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The trait flowering time regulated by genes determining vernalisation and photoperiod sensitivity was used as an example for presenting data on comparative major gene and QTL mapping within the Triticeae. The major genes are shown to be members of homoeologous series. Furthermore it was demonstrated that in genome regions carrying major genes also QTLs for the same traits were detected.
Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa (Xtu), has recently emerged as a significant threat to wheat production in the Northern Great Plains region of the United States. Deploying resistant cultivars is an economical and practical method of controlling BLS. To identify novel sources of BLS resistance, we screened a set of 355 bread wheat landraces and cultivars representing global diversity for their response to BLS. A wide distribution of seedling responses against BLS was observed, with most genotypes displaying a moderately to highly susceptible response. Notably, we identified 5 resistant and 33 moderately resistant responses. A high-resolution genome-wide association study using 302,524 high-quality single-nucleotide polymorphisms (SNPs) identified 10 significant marker-trait associations (MTAs) on chromosomes 1A, 1D, 3B, 4A, and 5A corresponding to unique genomic regions associated with BLS resistance. Compared with previous studies, four of these genomic regions are likely novel. Of these, MTA 'scaffold15531_2782724' associated with q5A.1 was highly significant (-log10P = 9.39) and exhibited the highest SNP effect (0.35). An association on chromosome 3B validated a previously identified 3B quantitative trait locus (QTL) mapped at approximately 6 Mbp in the hard red spring wheat cultivar 'Boost', and the high-resolution mapping from our study further refined the interval for this QTL. Furthermore, the narrow haplotype blocks reported in this study could be valuable for fine mapping of important regions. The novel resistant sources, along with identified genomic loci and corresponding SNP markers from this study, would be helpful for wheat-breeding programs to enhance BLS resistance.[Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
The enlarged inflorescence (curd) of cauliflower and broccoli provide not only a popular vegetable for human consumption, but also a unique opportunity for scientists who seek to understand the genetic basis of plant growth and development. By the comparison of quantitative trait loci (QTL) maps constructed from three different F(2) populations, we identified a total of 86 QTL that control eight curd-related traits in Brassica oleracea. The 86 QTL may reflect allelic variation in as few as 67 different genetic loci and 54 ancestral genes. Although the locations of QTL affecting a trait occasionally corresponded between different populations or between different homeologous Brassica chromosomes, our data supported other molecular and morphological data in suggesting that the Brassica genus is rapidly evolving. Comparative data enabled us to identify a number of candidate genes from Arabidopsis that warrant further investigation to determine if some of them might account for Brassica QTL. The Arabidopsis/Brassica system is an important example of both the challenges and opportunities associated with extrapolation of genomic information from facile models to large-genome taxa including major crops.
Induction of inflammatory bowel (IBD)-like disease in mice by a targeted mutation in the Il10 gene (Il10(-/-)) is inbred strain dependent. C3H/HeJBir (C3) mice are colitis susceptible, whereas C57BL/6J (B6) mice are resistant. Genetic dissection of this susceptibility revealed 10 colitogenic quantitative trait loci (QTL). The aim of this study was to identify valuable candidate genes by a combination of QTL mapping and microarray analyses. Sixteen genes were differentially expressed between B6- and C3-Il10(-/-) mice and were located within the QTL intervals. Three major candidate genes (Cd14, Gbp1, Pla2g2a) showed prominent expression differences between B6- and C3-Il10(-/-) as well as between B6 and C3 wild-type mice, which was confirmed by semiquantitative or real-time RT-PCR. Because strain differences are known for Gbp1 and Pla2g2a, further analyses focused on Cd14. Western blot analysis revealed strain differences also on the protein level. Cd14 expression in animals with defective and intact Toll-like receptor (TLR)4 signaling (C3, C3H/HeN, B6, B6-Tlr4(tm1Aki)) make the TLR4 defect of C3 mice unlikely to be the reason for higher Cd14 expression. Less Cd14 expression in germ-free mice indicates a contribution of the microflora on Cd14 expression. Stimulation of naive peritoneal macrophages with bacterial antigens showed lower CD14 surface expression in B6 than in C3 mice. In conclusion, the large number of candidate genes was reduced to three major candidates that play an important role in inflammatory processes and immune response. Strain differences for them are already known or are shown in this study.
