Small-effect Quantitative Trait Loci Research Articles

Genetic mechanisms of axial patterning in Apeltes quadracus

Abstract The genetic mechanisms underlying striking axial patterning changes in wild species are still largely unknown. Previous studies have shown that Apeltes quadracus fish, commonly known as fourspine sticklebacks, have evolved multiple different axial patterns in wild populations. Here, we revisit classic locations in Nova Scotia, Canada, where both high-spined and low-spined morphs are particularly common. Using genetic crosses and quantitative trait locus (QTL) mapping, we examine the genetic architecture of wild differences in several axial patterning traits, including the number and length of prominent dorsal spines, the number of underlying median support bones (pterygiophores), and the number and ratio of abdominal and caudal vertebrae along the anterior–posterior body axis. Our studies identify a highly significant QTL on chromosome 6 that controls a substantial fraction of phenotypic variation in multiple dorsal spine and pterygiophore traits (~15%–30% variance explained). An additional smaller-effect QTL on chromosome 14 contributes to the lengths of both the last dorsal spine and anal spine (~9% variance explained). 1 or no QTL were detected for differences in the numbers of abdominal and caudal vertebrae. The major-effect patterning QTL on chromosome 6 is centered on the HOXDB gene cluster, where sequence changes in a noncoding axial regulatory enhancer have previously been associated with prominent dorsal spine differences in Apeltes. The QTL that have the largest effects on dorsal spine number and length traits map to different chromosomes in Apeltes and Gasterosteus, 2 distantly related stickleback genera. However, in both genera, the major-effect QTL for prominent skeletal changes in wild populations maps to linked clusters of powerful developmental control genes. This study, therefore, bolsters the body of evidence that regulatory changes in developmental gene clusters provide a common genetic mechanism for evolving major morphological changes in natural species.

Genome-wide association analysis of the resistance to infectious hematopoietic necrosis virus in two rainbow trout aquaculture lines confirms oligogenic architecture with several moderate effect quantitative trait loci

Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV), which can cause substantial mortality and economic losses in rainbow trout aquaculture and fisheries enhancement hatchery programs. In a previous study on a commercial rainbow trout breeding line that has undergone selection, we found that genetic resistance to IHNV is controlled by the oligogenic inheritance of several moderate and many small effect quantitative trait loci (QTL). Here we used genome wide association analyses in two different commercial aquaculture lines that were naïve to previous exposure to IHNV to determine whether QTL were shared across lines, and to investigate whether there were major effect loci that were still segregating in the naïve lines. A total of 1,859 and 1,768 offspring from two commercial aquaculture strains were phenotyped for resistance to IHNV and genotyped with the rainbow trout Axiom 57K SNP array. Moderate heritability values (0.15–0.25) were estimated. Two statistical methods were used for genome wide association analyses in the two populations. No major QTL were detected despite the naïve status of the two lines. Further, our analyses confirmed an oligogenic architecture for genetic resistance to IHNV in rainbow trout. Overall, 17 QTL with notable effect (≥1.9% of the additive genetic variance) were detected in at least one of the two rainbow trout lines with at least one of the two statistical methods. Five of those QTL were mapped to overlapping or adjacent chromosomal regions in both lines, suggesting that some loci may be shared across commercial lines. Although some of the loci detected in this GWAS merit further investigation to better understand the biological basis of IHNV disease resistance across populations, the overall genetic architecture of IHNV resistance in the two rainbow trout lines suggests that genomic selection may be a more effective strategy for genetic improvement in this trait.

Genetic Mapping, Identification, and Characterization of a Candidate Susceptibility Gene for Powdery Mildew in Cannabis sativa.

