畜禽生产性状主效基因定位技术与方法研究进展

鉴定畜禽重要生产性状形成的关键遗传因子,揭示其产生的分子遗传机制,对动物新品种的培育及特色遗传资源的开发利用具有重要意义。高通量分析技术诞生前,标记数量性状位点(quantitative trait loci,QTL)连锁分析和候选基因分析法作为鉴定畜禽生产性状QTL和主效基因主要方法,但由于其技术局限性,性状因果基因鉴定的效率并不高。人类基因组计划(human genome project, HGP)开启了以大数据为特征的生命科学研究的序幕,在HGP完成后的20余年间,快速发展的高通量分析技术使人们研究生物学问题的思路和方法发生了巨大改变。本综述就近年来被广泛用于畜禽重要性状的候选基因定位的方法与技术进行了较全面的综述,以期为同行提供参考。     

Characterising functionally important and ecologically meaningful genetic diversity using a candidate gene approach

Over the past two decades the fields of molecular ecology and population genetics have been dominated by the use of putatively neutral DNA markers, primarily to resolve spatio-temporal patterns of genetic variation to inform our understanding of population structure, gene flow and pedigree. Recent emphasis in comparative functional genomics, however, has fuelled a resurgence of interest in functionally important genetic variation that underpins phenotypic traits of adaptive or ecological significance. It may prove a major challenge to transfer genomics information from classical model species to examine functional diversity in non-model species in natural populations, but already multiple gene-targeted candidate loci with major effect on phenotype and fitness have been identified. Here we briefly describe some of the research strategies used for isolating and characterising functional genetic diversity at candidate gene-targeted loci, and illustrate the efficacy of some of these approaches using our own studies on red grouse (Lagopus lagopus scoticus). We then review how candidate gene markers have been used to: (1) quantify genetic diversity among populations to identify those depauperate in genetic diversity and requiring specific management action; (2) identify the strength and mode of selection operating on individuals within natural populations; and (3) understand direct mechanistic links between allelic variation at single genes and variance in individual fitness.     

Incomplete Coverage of Candidate Genes: A Poorly Considered Bias

Current genetic investigations are performed both on the basis of a rational and biologically based choice of candidate genes and through genome wide scans. Nonetheless, lack of replication is a common problem in psychiatric genetics as well as in other genetic fields. There are a number of reasons for this inconsistency, among them a well known but poorly considered issue is gene coverage. The aim of the present paper is to focus on this well known and defectively deemed bias, especially when a candidate gene approach is chosen. The rational and the technical feasibility of this proposal are discussed as well as a survey of current investigations. The known consistent methodology to fix this bias is also discussed.Key Words: Candidate genes, association studies, psychiatry genetics, methodology.     

Investigation of Obesity Candidate Genes On Porcine Fat Deposition Quantitative Trait Loci Regions

Objectives: To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity‐related phenotypes. Research Methods and Procedures: Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a reference pig family. Statistical association analyses of these genes were performed for fat deposition phenotypes in several other commercial pig populations. Results: Eight candidate genes were mapped to QTL regions of pig chromosomes in this study. These candidate genes also served as anchor loci to determine homologous human chromosomal locations of pig fat deposition QTL. Preliminary analyses of relationships among polymorphisms of individual candidate genes and a variety of phenotypic measurements in a large number of pigs were performed. On the basis of available data, gene‐gene interactions were also studied. Discussion: Comparative analysis of obesity‐related genes in the pig is not only important for development of marker‐assisted selection on growth and fat deposition traits in the pig but also provides for an understanding of their genetic roles in the development of human obesity.     

Genetic epidemiology of tuberculosis susceptibility: impact of study design

Several candidate gene studies have provided evidence for a role of host genetics in susceptibility to tuberculosis (TB). However, the results of these studies have been very inconsistent, even within a study population. Here, we review the design of these studies from a genetic epidemiological perspective, illustrating important differences in phenotype definition in both cases and controls, consideration of latent M. tuberculosis infection versus active TB disease, population genetic factors such as population substructure and linkage disequilibrium, polymorphism selection, and potential global differences in M. tuberculosis strain. These considerable differences between studies should be accounted for when examining the current literature. Recommendations are made for future studies to further clarify the host genetics of TB.     

