Yield-enhancing quantitative trait loci (QTLs) from wild species

Wild species of crop plants are increasingly being used to improve various agronomic traits including yield in cultivars. Dense molecular maps have enabled mapping of quantitative trait loci (QTLs) for complex traits such as yield. QTLs for increased yield have been identified from wild relatives of several crop plants. Advanced backcross QTL analysis has been used to identify naturally occurring favorable QTL alleles for yield and minimize the effect of unwanted alleles from wild species. Yield QTLs from wild species are distributed on almost all chromosomes but more often in some regions. Many QTLs for yield and related traits derived from different wild accessions or species map to identical chromosomal regions. QTLs for highly correlated yield associated traits are also often co-located implying linkage or pleiotropic effects. Many QTLs have been detected in more than one environment and in more than one genetic background. The overall direction of effect of some QTLs however, may vary with genetic context. Thus, there is evidence of stable and consistent major effect yield-enhancing QTLs derived from wild species in several crops. Such QTLs are good targets for use in marker assisted selection though their context-dependency is a major constraint. Literature on yield QTLs mapped from wild species is summarized with special reference to rice and tomato.     

A genome scan for quantitative trait loci associated with body weight at different developmental stages in chickens

A genome scan to detect quantitative trait loci (QTL) affecting body weight in chickens was conducted on 238 F(2) chickens from a reciprocal cross of Silky Fowl and White Plymouth Rock using 125 microsatellite markers covering 23 autosomes and the Z chromosome. Two types of QTL were considered: static QTL (SQ) and developmental QTL (DQ). Static QTL affected the body weight from hatch to time t, and DQ affected the body weight from time t-1 to time t. Six SQ and nine DQ were detected. Of these QTL, four reached a genome-wide significance of 5% or better, with SQ1 and DQ1 being the most significant QTL. Static QTL1 was on chromosome 1 between GCT0006 and MCW0106 and explained 4.05-9.80% of the phenotypic variation in body weights from 3 to 12 weeks of age. At 9, 10 and 11 weeks, the genome-wide significance thresholds of SQ1 were <1%. Developmental QTL1 was located on chromosome 1 between MCW0168 and GCT0006, and explained 2.75% of the phenotypic variation for body weight from week 7 to 8 with a genome-wide significance level <1%. The results suggest that body weight from hatch to time t and developmental growth from time t-1 to time t may involve two different sets of genes or gene actions.     

Detection of quantitative trait loci for body weights and conformation traits in Beijing ducks

Quantitative trait loci (QTL) for body weights and conformation traits were detected in Beijing ducks. Traits included body weights (BW) at hatching and at 1-7 weeks of age; lengths of the body (BL), keel bone (KBL), shank (SL) and neck (NL) at 7 weeks of age; width of breast (BTW) at 7 weeks; and girths of shank (SG) and breast (BG) at 7 weeks. Using a half-sib analysis with a multiple-QTL model, linkage between the phenotypic traits and 95 microsatellite markers was studied. Six genome-wide suggestive QTL for three body weights and two conformation traits were identified in CAU1, CAU2, CAU6 and CAU12. Chromosome-wide significant QTL influencing one body weight trait and one conformation trait were located in CAU4 and CAU10 respectively. Twelve chromosome-wide suggestive QTL for six body weight traits and four conformation traits were found in seven linkage groups (CAU1, CAU2, CAU3, CAU4, CAU6, CAU10 and CAU12). In addition, the QTL in CAU6 at 21 and 73 cM jointly affected SG and explained 10.6% of the phenotypic variation. This study provides the first evidence for QTL involved in body weights and conformation traits in ducks, and will stimulate further investigations into the genetic architecture of these traits in this species.     

