Detection Of Quantitative Trait Loci Research Articles

Pooled DNA sequencing in hairy vetch (Vicia villosa Roth) reveals QTL for seed dormancy but not pod dehiscence.

Hairy vetch (Vicia villosa Roth) is a promising legume cover crop, but its use is limited by high rates of pod dehiscence and seed dormancy. We used phenotypically contrasting pooled DNA samples (n=24 with 29-74 individuals per sample) from an ongoing cover crop breeding program across four environments (site-year combinations: Maryland 2020, Maryland 2022, Wisconsin 2021, Wisconsin 2022) to find genetic associations and genomic prediction accuracies for pod dehiscence and seed dormancy. We also combined pooled DNA sample genetic association results with the results of a prior genome-wide association study. Genomic prediction resulted in positive predictive abilities for both traits between environments and with an independent dataset (0.34-0.50), but reduced predictive ability for DNA pools with divergent seed dormancy in the Maryland environments (0.07-0.15). The pooled DNA samples found six significant (false discovery rate q-value<0.01) quantitative trait loci (QTL) for seed dormancy and four significant QTL for pod dehiscence. Unfortunately, the minor alleles of the pod dehiscence QTL increased the rate of pod dehiscence and are not useful for marker-assisted selection. When combined with a prior association study, sixteen seed dormancy QTL and zero pod dehiscence QTL were significant. Combining the association studies did not increase the detection of useful QTL.

Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields.

A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.

Genetic dissection of advanced soybean (Glycine max L.) germplasm for spring season cultivation in Pakistan

AbstractImprovement in genetic gains of crops could be achieved by phenomics' characterization of agronomic, physiological and stress-related traits. Molecular and strategic breeding programmes require broad range of foreground and background phenotypic information for crop improvement. The current experiment was performed on 123 advanced soybean (Glycine max L.) genotypes including seven local lines belongs to four different maturity groups (000-lV) to estimate the endogenous potential of various yield-related traits. The experimental trial was repeated for two cropping seasons. Four traits out of six, yield per plant (YPP), number of seeds per plant, number of pods per plant and plant height (PH), showed maximum variation (CV%) that directly correlate with variability in the subjected population. PH, number of pods, 100-seed weight and YPP showed strong positive correlation in both years. Among the principal components, factors 1 and 2 showed maximum contribution in phenotypic variability ranges from 19 to 48.5% and 26 to 47.7% in the first and second years, respectively. Number of pods showed significant positive correlation with genotypes in both years. Dendrogram showed two distinct groups of soybean genotypes. Genetic variation and association among the accessions is indispensable for effective conservation and utilization of germplasm. Principal component analysis helps to identify the diverse genotypes that will be used as a parent for various breeding programmes. These phenotypic data will be used for detection of heat stress-related quantitative trait loci with genotypic data in genome-wide association studies experiments.

Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping.

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Linkage mapping and quantitative trait loci detection for seedling vigor and grain size in advanced backcross introgression lines from wild accessions of Oryza nivara

Linkage mapping and quantitative trait loci detection for seedling vigor and grain size in advanced backcross introgression lines from wild accessions of Oryza nivara

Meta-analysis of GWAS for sea lice load in Atlantic salmon

Sea lice (Caligus rogercresseyi) are ectoparasites that cause significant production losses in the salmon aquaculture industry. Atlantic salmon (Salmo salar) is an important salmonid species for the aquaculture industry and highly susceptible to sea lice infestation. Sea lice load has been shown to be a polygenic trait, controlled by several quantitative trait loci (QTL) with small to medium effects. To improve the detection of QTL associated with sea lice load, we imputed single nucleotide polymorphism (SNP) data from medium- to high-density and conducted genome-wide association studies (GWAS). The imputation from 50 K to 600 K SNP genotypes was performed on 6144 fish from four different populations, which were challenged against sea lice. A metaGWAS was carried out for lice count, lice density, and log-transformed lice density. We identified two genomic regions highly associated with sea lice load on chromosomes (ssa) 3 and 12. Important functional candidate genes are mucin-16-like (ssa3), filamentous-growth-regulator 23-like (ssa3) and fibroblast growth factor receptor-like 1 (ssa12). Several other genes found here suggest that tissue repair, cytoskeletal modification and immune response may play an important role in the genetic variation of sea lice load. Our results confirm the highly polygenic architecture of sea lice load and provide novel insights into the genomic regions and candidate genes underlying the genetic variation for this trait in Atlantic salmon.