Clustering threshold gradient descent regularization: with applications to microarray studies

MOTIVATION: An important goal of microarray studies is to discover genes that are associated with clinical outcomes, such as disease status and patient survival. While a typical experiment surveys gene expressions on a global scale, there may be only a small number of genes that have significant influence on a clinical outcome. Moreover, expression data have cluster structures and the genes within a cluster have correlated expressions and coordinated functions, but the effects of individual genes in the same cluster may be different. Accordingly, we seek to build statistical models with the following properties. First, the model is sparse in the sense that only a subset of the parameter vector is non-zero. Second, the cluster structures of gene expressions are properly accounted for. RESULTS: For gene expression data without pathway information, we divide genes into clusters using commonly used methods, such as K-means or hierarchical approaches. The optimal number of clusters is determined using the Gap statistic. We propose a clustering threshold gradient descent regularization (CTGDR) method, for simultaneous cluster selection and within cluster gene selection. We apply this method to binary classification and censored survival analysis. Compared to the standard TGDR and other regularization methods, the CTGDR takes into account the cluster structure and carries out feature selection at both the cluster level and within-cluster gene level. We demonstrate the CTGDR on two studies of cancer classification and two studies correlating survival of lymphoma patients with microarray expressions. AVAILABILITY: R code is available upon request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Recent insights into cotton functional genomics: progress and future perspectives

Functional genomics has transformed from futuristic concept to well‐established scientific discipline during the last decade. Cotton functional genomics promise to enhance the understanding of fundamental plant biology to systematically exploit genetic resources for the improvement of cotton fibre quality and yield, as well as utilization of genetic information for germplasm improvement. However, determining the cotton gene functions is a much more challenging task, which has not progressed at a rapid pace. This article presents a comprehensive overview of the recent tools and resources available with the major advances in cotton functional genomics to develop elite cotton genotypes. This effort ultimately helps to filter a subset of genes that can be used to assemble a final list of candidate genes that could be employed in future novel cotton breeding programme. We argue that next stage of cotton functional genomics requires the draft genomes refinement, re‐sequencing broad diversity panels with the development of high‐throughput functional genomics tools and integrating multidisciplinary approaches in upcoming cotton improvement programmes.     

Genomic regions controlling yield-related traits in spring wheat: a mini review and a case study for rainfed environments in Australia and China

A genome-wide association study (GWAS) was performed in six environments to identify major or consistent alleles responsible for wheat yield traits in Australia and North China where rainfed farming system is adopted. A panel of 228 spring wheat varieties were genotyped by double digest restriction-site associated DNA genotyping-by-sequencing. A total of 223 significant marker-trait association (MTAs) and 46 candidate genes for large- or consistent-effect MTAs were identified. The results were compared with previous studies based on a mini-review of 23 GWAS analyses on wheat yield. A phenomenon seldom reported in previous studies was that MTAs responsible for the trait tended to cluster together at certain chromosome segments, and many candidate genes were in the form of gene clusters. Although linkage disequilibrium (LD) might contribute to the co-segregation of the regions, it also suggested that marker-assisted selection (MAS) or transgenic method targeting a single gene might not be as effective as MAS targeting a larger genomic region where all the genes or gene clusters underlying play important roles.     

Mice as a mammalian model for research on the genetics of aging

Mice are an ideal mammalian model for studying the genetics of aging: considerable resources are available, the generation time is short, and the environment can be easily controlled, an important consideration when performing mapping studies to identify genes that influence lifespan and age-related diseases. In this review we highlight some salient contributions of the mouse in aging research: lifespan intervention studies in the Interventions Testing Program of the National Institute on Aging; identification of the genetic underpinnings of the effects of calorie restriction on lifespan; the Aging Phenome Project at the Jackson Laboratory, which has submitted multiple large, freely available phenotyping datasets to the Mouse Phenome Database; insights from spontaneous and engineered mouse mutants; and complex traits analyses identifying quantitative trait loci that affect lifespan. We also show that genomewide association peaks for lifespan in humans and lifespan quantitative loci for mice map to homologous locations in the genome. Thus, the vast bioinformatic and genetic resources of the mouse can be used to screen candidate genes identified in both mouse and human mapping studies, followed by functional testing, often not possible in humans, to determine their influence on aging.     