Validation of yield-enhancing quantitative trait loci from a low-yielding wild ancestor of rice

A set of introgression lines (ILs) containing chromosomal segments from O. rufipogon (IRGC 105491), a wild relative of O. sativa, in the genetic background of an elite US variety, cv. Jefferson, was developed to confirm the performance of six yield-enhancing quantitative trait loci (QTL). Fifty BC3F3 ILs containing homozygous O. rufipogon introgressions at each of the target QTL regions, and as few background introgressions as possible, were selected for evaluation of yield and 14 yield-related traits in field studies conducted over 2 years at four locations in the southern USA. Performance of the IL families was compared with three commercial inbreds and one hybrid variety. IL families carrying introgressions from the low-yielding wild parent at the QTL yld2.1 and yld6.1 yielded 27.7 and 26.1 % more than Jefferson, respectively. IL yld2A, which possesses yld2.1, also performed well under alternate wetting and drying conditions in two field locations. After the first year of field trials, 10 of the top-performing BC3F4 families, representing five of the QTL targets, were genotyped with an Illumina 1,536 assay to define the size and location of the wild introgressions. BC3F4 families with the fewest background introgressions were backcrossed to Jefferson and selfed. The resulting BC4F2 families were screened with targeted single nucleotide polymorphism assays to identify individuals carrying homozygous introgressions across the target QTL. Twelve ILs, representing each of the six QTL targets, have been submitted to the Genetic Stocks Oryza Collection for studies on transgressive variation and as interspecific pre-breeding lines.     

Quantitative trait loci for body size components in mice

Do body size components, such as weights of internal organs and long bone lengths, with different functions and different developmental histories also have different genetic architectures and pleiotropic patterns? We examine murine quantitative trait loci (QTL) for necropsy weight, four long bone lengths, and four organ weights in the LG/J × SM/J intercross. Differences between trait categories were found in number of QTL, dominance, and pleiotropic patterns. Ninety-seven QTLs for individual traits were identified: 52 for long bone lengths, 30 for organ weights, and 15 for necropsy weight. Results for long bones are typically more highly significant than for organs. Organ weights were more frequently over- or underdominant than long bone lengths or necropsy weight. The single-trait QTLs map to 35 pleiotropic loci. Long bones are much more frequently affected in groups while organs tend to be affected singly or in pairs. Organs and long bones are found at the same locus in only 11 cases, 8 of which also include necropsy weight. Our results suggest mainly separate genetic modules for organ weights and long bone lengths, with a few loci that affect overall body size. Antagonistic pleiotropy, in which a locus has opposite effects on different characteristics, is uncommon.     

Analysis of quantitative trait loci for behavioral laterality in mice

Laterality is believed to have genetic components, as has been deduced from family studies in humans and responses to artificial selection in mice, but these genetic components are unknown and the underlying physiological mechanisms are still a subject of dispute. We measured direction of laterality (preferential use of left or right paws) and degree of laterality (absolute difference between the use of left and right paws) in C57BL/6ByJ (B) and NZB/BlNJ (N) mice and in their F(1) and F(2) intercrosses. Measurements were taken of both forepaws and hind paws. Quantitative trait loci (QTL) did not emerge for direction but did for degree of laterality. One QTL for forepaw (LOD score = 5.6) and the second QTL for hind paw (LOD score = 7.2) were both located on chromosome 4 and their peaks were within the same confidence interval. A QTL for plasma luteinizing hormone concentration was also found in the confidence interval of these two QTL. These results suggest that the physiological mechanisms underlying degree of laterality react to gonadal steroids.     

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.     

Yield quantitative trait loci from wild tomato are predominately expressed by the shoot

Plant yield is the integrated outcome of processes taking place above and below ground. To explore genetic, environmental and developmental aspects of fruit yield in tomato, we phenotyped an introgression line (IL) population derived from a cross between the cultivated tomato (Solanum lycopersicum) and a wild species (Solanum pennellii). Both homozygous and heterozygous ILs were grown in irrigated and non-irrigated fields and evaluated for six yield components. Thirteen lines displayed transgressive segregation that increased agronomic yield consistently over 2?years and defined at least 11 independent yield-improving QTL. To determine if these QTL were expressed in the shoots or the roots of the plants, we conducted field trials of reciprocally grafted ILs; out of 13 lines with an effect on yield, 10 QTL were active in the shoot and only IL8-3 showed a consistent root effect. To further examine this unusual case, we evaluated the metabolic profiles of fruits from both the homo- and heterozygous lines for IL8-3 and compared these to those obtained from the fruit of their equivalent genotypes in the root effect population. We observed that several of these metabolic QTL, like the yield QTL, were root determined; however, further studies will be required to delineate the exact mechanism mediating this effect in this specific line. The results presented here suggest that genetic variation for root traits, in comparison to that present in the shoot, represents only a minor component in the determination of tomato fruit yield.     

