quantitative Trait Loci (QTL) 761 made, typical quantitative traits appear to be controlled by anywhere from five to a few dozen QTL. For the most part, effects of individual QTL are in the range of 1 to 3% of the trait mean. In some instances, the mapped QTL as a group are able to account for a large fraction of the observed genetic variation in the study population. Mapped QTL commonly exhibit various degrees of dominance, including overdominance; interactions (epi- stasis) among mapped QTL are common. FROM QTL TO CG (CANDIDATE GENE) TO QTG (QUANTITATIVE TRAIT GENE) When gene maps of vertebrate species, including humans, are compared, the order of the genes in large chromosomal regions (depending on the particular pair of species compared) are often found to be the same. As a result, when a QTL has been mapped to a particular chromo- somal region in a particular species, it is possible to look at the comparative gene map and identify the genes that are present in the comparable region in other species. Through bioinformatic data mining, all of the functional information accumulated across all living species on the genes in a given chromosomal region can be accessed. Among these genes may be those that have functions or expression patterns that make them attractive candidates to be the actual gene underlying the QTL. This can be tested by identifying markers within these candidate genes (CG), and then testing them for association with trait value by LD mapping. Candidate genes that show strong association with trait value become putative quantitative trait genes (QTG). Final confirmation that a putative QTG corresponds to the mapped QTL is difficult, but has been achieved successfully in a number of instances. In most cases, the identified QTG was one whose function was directly related to the physiology or development of the trait in question. CONCLUSION Mapping a large fraction of the QTL responsible for genetic variation in the traits of economic importance in farm animals and identifying the QTG underlying the mapped QTL are now the major challenges for farm animal genetics. The ultimate goal is to anchor 80% of the genetic variation in the traits of economic importance to specific QTL and QTG. Success in this will greatly increase our understanding of the molecular physiology of production traits, and our ability to achieve rapid and cost- effective genetic improvement. REFERENCES 1. Falconer, D.S.; Mackay, T.S.F. Introduction to Quantitative Genetics, 4th Ed.; Longman Sci. and Tech.: Harlow, UK, 1996. 2. Lynch, M. Genetics and Analysis of Quantitative Traits; Sinauer Associates, Inc.: Sunderland, MA, 1998. 3. Weller, J.I. Quantitative Trait Loci Analysis in Animals; CABI Publishing: New York, NY, 2001. 762 Quantitative Trait Loci (QTL) . r Recombinant mQ 0.5 r Parental mq 0.5(1 Àr) The progeny of the sire that receive the M marker allele from their sire will be of two types: MQ and Mq. 760 Encyclopedia of Animal Science DOI: 10.1081/E. by example, using the basic half-sib sire-family QTL mapping design. Let M be a marker locus and Q a nearby linked QTL, with alleles M and m and Q and q, respectively, where allele Q is a positive allele. gene underlying the QTL. RESULTS OF QTL MAPPING: NUMBER AND EFFECTS OF QTL When all QTL mapping studies in a farm animal species are considered together and appropriate extrapolations are Quantitative