Fine‐mapping natural alleles: quantitative complementation to the rescue

Mapping the genes responsible for natural variation and divergence is a challenging task. Many studies have mapped genes to genomic regions or generated lists of candidates, but few studies have implicated specific genes with a high standard of evidence. I propose that combining recent advances in genomic engineering with a modified version of the quantitative complementation test will help turn candidate genes into causal genes. By creating loss‐of‐function mutations in natural strains, and using these mutations to quantitatively fail‐to‐complement natural alleles, fine mapping should be greatly facilitated. As an example, I propose that the CRISPR/Cas9 system could be combined with the FLP/FRT system to fine‐map genes in the numerous systems where inversions have frustrated these efforts.     

Mapping of quantitative trait loci controlling lifespan in the short-lived fish Nothobranchius furzeri--a new vertebrate model for age research

The African annual fish Nothobranchius furzeri emerged as a new model for age research over recent years. Nothobranchius furzeri show an exceptionally short lifespan, age-dependent cognitive/behavioral decline, expression of age-related biomarkers, and susceptibility to lifespan manipulation. In addition, laboratory strains differ largely in lifespan. Here, we set out to study the genetics of lifespan determination. We crossed a short- to a long-lived strain, recorded lifespan, and established polymorphic markers. On the basis of genotypes of 411 marker loci in 404 F(2) progeny, we built a genetic map comprising 355 markers at an average spacing of 5.5 cM, 22 linkage groups (LGs) and 1965 cM. By combining marker data with lifespan values, we identified one genome-wide highly significant quantitative trait locus (QTL) on LG 9 (P < 0.01), which explained 11.3% of the F(2) lifespan variance, and three suggestive QTLs on LG 11, 14, and 17. We characterized the highly significant QTL by synteny analysis, because a genome sequence of N. furzeri was not available. We located the syntenic region on medaka chromosome 5, identified candidate genes, and performed fine mapping, resulting in a c. 40% reduction of the initial 95% confidence interval. We show both that lifespan determination in N. furzeri is polygenic, and that candidate gene detection is easily feasible by cross-species analysis. Our work provides first results on the way to identify loci controlling lifespan in N. furzeri and illustrates the potential of this vertebrate species as a genetic model for age research.     

Vanaso is a candidate quantitative trait gene for Drosophila olfactory behavior

Most animals depend on olfaction for survival and procreation. Odor-guided behavior is a quantitative trait, with phenotypic variation due to multiple segregating quantitative trait loci (QTL). Despite its profound biological importance, the genetic basis of naturally occurring variation in olfactory behavior remains unexplored. Here, we mapped a single Drosophila QTL affecting variation in avoidance response to benzaldehyde, using a population of recombinant inbred lines. Deficiency complementation mapping resolved this region into one female- and one male-specific QTL. Subsequent quantitative complementation tests to all available mutations of positional candidate genes showed that the female-specific QTL failed to complement a P-element insertional mutation, l(3)04276. The P-element insertion was in the intron of a novel gene, Vanaso, which contains a putative guanylate binding protein domain, is highly polymorphic, and is expressed in the third antennal segment, the major olfactory organ of Drosophila. No expression was detected in the fly brain, suggesting that Vanaso plays a role in peripheral chemosensory processes rather than in central integration of olfactory information. QTL mapping followed by quantitative complementation tests to deficiencies and mutations is an effective strategy for gene discovery that allows characterization of effects of recessive lethal genes on adult phenotypes and here enabled identification of a candidate gene that contributes to sex-specific quantitative variation in olfactory behavior.     

Accounting for variability in the use of permutation testing to detect quantitative trait loci

Locating quantitative trait loci (QTL), or genomic regions associated with known molecular markers, is of increasing interest in a wide variety of applications ranging from human genetics to agricultural genetics. The hope of locating QTL (or genes) affecting a quantitative trait is that it will lead to characterization and possible manipulations of these genes. However, the complexity of both statistical and genetic issues surrounding the location of these regions calls into question the asymptotic statistical results supplying the distribution of the test statistics employed. Coupled with the power of current-day computing, permutation theory was reintroduced for the purpose of estimating the distribution of any test statistic used to test for the location of QTL. Permutation techniques have offered an attractive alternative to significance measures based on asymptotic theory. The ideas of permutation testing are extended in this application to include confidence intervals for the thresholds and p-values estimated in permutation testing procedures. The confidence intervals developed account for the Monte Carlo error associated with practical applications of permutation testing and lead to an effective method of determining an efficient permutation sample size.     

