Large-effect Quantitative Trait Loci Research Articles

QTL Mapping for Agronomic Important Traits in Well-Adapted Wheat Cultivars

Wheat (Triticum aestivum L.) is one of the most important food crops worldwide and provides the staple food for 40% of the world’s population. Increasing wheat production has become an important goal to ensure global food security. The grain yield of wheat is a complex trait that is usually influenced by multiple agronomically important traits. Thus, the genetic dissection and discovery of quantitative trait loci (QTL) of wheat-yield-related traits are very important to develop high-yield cultivars to improve wheat production. To analyze the genetic basis and discover genes controlling important agronomic traits in wheat, a recombinant inbred lines (RILs) population consisting of 180 RILs derived from a cross between Xinong822 (XN822) and Yannong999 (YN999), two well-adapted cultivars, was used to map QTL for plant height (PH), spike number per spike (SNS), spike length (SL), grain number per spike (GNS), spike number per plant (SN), 1000- grain weight (TGW), grain length (GL), grain width (GW), length/width of grain (GL/GW), perimeter of grain (Peri), and surface area of grains (Sur) in three environments. A total of 64 QTL were detected and distributed on all wheat chromosomes except 3A and 5A. The identified QTL individually explained 2.24–38.24% of the phenotypic variation, with LOD scores ranging from 2.5 to 29. Nine of these QTL were detected in multiple environments, and seven QTL were associated with more than one trait. Additionally, Kompetitive Allele Specific PCR (KASP) assays for five major QTL QSns-1A.2 (PVE = 6.82), QPh-2D.1 (PVE = 37.81), QSl-2D (PVE = 38.24), QTgw-4B (PVE = 8.78), and QGns-4D (PVE = 13.54) were developed and validated in the population. The identified QTL and linked markers are highly valuable in improving wheat yield through marker-assisted breeding, and the large-effect QTL can be fine-mapped for further QTL cloning of yield-related traits in wheat.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.).

Chestnut blight (caused by Cryphonectria parasitica), together with Phytophthora root rot (caused by Phytophthora cinnamomi), has nearly extirpated American chestnut (Castanea dentata) from its native range. In contrast to the susceptibility of American chestnut, many Chinese chestnut (C. mollissima) genotypes are resistant to blight. In this research, we performed a series of genome-wide association studies for blight resistance originating from three unrelated Chinese chestnut trees (Mahogany, Nanking and M16) and a Quantitative Trait Locus (QTL) study on a Mahogany-derived inter-species F2 family. We evaluated trees for resistance to blight after artificial inoculation with two fungal strains and scored nine morpho-phenological traits that are the hallmarks of species differentiation between American and Chinese chestnuts. Results support a moderately complex genetic architecture for blight resistance, as 31 QTLs were found on 12 chromosomes across all studies. Additionally, although most morpho-phenological trait QTLs overlap or are adjacent to blight resistance QTLs, they tend to aggregate in a few genomic regions. Finally, comparison between QTL intervals for blight resistance and those previously published for Phytophthora root rot resistance, revealed five common disease resistance regions on chromosomes 1, 5, and 11. Our results suggest that it will be difficult, but still possible to eliminate Chinese chestnut alleles for the morpho-phenological traits while achieving relatively high blight resistance in a backcross hybrid tree. We see potential for a breeding scheme that utilizes marker-assisted selection early for relatively large effect QTLs followed by genome selection in later generations for smaller effect genomic regions.

Genetic Architecture of Body Fat Composition in Mice

Body fat composition is a quantitative measure of obesity, a major health concern in humans. Laboratory mice are considered an excellent model for dissecting the genetic basis of obesity due to the genetic variation present in inbred strains for body size and fat composition, as well as their historical use as a model organism for human disease studies. To identify the loci controlling fat pad weights and body weight in mice, we performed a quantitative trait loci (QTL) analysis of 513 (SM/J x NZB/BINJ) F2 individuals fed a high-fat diet for 14 weeks. Our analysis separated fat composition genetic effects from those affecting overall body sizes in mouse. Composite interval mapping (CIM) results showed that body weight was conditioned by three major additive QTLs, explaining 3 to 30% of the phenotypic variation. One significant QTL on chromosome 19 conditioned all fat pads with the exception of the inguinal fat weight, which was controlled by a different QTL also on chromosome 19. Significant QTLs associated with fat compositions were detected on chromosomes 17 and 19 and differed from those of body weight. The fat pad QTLs also showed mainly additive gene effects and they explained 2 to 7% of variation in fat composition. Joint analysis of correlated traits detected five additional large effect QTLs on five different linkage groups. These findings have indicated that fat composition and body weight in mouse are conditioned by one to three major additive genes and can therefore be potentially manipulated in controlling obesity.

