Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.     

Consistency between marker- and genealogy-based heritability estimates in an experimental stand of Prosopis alba (Leguminosae)

Prosopis represents a valuable forest resource in arid and semiarid regions. Management of promising species requires information about genetic parameters, mainly the heritability (h(2)) of quantitative profitable traits. This parameter is traditionally estimated from progeny tests or half-sib analysis conducted in experimental stands. Such an approach estimates h(2) from the ratio of between-family/total phenotypic variance. These analyses are difficult to apply to natural populations of species with a long life cycle, overlapping generations, and a mixed mating system, without genealogical information. A promising alternative is the use of molecular marker information to infer relatedness between individuals and to estimate h(2) from the regression of phenotypic similarity on inferred relatedness. In the current study we compared h(2) of 13 quantitative traits estimated by these two methods in an experimental stand of P. alba, where genealogical information was available. We inferred pairwise relatedness by Ritland's method using six microsatellite loci. Relatedness and heritability estimates from molecular information were highly correlated to the values obtained from genealogical data. Although Ritland's method yields lower h(2) estimates and tends to overestimate genetic correlations between traits, this approach is useful to predict the expected relative gain of different quantitative traits under selection without genealogical information.     

Primate population studies at Polonnaruwa. II. Heritability of body measurements in a natural population of toque macaques (Macaca sinica)

The heritability of quantitative traits, or the proportion of phenotypic variation due to additive genetic or heritable effects, plays an important role in determining the evolutionary response to natural selection. Most quantitative genetic studies are performed in the laboratory, due to difficulty in obtaining genealogical data in natural populations. Genealogies are known, however, from a unique 20-year study of toque macaques (Macaca sinica) at Polonnaruwa, Sri Lanka. Heritability in this natural population was, therefore, estimated. Twenty-seven body measurements representing the lengths and widths of the head, trunk, extremities, and tail were collected from 270 individuals. The sample included 172 offspring-mother pairs from 39 different matrilineal families. Heritabilities were estimated using traditional mother-offspring regression and maximum likelihood methods which utilize all genealogical relationships in the sample. On the common assumption that environmental (including social) factors affecting morphology were randomly distributed across families, all but two of the traits (25 of 27) were significantly heritable, with an average heritability of 0.51 for the mother-offspring analysis and 0.56 for the maximum likelihood analysis. Heritability estimates obtained from the two analyses were very similar. We conclude that the Polonnaruwa macaques exhibit a comparatively moderate to high level of heritability for body form. © 1992 Wiley-Liss, Inc.     

Mathematical consequences of the genealogical species concept

A genealogical species is defined as a basal group of organisms whose members are all more closely related to each other than they are to any organisms outside the group ("exclusivity"), and which contains no exclusive group within it. In practice, a pair of species is so defined when phylogenies of alleles from a sample of loci shows them to be reciprocally monophyletic at all or some specified fraction of the loci. We investigate the length of time it takes to attain this status when an ancestral population divides into two descendant populations of equal size with no gene exchange, and when genetic drift and mutation are the only evolutionary forces operating. The number of loci used has a substantial effect on the probability of observing reciprocal monophyly at different times after population separation, with very long times needed to observe complete reciprocal monophyly for a large number of loci. In contrast, the number of alleles sampled per locus has a relatively small effect on the probability of reciprocal monophyly. Because a single mitochondrial or chloroplast locus becomes reciprocally monophyletic much faster than does a single nuclear locus, it is not advisable to use mitochondrial and chloroplast DNA to recognize genealogical species for long periods after population divergence. Using a weaker criterion of assigning genealogical species status when more than 50% of sampled nuclear loci show reciprocal monophyly, genealogical species status depends much less on the number of sampled loci, and is attained at roughly 4-7 N generations after populations are isolated, where N is the historically effective population size of each descendant. If genealogical species status is defined as more than 95% of sampled nuclear loci showing reciprocal monophyly, this status is attained after roughly 9-12 N generations.     

