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A fast algorithm for functional mapping of complex traits.

By integrating the underlying developmental mechanisms for the phenotypic formation of traits into a mapping framework, functional mapping has emerged as an important statistical approach for mapping complex traits. In this note, we explore the feasibility of using the simplex algorithm as an alternative to solve the mixture-based likelihood for functional mapping of complex traits. The results from the simplex algorithm are consistent with those from the traditional EM algorithm, but the simplex algorithm has considerably reduced computational times. Moreover, because of its nonderivative nature and easy implementation with current software, the simplex algorithm enjoys an advantage over the EM algorithm in the dynamic modeling and analysis of complex traits.

Algorithms↗

Mapping quantitative trait loci affecting variation in Drosophila triacylglycerol storage.

OBJECTIVE: Recent genetic studies indicate that Drosophila melanogaster could be a powerful model to identify genes involved in mammalian adipocyte differentiation and fat storage. The objective of our study was to identify quantitative trait loci (QTLs) that contribute to variation in triacylglycerol (TAG) storage in two D. melanogaster laboratory strains. RESEARCH METHODS AND PROCEDURES: We used two genetic mapping procedures to identify loci with main and epistatic effects on TAG storage. First, using 68 recombinant inbred lines derived from the unrelated Oregon R and Russian 2b strains, we mapped the location of QTLs affecting TAG storage using both composite interval mapping and Bayesian epistatic methods. Second, we used the quantitative deficiency mapping procedure to identify candidate genes affecting this trait within one of the QTLs identified on the second chromosome. For both mapping experiments, flies were cultured in standard conditions. TAG content of 4- to 5-day-old flies, adjusted for live body mass and total proteins, was used as the phenotypic measure. RESULTS: Multiple QTLs associated with variation in TAG storage were identified by the genome-wide recombination mapping method, and some of them were sex-specific. The QTLs had main effects, but a male-specific epistatic interaction between two QTLs was also found. Finally, two closely linked QTLs were detected by deficiency mapping at 57E1-57E3 and 57E4-57F1 on chromosome 2, the first of which causes female-specific variation in TAG between the Oregon R and 2b strains. DISCUSSION: Our results suggest that variation in TAG storage in D. melanogaster is controlled by different genetic mechanisms and different sets of QTLs in male and female flies.

Adipogenesis↗

Simultaneous mining of linkage and linkage disequilibrium to fine map quantitative trait loci in outbred half-sib pedigrees: revisiting the location of a quantitative trait locus with major effect on milk production on bovine chromosome 14.

A maximum-likelihood QTL mapping method that simultaneously exploits linkage and linkage disequilibrium and that is applicable in outbred half-sib pedigrees is described. The method is applied to fine map a QTL with major effect on milk fat content in a 3-cM marker interval on proximal BTA14. This proximal location is confirmed by applying a haplotype-based association method referred to as recombinant ancestral haplotype analysis. The origin of the discrepancy between the QTL position derived in this work and that of a previous analysis is examined and shown to be due to the existence of distinct marker haplotypes associated with QTL alleles having large substitution effects.

Animals↗

In silico quantitative trait locus map for atherosclerosis susceptibility in apolipoprotein E-deficient mice.

OBJECTIVE: Atherosclerosis susceptibility is a genetic trait that varies between mouse strains. The goal of this study was to use a public mouse single nucleotide polymorphism (SNP) database to define the genetic loci that are associated with this trait, without the need to perform strain intercrosses that are normally required to obtain these loci. METHODS AND RESULTS: Apolipoprotein E (apoE)-deficient mice on 6 inbred genetic backgrounds were compared for atherosclerosis lesion size in the aortic root in 2 independent studies. After normalization to the C57BL/6 strain that was used in both studies, lesion areas were found in the following rank order: DBA/2J>C57BL/6>129/SV-ter>AKR/J approximately BALB/cByJ approximately C3H/HeJ. The log lesion difference in phenotypes between each of the 15 heterologous strain pairs was determined. A mouse SNP database was then used to calculate the genetic differences between the 15 strain pairs in partially overlapping 30-cM bins across the mouse genome. Correlation analyses were preformed to analyze the genetic and phenotypic differences among the strain pairs for each genetic region. The genetic regions with the highest correlations define the in silico quantitative trait loci (QTL) associated with the atherosclerosis phenotype. Five in silico atherosclerosis QTL were identified on chromosomes 1, 10, 14, 15, and 18. The loci on chromosomes 1, 10, 14, and 18 overlap with suggestive atherosclerosis QTL identified through analyses of an F(2) cohort derived from apoE-deficient mice on the C57BL/6 and FVB/N strains. CONCLUSIONS: The 5 identified in silico QTL are candidates for further study to confirm the presence and identity of atherosclerosis susceptibility genes within these loci.