QTL Detection and Candidate Gene Identification for Eating and Cooking Quality Traits in Rice (Oryza sativa L.) via a Genome-Wide Association Study.

The eating and cooking quality (ECQ) directly affects the taste of rice, being closely related to factors such as gelatinization temperature (GT), gel consistency (GC) and amylose content (AC). Mining the quantitative trait loci (QTLs), and gene loci controlling ECQ-related traits is vital. A genome-wide association study on ECQ-related traits was conducted, combining 1.2 million single nucleotide polymorphisms (SNPs) with the phenotypic data of 173 rice accessions. Two QTLs for GT, one for GC and five for AC were identified, of which two were found in previously reported genes, and six were newly found. There were 28 positional candidate genes in the region of qAC11. Based on a linkage disequilibrium (LD) analysis, three candidate genes were screened within the LD region associated with AC. There were significant differences between the haplotypes of LOC_Os11g10170, but no significant differences were found for the other two genes. The qRT-PCR results showed that the gene expression levels in the accessions with high ACs were significantly larger than those in the accessions with low ACs at 35d and 42d after flowering. Hap 2 and Hap 3 of LOC_Os11g10170 reduced the AC by 13.09% and 10.77%, respectively. These results provide a theoretical and material basis for improving the ECQ of rice.

Tree-based QTL mapping with expected local genetic relatedness matrices

Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide association studies (GWASs) are a powerful way to find genetic loci associated with phenotypes. GWASs are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history. One way to model this shared history is through the ancestral recombination graph (ARG), which encodes a series of local coalescent trees. Recent computational and methodological breakthroughs have made it feasible to estimate approximate ARGs from large-scale samples. Here, we explore the potential of an ARG-based approach to quantitative-trait locus (QTL) mapping, echoing existing variance-components approaches. We propose a framework that relies on the conditional expectation of a local genetic relatedness matrix (local eGRM) given the ARG. Simulations show that our method is especially beneficial for finding QTLs in the presence of allelic heterogeneity. By framing QTL mapping in terms of the estimated ARG, we can also facilitate the detection of QTLs in understudied populations. We use local eGRM to analyze two chromosomes containing known body size loci in a sample of Native Hawaiians. Our investigations can provide intuition about the benefits of using estimated ARGs in population- and statistical-genetic methods in general.

Exploring horticultural traits and disease resistance in Capsicum baccatum through segmental introgression lines.

Segmental introgression and advanced backcross lines were developed and validated as important tools for improving agronomically important traits in pepper, offering improved sensitivity in detecting quantitative trait loci for breeding. Segmental introgression lines (SILs) and advanced backcross lines (ABs) can accelerate genetics and genomics research and breeding in crop plants. This study presents the development of a complete collection of SILs and ABs in pepper using Capsicum annuum cv. 'CM334' as the recipient parent and Capsicum baccatum 'PBC81', which displays various agronomically important traits including powdery mildew and anthracnose resistance, as donor parent. Using embryo rescue to overcome abortion in interspecific crosses, and marker-assisted selection with genotyping-in-thousands by sequencing (GT-seq) to develop SILs and ABs containing different segments of the C. baccatum genome, we obtained 63 SILs and 44 ABs, covering 94.8% of the C. baccatum genome. We characterized them for traits including powdery mildew resistance, anthracnose resistance, anthocyanin accumulation, trichome density, plant architecture, and fruit morphology. We validated previously known loci for these traits and discovered new sources of variation and quantitative trait loci (QTLs). A total of 15 QTLs were identified, including four for anthracnose resistance with three novel loci, seven for plant architecture, and four for fruit morphology. This is the first complete collection of pepper SILs and ABs validated for agronomic traits and will enhance QTL detection and serve as valuable breeding resources. Further, these SILs and ABs will be useful for comparative genomics and to better understand the genetic mechanisms underlying important agronomic traits in pepper, ultimately leading to improved crop productivity and sustainability.

A derived weedy rice × ancestral cultivar cross identifies evolutionarily relevant weediness QTLs.