Comparison of population genetic structures of common wild rice (Oryza rufipogon Griff.), as revealed by analyses of quantitative traits, allozymes, and RFLPs

We investigated genetic diversity among and within natural populations of Asian common wild rice, Oryza rufipogon, from three different classes of data: quantitative traits, allozymes, and restriction fragment length polymorphisms (RFLPs). The seven populations examined showed polymorphism to varying degrees. The amount of intrapopulation variability appeared to be influenced not only by breeding system but also by the evolutionary history of each population. Interpopulation differentiation was clear, but different classes of data elucidated different patterns. Quantitative traits revealed ecotype differentiation into perennial and annual types of population, whereas allozyme and RFLP analyses revealed geographical differentiation among populations. These results suggest that the diversity patterns shown by quantitative trait analysis reflect mainly the occurrence of adaptive differentiation in response to habitat conditions and that those shown by allozyme and RFLP analyses reflect mainly the effect of isolation by distance. Population differentiation parameters (F(ST)) were highly variable among loci in allozymes as well as in RFLPs.     

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.     

Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.     

Families with familial combined hyperlipidemia and families enriched for coronary artery disease share genetic determinants for the atherogenic lipoprotein phenotype.

Small, dense LDL particles consistently have been associated with hypertriglyceridemia, premature coronary artery disease (CAD), and familial combined hyperlipidemia (FCH). Previously, we have observed linkage of LDL particle size with four separate candidate-gene loci in a study of families enriched for CAD. These loci contain the genes for manganese superoxide dismutase (MnSOD), on chromosome 6q; for apolipoprotein AI-CIII-AIV, on chromosome 11q; for cholesteryl ester transfer protein (CETP) and lecithin:cholesterol acyltransferase (LCAT), on chromosome 16q; and for the LDL receptor (LDLR), on chromosome 19p. We have now tested whether these loci also contribute to LDL particle size in families ascertained for FCH. The members of 18 families (481 individuals) were typed for genetic markers at the four loci, and linkage to LDL particle size was assessed by nonparametric sib-pair linkage analysis. The presence of small, dense LDL (pattern B) was much more frequent in the FCH probands (39%) than in the spouse controls (4%). Evidence for linkage was observed at the MnSOD (P=.02), CETP/LCAT (P=.03), and apolipoprotein AI-CIII-AIV loci (P=.005) but not at the LDLR locus. We conclude that there is a genetically based association between FCH and small, dense LDL and that the genetic determinants for LDL particle size are shared, at least in part, among FCH families and the more general population at risk for CAD.     

Characterization of Expression Quantitative Trait Loci in Pedigrees from Colombia and Costa Rica Ascertained for Bipolar Disorder

The observation that variants regulating gene expression (expression quantitative trait loci, eQTL) are at a high frequency among SNPs associated with complex traits has made the genome-wide characterization of gene expression an important tool in genetic mapping studies of such traits. As part of a study to identify genetic loci contributing to bipolar disorder and other quantitative traits in members of 26 pedigrees from Costa Rica and Colombia, we measured gene expression in lymphoblastoid cell lines derived from 786 pedigree members. The study design enabled us to comprehensively reconstruct the genetic regulatory network in these families, provide estimates of heritability, identify eQTL, evaluate missing heritability for the eQTL, and quantify the number of different alleles contributing to any given locus. In the eQTL analysis, we utilize a recently proposed hierarchical multiple testing strategy which controls error rates regarding the discovery of functional variants. Our results elucidate the heritability and regulation of gene expression in this unique Latin American study population and identify a set of regulatory SNPs which may be relevant in future investigations of complex disease in this population. Since our subjects belong to extended families, we are able to compare traditional kinship-based estimates with those from more recent methods that depend only on genotype information.     

Use of the robust sib-pair method to screen for single-locus, multiple-locus, and pleiotropic effects: application to traits related to hypertension.