Powdery mildew (PM) in Cannabis sativa is most frequently caused by the biotrophic fungus Golovinomyces ambrosiae. Based on previously characterized variation in susceptibility to PM, biparental populations were developed by crossing the most resistant cultivar evaluated, 'FL 58', with a susceptible cultivar, 'TJ's CBD'. F1 progeny were evaluated and displayed a range of susceptibility, and two were self-pollinated to generate two F2 populations. In 2021, the F2 populations (n = 706) were inoculated with PM and surveyed for disease severity. In both F2 populations, 25% of the progeny were resistant, while the remaining 75% showed a range of susceptibility. The F2 populations, as well as selected F1 progeny and the parents, were genotyped with a single-nucleotide polymorphism array, and a consensus genetic map was produced. A major effect quantitative trait locus on C. sativa chromosome 1 (Chr01) and other smaller-effect quantitative trait loci (QTL) on four other chromosomes were identified. The most associated marker on Chr01 was located near CsMLO1, a candidate susceptibility gene. Genomic DNA and cDNA sequencing of CsMLO1 revealed a 6.8-kb insertion in FL 58, relative to TJ's CBD, of which 846 bp are typically spliced into the mRNA transcript encoding a premature stop codon. Molecular marker assays were developed using CsMLO1 sequences to distinguish PM-resistant and PM-susceptible genotypes. These data support the hypothesis that a mutated MLO susceptibility gene confers resistance to PM in C. sativa and provides new genetic resources to develop resistant cultivars. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Genome-wide association identifies key loci controlling blackberry postharvest quality.

Blackberry (Rubus subgenus Rubus) is a soft-fruited specialty crop that often suffers economic losses due to degradation in the shipping process. During transportation, fresh-market blackberries commonly leak, decay, deform, or become discolored through a disorder known as red drupelet reversion (RDR). Over the past 50 years, breeding programs have achieved better fruit firmness and postharvest quality through traditional selection methods, but the underlying genetic variation is poorly understood. We conducted a genome-wide association of fruit firmness and RDRmeasured in 300 tetraploid fresh-market blackberry genotypes from 2019-2021 with 65,995 SNPs concentrated in genic regions of the R. argutus reference genome. Fruit firmness and RDR had entry-mean broad sense heritabilities of 68% and 34%, respectively. Three variants on homologs of polygalacturonase (PG), pectin methylesterase (PME), and glucan endo-1,3-β-glucosidase explained 27% of variance in fruit firmness and were located on chromosomes Ra06, Ra01, and Ra02, respectively. Another PG homolog variant on chromosome Ra02 explained 8% of variance in RDR, but it was in strong linkage disequilibrium with 212 other RDR-associated SNPs across a 23 Mb region. A large cluster of six PME and PME inhibitor homologs was located near the fruit firmness quantitative trait locus (QTL) identified on Ra01. RDR and fruit firmness shared a significant negative correlation (r = -0.28) and overlapping QTL regions on Ra02 in this study. Our work demonstrates the complex nature of postharvest quality traits in blackberry, which are likely controlled by many small-effect QTLs. This study is the first large-scale effort to map the genetic control of quantitative traits in blackberry and provides a strong framework for future GWAS. Phenotypic and genotypic datasets may be used to train genomic selection models that target the improvement of postharvest quality.

Variation in CD8 T cell IFNγ differentiation to strains of Toxoplasma gondii is characterized by small effect QTLs with contribution from ROP16.

Toxoplasma gondii induces a strong CD8 T cell response characterized by the secretion of IFNγ that promotes host survival during infection. The initiation of CD8 T cell IFNγ responses in vitro differs widely between clonal lineage strains of T. gondii, in which type I strains are low inducers, while types II and III strains are high inducers. We hypothesized this phenotype is due to a polymorphic "Regulator Of CD8 T cell Response" (ROCTR). Therefore, we screened F1 progeny from genetic crosses between the clonal lineage strains to identify ROCTR. Naïve antigen-specific CD8 T cells (T57) isolated from transnuclear mice, which are specific for the endogenous and vacuolar TGD057 antigen, were measured for their ability to become activated, transcribe Ifng and produce IFNγ in response to T. gondii infected macrophages. Genetic mapping returned four non-interacting quantitative trait loci (QTL) with small effect on T. gondii chromosomes (chr) VIIb-VIII, X and XII. These loci encompass multiple gene candidates highlighted by ROP16 (chrVIIb-VIII), GRA35 (chrX), TgNSM (chrX), and a pair of uncharacterized NTPases (chrXII), whose locus we report to be significantly truncated in the type I RH background. Although none of the chromosome X and XII candidates bore evidence for regulating CD8 T cell IFNγ responses, type I variants of ROP16 lowered Ifng transcription early after T cell activation. During our search for ROCTR, we also noted the parasitophorous vacuole membrane (PVM) targeting factor for dense granules (GRAs), GRA43, repressed the response suggesting PVM-associated GRAs are important for CD8 T cell activation. Furthermore, RIPK3 expression in macrophages was an absolute requirement for CD8 T cell IFNγ differentiation implicating the necroptosis pathway in T cell immunity to T. gondii. Collectively, our data suggest that while CD8 T cell IFNγ production to T. gondii strains vary dramatically, it is not controlled by a single polymorphism with strong effect. However, early in the differentiation process, polymorphisms in ROP16 can regulate commitment of responding CD8 T cells to IFNγ production which may have bearing on immunity to T. gondii.