Weedy rice (Oryza spp.) is a weedy relative of the cultivated rice that competes with the crop and causes significant production loss. The BHA (blackhull awned) US weedy rice group has evolved from aus cultivated rice and differs from its ancestors in several important weediness traits, including flowering time, plant height and seed shattering. Prior attempts to determine the genetic basis of weediness traits in plants using linkage mapping approaches have not often considered weed origins. However, the timing of divergence between crossed parents can affect the detection of quantitative trait loci (QTL) relevant to the evolution of weediness. Here, we used a QTL-seq approach that combines bulked segregant analysis and high-throughput whole genome resequencing to map the three important weediness traits in an F2 population derived from a cross between BHA weedy rice with an ancestral aus cultivar. We compared these QTLs with those previously detected in a cross of BHA with a more distantly related crop, indica. We identified multiple QTLs that overlapped with regions under selection during the evolution of weedy BHA rice and some candidate genes possibly underlying the evolution weediness traits in BHA. We showed that QTLs detected with ancestor-descendant crosses are more likely to be involved in the evolution of weediness traits than those detected from crosses of more diverged taxa.

Inheritance and Quantitative Trait Loci Mapping of Aromatic Compounds from Clementine (Citrus × clementina Hort. ex Tan.) and Sweet Orange (C. × sinensis (L.) Osb.) Fruit Essential Oils.

Despite their importance in food processing, perfumery and cosmetics, the inheritance of sweet orange aromatic compounds, as well as their yield in the fruit peel, has been little analyzed. In the present study, the segregation of aromatic compounds was studied in an F1 population of 77 hybrids resulting from crosses between clementine and blood sweet orange. Fruit-peel essential oils (PEOs) extracted by hydrodistillation were analyzed by gas chromatography coupled with flame ionization detection. Genotyping by sequencing was performed on the parents and the hybrids. The resulting "clementine × sweet blood orange" genetic map consists of 710 SNP markers distributed in nine linkage groups (LGs), representing the nine citrus chromosomes, and spanning 1054 centimorgans. Twenty quantitative trait loci (QTLs) were identified, explaining between 20.5 and 55.0% of the variance of the major aromatic compounds and PEO yield. The QTLs for monoterpenes and aliphatic aldehydes predominantly colocalized on LGs 5 and 8, as did the two QTLs for PEO yield. The sesquiterpene QTLs were located on LGs 1, 3, 6 and 8. The detection of major QTLs associated with the synthesis of aliphatic aldehydes, known for their strong aromatic properties, open the way for marker-assisted selection.

Genetics of evolved load resistance in the skeletons of unusually large mice from Gough Island.

A primary function of the skeleton is to resist the loads imparted by body weight. Genetic analyses have identified genomic regions that contribute to differences in skeletal load resistance between laboratory strains of mice, but these studies are usually restricted to 1 or 2 bones and leave open the question of how load resistance evolves in natural populations. To address these challenges, we examined the genetics of bone structure using the largest wild house mice on record, which live on Gough Island (GI). We measured structural traits connected to load resistance in the femur, tibia, scapula, humerus, radius, ulna, and mandible of GI mice, a smaller-bodied reference strain from the mainland, and 760 of their F2s. GI mice have bone geometries indicative of greater load resistance abilities but show no increase in bone mineral density compared to the mainland strain. Across traits and bones, we identified a total of 153 quantitative trait loci (QTL) that span all but one of the autosomes. The breadth of QTL detection ranges from a single bone to all 7 bones. Additive effects of QTL are modest. QTL for bone structure show limited overlap with QTL for bone length and width and QTL for body weight mapped in the same cross, suggesting a distinct genetic architecture for load resistance. Our findings provide a rare genetic portrait of the evolution of load resistance in a natural population with extreme body size.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.

Symbiotic Variations among Wheat Genotypes and Detection of Quantitative Trait Loci for Molecular Interaction with Auxin-Producing Azospirillum PGPR.