Characterization of a major X-linked quantitative trait locus influencing body weight of mice

Growth rate in mice is an archetypal quantitative trait that has long been studied genetically, physiologically, and metabolically, but its genetic basis is still poorly understood due to its complex inheritance and the influence of environment. We measured differences in 17 growth-related traits between a pair of partially congenic lines that differ for a segment of the X chromosome containing a quantitative trait locus (QTL) that we identified in a genomewide QTL scan. The QTL has a large effect on mean body weight of approximately 20% at all ages, and affects early growth rate to a greater extent than late growth rate. Feed is converted to body mass more efficiently in the high chromosome segment-bearing line than the low line. The weights of various internal organs are affected to a somewhat greater extent by the QTL than body weight. The proportional change in body length is smaller than body weight, but this may be an effect of scale. Body weight at late ages appears to allow the most efficient detection of allelic differences at the QTL, although assignment of genotypic state based on phenotype is never unambiguous.     

Mapping quantitative trait loci regulating chicken body composition traits

Genome scans were conducted on an F₂ resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F₂ individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 c m on GGA1 (explained 3.6% of phenotypic variance, P  < 0.01) and 51 c m on GGA5 (explained 3.3% of phenotypic variance, P  < 0.05) for the shank & claw weight and 502 c m on GGA1 (explained 1.4% of phenotypic variance, P  < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 c m , shank girth at 489 c m and intestine length at 481 c m . It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.     

Linking cellular zinc status to body weight and fat mass: mapping quantitative trait loci in Znt7 knockout mice

Zinc transporter 7 (Znt7, Slc30a7) knockout (KO) mice display abnormalities in body weight gain and body adiposity. Regulation of body weight and body fat accumulation is complex, involving multiple genetic and environmental factors. To understand how zinc homeostasis influences body weight and fat deposit and to identify quantitative trait loci (QTLs) that link zinc metabolism to growth and adiposity, we conducted a genome-wide mapping study using male F₂ Znt7 KO mice and wild-type (WT) littermates with a mixed 129P1/ReJ and C57BL/6J genetic background. The mice were fed a semi-purified diet containing 30-mg Zn/kg diet at weaning. Body weights and fat pad weights including epididymal, retroperitoneal, and femoral subcutaneous fat pads were measured at 16 weeks of age. We detected two significant QTLs (p < 0.05) for body weight and fat deposit. One was in the F₂ Znt7 KO population and the other in the F₂ WT population. In Znt7 KO mice, the body weight and fat deposit was significantly linked to a locus on chromosome 7 ranging from 64.3 to 78.3 Mb. In WT mice, a significant linkage of retroperitoneal fat mass was found on chromosome 8 between 14.5 and 63.5 Mb. In addition, several other suggestive QTLs (p < 0.63) for body weight and fat accumulation were detected in Znt7 KO and WT mice. In conclusion, the QTLs identified in this study may provide new hints to uncover the genes linking cellular zinc status to growth and body fat accumulation.     