RiceQTLPro: an integrated database for quantitative trait loci marker mapping in rice plant

The National Agricultural Biotechnology Information Center (NABIC) in South Korea reconstructed a RiceQTLPro database for gene positional analysis and structure prediction of the chromosomes. This database is an integrated web-based system providing information about quantitative trait loci (QTL) markers in rice plant. The RiceQTLPro has the three main features namely, (1) QTL markers list, (2) searching of markers using keyword, and (3) searching of marker position on the rice chromosomes. This updated database provides 112 QTL markers information with 817 polymorphic markers on each of the 12 chromosomes in rice.

Availability

The database is available for free at http://nabic.rda.go.kr/gere/rice/geneticMap/     

Large effect quantitative trait loci for salicinoid phenolic glycosides in Populus: Implications for gene discovery

Genomic studies have been used to identify genes underlying many important plant secondary metabolic pathways. However, genes for salicinoid phenolic glycosides (SPGs)—ecologically important compounds with significant commercial, cultural, and medicinal applications—remain largely undescribed. We used a linkage map derived from a full‐sib population of hybrid cottonwoods (Populus spp.) to search for quantitative trait loci (QTL) for the SPGs salicortin and HCH‐salicortin. SSR markers and primer sequences were used to anchor the map to the V3.0 P. trichocarpa genome. We discovered 21 QTL for the two traits, including a major QTL for HCH‐salicortin (R² = .52) that colocated with a QTL for salicortin on chr12. Using the V3.0 Populus genome sequence, we identified 2,983 annotated genes and 1,480 genes of unknown function within our QTL intervals. We note ten candidate genes of interest, including a BAHD‐type acyltransferase that has been potentially linked to PopulusSPGs. Our results complement other recent studies in Populus with implications for gene discovery and the evolution of defensive chemistry in a model genus. To our knowledge, this is the first study to use a full‐sib mapping population to identify QTL intervals and gene lists associated with SPGs.     

Tsc2, a positional candidate gene underlying a quantitative trait locus for hepatic steatosis

Nonalchoholic fatty liver disease (NAFLD) is the most common cause of liver dysfunction and is associated with metabolic diseases, including obesity, insulin resistance, and type 2 diabetes. We mapped a quantitative trait locus (QTL) for NAFLD to chromosome 17 in a cross between C57BL/6 (B6) and BTBR mouse strains made genetically obese with the Lep(ob/ob) mutation. We identified Tsc2 as a gene underlying the chromosome 17 NAFLD QTL. Tsc2 functions as an inhibitor of mammalian target of rapamycin, which is involved in many physiological processes, including cell growth, proliferation, and metabolism. We found that Tsc2(+/-) mice have increased lipogenic gene expression in the liver in an insulin-dependent manner. The coding single nucleotide polymorphism between the B6 and BTBR strains leads to a change in the ability to inhibit the expression of lipogenic genes and de novo lipogenesis in AML12 cells and to promote the proliferation of Ins1 cells. This difference is due to a different affinity of binding to Tsc1, which affects the stability of Tsc2.     

Maize association population: a high-resolution platform for quantitative trait locus dissection

Crop improvement and the dissection of complex genetic traits require germplasm diversity. Although this necessary phenotypic variability exists in diverse maize, most research is conducted using a small subset of inbred lines. An association population of 302 lines is now available--a valuable research tool that captures a large proportion of the alleles in cultivated maize. Provided that appropriate statistical models correcting for population structure are included, this tool can be used in association analyses to provide high-resolution evaluation of multiple alleles. This study describes the population structure of the 302 lines, and investigates the relationship between population structure and various measures of phenotypic and breeding value. On average, our estimates of population structure account for 9.3% of phenotypic variation, roughly equivalent to a major quantitative trait locus (QTL), with a high of 35%. Inclusion of population structure in association models is critical to meaningful analyses. This new association population has the potential to identify QTL with small effects, which will aid in dissecting complex traits and in planning future projects to exploit the rich diversity present in maize.     

Identification of quantitative trait loci and associated candidate genes for low-temperature tolerance in cold-hardy winter wheat

Low-temperature (LT) tolerance is an important economic trait in winter wheat (Triticum aestivum L.) that determines the plants’ ability to cope with below freezing temperatures. Essential elements of the LT tolerance mechanism are associated with the winter growth habit controlled by the vernalization loci (Vrn-1) on the group 5 chromosomes. To identify genomic regions, which in addition to vrn-1 determine the level of LT tolerance in hexaploid wheat, two doubled haploid (DH) mapping populations were produced using parents with winter growth habit (vrn-A1, vrn-B1, and vrn-D1) but showing different LT tolerance levels. A total of 107 DH lines were analyzed by genetic mapping to produce a consensus map of 2,873 cM. The LT tolerance levels for the Norstar (LT₅₀=−20.7°C) × Winter Manitou (LT₅₀=−14.3°C) mapping population ranged from −12.0 to −22.0°C. Single marker analysis and interval mapping of phenotyped lines revealed a major quantitative trait locus (QTL) on chromosome 5A and a weaker QTL on chromosome 1D. The 5A QTL located 46 cM proximal to the vrn-A1 locus explained 40% of the LT tolerance variance. Two C-repeat Binding Factor (CBF) genes expressed during cold acclimation in Norstar were located at the peak of the 5A QTL.     