Increased 90-kDa ribosomal S6 kinase (Rsk) activity is protective against mutant huntingtin toxicity

Uncovering the underlying genetic component of any disease is key to the understanding of its pathophysiology and may open new avenues for development of therapeutic strategies and biomarkers. In the past several years, there has been an explosion of genome-wide association studies (GWAS) resulting in the discovery of novel candidate genes conferring risk for complex diseases, including neurodegenerative diseases. Despite this success, there still remains a substantial genetic component for many complex traits and conditions that is unexplained by the GWAS findings. Additionally, in many cases, the mechanism of action of the newly discovered disease risk variants is not inherently obvious. Furthermore, a genetic region with multiple genes may be identified via GWAS, making it difficult to discern the true disease risk gene. Several alternative approaches are proposed to overcome these potential shortcomings of GWAS, including the use of quantitative, biologically relevant phenotypes. Gene expression levels represent an important class of endophenotypes. Genetic linkage and association studies that utilize gene expression levels as endophenotypes determined that the expression levels of many genes are under genetic influence. This led to the postulate that there may exist many genetic variants that confer disease risk via modifying gene expression levels. Results from the handful of genetic studies which assess gene expression level endophenotypes in conjunction with disease risk suggest that this combined phenotype approach may both increase the power for gene discovery and lead to an enhanced understanding of their mode of action. This review summarizes the evidence in support of gene expression levels as promising endophenotypes in the discovery and characterization of novel candidate genes for complex diseases, which may also represent a novel approach in the genetic studies of Alzheimer's and other neurodegenerative diseases.     

Time trees and clock genes: a systematic review and comparative analysis of contemporary avian migration genetics

Timing is a crucial aspect for survival and reproduction in seasonal environments leading to carefully scheduled annual programs of migration in many species. But what are the exact mechanisms through which birds (class: Aves) can keep track of time, anticipate seasonal changes, and adapt their behaviour? One proposed mechanism regulating annual behaviour is the circadian clock, controlled by a highly conserved set of genes, collectively called ‘clock genes’ which are well established in controlling the daily rhythmicity of physiology and behaviour. Due to diverse migration patterns observed within and among species, in a seemingly endogenously programmed manner, the field of migration genetics has sought and tested several candidate genes within the clock circuitry that may underlie the observed differences in breeding and migration behaviour. Among others, length polymorphisms within genes such as Clock and Adcyap1 have been hypothesised to play a putative role, although association and fitness studies in various species have yielded mixed results. To contextualise the existing body of data, here we conducted a systematic review of all published studies relating polymorphisms in clock genes to seasonality in a phylogenetically and taxonomically informed manner. This was complemented by a standardised comparative re-analysis of candidate gene polymorphisms of 76 bird species, of which 58 are migrants and 18 are residents, along with population genetics analyses for 40 species with available allele data. We tested genetic diversity estimates, used Mantel tests for spatial genetic analyses, and evaluated relationships between candidate gene allele length and population averages for geographic range (breeding- and non-breeding latitude), migration distance, timing of migration, taxonomic relationships, and divergence times. Our combined analysis provided evidence (i) of a putative association between Clock gene variation and autumn migration as well as a putative association between Adcyap1 gene variation and spring migration in migratory species; (ii) that these candidate genes are not diagnostic markers to distinguish migratory from sedentary birds; and (iii) of correlated variability in both genes with divergence time, potentially reflecting ancestrally inherited genotypes rather than contemporary changes driven by selection. These findings highlight a tentative association between these candidate genes and migration attributes as well as genetic constraints on evolutionary adaptation.     

A global barley panel revealing genomic signatures of breeding in modern Australian cultivars

The future of plant cultivar improvement lies in the evaluation of genetic resources from currently available germplasm. Today’s gene pool of crop genetic diversity has been shaped during domestication and more recently by breeding. Recent efforts in plant breeding have been aimed at developing new and improved varieties from poorly adapted crops to suit local environments. However, the impact of these breeding efforts is poorly understood. Here, we assess the contributions of both historical and recent breeding efforts to local adaptation and crop improvement in a global barley panel by analysing the distribution of genetic variants with respect to geographic region or historical breeding category. By tracing the impact that breeding had on the genetic diversity of Hordeum vulgare (barley) released in Australia, where the history of barley production is relatively young, we identify 69 candidate regions within 922 genes that were under selection pressure. We also show that modern Australian barley varieties exhibit 12% higher genetic diversity than historical cultivars. Finally, field-trialling and phenotyping for agriculturally relevant traits across a diverse range of Australian environments suggests that genomic regions under strong breeding selection and their candidate genes are closely associated with key agronomic traits. In conclusion, our combined data set and germplasm collection provide a rich source of genetic diversity that can be applied to understanding and improving environmental adaptation and enhanced yields.     