Crop varieties differ in their ability to interact with Plant Growth-Promoting Rhizobacteria (PGPR), but the genetic basis for these differences is unknown. This issue was addressed with the PGPR Azospirillum baldaniorum Sp245, using 187 wheat accessions. We screened the accessions based on the seedling colonization by the PGPR and the expression of the phenylpyruvate decarboxylase gene ppdC (for synthesis of the auxin indole-3-acetic acid), using gusA fusions. Then, the effects of the PGPR on the selected accessions stimulating Sp245 (or not) were compared in soil under stress. Finally, a genome-wide association approach was implemented to identify the quantitative trait loci (QTL) associated with PGPR interaction. Overall, the ancient genotypes were more effective than the modern genotypes for Azospirillum root colonization and ppdC expression. In non-sterile soil, A. baldaniorum Sp245 improved wheat performance for three of the four PGPR-stimulating genotypes and none of the four non-PGPR-stimulating genotypes. The genome-wide association did not identify any region for root colonization but revealed 22 regions spread on 11 wheat chromosomes for ppdC expression and/or ppdC induction rate. This is the first QTL study focusing on molecular interaction with PGPR bacteria. The molecular markers identified provide the possibility to improve the capacity of modern wheat genotypes to interact with Sp245, as well as, potentially, other Azospirillum strains.

Multi-parental fungal mapping population study to detect genomic regions associated with Pyrenophora teres f. teres virulence

In recent years multi-parental mapping populations (MPPs) have been widely adopted in many crops to detect quantitative trait loci (QTLs) as this method can compensate for the limitations of QTL analyses using bi-parental mapping populations. Here we report the first multi-parental nested association mapping (MP-NAM) population study used to detect genomic regions associated with host-pathogenic interactions. MP-NAM QTL analyses were conducted on 399 Pyrenophora teres f. teres individuals using biallelic, cross-specific and parental QTL effect models. A bi-parental QTL mapping study was also conducted to compare the power of QTL detection between bi-parental and MP-NAM populations. Using MP-NAM with 399 individuals detected a maximum of eight QTLs with a single QTL effect model whilst only a maximum of five QTLs were detected with an individual bi-parental mapping population of 100 individuals. When reducing the number of isolates in the MP-NAM to 200 individuals the number of QTLs detected remained the same for the MP-NAM population. This study confirms that MPPs such as MP-NAM populations can be successfully used in detecting QTLs in haploid fungal pathogens and that the power of QTL detection with MPPs is greater than with bi-parental mapping populations.

Ecological genetics of local adaptation in Arabidopsis: An 8-year field experiment.

There is considerable evidence for local adaptation in nature, yet important questions remain regarding its genetic basis. How many loci are involved? What are their effect sizes? What is the relative importance of conditional neutrality versus genetic trade-offs? Here we address these questions in the self-pollinating, annual plant Arabidopsis thaliana. We used 400 recombinant inbred lines (RILs) derived from two locally adapted populations in Italy and Sweden, grew the RILs and parents at the parental locations, and mapped quantitative trait loci (QTL) for mean fitness (fruits/seedling planted). We previously published results from the first 3 years of the study, and here add five additional years, providing a unique opportunity to assess how temporal variation in selection might affect QTL detection and classification. We found 10 adaptive and one maladaptive QTL in Italy, and six adaptive and four maladaptive QTL in Sweden. The discovery of maladaptive QTL at both sites suggests that even locally adapted populations are not always at their genotypic optimum. Mean effect sizes for adaptive QTL, 0.97 and 0.55 fruits in Italy and Sweden, respectively, were large relative to the mean fitness of the RILs (approximately 8 fruits/seedling planted at both sites). Both genetic trade-offs (four cases) and conditional neutrality (seven cases) contribute to local adaptation in this system. The 8-year dataset provided greater power to detect QTL and to estimate their locations compared to our previous 3-year study, identifying one new genetic trade-off and resolving one genetic trade-off into two conditionally adaptive QTL.

Population size in QTL detection using quantile regression in genome-wide association studies

The aim of this study was to evaluate the performance of Quantile Regression (QR) in Genome-Wide Association Studies (GWAS) regarding the ability to detect QTLs (Quantitative Trait Locus) associated with phenotypic traits of interest, considering different population sizes. For this, simulated data was used, with traits of different levels of heritability (0.30 and 0.50), and controlled by 3 and 100 QTLs. Populations of 1,000 to 200 individuals were defined, with a random reduction of 100 individuals for each population. The power of detection of QTLs and the false positive rate were obtained by means of QR considering three different quantiles (0.10, 0.50 and 0.90) and also by means of the General Linear Model (GLM). In general, it was observed that the QR models showed greater power of detection of QTLs in all scenarios evaluated and a relatively low false positive rate in scenarios with a greater number of individuals. The models with the highest detection power of true QTLs at the extreme quantils (0.10 and 0.90) were the ones with the highest detection power of true QTLs. In contrast, the analysis based on the GLM detected few (scenarios with larger population size) or no QTLs in the evaluated scenarios. In the scenarios with low heritability, QR obtained a high detection power. Thus, it was verified that the use of QR in GWAS is effective, allowing the detection of QTLs associated with traits of interest even in scenarios with few genotyped and phenotyped individuals.