Robust sib-pair linkage analysis can be used as a screening tool in the search for the potential involvement of single-loci, multiple-loci, and pleiotropic effects of single loci underlying phenotypic variation. Four large families were each ascertained through one adult white male with essential hypertension. The robust sib-pair method was used to screen these families for evidence of linkage between 39 quantitative traits related to hypertension and 25 genetic marker loci. All traits were analyzed on the untransformed, square-root and log-transformed scales. Among other findings, there is a suggestion of linkage between the 6-phosphogluconate dehydrogenase locus on chromosome 1p36 and mean fifth-phase diastolic blood pressure. There may also be linkage between the following markers and traits: the adenylate kinase-1 marker and/or the Lewis blood group marker and the traits height, weight, and biacromial breadth; the glyoxylase I marker and the traits upper-arm circumference and suprailiac skinfold thickness; the ABO blood group and adenylate kinase-1 markers on chromosome 9q34 and the third component of complement marker on chromosome 19p13 and dopamine-beta-hydroxylase; and the P1 blood group and the traits weight and 1-h postload serum glucose level.     

Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F₂ population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.     

Native American Admixture in the Quebec Founder Population

For years, studies of founder populations and genetic isolates represented the mainstream of genetic mapping in the effort to target genetic defects causing Mendelian disorders. The genetic homogeneity of such populations as well as relatively homogeneous environmental exposures were also seen as primary advantages in studies of genetic susceptibility loci that underlie complex diseases. European colonization of the St-Lawrence Valley by a small number of settlers, mainly from France, resulted in a founder effect reflected by the appearance of a number of population-specific disease-causing mutations in Quebec. The purported genetic homogeneity of this population was recently challenged by genealogical and genetic analyses. We studied one of the contributing factors to genetic heterogeneity, early Native American admixture that was never investigated in this population before. Consistent admixture estimates, in the order of one per cent, were obtained from genome-wide autosomal data using the ADMIXTURE and HAPMIX software, as well as with the fastIBD software evaluating the degree of the identity-by-descent between Quebec individuals and Native American populations. These genomic results correlated well with the genealogical estimates. Correlations are imperfect most likely because of incomplete records of Native founders’ origin in genealogical data. Although the overall degree of admixture is modest, it contributed to the enrichment of the population diversity and to its demographic stratification. Because admixture greatly varies among regions of Quebec and among individuals, it could have significantly affected the homogeneity of the population, which is of importance in mapping studies, especially when rare genetic susceptibility variants are in play.     

Genetic Models in Applied Physiology. HXB/BXH rat recombinant inbred strain platform: a newly enhanced tool for cardiovascular, behavioral, and developmental genetics and genomics.

This review deals with the largest set of rat recombinant inbred (RI) strains and summarizes past and recent accomplishments with this platform for genetic mapping and analyses of divergent and complex traits. This strain, derived by crossing the spontaneously hypertensive rat, SHR/Ola, with a Brown Norway congenic, BN-Lx, carrying polydactyly-luxate syndrome, is referred to as HXB/BXH. The RI strain set has been used for linkage and association studies to identify quantitative trait loci for numerous cardiovascular phenotypes, including arterial pressure, stress-elicited heart rate, and pressor response, and metabolic traits, including insulin resistance, dyslipidemia and glucose handling, and left ventricular hypertrophy. The strain's utility has been enhanced with development of a new framework marker-based map and strain distribution patterns of polymorphic markers. Quantitative trait loci for behavioral traits mapped include loci for startle motor response and habituation, anxiety and locomotion traits associated with elevated plus maze, and conditioned taste aversion. The polydactyly-luxate syndrome Lx mutation has allowed the study of alleles important to limb development and malformation phenotypes as well as teratogens. The RI strains have guided development of numerous congenic strains to test locus assignments and to study the effect of genetic background. Although these strains were originally developed to aid in studies of rat genetic hypertension and morphogenetic abnormalities, this rodent platform has been shown to be equally powerful for a wide spectrum of traits and endophenotypes. These strains provide a ready and available vehicle for many physiological and pharmacological studies.     

