Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses

Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background

Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H2 > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPVNOPA and EPVHY+Q when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01489-2.

Intraspecific Genetic Variation for Behavioral Isolation Loci in Drosophila

Behavioral isolation is considered to be the primary mode of species isolation, and the lack of identification of individual genes for behavioral isolation has hindered our ability to address fundamental questions about the process of speciation. One of the major questions that remains about behavioral isolation is whether the genetic basis of isolation between species also varies within a species. Indeed, the extent to which genes for isolation may vary across a population is rarely explored. Here, we bypass the problem of individual gene identification by addressing this question using a quantitative genetic comparison. Using strains from eight different populations of Drosophila simulans, we genetically mapped the genomic regions contributing to behavioral isolation from their closely related sibling species, Drosophila mauritiana. We found extensive variation in the size of contribution of different genomic regions to behavioral isolation among the different strains, in the location of regions contributing to isolation, and in the ability to redetect loci when retesting the same strain.

QTL mapping for bioenergy traits in sweet sorghum recombinant inbred lines

During the past decade, sweet sorghum (Sorghum bicolor Moench L.) has shown great potential for bioenergy production, especially biofuels. In this study, 223 recombinant inbred lines (RILs) derived from a cross between two sweet sorghum lines (Brandes × Wray) were evaluated in three trials. Single-nucleotide polymorphisms (SNPs) derived from genotyping by sequencing of 272 RILs were used to build a high-density genetic map comprising 3,767 SNPs spanning 1,368.83 cM. Multitrait multiple interval mapping (MT-MIM) was carried out to map quantitative trait loci (QTL) for eight bioenergy traits. A total of 33 QTLs were identified for flowering time, plant height, total soluble solids and sucrose (five QTLs each), fibers (four QTLs), and fresh biomass yield, juice extraction yield, and reducing sugars (three QTLs each). QTL hotspots were found on chromosomes 1, 3, 6, 9, and 10, in addition to other QTLs detected on chromosomes 4 and 8. We observed that 14 out of the 33 mapped QTLs were found in all three trials. Upon further development and validation in other crosses, the results provided by the present study have a great potential to be used in marker-assisted selection in sorghum breeding programs for biofuel production.

Multiple QTL Mapping in Autopolyploids: A Random-Effect Model Approach with Application in a Hexaploid Sweetpotato Full-Sib Population

In developing countries, the sweetpotato, Ipomoea batatas (L.) Lam. [Formula: see text], is an important autopolyploid species, both socially and economically. However, quantitative trait loci (QTL) mapping has remained limited due to its genetic complexity. Current fixed-effect models can fit only a single QTL and are generally hard to interpret. Here, we report the use of a random-effect model approach to map multiple QTL based on score statistics in a sweetpotato biparental population ('Beauregard' × 'Tanzania') with 315 full-sibs. Phenotypic data were collected for eight yield component traits in six environments in Peru, and jointly adjusted means were obtained using mixed-effect models. An integrated linkage map consisting of 30,684 markers distributed along 15 linkage groups (LGs) was used to obtain the genotype conditional probabilities of putative QTL at every centiMorgan position. Multiple interval mapping was performed using our R package QTLpoly and detected a total of 13 QTL, ranging from none to four QTL per trait, which explained up to 55% of the total variance. Some regions, such as those on LGs 3 and 15, were consistently detected among root number and yield traits, and provided a basis for candidate gene search. In addition, some QTL were found to affect commercial and noncommercial root traits distinctly. Further best linear unbiased predictions were decomposed into additive allele effects and were used to compute multiple QTL-based breeding values for selection. Together with quantitative genotyping and its appropriate usage in linkage analyses, this QTL mapping methodology will facilitate the use of genomic tools in sweetpotato breeding as well as in other autopolyploids.