Development of SSR Molecular Markers and Genetic Diversity Analysis of TPS Gene Family in Chimonanthus praecox

Terpene synthase (TPS) plays a key role in the biosynthesis of terpenoids, which are the most important components of the volatile compounds of wintersweet (Chimonanthus praecox). In this study, 52 CpTPS genes were found in wintersweet which were divided into 5 subfamilies. We identified 146 SSRs in the CpTPS genes, and obtained 33 pairs of SSR primers with good polymorphism through amplification in 6 wintersweet samples. Then, these primers were amplified in 69 samples from China’s main wintersweet production areas. Through structural analysis, 69 samples were divided into 2 clusters, and were divided into 4 groups in a genetic cluster analysis, of which SH-33 and SW were separate groups. Through AMOVA analysis, it was found that the variation mainly occurred in the population, and that the gene flow between populations was Nm &gt; 1, so it might lead to population differentiation. In other words, these findings provided useful information for the biosynthesis of terpenoids, the construction of a genetic linkage map, the detection of quantitative trait loci, marker-assisted selection and other aspects of wintersweet.

Meiotic Behaviors of Allotetraploid Citrus Drive the Interspecific Recombination Landscape, the Genetic Structures, and Traits Inheritance in Tetrazyg Progenies Aiming to Select New Rootstocks.

Sexual breeding at the tetraploid level is a promising strategy for rootstock breeding in citrus. Due to the interspecific origin of most of the conventional diploid citrus rootstocks that produced the tetraploid germplasm, the optimization of this strategy requires better knowledge of the meiotic behavior of the tetraploid parents. This work used Genotyping By Sequencing (GBS) data from 103 tetraploid hybrids to study the meiotic behavior and generate a high-density recombination landscape for their tetraploid intergenic Swingle citrumelo and interspecific Volkamer lemon progenitors. A genetic association study was performed with root architecture traits. For citrumelo, high preferential chromosome pairing was revealed and led to an intermediate inheritance with a disomic tendency. Meiosis in Volkamer lemon was more complex than that of citrumelo, with mixed segregation patterns from disomy to tetrasomy. The preferential pairing resulted in low interspecific recombination levels and high interspecific heterozygosity transmission by the diploid gametes. This meiotic behavior affected the efficiency of Quantitative Trait Loci (QTL) detection. Nevertheless, it enabled a high transmission of disease and pest resistance candidate genes from P. trifoliata that are heterozygous in the citrumelo progenitor. The tetrazyg strategy, using doubled diploids of interspecific origin as parents, appears to be efficient in transferring the dominant traits selected at the parental level to the tetraploid progenies.

Combined QTL mapping on bi-parental immortalized heterozygous populations to detect the genetic architecture on heterosis.

From bi-parental pure-inbred lines (PIL), immortalized backcross (i.e., IB1 and IB2, representing the two directions of backcrossing) and F2 (i.e., IF2) populations can be developed. These populations are suitable for genetic studies on heterosis, due to the present of both homozygous and heterozygous genotypes, and in the meantime allow repeated phenotyping trials across multiple locations and years. In this study, we developed a combined approach of quantitative trait locus (QTL) mapping, when some or all of the four immortalized populations (i.e., PIL, IB1, IB2, and IF2) are available. To estimate the additive and dominant effects simultaneously and accurately, suitable transformations are made on phenotypic values from different populations. When IB1 and IB2 are present, summation and subtraction are used. When IF2 and PIL are available, mid-parental values and mid-parental heterosis are used. One-dimensional genomic scanning is performed to detect the additive and dominant QTLs, based on the algorithm of inclusive composite interval mapping (ICIM). The proposed approach was applied to one IF2 population together with PIL in maize, and identified ten QTLs on ear length, showing varied degrees of dominance. Simulation studies indicated the proposed approach is similar to or better than individual population mapping by QTL detection power, false discovery rate (FDR), and estimated QTL position and effects.