Mapping trait loci by use of inferred ancestral recombination graphs

Large-scale association studies are being undertaken with the hope of uncovering the genetic determinants of complex disease. We describe a computationally efficient method for inferring genealogies from population genotype data and show how these genealogies can be used to fine map disease loci and interpret association signals. These genealogies take the form of the ancestral recombination graph (ARG). The ARG defines a genealogical tree for each locus, and, as one moves along the chromosome, the topologies of consecutive trees shift according to the impact of historical recombination events. There are two stages to our analysis. First, we infer plausible ARGs, using a heuristic algorithm, which can handle unphased and missing data and is fast enough to be applied to large-scale studies. Second, we test the genealogical tree at each locus for a clustering of the disease cases beneath a branch, suggesting that a causative mutation occurred on that branch. Since the true ARG is unknown, we average this analysis over an ensemble of inferred ARGs. We have characterized the performance of our method across a wide range of simulated disease models. Compared with simpler tests, our method gives increased accuracy in positioning untyped causative loci and can also be used to estimate the frequencies of untyped causative alleles. We have applied our method to Ueda et al.'s association study of CTLA4 and Graves disease, showing how it can be used to dissect the association signal, giving potentially interesting results of allelic heterogeneity and interaction. Similar approaches analyzing an ensemble of ARGs inferred using our method may be applicable to many other problems of inference from population genotype data.     

Genomewide scan in families with schizophrenia from the founder population of Afrikaners reveals evidence for linkage and uniparental disomy on chromosome 1

We report on our initial genetic linkage studies of schizophrenia in the genetically isolated population of the Afrikaners from South Africa. A 10-cM genomewide scan was performed on 143 small families, 34 of which were informative for linkage. Using both nonparametric and parametric linkage analyses, we obtained evidence for a small number of disease loci on chromosomes 1, 9, and 13. These results suggest that few genes of substantial effect exist for schizophrenia in the Afrikaner population, consistent with our previous genealogical tracing studies. The locus on chromosome 1 reached genomewide significance levels (nonparametric LOD score of 3.30 at marker D1S1612, corresponding to an empirical P value of.012) and represents a novel susceptibility locus for schizophrenia. In addition to providing evidence for linkage for chromosome 1, we also identified a proband with a uniparental disomy (UPD) of the entire chromosome 1. This is the first time a UPD has been described in a patient with schizophrenia, lending further support to involvement of chromosome 1 in schizophrenia susceptibility in the Afrikaners.     

Quantitative trait loci underlying milk production traits in sheep

Improvement of milk production traits in dairy sheep is required to increase the competitiveness of the industry and to maintain the production of high quality cheese in regions of Mediterranean countries with less favourable conditions. Additional improvement over classical selection could be reached if genes with significant effects on the relevant traits were specifically targeted by selection. However, so far, few studies have been undertaken to detect quantitative trait loci (QTL) in dairy sheep. In this study, we present a complete genome scan performed in a commercial population of Spanish Churra sheep to identify chromosomal regions associated with phenotypic variation observed in milk production traits. Eleven half-sib families, including a total of 1213 ewes, were analysed following a daughter design. Genome-wise multi-marker regression analysis revealed a genome-wise significant QTL for milk protein percentage on chromosome 3. Eight other regions, localized on chromosomes 1, 2, 20, 23 and 25, showed suggestive significant linkage associations with some of the analysed traits. To our knowledge, this study represents the first complete genome scan for milk production traits reported in dairy sheep. The experiment described here shows that analysis of commercial dairy sheep populations has the potential to increase our understanding of the genetic determinants of complex production-related traits.     