Identification of QTL associated with resistance to Phytophthora fruit rot in cucumber (Cucumis sativus L.).

Phytophthora fruit rot (PFR) caused by the soilborne oomycete pathogen, Phytophthora capsici, can cause severe yield loss in cucumber. With no resistant variety available, genetic resources are needed to develop resistant varieties. The goal of this work was to identify quantitative trait loci (QTL) associated with resistance to PFR using multiple genomic approaches and populations. Two types of resistances have been identified: age-related resistance (ARR) and young fruit resistance. ARR occurs at 12-16 days post pollination (dpp), coinciding with the end of exponential fruit growth. A major QTL for ARR was discovered on chromosome 3 and a candidate gene identified based on comparative transcriptomic analysis. Young fruit resistance, which is observed during the state of rapid fruit growth prior to commercial harvest, is a quantitative trait for which multiple QTL were identified. The largest effect QTL, qPFR5.1, located on chromosome 5 was fine mapped to a 1-Mb region. Genome-wide association studies (GWAS) and extreme-phenotype genome-wide association study (XP-GWAS) for young fruit resistance were also performed on a cucumber core collection representing > 96% of the genetic diversity of the USDA cucumber germplasm. Several SNPs overlapped with the QTL identified from QTL-seq analysis on biparental populations. In addition, novel SNPs associated with the resistance were identified from the germplasm. The resistant alleles were found mostly in accessions from India and South Asia, the center of diversity for cucumber. The results from this work can be applied to future disease resistance studies and marker-assisted selection in breeding programs.

EQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

High-density genetic mapping of Fusarium head blight resistance and agronomic traits in spring wheat.

Fusarium head blight (FHB) has rapidly become a major challenge to successful wheat production and competitive end-use quality in western Canada. Continuous effort is required to develop germplasm with improved FHB resistance and understand how to incorporate the material into crossing schemes for marker-assisted selection and genomic selection. The aim of this study was to map quantitative trait loci (QTL) responsible for the expression of FHB resistance in two adapted cultivars and to evaluate their co-localization with plant height, days to maturity, days to heading, and awnedness. A large doubled haploid population of 775 lines developed from cultivars Carberry and AC Cadillac was assessed for FHB incidence and severity in nurseries near Portage la Prairie, Brandon, and Morden in different years, and for plant height, awnedness, days to heading, and days to maturity near Swift Current. An initial linkage map using a subset of 261 lines was constructed using 634 polymorphic DArT and SSR markers. QTL analysis revealed five resistance QTL on chromosomes 2A, 3B (two loci), 4B, and 5A. A second genetic map with increased marker density was constructed using the Infinium iSelect 90k SNP wheat array in addition to the previous DArT and SSR markers, which revealed two additional QTL on 6A and 6D. The complete population was genotyped, and a total of 6,806 Infinium iSelect 90k SNP polymorphic markers were used to identify 17 putative resistance QTL on 14 different chromosomes. As with the smaller population size and fewer markers, large-effect QTL were detected on 3B, 4B, and 5A that were consistently expressed across environments. FHB resistance QTL were co-localized with plant height QTL on chromosomes 4B, 6D, and 7D; days to heading on 2B, 3A, 4A, 4B, and 5A; and maturity on 3A, 4B, and 7D. A major QTL for awnedness was identified as being associated with FHB resistance on chromosome 5A. Nine small-effect QTL were not associated with any of the agronomic traits, whereas 13 QTL that were associated with agronomic traits did not co-localize with any of the FHB traits. There is an opportunity to select for improved FHB resistance within adapted cultivars by using markers associated with complementary QTL.