A Plasmodium-refractory strain of Anopheles gambiae melanotically encapsulates many species of Plasmodium, whereas wild-type mosquitoes are usually susceptible. This encapsulation trait can also be observed by studying the response of refractory and susceptible strains to intrathoracically injected CM-Sephadex beads. We report the results of broad-scale quantitative trait locus (QTL) mapping of the encapsulation trait using the bead model system. Interval mapping using the method of maximum likelihood identified one major QTL, Pen1. The 13.7-cM interval containing Pen1 was defined by marker AGH157 at 8E and AGH46 at 7A on 2R. Pen1 was associated with a maximum LOD score of 9.0 and accounted for 44% of the phenotypic variance in the distribution of phenotypes in the backcross. To test if this QTL is important for encapsulation of Plasmodium berghei, F2 progeny were infected with P. berghei and evaluated for degree of parasite encapsulation. For each of the two markers that define the interval containing Pen1, a significant difference of encapsulation was seen in progeny with at least one refractory allele in contrast with homozygous susceptible progeny. These results suggest that Pen1 is important for melanotic encapsulation of Plasmodium as well as beads.
Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained approximately 50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.
The extent to which epistasis contributes to adaptation and speciation has been a controversial topic in evolutionary genetics. One experimental approach to study epistasis is based on quantitative trait locus (QTL) mapping using molecular markers. Comparisons can be made among all possible pair-wise combinations of the markers, irrespective of whether an additive QTL is associated with a marker; several software packages have been developed that facilitate this. We review several examples of using this approach to identify epistatic QTLs for traits of evolutionary or ecological interest. While there is variability in the results, the number of epistatic QTL interactions is often greater than or equal to the number of additive QTLs. The magnitude of epistatic effects can be larger than the additive effects. Thus, epistatic interactions seem to be an important part of natural genetic variation. Future studies of epistatic QTLs could lead to descriptions of the genetic networks underlying variation for fitness-related traits.
Markers with segregation ratio distortion are commonly observed in data sets used for quantitative trait locus (QTL) mapping. In this study, a multipoint method of maximum likelihood (ML) was newly developed to estimate the positions and effects of the segregation distortion loci (SDLs) in two F2 populations of rice (Oryza sativa L.), i.e. Taichung65/Bhadua (TB; japonica-indica cross) and CPSLO17/W207-2 (CW; japonica-japonica). Of the four parents, W207-2 and Bhadua were found to be spikelet semi-sterile and stably inherited through selfing, and spikelet fertility segregated in the two populations. Therefore, recombination frequencies were recalculated after mapping the SDLs by using the multipoint method, and the molecular linkage maps of the two F2 populations were constructed to detect QTLs underlying spikelet fertility. As a result, five SDLs in the TB population were mapped on chromosomes 1, 3, 8 and 9, respectively. Two major QTLs underlying spikelet fertility, namely qSS-6a and qSS-8a, were detected on chromosomes 6 and 8, respectively. In the CW population, a total of 12 SDLs were detected on all 12 chromosomes except 1, 5, 7 and 11. Three QTLs underlying spikelet sterility, namely qSS-2, qSS-6b and qSS-8b on chromosomes 2, 6 and 8, were determined on the whole genome scale. Interestingly, both qSS-6a and qSS-6b, detected in the two F2 populations respectively, were located on a similar position as the S5 gene on chromosome 6; while qSS-8a and qSS-8b were also simultaneously detected on similar positions of the short arm of chromosome 8 in the two populations, which should be a new sterility gene showing the same type of zygotic selection.
Ontogenetic growth can be described by mathematical equations constructed on the goodness of fit. Recently, the biological mechanism underlying mathematical growth equations has been explored using basic cellular properties. Here, we derive a general statistical model for understanding the genetic regulation of ontogenetic growth by integrating those biologically-proven meaningful growth equations into a quantitative trait locus (QTL) mapping framework. We can characterize the dynamic patterns of effects of QTL governing growth curves and estimate the global effect of the underlying QTL throughout the entire course of growth. The model provides the basis for deciphering genetic relationships for growth rates and the timing of life history events for any kind of organisms.