High-Density Genetic Linkage Maps Provide Novel Insights Into ZW/ZZ Sex Determination System and Growth Performance in Mud Crab (Scylla paramamosain)

Mud crab, Scylla paramamosain is one of the most important crustacean species in global aquaculture. To determine the genetic basis of sex and growth-related traits in S. paramamosain, a high-density genetic linkage map with 16,701 single nucleotide polymorphisms (SNPs) was constructed using SLAF-seq and a full-sib family. The consensus map has 49 linkage groups, spanning 5,996.66 cM with an average marker-interval of 0.81 cM. A total of 516 SNP markers, including 8 female-specific SNPs segregated in two quantitative trait loci (QTLs) for phenotypic sex were located on LG32. The presence of female-specific SNP markers only on female linkage map, their segregation patterns and lower female: male recombination rate strongly suggest the conformation of a ZW/ZZ sex determination system in S. paramamosain. The QTLs of most (90%) growth-related traits were found within a small interval (25.18–33.74 cM) on LG46, highlighting the potential involvement of LG46 in growth. Four markers on LG46 were significantly associated with 10–16 growth-related traits. BW was only associated with marker 3846. Based on the annotation of transcriptome data, 11 and 2 candidate genes were identified within the QTL regions of sex and growth-related traits, respectively. The newly constructed high-density genetic linkage map with sex-specific SNPs, and the identified QTLs of sex- and growth-related traits serve as a valuable genetic resource and solid foundation for marker-assisted selection and genetic improvement of crustaceans.

The genetic architecture of phosphorus efficiency in sorghum involves pleiotropic QTL for root morphology and grain yield under low phosphorus availability in the soil

BACKGROUND

Phosphorus (P) fixation on aluminum (Al) and iron (Fe) oxides in soil clays restricts P availability for crops cultivated on highly weathered tropical soils, which are common in developing countries. Hence, P deficiency becomes a major obstacle for global food security. We used multi-trait quantitative trait loci (QTL) mapping to study the genetic architecture of P efficiency and to explore the importance of root traits on sorghum grain yield on a tropical low-P soil.

RESULTS

P acquisition efficiency was the most important component of P efficiency, and both traits were highly correlated with grain yield under low P availability. Root surface area was positively associated with grain yield. The guinea parent, SC283, contributed 58% of all favorable alleles detected by single-trait mapping. Multi-trait mapping detected 14 grain yield and/or root morphology QTLs. Tightly linked or pleiotropic QTL underlying the surface area of fine roots (1-2 mm in diameter) and grain yield were detected at positions 1-7 megabase pairs (Mb) and 71 Mb on chromosome 3, respectively, and a root diameter/grain yield QTL was detected at 7 Mb on chromosome 7. All these QTLs were near sorghum homologs of the rice serine/threonine kinase, OsPSTOL1. The SbPSTOL1 genes on chromosome 3, Sb03g006765 at 7 Mb and Sb03g031690 at 60 Mb were more highly expressed in SC283, which donated the favorable alleles at all QTLs found nearby SbPSTOL1 genes. The Al tolerance gene, SbMATE, may also influence a grain yield QTL on chromosome 3. Another PSTOL1-like gene, Sb07g02840, appears to enhance grain yield via small increases in root diameter. Co-localization analyses suggested a role for other genes, such as a sorghum homolog of the Arabidopsis ubiquitin-conjugating E2 enzyme, phosphate 2 (PHO2), on grain yield advantage conferred by the elite parent, BR007 allele.

CONCLUSIONS

Genetic determinants conferring higher root surface area and slight increases in fine root diameter may favor P uptake, thereby enhancing grain yield under low-P availability in the soil. Molecular markers for SbPSTOL1 genes and for QTL increasing grain yield by non-root morphology-based mechanisms hold promise in breeding strategies aimed at developing sorghum cultivars adapted to low-P soils.

Simultaneous estimation of QTL parameters for mapping multiple traits

The analysis of quantitative trait loci (QTLs) aims at mapping and estimating the positions and effects of the genes that may affect the quantitative trait, and evaluating the relationship between the gene variation and the phenotype. In existing studies, most methods mainly focus on the association/linkage between multiple gene loci and one trait, in which some useful joint information of multiple traits may be ignored. In this paper, we proposed a method of simultaneously estimating all QTL parameters in the framework of multiple-trait multiple-interval mapping. Simulation results show that in accuracy aspect, the proposed method outperforms an existing method for mapping multiple traits. A real example is also provided to validate the performance of the new method.

