Int. J. Biol. Sci. 2007, 3 420 International Journal of Biological Sciences ISSN 1449-2288 www.biolsci.org 2007 3(7):420-427 ©Ivyspring International Publisher. All rights reserved Review Candidate Gene Identification Approach: Progress and Challenges Mengjin Zhu and Shuhong Zhao Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, P. R. China Correspondence to: Shuhong Zhao, Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, P. R. China. Tel: +86-27-87281306; Fax: +86-27-87280408; E-mail: [email protected] Received: 2007.08.26; Accepted: 2007.10.24; Published: 2007.10.25 Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach. Key words: candidate gene approach; information bottleneck; digital candidate gene approach 1. Introduction which the principal disadvantage is expensive and resource intensive. In general, genome-wide scanning Based on the polygenic hypothesis, classical only locates the glancing chromosomal regions of quantitative genetics considers a black box to reveal quantitative trait loci (QTLs) at cM-level with the aid the holistic status of all genes associated with of DNA markers under family-based or variation of complex and quantitative traits by population-based experimental designs, which complicated statistical methods. Such strategy could usually embed a large number of candidate genes. In not independently decompose individual genes, comparison, the alternative candidate gene approach which usually follow the Mendel's law, from the has been proven to be extremely powerful for polygenic system of the investigated traits. Advances studying the genetic architecture of complex traits, in molecular methods and quantitative techniques which is a far more effective and economical method have clearly changed this status, which are able to for direct gene discovery. Nevertheless, the look inside the black box of polygenic control for practicability of traditional candidate gene approach is complex and quantitative traits with a more accurate largely limited by its reliance on existing knowledge description of how genes act to determine the about the known or presumed biology of the phenotypic variation. More recently, major progress phenotype under investigation, and unfortunately the has been made in this field with the advent of detailed molecular anatomy of most biological traits genomics and its potential contribution to remains unknown. It is quite necessary to develop development of quantitative genetics. One of the hot new strategies to break the restriction of information interests of current quantitative genetics is bottleneck, although considerable candidate genes systematically exploring an exact genetic architecture have already been identified. of the number, distribution and interaction of loci In this article, we review and summarize the affecting the variations of biomedically, economically, main research advances in the subject, including the and evolutionarily important complex and outline of candidate gene approach and the extended quantitative traits. strategies for breaking the information bottleneck of There are two approaches for genetic dissections traditional candidate gene approach. Finally, as a new of complex and quantitative traits, i.e., genome-wide development of candidate gene approach, digital scanning and candidate gene approach, which each candidate gene approach (DigiCGA) was discussed has specific advantages and disadvantages. and some research outlooks were given to further Genome-wide scanning usually proceeds without any promote this valuable research subject. presuppositions regarding the importance of specific functional features of the investigated traits, but of Int. J. Biol. Sci. 2007, 3 421 2. A glance of traditional candidate gene physical linkage information in a QTL-identified approach chromosomal segment. Such strategy resulted in the emergence of positional candidate gene approach, the The rationale of candidate gene approach states post-genomic version of the positional cloning that a major component of quantitative genetic method. This approach aims at the vicinity of known variation of phenotype under investigation is caused QTLs, and candidate genes are sought out from tens to by functional mutation of putative gene. Candidate hundreds of gene members harbored in the targeted genes are generally the genes with known biological chromosomal region. Some successful applications of function directly or indirectly regulating the position-dependent strategy have already been developmental processes of the investigated traits, reported in different fields (including the classical which could be confirmed by evaluating the effects of examples of DGAT1 in cattle, GDF8 in sheep and IGF2 the causative gene variants in an association analysis. in swine) [2-10]. Using this strategy, a recent study has Candidate gene approach has been ubiquitously testified that a single-nucleotide polymorphism applied for gene-disease research, genetic association haplotype of IGF1 contributes to the control of body studies, biomarker and drug target selection in many size in dogs [11]. In general, a combination of linkage organisms from animals to humans [1]. To date, many studies and candidate gene analyses for promising candidate genes of economic traits or disease chromosomal regions is a straightforward strategy, resistance/susceptibility were primarily or even and of which the unifying can effectively improve the repeatedly detected, although the total number of the hitting accuracy [12]. publicly accepted genes is still absolutely small. Most However, the successful map-based positional importantly, candidate gene analysis is usually the cloning was mainly involved in the genes that are indispensable procedure for subsequent positional responsible for Mendelian traits with discrete cloning of QTLs controlling the major genetic phenotypic differences, while the studies that have variation of interested traits after initial genome scans. attempted to identify the positionally causative genes In general, significant components of QTLs in a responsible for typical quantitative traits have met chromosomal region affecting genetic variation of with limited success. At the same time, many investigated traits are causative genes, so the ultimate statistically positive genes detected by the gene-trait pinpoint location of a QTL, with dozens or even associations could not be verified to locate in or near hundreds of genes assembled in the about ~20cM to the known QTL region, which also hints that the confidence interval, to a specific polymorphic gene is position-dependent strategy can not always work inevitably involved in candidate gene analysis. well. Although there were some successful examples However, candidate gene approach has been criticized of positional cloning in animals, the pinpoint location owing to low replication of results and its limited of a causative gene or even underlying functional QTL ability to include all possible causative genes [1]. nucleotide in a conserved block is highly challenged. Moreover, this approach is by necessity highly Usually, there is no guarantee that an identified QTL subjective in the process of choosing specific represents a single gene [13] and there are also many candidates from numbers of potential possibilities. false-positive QTLs that directly fail the application of The main disadvantage is that it requires the position-dependent strategy. The difficulty of information that comes from the existed well-known prioritization of positional candidate gene might be physiological, biochemical or functional knowledge resulted in by the low penetrance of multiple such as hormonal regulation, biochemical metabolism contributing genes. Moreover, the commonly used pathway and etc., which is generally finite or linkage analysis often contains hundreds of genes in sometimes not available at all. The actual absence of the LOD support interval for a QTL. High-density background knowledge for unscrambling the markers in the same region and alternative analytical molecular stories of most complex and quantitative methods such as linkage disequilibrium analysis can traits has obviously became an information bottleneck refine the span of confidence interval small enough to to clag