We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect.
In recent work, a statistical model was proposed for the purpose of estimating parameters associated with quantitative trait locus (QTL) mapping and preferential pairing within a polyploidy framework. The statistical model contained several parameters that, when estimated from experimental data, supplied information about QTL, including a preferential pairing factor. Among the results reported were estimates of preferential pairing, many of which indicated high levels of preferential pairing (p = 0.60) that were inconsistent with biological expectations. By using the biological inconsistencies as our motivation, we present a reformulated statistical method for estimating preferential pairing, and use this method to reanalyze the same autotetraploid alfalfa data and to conduct a simulation study. Our results directly contradict the current findings of significant preferential pairing and affirm the traditional view of random chromosome segregation in alfalfa.
We are mapping the genes (quantitative trait loci or QTLs) that are responsible for individual differences in ethanol sensitivity, measured as the duration of loss of righting, reflex (LORR) and blood ethanol concentrations upon recovery of the righting reflex (BEC). The Long-Sleep (LS) and Short-Sleep (SS) selected lines of mice manifest an 18-fold difference in LORR and serve as a rodent model for ethanol sensitivity. The LS x SS recombinant inbred (RI) series, developed from LS and SS lines, are an important resource for QTL mapping of ethanol-related responses. The current report summarizes the initial QTL analysis of LORR and BEC in the LS x SS strains and compares the results of correlational analysis with an interval-mapping approach. The data provide strong evidence for QTLs that influence ethanol sensitivity on mouse chromosomes 1 and 2 and possible QTLs on chromosomes 1, 3, 4, 5, 6, 7, 12, 13, 16, and 18. These results are compared to those from an F2 cross which confirms QTLs on chromosomes 1, 2, 4, and 18.
Prepulse inhibition (PPI) of acoustic startle is a genetically complex quantitative phenotype of considerable medical interest due to its impairment in psychiatric disorders such as schizophrenia. To identify quantitative trait loci (QTL) involved in mouse PPI, we studied mouse chromosome substitution strains (CSS) that each carry a homologous chromosome pair from the A/J inbred strain on a host C57BL/6J inbred strain background. We determined that the chromosome 16 substitution strain has elevated PPI compared to C57BL/6J (P = 1.6 x 10(-11)), indicating that chromosome 16 carries one or more PPI genes. QTL mapping using 87 F(2) intercross progeny identified two significant chromosome 16 loci with LODs of 3.9 and 4.7 (significance threshold LOD is 2.3). The QTL were each highly significant independently and do not appear to interact. Sequence variation between B6 and A/J was used to identify strong candidate genes in the QTL regions, some of which have known neuronal functions. In conclusion, we used mouse CSS to rapidly and efficiently identify two significant QTL for PPI on mouse chromosome 16. The regions contain a limited number of strong biological candidate genes that are potential risk genes for psychiatric disorders in which patients have PPI impairments.
Resistance against a Ralstonia solanacearum race 3-phylotype II strain JT516 was assessed in a F(2:3) and a population of inbred lines (RIL), both derived from a cross between L. esculentum cv. Hawaii 7996 (partially resistant) and L. pimpinellifolium WVa700 (susceptible). Resistance criteria used were the percentage of wilted plants to calculate the AUDPC value, and bacterial colonization scores in roots and stem (hypocotyl and epicotyl) assessed in two independent greenhouse experiments conducted during the cool and hot seasons in Réunion Island, France. Symptoms were more severe during the cool season trials. Heritability estimates in individual seasons ranged from 0.82 to 0.88, depending on resistance criterion. A set of 76 molecular markers was used for quantitative trait loci (QTL) mapping using the single- and composite- interval mapping methods, as well as ANOVA. Four QTLs, named Bwr- followed by a number indicating their map location, were identified. They explained from 3.2 to 29.8% of the phenotypic variation, depending on the resistance criterion and the season. A major QTL, Bwr-6, and a minor one, Bwr-3, were detected in each season for all resistance criteria. Both QTLs showed stronger effects in the hot season than in the cool one. Their role in resistance to R. solanacearum race 3-phylotype II was subsequently confirmed in the RIL population derived from the same cross. Two other QTLs, Bwr-4 and Bwr-8, with intermediate and minor effects, respectively, were only detected in the hot season, demonstrating that environmental factors may strongly influence the expression of resistance against the race 3-phylotype II strain JT516. These QTLs were compared with those detected in the RIL population against race 1-phylotype I strain JT519 as well as those detected in other previous studies in the same genetic background against other race 1-phylotype I and II strains. This comparison revealed the possible occurrence of some phylotype-specific resistance QTLs in Hawaii 7996.