凡纳滨对虾微卫星位点在两个选育家系中遗传的初步研究

利用两个选育凡纳滨对虾全同胞家系研究了10个微卫星位点的遗传特征。通过ABI310或3100测序仪检测, 在所观察到的20个基因型比例（genotypic ratios）(10个微卫星位点 X 2个家系)中,有17个基因型比例符合孟德尔遗传。微卫星位点TUMXLv8.220在两个家系中均存在无效等位基因,从而3个不符合孟德尔遗传基因型中2个可由无效等位基因来解释。TUMXLv 3.1在06家系偏离了1：1：1：1的孟德尔预期比。3个微卫星位点（TUMXLv5.66,TUMXLv7.74,TUMXLv8.224）在两个家系中均表现单态。3个微卫星位点（TUMXLv5.45,TUMXLv7.56,TUMXLv8.256）在两个家系均既表现多态又遵循孟德尔共显性遗传, 是亲子鉴定和种群遗传分析的较好选择。结果显示在应用微卫星标记进行遗传分析之前利用全同胞家系进行遗传模式研究是非常必要的。     

Cystic fibrosis in Finland: a molecular and genealogical study

Summary The incidence of cystic fibrosis (CF) in Finland is one tenth that in other Caucasian populations. To study the genetics of CF in Finland, we used a combined molecular and genealogical approach. Out of the 20 Finnish families with a living CF patient, 19 were typed for eight closely linked restriction fragment length polymorphisms (RFLP) at the MET, D7S8, and D7S23 loci. The birthplaces of the parents and grandparents were traced using population registries. Allele and haplotype frequencies in Finland are similar to those of other European and North American populations, but are modified by sampling: two regional CF gene clusters, evidently the results of a founder effect, were identified. Generally, the gene was evenly distributed over the population, carrier frequency being estimated at approximately 1.3%. We conclude that CF in Finland is caused by the common Caucasian mutation(s), and that the low frequency of the gene can be explained by a negative sampling effect and genetic drift.     

Positional cloning of disease genes: advantages of genetic isolates.

Genetic isolates with a history of a small founder population, long-lasting isolation and population bottlenecks represent exceptional resources in the identification of disease genes. Specific rare, monogenic diseases become enriched, and families with multiple affected individuals occur frequently enough to be used in linkage analyses for locus identification. Further, the vast majority of cases are caused by the same mutation, and disease alleles reveal linkage disequilibrium (LD) with markers over significant genetic intervals; this facilitates disease locus identification by similarity search for a shared genotype or haplotype in small study samples consisting of few affected individuals. LD observed in disease alleles adds power to linkage analyses and helps to define the exact location of disease loci on the genetic map. Typically, based on the linkage disequilibrium and the ancient haplotype, the critical DNA region can be defined from the original 1- to 2-cM resolution obtained in linkage analysis to 50-200 kb, greatly facilitating the targeting of physical cloning and sequencing efforts. These advantages have been well demonstrated in the positional cloning of several rare monogenic diseases enriched in population isolates like the example of Finland used here. How useful genetic isolates will prove to be in the identification of complex disease genes is dependent on the genealogical history of the isolate, including the size of the founding population and the expansion rate during the history of the population.     

Development of a wide population of chromosome single-segment substitution lines in the genetic background of an elite cultivar of rice (Oryza sativa L.).

Naturally occurring allelic variations underlying complex traits are useful resources for the functional analysis of plant genes. To facilitate the genetic analysis of complex traits and the use of marker-assisted breeding in rice, we developed a wide population consisting of 217 chromosome single-segment substitution lines (SSSLs) using Oryza sativa L. 'Hua-Jing-Xian74' (HJX74), an elite Indica cultivar, as recipient, and 6 other accessions, including 2 Indica and 4 Japonica, as donors. Each SSSL contains a single substituted chromosome segment derived from 1 of the 6 donors in the genetic background of HJX74. The total size of the substituted segments in the SSSL population was 4695.0 cM, which was 3.1 times that of rice genome. To evaluate the potential application of these SSSLs for quantitative trait loci detection, phenotypic variations of the quantitative traits of days to heading and grain length in the population consisting of 210 SSSLs were observed under natural environmental conditions. The results demonstrated that there was a wide range of phenotypic variation in the traits in the SSSL population. These genetic materials will be powerful tools to dissect complex traits into a set of monogenic loci and to assign phenotypic values to different alleles at the locus of interest.