Natural genetic variation as a tool for discovery in Caenorhabditis nematodes

Over the last 20 years, studies of Caenorhabditis elegans natural diversity have demonstrated the power of quantitative genetic approaches to reveal the evolutionary, ecological, and genetic factors that shape traits. These studies complement the use of the laboratory-adapted strain N2 and enable additional discoveries not possible using only one genetic background. In this chapter, we describe how to perform quantitative genetic studies in Caenorhabditis, with an emphasis on C. elegans. These approaches use correlations between genotype and phenotype across populations of genetically diverse individuals to discover the genetic causes of phenotypic variation. We present methods that use linkage, near-isogenic lines, association, and bulk-segregant mapping, and we describe the advantages and disadvantages of each approach. The power of C. elegans quantitative genetic mapping is best shown in the ability to connect phenotypic differences to specific genes and variants. We will present methods to narrow genomic regions to candidate genes and then tests to identify the gene or variant involved in a quantitative trait. The same features that make C. elegans a preeminent experimental model animal contribute to its exceptional value as a tool to understand natural phenotypic variation.     

Comparative studies of quantitative trait and neutral marker divergence: a meta-analysis

Comparative studies of quantitative genetic and neutral marker differentiation have provided means for assessing the relative roles of natural selection and random genetic drift in explaining among-population divergence. This information can be useful for our fundamental understanding of population differentiation, as well as for identifying management units in conservation biology. Here, we provide comprehensive review and meta-analysis of the empirical studies that have compared quantitative genetic (Q(ST)) and neutral marker (F(ST)) differentiation among natural populations. Our analyses confirm the conclusion from previous reviews - based on ca. 100% more data - that the Q(ST) values are on average higher than F(ST) values [mean difference 0.12 (SD 0.27)] suggesting a predominant role for natural selection as a cause of differentiation in quantitative traits. However, although the influence of trait (life history, morphological and behavioural) and marker type (e.g. microsatellites and allozymes) on the variance of the difference between Q(ST) and F(ST) is small, there is much heterogeneity in the data attributable to variation between specific studies and traits. The latter is understandable as there is no reason to expect that natural selection would be acting in similar fashion on all populations and traits (except for fitness itself). We also found evidence to suggest that Q(ST) and F(ST) values across studies are positively correlated, but the significance of this finding remains unclear. We discuss these results in the context of utility of the Q(ST)-F(ST) comparisons as a tool for inferring natural selection, as well as associated methodological and interpretational problems involved with individual and meta-analytic studies.     

Environment-dependent survival of Drosophila melanogaster: a quantitative genetic analysis

Summary Survival under starvation conditions was investigated in relationship to survival when food was present because these traits could be linked by evolutionary history. Recombinant inbred lines derived from natural populations of Drosophila melanogaster were used to test genetic correlations and architecture of these survival traits. Sexes were genetically correlated within traits and there was significant correlation between survival traits. A number of quantitative trait loci (QTLs) were present for starvation survival and/or survival on food. In general, the QTL effects were consistent for sexes and environments. QTL effects were found on each major chromosome, but the major effects were largely localized on the second chromosome. Importantly, the 'four-allele' progenitor of the recombinant inbred lines used in the present study allowed the sign and magnitude of effects to be assigned to linkage groups. One such linkage group on the second chromosome conferred starvation resistance and longevity, supporting the hypothesis of an association between starvation resistance and lifespan.     