Mutation detection and physical mapping of the CD11 gene cluster in association with inflammatory bowel disease

A genetic component in the etiology of inflammatory bowel disease (IBD) has clearly been demonstrated by epidemiological and genetic linkage studies. Linkage to IBD on proximal Chromosome (Chr) 16p is well established and replicated. A stratification experiment showed that the recent identification of a disease gene on the q arm does not interfere with the approach on the p arm, and the linkage peak is still significant. Here we present a candidate gene study of the alpha integrins (CD11A-D) on Chr 16. The alpha integrins play a key role in inflammatory processes, including leukocyte adhesion and migration. Their genes are located on the p arm of Chr 16, and therefore represent excellent positional and functional candidates. Since the assignment of the CD11 genes in the genome was not clear, we performed physical, radiation hybrid, and fluorescent in situ hybridization mapping of the gene family. All CD11 genes map on Chr 16p11-12. CD11B-D are arranged in a gene cluster within 300 kb and CD11A is located about 2.5 Mb telomeric. Thirteen new single nucleotide polymorphisms (SNPs) and eight SNPs from databases were identified through full-length sequencing. Case-control statistics demonstrated an association lead in the CD11 gene cluster, which was not confirmed in further family based association/linkage analyses using single markers and haplotypes. It is unlikely that the CD11 genes play an important role in the pathogenesis of IBD. The marginally significant results could indicate a disease gene in the vicinity of the gene cluster.     

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.     

Naturally occurring variation in Arabidopsis: an underexploited resource for plant genetics

The definition of gene functions requires the phenotypic characterization of genetic variants. Currently, such functional analysis of Arabidopsis genes is based largely on laboratory-induced mutants that are selected in forward and reverse genetic studies. An alternative complementary source of genetic variation is available: the naturally occurring variation among accessions. The multigenic nature of most of this variation has limited its application until now. However, the use of genetic methods developed to map quantitative trait loci, in combination with the characteristics and resources available for molecular biology in Arabidopsis, allow this variation to be exploited up to the molecular level. Here, we describe the current tools available for the forward genetic analysis of this variation, and review the recent progress in the detection and mapping of loci and the cloning of large-effect genes.     

Positive selection in the evolution of cancer

We hypothesize that forms of antagonistic coevolution have forged strong links between positive selection at the molecular level and increased cancer risk. By this hypothesis, evolutionary conflict between males and females, mothers and foetuses, hosts and parasites, and other parties with divergent fitness interests has led to rapid evolution of genetic systems involved in control over fertilization and cellular resources. The genes involved in such systems promote cancer risk as a secondary effect of their roles in antagonistic coevolution, which generates evolutionary disequilibrium and maladaptation. Evidence from two sources: (1) studies on specific genes, including SPANX cancer/testis antigen genes, several Y-linked genes, the pem homebox gene, centromeric histone genes, the breast cancer gene BRCA1, the angiogenesis gene ANG, cadherin genes, cytochrome P450 genes, and viral oncogenes; and (2) large-scale database studies of selection on different functional categories of genes, supports our hypothesis. These results have important implications for understanding the evolutionary underpinnings of cancer and the dynamics of antagonistically-coevolving molecular systems.     

Accommodating pathway information in expression quantitative trait locus analysis

The availability of high-throughput genotyping technologies and microarray assays has allowed researchers to consider pursuing investigations whose ultimate goal is the identification of genetic variations that influence levels of gene expression, e.g., "expression quantitative trait locus" or "eQTL" mapping studies. However, the large number of genes whose expression levels can be tested for association with genetic variations in such studies can create both statistical and biological interpretive problems. We consider the integrated analysis of eQTL mapping data that incorporates pathway, function, and disease process information. The goal of this analysis is to determine if compelling patterns emerge from the data that are consistent with the notion that perturbations in the molecular physiologic environment induced by genetic variations implicate the expression patterns of multiple genes via genetic network relationships or feedback mechanisms. We apply available genetic network and pathway analysis software, as well as a novel regression analysis technique, to carry out the proposed studies. We also consider extensions of the proposed strategies and areas of future research.