Genomewide selection for fruit quality traits in apple: breeding insights gained from prediction and postdiction.

Many fruit quality traits in apple (Malus domestica Borkh.) are controlled by multiple small-effect quantitative trait loci (QTLs). Genomewide selection (genomic selection) might be an effective breeding approach for highly quantitative traits in woody perennial crops with long generation times like apple. The goal of this study was to determine if genomewide prediction is an effective breeding approach for fruit quality traits in an apple scion breeding program. Representative apple scion breeding germplasm (nindividuals= 955), high-quality single nucleotide polymorphism (SNP) data (nSNPs= 977), and breeding program fruit quality trait data at harvest were analyzed. Breeding parents `Honeycrisp' and `Minneiska' were highly represented. Moderate to high predictive abilities were observed for most fruit quality traits at harvest. For example, when 25% random subsets of the germplasm set were used as training sets, mean predictive abilities ranged from 0.35 to 0.54 across traits. Trait, training and test sets, family size for within family prediction, and number of SNPs per chromosome affected model predictive ability. Inclusion of large-effect QTLs as fixed effects resulted in higher predictive abilities for some traits (e.g. percent red overcolor). Postdiction (i.e. retrospective) analyses demonstrated the impact of culling threshold on selection decisions. The results of this study demonstrate that genomewide selection is a useful breeding approach for certain fruit quality traits in apple.

Genetic dissection of QTLs for oil content in four maize DH populations.

Oil is one of the main components in maize kernels. Increasing the total oil content (TOC) is favorable to optimize feeding requirement by improving maize quality. To better understand the genetic basis of TOC, quantitative trait loci (QTL) in four double haploid (DH) populations were explored. TOC exhibited continuously and approximately normal distribution in the four populations. The moderate to high broad-sense heritability (67.00-86.60%) indicated that the majority of TOC variations are controlled by genetic factors. A total of 16 QTLs were identified across all chromosomes in a range of 3.49-30.84% in term of phenotypic variation explained. Among them, six QTLs were identified as the major QTLs that explained phenotypic variation larger than 10%. Especially, qOC-1-3 and qOC-2-3 on chromosome 9 were recognized as the largest effect QTLs with 30.84% and 21.74% of phenotypic variance, respectively. Seventeen well-known genes involved in fatty acid metabolic pathway located within QTL intervals. These QTLs will enhance our understanding of the genetic basis of TOC in maize and offer prospective routes to clone candidate genes regulating TOC for breeding program to cultivate maize varieties with the better grain quality.

Genotype-by-environment and QTL-by-environment interactions in sweet cherry (Prunus avium L.) for flowering date

In sweet cherry (Prunus avium L.), flowering date is strongly dependent on the environment conditions and, therefore, is a trait of major interest for adaptation to climate change. Such trait can be influenced by genotype-by-environment interaction (G×E), that refers to differences in the response of genotypes to different environments. If not taken into account, G×E can reduce selection accuracy and overall genetic gain. However, little is known about G×E in fruit tree species. Flowering date is a highly heritable and polygenic trait for which many quantitative trait loci (QTLs) have been identified. As for the overall genetic performance, differential expression of QTLs in response to environment (QTL-by-environment interaction, QTL×E) can occur. The present study is based on the analysis of a multi-environment trial (MET) suitable for the study of G×E and QTL×E in sweet cherry. It consists of a sweet cherry F1 full-sib family (n = 121) derived from the cross between cultivars 'Regina' and 'Lapins' and planted in two copies in five locations across four European countries (France, Italy, Slovenia and Spain) covering a large range of climatic conditions. The aim of this work was to study the effect of the environment on flowering date and estimate G×E, to carry QTL detection in different environments in order to study the QTL stability across environments and to estimate QTL×E. A strong effect of the environment on flowering date and its genetic control was highlighted. Two large-effect and environment-specific QTLs with significant QTL×E were identified on linkage groups (LGs) 1 and 4. This work gives new insights into the effect of the environment on a trait of main importance in one of the most economically important fruit crops in temperate regions. Moreover, molecular markers were developed for flowering date and a strategy consisting in using specific markers for warm or cold regions was proposed to optimize marker-assisted selection (MAS) in sweet cherry breeding programs.