MVQTLCIM: composite interval mapping of multivariate traits in a hybrid F1 population of outbred species

Background

With the plummeting cost of the next-generation sequencing technologies, high-density genetic linkage maps could be constructed in a forest hybrid F₁ population. However, based on such genetic maps, quantitative trait loci (QTL) mapping cannot be directly conducted with traditional statistical methods or tools because the linkage phase and segregation pattern of molecular markers are not always fixed as in inbred lines.

Results

We implemented the traditional composite interval mapping (CIM) method to multivariate trait data in forest trees and developed the corresponding software, mvqtlcim. Our method not only incorporated the various segregations and linkage phases of molecular markers, but also applied Takeuchi’s information criterion (TIC) to discriminate the QTL segregation type among several possible alternatives. QTL mapping was performed in a hybrid F₁ population of Populus deltoides and P. simonii, and 12 QTLs were detected for tree height over 6 time points. The software package allowed many options for parameters as well as parallel computing for permutation tests. The features of the software were demonstrated with the real data analysis and a large number of Monte Carlo simulations.

Conclusions

We provided a powerful tool for QTL mapping of multiple or longitudinal traits in an outbred F₁ population, in which the traditional software for QTL mapping cannot be used. This tool will facilitate studying of QTL mapping and thus will accelerate molecular breeding programs especially in forest trees. The tool package is freely available from https://github.com/tongchf /mvqtlcim.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1908-1) contains supplementary material, which is available to authorized users.

The roles of pleiotropy and close linkage as revealed by association mapping of yield and correlated traits of wheat (Triticum aestivum L.)

Grain yield (GY) of bread wheat (Triticum aestivum L.) is quantitatively inherited. Correlated GY-syndrome traits such as plant height (PH), heading date (HD), thousand grain weight (TGW), test weight (TW), grains per ear (GPE), and ear weight (EW) influence GY. Most quantitative genetics studies assessed the multiple-trait (MT) complex of GY-syndrome using single-trait approaches, and little is known about its underlying pleiotropic architecture. We investigated the pleiotropic architecture of wheat GY-syndrome through MT association mapping (MT-GWAS) using 372 varieties phenotyped in up to eight environments and genotyped with 18 832 single nucleotide polymorphisms plus 24 polymorphic functional markers. MT-GWAS revealed a total of 345 significant markers spread genome wide, representing 8, 40, 11, 40, 34, and 35 effective GY-PH, GY-HD, GY-TGW, GY-TW, GY-GPE, and GY-EW associations, respectively. Among them, pleiotropic roles of Rht-B1 and TaGW2-6B loci were corroborated. Only one marker presented simultaneous associations for three traits (i.e. GY-TGW-TW). Close linkage was difficult to differentiate from pleiotropy; thus, the pleiotropic architecture of GY-syndrome was dissected more as a cause of pleiotropy rather than close linkage. Simulations showed that minor allele frequencies, along with sizes and distances between quantitative trait loci for two traits, influenced the ability to distinguish close linkage from pleiotropy.

Novel Resampling Improves Statistical Power for Multiple-Trait QTL Mapping

Multiple-trait analysis typically employs models that associate a quantitative trait locus (QTL) with all of the traits. As a result, statistical power for QTL detection may not be optimal if the QTL contributes to the phenotypic variation in only a small proportion of the traits. Excluding QTL effects that contribute little to the test statistic can improve statistical power. In this article, we show that an optimal power can be achieved when the number of QTL effects is best estimated, and that a stringent criterion for QTL effect selection may improve power when the number of QTL effects is small but can reduce power otherwise. We investigate strategies for excluding trivial QTL effects, and propose a method that improves statistical power when the number of QTL effects is relatively small, and fairly maintains the power when the number of QTL effects is large. The proposed method first uses resampling techniques to determine the number of nontrivial QTL effects, and then selects QTL effects by the backward elimination procedure for significance test. We also propose a method for testing QTL-trait associations that are desired for biological interpretation in applications. We validate our methods using simulations and Arabidopsis thaliana transcript data.