Detection of quantitative trait loci for meat quality traits in cattle

A whole-genome scan was carried out to detect quantitative trait loci (QTL) affecting sensory, organoleptic, physical and chemical properties of meat. The study used phenotypic data from 235 second-generation cross-bred bull calves of a Charolais × Holstein experimental population. Loin muscle samples were evaluated for yield force, intramuscular fat and nitrogen contents, myofibrillar fragmentation index, haem pigment concentration, moisture content and pH at 24 h postmortem. A sensory assessment was performed on grilled loin and roasted silverside joints by trained panellists. A linear regression analysis based on 165 markers revealed 35 QTL at the 5% chromosome-wide significance level (20 for sensory traits and 15 for physical and chemical traits), five of which were highly significant ( F -value: ≥9). The most significant QTL was located on chromosome 6 (with the best likely position at 39 cM) and affected haem pigment concentration. The Holstein allele for this QTL was associated with an increase of 0.53 SD in the haem scores. A QTL for pH_24h was identified on chromosome 14 (at 40 cM) and a QTL for moisture content was identified on chromosome 22 (at 21 cM). Two highly significant QTL were identified for sensory panel-assessed traits: beef odour intensity (grilled sample) on chromosome 10 (at 119 cM), and juiciness (roast sample) on chromosome 16 (at 70 cM). The proportion of phenotypic variance explained by the significant QTL ranged from 3.6% (for nitrogen content on chromosome 10) to 9.5% (for juiciness, roast sample on chromosome 16).     

Detection of quantitative trait loci for growth and fatness in pigs

A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.     

Identification of quantitative trait loci for prolificacy and growth in mice

Marker–quantitative trait locus (QTL) linkage was evaluated in F₂ intercross and backcross mouse populations derived from stocks differing dramatically in prolificacy and mature weight. A highly prolific outbred Quackenbush-Swiss mouse line, or an inbred line derived from it (16.62 ± 0.22 and 14.64 ± 0.27 pups per litter, respectively) were used as one of the grandparents in these populations. The less prolific C57BL/6J inbred mouse line (6.67 ± 0.37 pups per litter) was used as the other grandparent. Linkage was evaluated in a three-step process that involved selective genotyping of F₂ intercross progeny representing extremes for prolificacy, genotyping of the full F₂ for chromosomal regions potentially associated with prolificacy, and genotyping of the backcross for genomic regions significantly associated with prolificacy in the F₂. Segments of Chromosomes (Chrs) 2 and 4 were significantly (P < 0.05, experiment-wise error rate) associated with prolificacy, and LOD scores suggestive of linkage were observed for litter size on Chr 9 and growth on Chrs 4 and 11. Existence of growth QTL was also supported by marker effects that were significant (P < 0.05) or approaching significance (P < 0.10) in the backcross. Additive litter size QTL effects ranged from 0.56 to 0.79 pups per litter, and dominance deviations ranged from −0.56 to 1.19 pups per litter, suggesting overdominance as a possible mode of gene action in some cases. The observation of pleiotropic or linked QTL for growth and prolificacy corresponds well with results from many selection experiments identifying positively correlated responses to selection for these two traits. Received: 9 August 1997 / Accepted: 30 September 1997     

Mapping major quantitative trait loci for postnatal growth in an intersubspecific backcross between C57BL/6J and Philippine wild mice by using principal component analysis

A number of quantitative trait loci (QTLs) for postnatal growth have previously been reported in mice. As effects of the QTLs are usually small and similar to one another in magnitude, it is generally difficult to know which loci are major contributors to postnatal growth. We applied principal component analysis to a genome-wide search for QTLs affecting postnatal growth in body weight weekly recorded from 3 to 10 weeks of age in an intersubspecific backcross population of C57BL/6J inbred mice (Mus musculus domesticus) and wild mice (M. m. castaneus) captured in the Philippines, in order to discover new QTLs from a gene pool of the wild mice and uncover major loci underlying variation in postnatal growth. Principal component analysis classified phenotypic variation in body weights at different ages into two independent principal components: the first principal component (PC1) extracted information on the entire growth process and the second principal component (PC2) contrasted middle (3-6 weeks of age) with late (6-10 weeks) growth phases. Simple interval mapping and composite interval mapping revealed 10 significant QTLs with main effects on PC1 or PC2 on eight chromosomes. Of these, the six main-effect QTLs interacted epistatically with one another or three new additional QTLs on different chromosomal regions without main effects. Several of the identified QTLs with main effects and/or epistatic interaction effects appeared to be sex specific. These results suggest that the identified 13 QTLs, most of which affected the entire growth process, are very important contributors to complex genetic networks of postnatal growth.     