Identification of chromosome regions for high-temperature tolerance in the japonica rice cultivar ‘Genkitsukushi’ (Oryza sativa L.)

ABSTRACT Degradation of the appearance of rice grains due to high temperatures during ripening is a serious problem being worsened by global warming. QTLs for tolerance to high temperature during ripening must be identified in order to develop new cultivars efficiently. Here, we developed recombinant inbred lines (RILs) from crosses between the high-temperature-tolerant ‘Genkitsukushi’ and the high-temperature-sensitive ‘Tsukushiroman’. The occurrence of white-back grains is significantly lower in ‘Genkitsukushi’ than in ‘Tsukushiroman’. We evaluated their high-temperature tolerance and performed quantitative trait locus (QTL) analysis. A QTL for white-back grains on chromosome (chr.) 6 and a large-effect QTL on chr. 8 were identified in the two-year experiments. The QTL on chr. 8 was close to one we previously detected using RILs derived from ‘Chikushi 52’ × ‘Tsukushiroman’. The results indicate that the QTL on chr. 6 is unique to ‘Genkitsukushi’ × ‘Tsukushiroman’, and that on chr. 8 could be identical between ‘Genkitsukushi’ and ‘Chikushi 52’. Backcrossed lines which harbor the QTL region on chr. 8 of ‘Genkitsukushi’ in the background of ‘Tsukushiroman’ verified its effects. We also analyzed the marker genotypes near the QTLs on chr. 6 and 8 in relatives of ‘Genkitsukushi’. We discuss the interaction between these QTLs and their relationship with high-temperature tolerance.

Multi-environment genomic prediction for soluble solids content in peach (Prunus persica).

Genotype-by-environment interaction (G × E) is a common phenomenon influencing genetic improvement in plants, and a good understanding of this phenomenon is important for breeding and cultivar deployment strategies. However, there is little information on G × E in horticultural tree crops, mostly due to evaluation costs, leading to a focus on the development and deployment of locally adapted germplasm. Using sweetness (measured as soluble solids content, SSC) in peach/nectarine assessed at four trials from three US peach-breeding programs as a case study, we evaluated the hypotheses that (i) complex data from multiple breeding programs can be connected using GBLUP models to improve the knowledge of G × E for breeding and deployment and (ii) accounting for a known large-effect quantitative trait locus (QTL) improves the prediction accuracy. Following a structured strategy using univariate and multivariate models containing additive and dominance genomic effects on SSC, a model that included a previously detected QTL and background genomic effects was a significantly better fit than a genome-wide model with completely anonymous markers. Estimates of an individual’s narrow-sense and broad-sense heritability for SSC were high (0.57–0.73 and 0.66–0.80, respectively), with 19–32% of total genomic variance explained by the QTL. Genome-wide dominance effects and QTL effects were stable across environments. Significant G × E was detected for background genome effects, mostly due to the low correlation of these effects across seasons within a particular trial. The expected prediction accuracy, estimated from the linear model, was higher than the realised prediction accuracy estimated by cross-validation, suggesting that these two parameters measure different qualities of the prediction models. While prediction accuracy was improved in some cases by combining data across trials, particularly when phenotypic data for untested individuals were available from other trials, this improvement was not consistent. This study confirms that complex data can be combined into a single analysis using GBLUP methods to improve understanding of G × E and also incorporate known QTL effects. In addition, the study generated baseline information to account for population structure in genomic prediction models in horticultural crop improvement.

Genomic and gene expression associations to morphology of a sexual ornament in the chicken.