Gene expression and expression quantitative trait locianalyses uncover natural variations underlying the improvement of important agronomic traits during modern maize breeding.

Maize (Zea mays L.) is a major staple crop worldwide, and during modern maize breeding, cultivars with increased tolerance to high-density planting and higher yield per plant have contributed significantly to the increased yield per unit land area. Systematically identifying key agronomic traits and their associated genomic changes during modern maize breeding remains a significant challenge because of the complexity of genetic regulation and the interactions of the various agronomic traits, with most of them being controlled by numerous small-effect quantitative trait loci (QTLs). Here, we performed phenotypic and gene expression analyses for a set of 137 elite inbred lines of maize from different breeding eras in China. We found four yield-related traits are significantly improved during modern maize breeding. Through gene-clustering analyses, we identified four groups of expressed genes with distinct trends of expression pattern change across the historical breeding eras. In combination with weighted gene co-expression network analysis, we identified several candidate genes regulating various plant architecture- and yield-related agronomic traits, such as ZmARF16, ZmARF34, ZmTCP40, ZmPIN7, ZmPYL10, ZmJMJ10, ZmARF1, ZmSWEET15b, ZmGLN6 and Zm00001d019150. Further, by combining expression quantitative trait loci (eQTLs) analyses, correlation coefficient analyses and population genetics, we identified a set of candidate genes that might have been under selection and contributed to the genetic improvement of various agronomic traits during modern maize breeding, including a number of known key regulators of plant architecture, flowering time and yield-related traits, such as ZmPIF3.3, ZAG1, ZFL2 and ZmBES1. Lastly, we validated the functional variations in GL15, ZmPHYB2 and ZmPYL10 that influence kernel row number, flowering time, plant height and ear height, respectively. Our results demonstrates the effectiveness of our combined approaches for uncovering key candidate regulatory genes and functional variation underlying the improvement of important agronomic traits during modern maize breeding, and provide a valuable genetic resource for the molecular breeding of maize cultivars with tolerance for high-density planting.

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.

The use of PI 277012-derived Fusarium head blight resistance QTL in winter wheat breeding

Fusarium head blight (FHB) caused by Fusarium graminearum results in substantial grain yield and quality losses in common wheat (Triticum aestivum L.). Genetic resistance is partial but crucial for effective, integrated management of the disease. Host resistance is conditioned by numerous small effect quantitative trait loci (QTL) that are strongly affected by the environment and genetic background. Qfhb.rwg-5A.1 and Qfhb.rwg-5A.2 (PI 277012 is the source for both genes) are two recently discovered FHB resistance QTL that also occur in spring wheat GP80 (PI 277012 derivative). To transfer the PI 277012 resistance from GP80 to hard winter wheat (HWW), GP80 was first crossed with Novus-4. The F1 hybrid was crossed with SY Monument, following which marker-selected progeny were crossed with, and backcrossed to, ND Noreen. To potential carriers of FHB resistance QTL among the 22 F1 of the ND Noreen cross, simple sequence repeat (SSR) markers, Illumina 90 K single nucleotide polymorphism (SNP) haplotypes and greenhouse FHB Type II resistance tests were done. Likely homozygotes for Qfhb.rwg.5A.1 and Qfhb.rwg.5A.2, were selected and backcrossed to ND Noreen. In the B1F1, 131 plants were evaluated for SNP haplotypes, SSR markers and FHB resistance. Nine B1F2:3 lines were derived, and their resistance confirmed in a third greenhouse FHB trial. The results suggested that eight lines had higher resistance and were comparable to GP80 with the Qfhb.rwg-5A.2 markers occurring in all eight and the Qfhb.rwg-5A.1 markers occurring in four lines. The eight selections constitute a valuable HWW resistance breeding resource.