Mapping quantitative trait loci for anxiety in chromosome substitution strains of mice

Anxious behavior in the mouse is a complex quantitative phenotype that varies widely among inbred mouse strains. We examined a panel of chromosome substitution strains bearing individual A/J chromosomes in an otherwise C57BL/6J background in open-field and light-dark transition tests. Our results confirmed previous reports of quantitative trait loci (QTL) on chromosomes 1, 4, and 15 and identified novel loci on chromosomes 6 and 17. The studies were replicated in two separate laboratories. Systematic differences in the overall activity level were found between the two facilities, but the presence of the QTL was confirmed in both laboratories. We also identified specific effects on open-field defecation and center avoidance and distinguished them from overall open-field activity.     

Polymerase chain reaction multiplexing of microsatellites and single nucleotide polymorphism markers for quantitative trait loci mapping of wild house mice

We tested 96 microsatellites and 10 single nucleotide polymorphisms for their allelic distribution in two subspecies of the house mouse, Mus musculus musculus and M. m. domesticus. Sixty‐two microsatellites discriminated strain‐specific differences among nine wild‐derived ‘musculus’ and ‘domesticus’ and three ‘classical’ laboratory strains. For efficient genotyping, we optimized multiplex conditions using five microsatellites per polymerase chain reaction. All 10 single nucleotide polymorphisms were also optimized for simultaneous analysis in one reaction using SNaPshot multiplex. The uniform distribution of markers on autosomes and on the X chromosome makes these panels potentially useful tools for quantitative trait loci mapping of wild house mice.     

Identification of trait-improving quantitative trait loci alleles from a wild rice relative,Oryza rufipogon.

Wild species are valued as a unique source of genetic variation, but they have rarely been used for the genetic improvement of quantitative traits. To identify trait-improving quantitative trait loci (QTL) alleles from exotic species, an accession of Oryza rufipogon, a relative of cultivated rice, was chosen on the basis of a genetic diversity study. An interspecific BC2 testcross population (V20A/O. rufipogon//V20B///V20B////Ce64) consisting of 300 families was evaluated for 12 agronomically important quantitative traits. The O. rufipogon accession was phenotypically inferior for all 12 traits. However, transgressive segregants that outperformed the original elite hybrid variety, V20A/Ce64, were observed for all traits examined. A set of 122 RFLP and microsatellite markers was used to identify QTL. A total of 68 significant QTL were identified, and of these, 35 (51%) had beneficial alleles derived from the phenotypically inferior O. rufipogon parent. Nineteen (54%) of these beneficial QTL alleles were free of deleterious effects on other characters. O. rufipogon alleles at two QTL on chromosomes 1 and 2 were associated with an 18 and 17% increase in grain yield per plant, respectively, without delaying maturity or increasing plant height. This discovery suggests that the innovative use of molecular maps and markers can alter the way geneticists utilize wild and exotic germplasm.     

Bayesian LASSO for quantitative trait loci mapping

The mapping of quantitative trait loci (QTL) is to identify molecular markers or genomic loci that influence the variation of complex traits. The problem is complicated by the facts that QTL data usually contain a large number of markers across the entire genome and most of them have little or no effect on the phenotype. In this article, we propose several Bayesian hierarchical models for mapping multiple QTL that simultaneously fit and estimate all possible genetic effects associated with all markers. The proposed models use prior distributions for the genetic effects that are scale mixtures of normal distributions with mean zero and variances distributed to give each effect a high probability of being near zero. We consider two types of priors for the variances, exponential and scaled inverse-chi(2) distributions, which result in a Bayesian version of the popular least absolute shrinkage and selection operator (LASSO) model and the well-known Student's t model, respectively. Unlike most applications where fixed values are preset for hyperparameters in the priors, we treat all hyperparameters as unknowns and estimate them along with other parameters. Markov chain Monte Carlo (MCMC) algorithms are developed to simulate the parameters from the posteriors. The methods are illustrated using well-known barley data.