How sexual selection affects the genome ultimately relies on the strength and type of selection, and the genetic architecture of the involved traits. While associating genotype with phenotype often utilizes standard trait morphology, trait representations in morphospace using geometric morphometric approaches receive less focus in this regard. Here, we identify genetic associations to a sexual ornament, the comb, in the chicken system (Gallus gallus). Our approach combined genome-wide genotype and gene expression data (>30k genes) with different aspects of comb morphology in an advanced intercross line (F8) generated by crossing a wild-type Red Junglefowl with a domestic breed of chicken (White Leghorn). In total, 10 quantitative trait loci were found associated to various aspects of comb shape and size, while 1,184 expression QTL were found associated to gene expression patterns, among which 98 had overlapping confidence intervals with those of quantitative trait loci. Our results highlight both known genomic regions confirming previous records of a large effect quantitative trait loci associated to comb size, and novel quantitative trait loci associated to comb shape. Genes were considered candidates affecting comb morphology if they were found within both confidence intervals of the underlying quantitative trait loci and eQTL. Overlaps between quantitative trait loci and genome-wide selective sweeps identified in a previous study revealed that only loci associated to comb size may be experiencing on-going selection under domestication.

Genome-wide association identifies a missing hydrolase for tocopherol synthesis in plants

The tocopherol biosynthetic pathway, encoded by VTE genes 1 through 6, is highly conserved in plants but most large effect quantitative trait loci for seed total tocopherols (totalT) lack VTE genes, indicating other activities are involved. A genome-wide association study of Arabidopsis seed tocopherols showed five of seven significant intervals lacked VTE genes, including the most significant, which mapped to an uncharacterized, seed-specific, envelope-localized, alpha/beta hydrolase with esterase activity, designated AtVTE7. Atvte7 null mutants decreased seed totalT 55% while a leaky allele of the maize ortholog, ZmVTE7, decreased kernel and leaf totalT 38% and 49%, respectively. Overexpressing AtVTE7 or ZmVTE7 partially or fully complemented the Atvte7 seed phenotype and increased leaf totalT by 3.6- and 6.9-fold, respectively. VTE7 has the characteristics of an esterase postulated to provide phytol from chlorophyll degradation for tocopherol synthesis, but bulk chlorophyll levels were unaffected in vte7 mutants and overexpressing lines. Instead, levels of specific chlorophyll biosynthetic intermediates containing partially reduced side chains were impacted and strongly correlated with totalT. These intermediates are generated by a membrane-associated biosynthetic complex containing protochlorophyllide reductase, chlorophyll synthase, geranylgeranyl reductase (GGR) and light harvesting-like 3 protein, all of which are required for both chlorophyll and tocopherol biosynthesis. We propose a model where VTE7 releases prenyl alcohols from chlorophyll biosynthetic intermediates, which are then converted to the corresponding diphosphates for tocopherol biosynthesis.

Genomic and Transcriptomic Dissection of the Large-Effect Loci Controlling Drought-Responsive Agronomic Traits in Wheat

Drought tolerance is one of the most important targets for wheat breeding. Previous population genetics studies have uncovered 20 large-effect quantitative trait loci (QTLs) that contribute to stress-responsive agronomic traits. Here, we identified 19,035,814 single nucleotide polymorphisms and 719,049 insertion/deletion variations in the genomes of two popular winter wheat cultivars, Lu-Mai 14 and Han-Xuan 10, using a whole-genome re-sequencing assay. There were 4972 loss-of-function mutations carried by protein-coding genes, such as CCA1/LHY, AGO1, ABI3/VP1, EIN3, TPP, and ARFs. We carried out a time-course abscisic acid (ABA)-treatment experiment and profiled 61,251 expressed genes in the roots using a strand-specific RNA sequencing approach. A large number of genes showed time-point specific and/or cultivar-preferential responsive expression patterns. Gene ontology enrichment analysis revealed that ABA-responsive genes were associated with stress-related functions. Among the 20 QTLs, we uncovered 306 expressed genes with high- and/or moderate-effect variations and 472 differentially expressed genes. Detailed analysis and verification of the homozygous genomic variations in the candidate genes encoding sulfotransferase, proteinase, kinase, nitrate transporter, and transcription factors suggested previously unexpected pathways associated with abiotic stress responses in wheat.