Animals↗

Mouse inbred strain sequence information and yin-yang crosses for quantitative trait locus fine mapping.

The shared ancestry of mouse inbred strains, together with the availability of sequence and phenotype information, is a resource that can be used to map quantitative trait loci (QTL). The difficulty in using only sequence information lies in the fact that in most instances the allelic state of the QTL cannot be unambiguously determined in a given strain. To overcome this difficulty, the performance of multiple crosses between various inbred strains has been proposed. Here we suggest and evaluate a general approach, which consists of crossing the two strains used initially to map the QTL and any new strain. We have termed these crosses "yin-yang," because they are complementary in nature as shown by the fact that the QTL will necessarily segregate in only one of the crosses. We used the publicly available SNP database of chromosome 16 to evaluate the mapping resolution achievable through this approach. Although on average the improvement of mapping resolution using only four inbred strains was relatively small (i.e., reduction of the QTL-containing interval by half at most), we found a great degree of variability among different regions of chromosome 16 with regard to mapping resolution. This suggests that with a large number of strains in hand, selecting a small number of strains may provide a significant contribution to the fine mapping of QTL.

Alleles↗

Mapping quantitative trait loci for principal components of bone measurements and osteochondrosis scores in a wild boar x large white intercross.

Data on osteochondrosis and femur dimensions from 195 F2 pigs from a wild boar x Large White intercross were analysed with the aim of detecting quantitative trait loci (QTLs) for normal and disturbed bone formation. The information from numerous recorded traits was summarized by principal component analysis and analysed by least-squares interval mapping. An increase in the proportion of wild boar alleles across the genome increased length versus width of femur and reduced the prevalence of osteochondrosis. The presence of QTLs with an impact on femur dimensions was indicated on chromosomes 2, 4, 16 and 17 and on osteochondrosis on chromosomes 5, 13 and 15. A substantial effect of the chromosome 5 QTL calls for further studies within commercial populations to evaluate whether marker-assisted selection could be used to reduce the prevalence of osteochondrosis.

Alleles↗

Using advanced intercross lines for high-resolution mapping of HDL cholesterol quantitative trait loci.

Mapping quantitative trait loci (QTLs) with high resolution facilitates identification and positional cloning of the underlying genes. The novel approach of advanced intercross lines (AILs) generates many more recombination events and thus can potentially narrow QTLs significantly more than do conventional backcrosses and F2 intercrosses. In this study, we carried out QTL analyses in (C57BL/6J x NZB/BlNJ) x C57BL/6J backcross progeny fed either chow or an atherogenic diet to detect QTLs that regulate high-density lipoprotein cholesterol (HDL)concentrations, and in (C57BL/6J x NZB/BlNJ) F11 AIL progeny to confirm and narrow those QTLs. QTLs for HDL concentrations were found on chromosomes 1, 5, and 16. AIL not only narrowed the QTLs significantly more than did a conventional backcross but also resolved a chromosome 5 QTL identified in the backcross into two QTLs, the peaks of both being outside the backcross QTL region. We tested 27 candidate genes and found significant mRNA expression differences for 12 (Nr1i3, Apoa2, Sap, Tgfb2, Fgfbp1, Prom, Ppargc1, Tcf1, Ncor2, Srb1, App, and Ifnar). Some of these underlay the same QTL, indicating that expression differences are common and not sufficient to identify QTL genes. All the major HDL QTLs in our study had homologous counterparts in humans, implying that their underlying genes regulate HDL in humans.

Animals↗

Mapping quantitative trait loci for a common bean (Phaseolus vulgaris L.) ideotype.

Breeding a model plant that encompasses individual traits thought to enhance yield potential, known as ideotype breeding, has traditionally focused on phenotypic selection of plants with desirable morphological traits. Broadening this breeding method to the molecular level through the use of molecular markers would avoid the environmental interactions associated with phenotypic selection. A population of 110 F5 recombinant inbred lines (RILs), derived from the cross between WO3391 and 'OAC Speedvale', was used to develop a genetic linkage map consisting of 105 random amplified polymorphic DNA (RAPD), simple sequence repeat (SSR), and sequence-tagged site (STS) markers. The map has a total length of 641 cM distributed across 8 linkage groups (LGs). Five of them were aligned on the core linkage map of bean. Twenty-one quantitative trait loci (QTLs) were identified over three environments for eight agronomic and architectural traits previously defined for a bean (Phaseolus vulgaris L.) ideotype. The QTLs were mapped to seven LGs with several regions containing QTLs for multiple traits. At least one QTL was located for each trait and a maximum of four were associated with lodging. Total explained phenotypic variance ranged from 10.6% for hypocotyl diameter to 45.4% for maturity. Some of the QTLs identified will be useful for early generation selection of tall, upright, high-yielding lines in a breeding program.