Systems genetics approach reveals candidate genes for parasite resistance from quantitative trait loci studies in agricultural species

A systems genetics approach combining pathway analysis of quantitative trait loci (QTL) and gene expression information has provided strong evidence for common pathways associated with genetic resistance to internal parasites. Gene data, collected from published QTL regions in sheep, cattle, mice, rats and humans, and microarray data from sheep, were converted to human Entrez Gene IDs and compared to the KEGG pathway database. Selection of pathways from QTL data was based on a selection index that ensured that the selected pathways were in all species and the majority of the projects overall and within species. Pathways with either up- and down-regulated genes, primarily up-regulated genes or primarily down-regulated genes, were selected from gene expression data. After comparing the data sets independently, the pathways from each data set were compared and the common set of pathways and genes was identified. Comparisons within data sets identified 21 pathways from QTL data and 66 pathways from gene expression data. Both selected sets were enriched with pathways involved in immune functions, disease and cell responses to signals. The analysis identified 14 pathways that were common between QTL and gene expression data, and four directly associated with IFNγ or MHCII, with 31 common genes, including three MHCII genes. In conclusion, a systems genetics approach combining data from multiple QTL and gene expression projects led to the discovery of common pathways associated with genetic resistance to internal parasites. This systems genetics approach may prove significant for the discovery of candidate genes for many other multifactorial, economically important traits.     

Identification of quantitative trait loci influencing foliar concentrations of terpenes and formylated phloroglucinol compounds in Eucalyptus nitens

Leaves of eucalypt species contain a variety of plant secondary metabolites, including terpenoids and formylated phloroglucinol compounds (FPCs). Both terpene and FPC concentrations are quantitative traits that can show large variation within a population and have been shown to be heritable. The molecular genetic basis of this variation is currently unknown. Progeny from a field trial of a three-generation mapping pedigree of Eucalyptus nitens were assayed for terpenes and FPCs. Quantitative trait loci (QTL) analyses were conducted using a map constructed from 296 markers to locate regions of the genome influencing foliar concentrations of these plant secondary compounds. A large number of significant QTL for 14 traits were located across nine linkage groups, with significant clustering of QTL on linkage groups 7, 8 and 9. As expected, QTL for biosynthetically related compounds commonly colocated, but QTL for unrelated monterpenes and FPCs also mapped closely together. Colocation of these QTL with mapped candidate genes from the various biosynthetic pathways, and subsequent use of these genes in association mapping, will assist in determining the causes of variation in plant secondary metabolites in eucalypts.     

Model selection for quantitative trait loci mapping in a full-sib family

Statistical methods for mapping quantitative trait loci (QTLs) in full-sib forest trees, in which the number of alleles and linkage phase can vary from locus to locus, are still not well established. Previous studies assumed that the QTL segregation pattern was fixed throughout the genome in a full-sib family, despite the fact that this pattern can vary among regions of the genome. In this paper, we propose a method for selecting the appropriate model for QTL mapping based on the segregation of different types of markers and QTLs in a full-sib family. The QTL segregation patterns were classified into three types: test cross (1:1 segregation), F₂ cross (1:2:1 segregation) and full cross (1:1:1:1 segregation). Akaike’s information criterion (AIC), the Bayesian information criterion (BIC) and the Laplace-empirical criterion (LEC) were used to select the most likely QTL segregation pattern. Simulations were used to evaluate the power of these criteria and the precision of parameter estimates. A Windows-based software was developed to run the selected QTL mapping method. A real example is presented to illustrate QTL mapping in forest trees based on an integrated linkage map with various segregation markers. The implications of this method for accurate QTL mapping in outbred species are discussed.     

Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici

We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High‐throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site‐associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large‐ and small‐effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large‐effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.     

Identification of X-linked quantitative trait loci affecting cold tolerance in Drosophila melanogaster and fine mapping by selective sweep analysis

Drosophila melanogaster is a cosmopolitan species that colonizes a great variety of environments. One trait that shows abundant evidence for naturally segregating genetic variance in different populations of D. melanogaster is cold tolerance. Previous work has found quantitative trait loci (QTL) exclusively on the second and the third chromosomes. To gain insight into the genetic architecture of cold tolerance on the X chromosome and to compare the results with our analyses of selective sweeps, a mapping population was derived from a cross between substitution lines that solely differed in the origin of their X chromosome: one originates from a European inbred line and the other one from an African inbred line. We found a total of six QTL for cold tolerance factors on the X chromosome of D. melanogaster. Although the composite interval mapping revealed slightly different QTL profiles between sexes, a coherent model suggests that most QTL overlapped between sexes, and each explained around 5–14% of the genetic variance (which may be slightly overestimated). The allelic effects were largely additive, but we also detected two significant interactions. Taken together, this provides evidence for multiple QTL that are spread along the entire X chromosome and whose effects range from low to intermediate. One detected transgressive QTL influences cold tolerance in different ways for the two sexes. While females benefit from the European allele increasing their cold tolerance, males tend to do better with the African allele. Finally, using selective sweep mapping, the candidate gene CG16700 for cold tolerance colocalizing with a QTL was identified.