Optimizing Plant Breeding Programs for Genomic Selection

Plant geneticists and breeders have used marker technology since the 1980s in quantitative trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but has been challenging to use with quantitative traits controlled by multiple minor effect alleles. Therefore, genomic selection (GS) was proposed to estimate all markers simultaneously, thereby capturing all their effects. However, breeding programs are still struggling to identify the best strategy to implement it into their programs. Traditional breeding programs need to be optimized to implement GS effectively. This review explores the optimization of breeding programs for variety release based on aspects of the breeder’s equation. Optimizations include reorganizing field designs, training populations, increasing the number of lines evaluated, and leveraging the large amount of genomic and phenotypic data collected across different growing seasons and environments to increase heritability estimates, selection intensity, and selection accuracy. Breeding programs can leverage their phenotypic and genotypic data to maximize genetic gain and selection accuracy through GS methods utilizing multi-trait and, multi-environment models, high-throughput phenotyping, and deep learning approaches. Overall, this review describes various methods that plant breeders can utilize to increase genetic gains and effectively implement GS in breeding.

Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci

BackgroundDeleterious recessive conditions have been primarily studied in the context of Mendelian diseases. Recently, several deleterious recessive mutations with large effects were discovered via non-additive genome-wide association studies (GWAS) of quantitative growth and developmental traits in cattle, which showed that quantitative traits can be used as proxies of genetic disorders when such traits are indicative of whole-animal health status. We reasoned that lactation traits in cattle might also reflect genetic disorders, given the increased energy demands of lactation and the substantial stresses imposed on the animal. In this study, we screened more than 124,000 cows for recessive effects based on lactation traits.ResultsWe discovered five novel quantitative trait loci (QTL) that are associated with large recessive impacts on three milk yield traits, with these loci presenting missense variants in the DOCK8, IL4R, KIAA0556, and SLC25A4 genes or premature stop variants in the ITGAL, LRCH4, and RBM34 genes, as candidate causal mutations. For two milk composition traits, we identified several previously reported additive QTL that display small dominance effects. By contrasting results from milk yield and milk composition phenotypes, we note differing genetic architectures. Compared to milk composition phenotypes, milk yield phenotypes had lower heritabilities and were associated with fewer additive QTL but had a higher non-additive genetic variance and were associated with a higher proportion of loci exhibiting dominance.ConclusionsWe identified large-effect recessive QTL which are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits, with yield phenotypes acting as a better proxy of underlying biological disorders through presentation of a larger number of major recessive impacts.

A toolkit to rapidly modify root systems through single plant selection

BackgroundThe incorporation of root traits into elite germplasm is typically a slow process. Thus, innovative approaches are required to accelerate research and pre-breeding programs targeting root traits to improve yield stability in different environments and soil types. Marker-assisted selection (MAS) can help to speed up the process by selecting key genes or quantitative trait loci (QTL) associated with root traits. However, this approach is limited due to the complex genetic control of root traits and the limited number of well-characterised large effect QTL. Coupling MAS with phenotyping could increase the reliability of selection. Here we present a useful framework to rapidly modify root traits in elite germplasm. In this wheat exemplar, a single plant selection (SPS) approach combined three main elements: phenotypic selection (in this case for seminal root angle); MAS using KASP markers (targeting a root biomass QTL); and speed breeding to accelerate each cycle.ResultsTo develop a SPS approach that integrates non-destructive screening for seminal root angle and root biomass, two initial experiments were conducted. Firstly, we demonstrated that transplanting wheat seedlings from clear pots (for seminal root angle assessment) into sand pots (for root biomass assessment) did not impact the ability to differentiate genotypes with high and low root biomass. Secondly, we demonstrated that visual scores for root biomass were correlated with root dry weight (r = 0.72), indicating that single plants could be evaluated for root biomass in a non-destructive manner. To highlight the potential of the approach, we applied SPS in a backcrossing program which integrated MAS and speed breeding for the purpose of rapidly modifying the root system of elite bread wheat line Borlaug100. Bi-directional selection for root angle in segregating generations successfully shifted the mean root angle by 30° in the subsequent generation (P ≤ 0.05). Within 18 months, BC2F4:F5 introgression lines were developed that displayed a full range of root configurations, while retaining similar above-ground traits to the recurrent parent. Notably, the seminal root angle displayed by introgression lines varied more than 30° compared to the recurrent parent, resulting in lines with both narrow and wide root angles, and high and low root biomass phenotypes.ConclusionThe SPS approach enables researchers and plant breeders to rapidly manipulate root traits of future crop varieties, which could help improve productivity in the face of increasing environmental fluctuations. The newly developed elite wheat lines with modified root traits provide valuable materials to study the value of different root systems to support yield in different environments and soil types.