Analysis of Variance↗

Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree.

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Analysis of Variance↗

High-resolution quantitative trait locus mapping for body weight in mice by recombinant progeny testing.

A major obstacle to the positional cloning of quantitative trait loci (QTLs) lies in resolving genetic factors whose allelic effects are blurred by environmental and background genetic variation. We investigate a fine-mapping approach that combines the use of an interval-specific congenic strain with progeny testing of recombinants for markers flanking a QTL. We apply the approach to map a murine QTL with an approximately 20% effect on growth rate by progeny testing 39 recombinants in a 12 cM region of the X chromosome. We use a likelihood analysis in an attempt to maximize the information on QTL map location and effect. The major X-linked effect is mapped to an approximately 2 cM region flanked by markers about 5 cM apart, outside which LOD support for the QTL drops extremely steeply by about 80. Nearly unambiguous assignment of the QTL genotypic state is obtained for each recombinant. The resolution of individual recombinants in the region is therefore sufficiently high to facilitate the positional cloning of the locus, although progress has been hampered because the genomic region containing the QTL shows an exceptionally low level of polymorphism in comparison with recent studies.

Alleles↗

Quantitative trait locus mapping of genes that regulate HDL cholesterol in SM/J and NZB/B1NJ inbred mice.

To investigate the quantitative trait loci (QTL) regulating plasma cholesterol, the female progeny of an (SMxNZB/ B1NJ)xNZB/B1NJ backcross were fed an atherogenic diet. After 18 wk, plasma total cholesterol and high-density lipoprotein cholesterol (HDL-C) was measured. HDL-C concentrations were greater in NZB than in SM mice. For standard chow-fed mice, QTL were found near D5Mit370 and D18Mit34. For mice fed an atherogenic diet, a QTL was found near D5Mit239. The QTL for chow-fed and atherogenic-fed mice on chromosome 5 seem to be two different loci. We used a multitrait analysis to rule out pleiotropy in favor of a two-QTL hypothesis. Furthermore, the HDL-C in these strains was induced by the high-fat diet. For inducible HDL-C, one significant locus was found near D15Mit39. The gene for an HDL receptor, Srb1, maps close to the HDL-C QTL at D5Mit370, but the concentrations of Srb1 mRNA and SR-B1 protein and the gene sequence of NZB/B1NJ and SM/J did not support Srb1 as a candidate gene. With these QTL, we have identified chromosomal regions that affect lipoprotein profiles in these strains.

Animals↗

Some properties of a variance components model for fine-mapping quantitative trait loci.

Identifying etiological variants for multifactorial traits by allelic association holds promise when many markers are available in close proximity. However, evidence for or against association at any particular marker does not provide any direct information about the influence of causal variants or the frequency of the etiologic allele(s). Recently, a variance components model of linkage and association was developed for quantitative traits which is sufficiently flexible to provide some insights into these issues. We show that this combined linkage/association model provides an estimate of the additive genetic variance of a trait that is attributable to disequilibrium between the marker and QTL. We use this estimate to construct approximate boundaries of the minimum level of disequilibrium between an observed marker and unobserved QTL and to delimit the permissible range of allele frequencies at the QTL based on available data at nearby markers. This information may facilitate fine-mapping studies of complex traits that aim to localize QTLs by assessment of association with many markers in a candidate region of interest.

Alleles↗

Quantitative trait locus mapping using human pedigrees.

In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.

Bias↗

Empirical nonparametric bootstrap strategies in quantitative trait loci mapping: conditioning on the genetic model.

Several nonparametric bootstrap methods are tested to obtain better confidence intervals for the quantitative trait loci (QTL) positions, i.e., with minimal width and unbiased coverage probability. Two selective resampling schemes are proposed as a means of conditioning the bootstrap on the number of genetic factors in our model inferred from the original data. The selection is based on criteria related to the estimated number of genetic factors, and only the retained bootstrapped samples will contribute a value to the empirically estimated distribution of the QTL position estimate. These schemes are compared with a nonselective scheme across a range of simple configurations of one QTL on a one-chromosome genome. In particular, the effect of the chromosome length and the relative position of the QTL are examined for a given experimental power, which determines the confidence interval size. With the test protocol used, it appears that the selective resampling schemes are either unbiased or least biased when the QTL is situated near the middle of the chromosome. When the QTL is closer to one end, the likelihood curve of its position along the chromosome becomes truncated, and the nonselective scheme then performs better inasmuch as the percentage of estimated confidence intervals that actually contain the real QTL's position is closer to expectation. The nonselective method, however, produces larger confidence intervals. Hence, we advocate use of the selective methods, regardless of the QTL position along the chromosome (to reduce confidence interval sizes), but we leave the problem open as to how the method should be altered to take into account the bias of the original estimate of the QTL's position.