Tipburn resilience in lettuce (Lactuca spp.) - the importance of germplasm resources and production system-specific assays.

Tipburn is a physiological disorder of lettuce (Lactuca spp.). It causes discoloration and collapse of leaf margins, leading to unsaleable crops in both protected (glasshouse, hydroponic) and outdoor production systems. The occurrence of tipburn is hard to predict and is sensitive to environmental conditions. Phenotyping for tipburn resilience requires diverse germplasm resources and, to date, limited material has been investigated for this condition. Using a Lactuca diversity fixed foundation set (DFFS) under glasshouse conditions, we identified a significant (P < 0.001) genotypic effect on tipburn resilience across both the entire population and across lines belonging to the cultivated species L. sativa alone. Latuca sativa lines exhibited significantly (P < 0.05) higher average tipburn severity than those belonging to the wild species L. saligna, L. serriola, and L. virosa but we were able to identify both cultivated and wild tipburn-resilient lines. Leaf morphology factors, which included pigmentation, width, and serration, also significantly (P < 0.05) influenced tipburn resilience. Using a recombinant inbred line (RIL) mapping population derived from two DFFS lines, different small-effect quantitative trait loci (QTLs) accounting for 12.3% and 25.2% of total tipburn variation were identified in glasshouse and field conditions, respectively. These results reflect the advantages of phenotyping under production-system-specific conditions for the examination of environmentally sensitive traits and highlight genetic markers and germplasm resources for the development of tipburn resilient lines for use in both protected and outdoor lettuce production. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Identification and Characterization of a QTL for Growth of Fusarium circinatum on Pine-Based Medium.

Fusarium circinatum is an economically important pathogen of pine and resides in the Fusarium fujikuroi species complex. Here we investigated the molecular processes underlying growth in F. circinatum by exploring the association between growth and the nutritional environment provided by the pine host. For this purpose, we subjected a mapping population consisting of F. circinatum X F. temperatum hybrid progeny to an analysis of growth rate on a pine-tissue derived medium. These data, together with the available genetic linkage map for F. circinatum, were then used to identify Quantitative Trait Loci (QTLs) associated with growth. The single significant QTL identified was then characterized using the available genome sequences for the hybrid progeny's parental isolates. This revealed that the QTL localized to two non-homologous regions in the F. circinatum and F. temperatum genomes. For one of these, the F. circinatum parent contained a two-gene deletion relative to the F. temperatum parent. For the other region, the two parental isolates encoded different protein products. Analysis of repeats, G+C content, and repeat-induced point (RIP) mutations further suggested a retrotransposon origin for the two-gene deletion in F. circinatum. Nevertheless, subsequent genome and PCR-based analyses showed that both regions were similarly polymorphic within a collection of diverse F. circinatum. However, we observed no clear correlation between the respective polymorphism patterns and growth rate in culture. These findings support the notion that growth is a complex multilocus trait and raise the possibility that the identified QTL contains multiple small-effect QTLs, of which some might be dependent on the genetic backgrounds. This study improved our current knowledge of the genetic determinants of vegetative growth in F. circinatum and provided an important foundation for determining the genes and processes underpinning its ability to colonize its host environment.