We have mapped the quantitative trait loci (QTLs) conferring resistance to sorghum downy mildew (Peronosclerospora sorghi; SDM) and Rajasthan downy mildew (P. heteropogoni; RDM), two species of DM prevalent throughout India. QTL mapping was carried out on a backcross population of 151 individuals derived from a cross between CM139 (susceptible parent) and NAI116 (highly resistant to both SDM and RDM). Heritability estimates were 0.74 for SDM and 0.67 for RDM. Composite interval mapping combined with a linkage map constructed with 80 simple sequence repeat (SSR) markers resulted in the identification of three QTLs (one each on chromosomes 2, 3 and 6) for SDM resistance and two QTLs (one each on chromosomes 3 and 6) for RDM resistance, all of which were contributed by NAI116. The significance of the major QTL on chromosome 6 (bin 6.05) that confers resistance to diverse DMs in tropical Asia, including SDM and RDM in India, was also verified. The results confirmed that some common QTLs contribute to both SDM and RDM resistance, while additional loci might specifically govern resistance to SDM. The QTL information generated in this study provide information that will aid in undertaking an integrated breeding strategy for the transfer of resistance to SDM and RDM in maize lines using marker-assisted selection.
A total of four unambiguous quantitative resistance loci (QRLs) controlling latency periods in partially resistant barley against leaf rust were detected by means of AFLP linkage mapping markers and Map QTL V3.0 software, which were located on chromosome 1,2,6,7 at 79cM, 186cM, 58cM and 117cM oriented with the short arms at the top, respectively. The QRL on chromosome 7 was effective to isolate 24, but not to isolate 121 of Puccinia hordei. The merits and demerits of interval mapping (IM) and composite interval mapping (CIM) was discussed and it is advocated to declare a QTL when detected simultaneously by both methods in the paper.
The porcine orthologues of human chromosome HSA9q22.31 genes osteoglycin (OGN) and asporin (ASPN) were mapped to porcine chromosome SSC3 using linkage analysis and a somatic cell hybrid panel. This mapping was refined to SSC3q11 using fluorescence in situ hybridization. These results confirm the existence of a small conserved synteny group between SSC3 and HSA9. Polymorphisms were revealed in both genes, including a pentanucleotide microsatellite (SCZ003) in OGN and two single nucleotide polymorphisms (AM181682.1:g.780G>T and AM181682.1:g.825T>C) in ASPN. The two genes were included in a set of markers for quantitative trait loci (QTL) mapping on SSC3 in the Hohenheim Meishan x Piétrain F2 family. Major QTL for growth and carcass traits were centred in the ASPN-SW902 region.
We herein report the results of a whole genome scan performed in a Piétrain x Large White intercross counting 525 offspring to map QTL influencing economically important growth and carcass traits. We report experiment-wide significant lod scores (>4.6) for meatiness and fat deposition on chromosome SSC2, and for average daily gain and carcass length on chromosome SSC7. Additional suggestive lod scores (>3.3) for fat deposition are reported on chromosomes SSC1, SSC7 and SSC13. A significant dominance deviation was found for the QTL on SSC1, while the hypothesis of an additive QTL could not be rejected for the QTL on SSC7 and SSC13. No evidence for imprinted QTL could be found for QTL other than the one previously reported on SSC2.