Chromosome Mapping↗

Mapping quantitative trait loci mediating sensitivity to etomidate.

Long- and Short-Sleep (LS and SS) mice were selectively bred for differences in ethanol-induced loss of the righting reflex (LORR) and have been found to differ in LORR induced by various anesthetic agents. We used a two-stage mapping strategy to identify quantitative trait loci (QTLs) affecting duration of LORR caused by the general anesthetic etomidate and brain levels of etomidate (BEL) following regain of the righting reflex. Analysis of recombinant-inbred strains derived from a cross between LS and SS mice (LSXSS) yielded a heritability estimate of 0.23 for etomidate-induced LORR and identified one marker that showed suggestive linkage for a QTL, on mouse Chromosome (chr) 12. Mapping in an F(2) population derived from a cross between inbred LS and SS (ILS and ISS) revealed a significant QTL for etomidate-induced LORR on Chr 12, and two significant QTLs mediating BEL on Chrs 6 and 12. Several QTLs showing suggestive linkage for etomidate-induced LORR and BEL were also identified in the F(2) population. Brain levels of etomidate in the RI and F(2) mice suggested that differences in LORR were due to differential central nervous system sensitivity, rather than differential etomidate metabolism. Interestingly, the region on Chr 7 has also been identified as a region influencing ethanol-induced LORR, suggesting the possibility of a common genetic mechanism mediating etomidate and ethanol sensitivity. These QTL regions need to be further narrowed before the testing of candidate genes is feasible.

Analysis of Variance↗

Mapping quantitative trait loci for milk production traits on ovine chromosome 6.

Spanish Churra sheep were studied in a daughter design for the presence on chromosome 6 of quantitative trait loci (QTL) influencing milk production traits. Eight half-sib families were genotyped for 11 microsatellites and marker-QTL effects analysed using yield deviations (YD) as quantitative measurements for the following traits: milk yield, protein yield, and protein percentage. QTL analysis was performed by interval mapping based on multimarker regression principles. Significance thresholds were estimated through a permutation test followed by a correction for multiple testing. The results suggest a region on ovine chromosome 6, close to the casein cluster, with an influence on milk traits and particularly on protein percentage. These results, the first ones reported for QTL affecting milk traits in sheep, are discussed in relation to data available for cattle, a closely related species.

Animals↗

General formulas for obtaining the MLEs and the asymptotic variance-covariance matrix in mapping quantitative trait loci when using the EM algorithm.

We present in this paper general formulas for deriving the maximum likelihood estimates and the asymptotic variance-covariance matrix of the positions and effects of quantitative trait loci (QTLs) in a finite normal mixture model when the EM algorithm is used for mapping QTLs. The general formulas are based on two matrices D and Q, where D is the genetic design matrix, characterizing the genetic effects of the QTLs, and Q is the conditional probability matrix of QTL genotypes given flanking marker genotypes, containing the information on QTL positions. With the general formulas, it is relatively easy to extend QTL mapping analysis to using multiple marker intervals simultaneously for mapping multiple QTLs, for analyzing QTL epistasis, and for estimating the heritability of quantitative traits. Simulations were performed to evaluate the performance of the estimates of the asymptotic variances of QTL positions and effects.

Algorithms↗

Quantitative trait loci mapping in F(2) crosses between outbred lines.

We develop a mixed-model approach for QTL analysis in crosses between outbred lines that allows for QTL segregation within lines as well as for differences in mean QTL effects between lines. We also propose a method called "segment mapping" that is based in partitioning the genome in a series of segments. The expected change in mean according to percentage of breed origin, together with the genetic variance associated with each segment, is estimated using maximum likelihood. The method also allows the estimation of differences in additive variances between the parental lines. Completely fixed random and mixed models together with segment mapping are compared via simulation. The segment mapping and mixed-model behaviors are similar to those of classical methods, either the fixed or random models, under simple genetic models (a single QTL with alternative alleles fixed in each line), whereas they provide less biased estimates and have higher power than fixed or random models in more complex situations, i.e., when the QTL are segregating within the parental lines. The segment mapping approach is particularly useful to determining which chromosome regions are likely to contain QTL when these are linked.

Chromosome Mapping↗