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

Plant architecture, flowering time and maturity traits are important determinants of yield and fiber quality of cotton. Genetic dissection of loci determining these yield and quality components is complicated by numerous loci with alleles conferring small differences. Therefore, mapping populations segregating for smaller numbers and sizes of introgressed segments is expected to facilitate dissection of these complex quantitative traits. At an advanced stage in the development of reciprocal advanced backcross populations from crosses between elite Gossypium hirsutum cultivar 'Acala Maxxa' (GH) and G. barbadense 'Pima S6' (GB), we undertook mapping of plant architectural traits, flowering time and maturity. A total of 284 BC4F1 and BC4F2 progeny rows, 120 in GH and 164 in GB background, were evaluated for phenotype, with only 4 and 3 (of 7) traits showing significant differences among progenies. Genotyping by sequencing yielded 3,186 and 3,026 SNPs, respectively, that revealed a total of 27 QTLs in GH background and 22 in GB, for plant height, days to flowering, residual flowering at maturity and maturity. More than of 90% QTLs identified in both backgrounds had small effects (%PV < 10), supporting the merit of this population structure to reduce background noise and small effect QTLs. Germplasm developed in this study may serve as potential pre-breeding material to develop improved cotton cultivars.

Small genetic steps lead to mechanical isolation in hummingbird-pollinated gingers.

Interactions with pollinators are a potent source of natural selection driving the spectacular array of flowering plant diversity on Earth (Kay & Sargent, 2009; Van der Niet et al., 2014). Floral traits play a central role in this process: reliable and effective pollination by animal pollinators depends on complex floral features, including traits that determine pollinator attraction and reward, as well as the mechanics of pollen transfer. Pollinators specify mating events between individuals, and thus differences in flowers have the potential to generate reproductive isolating barriers (floral isolation). A compelling case of floral isolation comes from spiral gingers (Costus), where hummingbird-adapted species have evolved distinct pollen placement strategies (on the bills vs. foreheads of pollinators) due to differences in flower shape and the arrangements of flower parts. This difference in pollen placement causes a mechanical barrier to cross-pollination. In this issue of Molecular Ecology, Kay and Surget-Groba (2022) dissect the genetic basis of these floral differences using a quantitative trait locus (QTL) mapping approach. They find small-effect QTLs that influence multiple correlated traits and allelic effects that suggest a history of directional selection. Their results indicate mechanical isolation reflects adaptive divergence that has built up piecemeal over time.

Accounting for heading date gene effects allows detection of small-effect QTL associated with resistance to Septoria nodorum blotch in wheat.

In humid and temperate areas, Septoria nodorum blotch (SNB) is a major fungal disease of common wheat (Triticum aestivum L.) in which grain yield is reduced when the pathogen, Parastagonospora nodorum, infects leaves and glumes during grain filling. Foliar SNB susceptibility may be associated with sensitivity to P. nodorum necrotrophic effectors (NEs). Both foliar and glume susceptibility are quantitative, and the underlying genetics are not understood in detail. We genetically mapped resistance quantitative trait loci (QTL) to leaf and glume blotch using a double haploid (DH) population derived from the cross between the moderately susceptible cultivar AGS2033 and the resistant breeding line GA03185-12LE29. The population was evaluated for SNB resistance in the field in four successive years (2018-2021). We identified major heading date (HD) and plant height (PH) variants on chromosomes 2A and 2D, co-located with SNB escape mechanisms. Five QTL with small effects associated with adult plant resistance to SNB leaf and glume blotch were detected on 1A, 1B, and 6B linkage groups. These QTL explained a relatively small proportion of the total phenotypic variation, ranging from 5.6 to 11.8%. The small-effect QTL detected in this study did not overlap with QTL associated with morphological and developmental traits, and thus are sources of resistance to SNB.