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits.

Mapping QTLs for Fusarium Head Blight Resistance in an Interspecific Wheat Population

Fusarium head blight (scab) is one of the most widespread and damaging diseases of wheat, causing grain yield and quality losses and production of harmful mycotoxins. Development of resistant varieties is hampered by lack of effective resistance sources in the tetraploid wheat primary gene pool. Here we dissected the genetic basis of resistance in a new durum wheat (Triticum turgidum ssp. durum) Recombinant inbred lines (RILs) population obtained by crossing an hexaploid resistant line and a durum susceptible cultivar. A total of 135 RILs were used for constituting a genetic linkage map and mapping loci for head blight incidence, severity, and disease-related plant morphological traits (plant height, spike compactness, and awn length). The new genetic map accounted for 4,366 single nucleotide polymorphism markers assembled in 52 linkage groups covering a total length of 4,227.37 cM. Major quantitative trait loci (QTL) for scab incidence and severity were mapped on chromosomes 2AS, 3AL, and 2AS, 2BS, 4BL, respectively. Plant height loci were identified on 3A, 3B, and 4B, while major QTL for ear compactness were found on 4A, 5A, 5B, 6A, and 7A. In this work, resistance to Fusarium was transferred from hexaploid to durum wheat, and correlations between the disease and morphological traits were assessed.

Mapping QTLs for Fusarium Head Blight Resistance in an Interspecific Wheat Population

Fusarium head blight (scab) is one of the most widespread and damaging diseases of wheat, causing grain yield and quality losses and production of harmful mycotoxins. Development of resistant varieties is hampered by lack of effective resistance sources in the tetraploid wheat primary gene pool. Here we dissected the genetic basis of resistance in a new durum wheat (Triticum turgidum ssp. durum) Recombinant inbred lines (RILs) population obtained by crossing an hexaploid resistant line and a durum susceptible cultivar. A total of 135 RILs were used for constituting a genetic linkage map and mapping loci for head blight incidence, severity, and disease-related plant morphological traits (plant height, spike compactness, and awn length). The new genetic map accounted for 4,366 single nucleotide polymorphism markers assembled in 52 linkage groups covering a total length of 4,227.37 cM. Major quantitative trait loci (QTL) for scab incidence and severity were mapped on chromosomes 2AS, 3AL, and 2AS, 2BS, 4BL, respectively. Plant height loci were identified on 3A, 3B, and 4B, while major QTL for ear compactness were found on 4A, 5A, 5B, 6A, and 7A. In this work, resistance to Fusarium was transferred from hexaploid to durum wheat, and correlations between the disease and morphological traits were assessed.

Genetic Analysis in Maize Foundation Parents with Mapping Population and Testcross Population: Ye478 Carried More Favorable Alleles and Using QTL Information Could Improve Foundation Parents

The development of maize foundation parents is an important part of genetics and breeding research, and applying new genetic information to produce foundation parents has been challenging. In this study, we focused on quantitative trait loci (QTLs) and general combining ability (GCA) of Ye478, a widely used foundation parent in China. We developed three sets of populations for QTL mapping and to analyze the GCA for some agronomic traits. The assessment of 15 traits resulted in the detection of 251 QTLs in six tested environments, with 119 QTLs identified through a joint analysis across all environments. Further, analyses revealed that most favorable alleles for plant type-related traits were from Ye478, and more than half of the favorable alleles for yield-related traits were from R08, another foundation parent used in southwestern China, suggesting that different types of foundation parents carried different favorable alleles. We observed that the GCA for most traits (e.g., plant height and 100-kernel weight) was maintained in the inbred lines descended from the foundation parents. Additionally, the continuous improvement in the GCA of the descendants of the foundation parents was consistent with the main trend in maize breeding programs. We identified three significant genomic regions that were highly conserved in three Ye478 descendants, including the stable QTL for plant height. The GCA for the traits in the F₇ generation revealed that the QTLs for the given traits per se were affected by additive effects in the same way in different populations.

Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P

BACKGROUND

Modifications in root morphology are important strategies to maximize soil exploitation under phosphorus starvation in plants. Here, we used two multiple interval models to map QTLs related to root traits, biomass accumulation and P content in a maize RIL population cultivated in nutrient solution. In addition, we searched for putative maize homologs to PSTOL1, a gene responsible to enhance early root growth, P uptake and grain yield in rice and sorghum.

RESULTS

Based on path analysis, root surface area was the root morphology component that most strongly contributed to total dry weight and to P content in maize seedling under low-P availability. Multiple interval mapping models for single (MIM) and multiple traits (MT-MIM) were combined and revealed 13 genomic regions significantly associated with the target traits in a complementary way. The phenotypic variances explained by all QTLs and their epistatic interactions using MT-MIM (23.4 to 35.5 %) were higher than in previous studies, and presented superior statistical power. Some of these QTLs were coincident with QTLs for root morphology traits and grain yield previously mapped, whereas others harbored ZmPSTOL candidate genes, which shared more than 55 % of amino acid sequence identity and a conserved serine/threonine kinase domain with OsPSTOL1. Additionally, four ZmPSTOL candidate genes co-localized with QTLs for root morphology, biomass accumulation and/or P content were preferentially expressed in roots of the parental lines that contributed the alleles enhancing the respective phenotypes.

CONCLUSIONS

QTL mapping strategies adopted in this study revealed complementary results for single and multiple traits with high accuracy. Some QTLs, mainly the ones that were also associated with yield performance in other studies, can be good targets for marker-assisted selection to improve P-use efficiency in maize. Based on the co-localization with QTLs, the protein domain conservation and the coincidence of gene expression, we selected novel maize genes as putative homologs to PSTOL1 that will require further validation studies.

Mapping resistance to the bird cherry-oat aphid and the greenbug in wheat using sequence-based genotyping

Identification of novel resistance QTL against wheat aphids. First QTL-resistance report for R. padi in wheat and chromosome 2DL for S. graminum . These sources have potential use in wheat breeding. The aphids Rhopalosiphum padi and Schizaphis graminum are important pests of common wheat (Triticum aestivum L.). Characterization of the genetic bases of resistance sources is crucial to facilitate the development of resistant wheat cultivars to these insects. We examined 140 recombinant inbred lines (RILs) from the cross of Seri M82 wheat (susceptible) with the synthetic hexaploid wheat CWI76364 (resistant). RILs were phenotyped for R. padi antibiosis and tolerance traits. Phenotyping of S. graminum resistance was based on leaf chlorosis in a greenhouse screening and the number of S. graminum/tiller in the field. RILs were also scored for pubescence. Using a sequence-based genotyping method, we located genomic regions associated with these resistance traits. A quantitative trait locus (QTL) for R. padi antibiosis (QRp.slu.4BL) that explained 10.2 % of phenotypic variation was found in chromosome 4BL and located 14.6 cM apart from the pubescence locus. We found no association between plant pubescence and the resistance traits. We found two QTLs for R. padi tolerance (QRp.slu.5AL and QRp.slu.5BL) in chromosomes 5AL and 5BL, with an epistatic interaction between a locus in chromosome 3AL (EnQRp.slu.5AL) and QRp.slu.5AL. These genomic regions explained about 35 % of the phenotypic variation. We re-mapped a previously reported gene for S. graminum resistance (putatively Gba) in 7DL and found a novel QTL associated with the number of aphids/tiller (QGb.slu-2DL) in chromosome 2DL. This is the first report on the genetic mapping of R. padi resistance in wheat and the first report where chromosome 2DL is shown to be associated with S. graminum resistance.

A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana

When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F₁ sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could ‘mask’ the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F₁ hybrid sterility.