Genome Wide Association Studies to Dissect Genetic Factors Conferring Sheath Blight Resistance in Rice (Oryza sativa L.)

Rice Sheath blight (ShB) is one of the most serious fungal diseases caused by Rhizoctonia solani. Breeding for sheath blight resistance has been ineffective exercise so far, mainly because of lack of good number of reliable sources of resistance in rice germplasm. In this context our studies indicated that the lines Tetep, Jasmine 85 and MTU 9992 confer resistant to moderately resistant reaction against the pathogen. The current investigation was carried out to dissect the genetic factors governing resistance to sheath blight through genome wide association study (GWAS) from the mapping populations developed by design where in, each of the resistant parents were crossed to three to four highly susceptible parents to generate eleven populations (Jasmine 85XTN1, Jasmine 85XSwarnaSub1, Jasmine 85XII32B, Jasmine 85XIR54, TetepXTN1, TetepXSwarnaSub1, TetepXII32B, TetepXIR54, MTU 9992XTN1, MTU 9992XII32B and MTU 9992XIRBB4). A total of 1545 Recombinant inbred lines (RILs) derived from eleven crosses were used for the study. During rainy 2020 the F7 RILs were screened for their reaction to Sheath blight in two hot spot locations. The genotyping was done with Illumina platform having 6564 SNP markers. Genome wide association study was done with two models Generalized Linear Model (GLM) and Mixed Linear Model (MLM). Results clearly indicate the superiority of MLM over GLM in correcting the population structure. With MLM model, in Jasmine 85 half-sib populations with 565 RILs analyzed, five QTLs (Quantitative Trait Loci) were detected on Chr1, Chr3, Chr9, Chr10 and Chr11 with –log10 (P-Value) more than 3. In TETEP half-sib populations with 714 RILs examined, seven QTLs were observed on Chr1, Chr2, Chr5, Chr6, Chr7, Chr8, and Chr11 with –log10 (P-Value) more than 4. Whereas in MTU 9992 half-sib populations with 266 RILs studied, three novel QTLs were identified on Chr2, Chr6 and Chr11 with –log10 (P-Value) more than 3. Some of these QTLs were reported by researches earlier. In the current research, some novel QTLs were detected in Jasmine 85 (Chr10) and Tetep (Chr2, Chr5 and Chr6) apart from three new QTLs discovered in MTU 9992. The results facilitated to have better understanding of the genetic basis for sheath blight resistance in rice. Pyramiding all the QTL identified so far into a susceptible varieties is complicated affair as resistance is governed by not only several large effect QTLs but also medium to small effect QTLs as well, hence genomic selection approach could be rewarding for breeding for sheath blight resistance.

Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

Identification of the Capsicum baccatum NLR Protein CbAR9 Conferring Disease Resistance to Anthracnose.

Anthracnose is caused by Colletotrichum species and is one of the most virulent fungal diseases affecting chili pepper (Capsicum) yield globally. However, the noble genes conferring resistance to Colletotrichum species remain largely elusive. In this study, we identified CbAR9 as the causal locus underlying the large effect quantitative trait locus CcR9 from the anthracnose-resistant chili pepper variety PBC80. CbAR9 encodes a nucleotide-binding and leucine-rich repeat (NLR) protein related to defense-associated NLRs in several other plant species. CbAR9 transcript levels were induced dramatically after Colletotrichum capsici infection. To explore the biological function, we generated transgenic Nicotiana benthamiana lines overexpressing CbAR9, which showed enhanced resistance to C. capsici relative to wild-type plants. Transcript levels of pathogenesis-related (PR) genes increased markedly in CbAR9-overexpressing N. benthamiana plants. Moreover, resistance to anthracnose and transcript levels of PR1 and PR2 were markedly reduced in CbAR9-silenced chili pepper fruits after C. capsici infection. Our results revealed that CbAR9 contributes to innate immunity against C. capsici.