Comparison of Single-Trait and Multi-Trait Genome-Wide Association Models and Inclusion of Correlated Traits in the Dissection of the Genetic Architecture of a Complex Trait in a Breeding Program

Unknown genetic architecture makes it difficult to characterize the genetic basis of traits and associated molecular markers because of the complexity of small effect quantitative trait loci (QTLs), environmental effects, and difficulty in phenotyping. Seedling emergence of wheat (Triticum aestivum L.) from deep planting, has a poorly understood genetic architecture, is a vital factor affecting stand establishment and grain yield, and is historically correlated with coleoptile length. This study aimed to dissect the genetic architecture of seedling emergence while accounting for correlated traits using one multi-trait genome-wide association study (MT-GWAS) model and three single-trait GWAS (ST-GWAS) models. The ST-GWAS models included one single-locus model [mixed-linear model (MLM)] and two multi-locus models [fixed and random model circulating probability unification (FarmCPU) and Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK)]. We conducted GWAS using two populations. The first population consisted of 473 varieties from a diverse association mapping panel phenotyped from 2015 to 2019. The second population consisted of 279 breeding lines phenotyped in 2015 in Lind, WA, with 40,368 markers. We also compared the inclusion of coleoptile length and markers associated with reduced height as covariates in our ST-GWAS models. ST-GWAS found 107 significant markers across 19 chromosomes, while MT-GWAS found 82 significant markers across 14 chromosomes. The FarmCPU and BLINK models, including covariates, were able to identify many small effect markers while identifying large effect markers on chromosome 5A. By using multi-locus model breeding, programs can uncover the complex nature of traits to help identify candidate genes and the underlying architecture of a trait, such as seedling emergence.

Dissection of Closely Linked Quantitative Trait Locis Controlling Grain Size in Rice.

Grain size is a key constituent of grain weight and appearance in rice. However, insufficient attention has been paid to the small-effect quantitative trait loci (QTLs) on the grain size. In the present study, residual heterozygous populations were developed for mapping two genetically linked small-effect QTLs for grain size. After the genotyping and the phenotyping of five successive generations, qGS7.1 was dissected into three QTLs and two were selected for further analysis. The qTGW7.2a was finally mapped into a 21.10 kb interval containing four annotated candidate genes. Transcript levels assay showed that the expression of the candidates LOC_Os07g39490 and the LOC_Os07g39500 were significantly reduced in the NIL-qTGW7.2aBG1. The cytological observation indicated that qTGW7.2a regulated the grain width through controlling the cell expansion. Using the same strategy, qTGW7.2b was fine-mapped into a 52.71 kb interval containing eight annotated candidate genes, showing a significant effect on the grain length and width with opposite allelic directions, but little on the grain weight. Our study provides new genetic resources for yield improvement and for fine-tuning of grain size in rice.

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.

Genetic variation in the heat-stress survival of embryos is largely decoupled from adult thermotolerance in an intercontinental set of recombinant lines of Drosophila melanogaster.

In insects, thermal adaptation works on the genetic variation for thermotolerance of not only larvae and adults but also of the immobile stages of the life cycle including eggs. In contrast to adults and larvae, the genetic basis for thermal adaptation in embryos (eggs) remains to be tested in the model insect Drosophila melanogaster. Quantitative-trait loci (QTL) for heat-stress resistance in embryos could largely differ from previously identified QTL for larvae and adults. Here we used an intercontinental set of recombinant inbred lines (RIL), which were previously used to identify thermotolerance-QTLs in adults and larvae because of their high variation segregating for adult thermotolerance. Eggs appeared to be more heat resistant than larvae and adults from previous studies on these RIL, though different heat-shock assays were used in previous studies. We found that variation in thermotolerance in embryos can be, at least partially, genetically decoupled from thermotolerance in the adult insect. Some RIL that are heat resistant in the adult and larvae can be heat susceptible in embryos. Only one small-effect QTL out of five autosomal QTL co-localized between embryo and other ontogenetic stages. These results suggest that selection for thermal adaptation in adult flies and larvae is predicted to have only a small impact on embryo thermotolerance. In addition, heat-stress tolerance of insects can be measured across ontogenetic stages including embryos in order to better predict thermal adaptive limits of populations and species.

Genetic basis of kernel starch content decoded in a maize multi-parent population.

SummaryStarch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome‐wide association study in a multi‐parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large‐effect and many small‐effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non‐starch‐pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway‐driven analysis identified ZmTPS9, which encodes a trehalose‐6‐phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4−2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.