Mapping QTLs with epistatic effects and QTL × environment interactions for plant height using a doubled haploid population in cultivated wheat

Identification of QTLs associated with yield-related traits and superior genotype prediction using recombinant inbred line population in tobacco

Tobacco is an economically significant industrial crop and model plant for genetic research, yet little is known about its genetic architecture. Quantitative trait loci (QTL) analysis was performed for six agronomic traits on an F_7 population of 341 genotypes, parents, and F1 plants using 1974 SSR markers across two environments. 31 QTLs contributing single-locus additive effects on 13 linkage groups (LGs) and 6 QTL pairs contributing epistatic effects on 6 LGs, were detected by the QTLNetwork 2.0 which was developed for the mixed-linear-model-based composite interval mapping (MCIM). Notably, 5 QTLs and 1 epistatic QTL pair were found to have pleiotropic effects on some genetically related traits. Moreover, the Broad sense heritability of the detected QTLs ranged from 1.05% to 43.33%, while genotype-by-environment interaction heritability spanned from 27.09% to 56.25%. Based on the results of QTL mapping, the potential superior lines for all or specific environments were designed and evaluated. Five major QTLs were finely dissected based on the tobacco reference genome of K326, and 31 candidate genes were predicted. This study offered new insights into the complicated genetic architecture and QTL resources for efficient breeding design for genetic improvement of agronomic traits in tobacco.

Prediction of wheat SPAD using integrated multispectral and support vector machines

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69-0.79, RMSE was 2.30-12.94, and RE was 0.10%-1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.)

BACKGROUND

In hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM).

RESULTS

Eight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox.

CONCLUSION

Identification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.

Improving genomic predictions with inbreeding and nonadditive effects in two admixed maize hybrid populations in single and multienvironment contexts

Genetic admixture, resulting from the recombination between structural groups, is frequently encountered in breeding populations. In hybrid breeding, crossing admixed lines can generate substantial nonadditive genetic variance and contrasted levels of inbreeding which can impact trait variation. This study aimed at testing recent methodological developments for the modeling of inbreeding and nonadditive effects in order to increase prediction accuracy in admixed populations. Using two maize (Zea mays L.) populations of hybrids admixed between dent and flint heterotic groups, we compared a suite of five genomic prediction models incorporating (or not) parameters accounting for inbreeding and nonadditive effects with the natural and orthogonal interaction approach in single and multienvironment contexts. In both populations, variance decompositions showed the strong impact of inbreeding on plant yield, height, and flowering time which was supported by the superiority of prediction models incorporating this effect (+0.038 in predictive ability for mean yield). In most cases dominance variance was reduced when inbreeding was accounted for. The model including additivity, dominance, epistasis, and inbreeding effects appeared to be the most robust for prediction across traits and populations (+0.054 in predictive ability for mean yield). In a multienvironment context, we found that the inclusion of nonadditive and inbreeding effects was advantageous when predicting hybrids not yet observed in any environment. Overall, comparing variance decompositions was helpful to guide model selection for genomic prediction. Finally, we recommend the use of models including inbreeding and nonadditive parameters following the natural and orthogonal interaction approach to increase prediction accuracy in admixed populations.

Mapping QTL for seedling morphological and physiological traits under normal and salt treatments in a RIL wheat population

The genetic basis of 27 seedling traits under normal and salt treatments was fully analyzed in a RIL wheat population, and seven QTL intervals were validated in two other genetic populations. Soil salinity seriously constrains wheat (Triticum aestivum L.) production globally by influencing its growth and development. To explore the genetic basis of salt tolerance in wheat, a recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 (ZM175) and salt-tolerant cultivar Xiaoyan 60 (XY60) was used to map QTL for seedling traits under normal and salt treatments based on a high-density genetic linkage map. A total of 158 stable additive QTL for 27 morphological and physiological traits were identified and distributed on all wheat chromosomes except 3A and 4D. They explained 2.35-46.43% of the phenotypic variation with a LOD score range of 2.61-40.38. The alleles from XY60 increased corresponding traits for 100 QTL, while the alleles from ZM175 had positive effects for the other 58 QTL. Nearly half of the QTL (78/158) were mapped in nine QTL clusters on chromosomes 2A, 2B, 2D, 4B, 5A, 5B, 5D, and 7D (2), respectively. To prove the reliability and potentiality in molecular marker-assisted selection (MAS), seven QTL intervals were validated in two other genetic populations. Besides additive QTL, 94 pairs of loci were detected with significant epistatic effect and 20 QTL were found to interact with treatment. This study provides a full elucidation of the genetic basis of seedling traits (especially root system-related traits) associated with salt tolerance in wheat, and the developed kompetitive allele-specific PCR markers closely linked to stable QTL would supply strong supports to MAS in salt-tolerant wheat breeding.

Utilization of a Wheat55K SNP array-derived high-density genetic map for high-resolution mapping of quantitative trait loci for important kernel-related traits in common wheat

This study mapped QTLs associated with kernel-related traits by high-density genetic map. Five new major and stable QTLs for KL, KDR, SN, and KWPS were mapped in multiple environments. In the present study, a recombinant inbred line population including 371 lines derived from the cross of Chuannong18 and T1208 was genotyped using the Wheat55K single nucleotide polymorphism array. A novel high-density genetic map consisting of 11,583 markers spanning 4192.62 cM and distributed across 21 wheat chromosomes was constructed. QTLs for important kernel-related traits were mapped in multiple environments. A total of 96 and 151 QTLs were mapped by using the ICIM method and the MET method, respectively. And a total of 114 digenic epistatic QTLs were also detected across 21 chromosomes, and the epistatic effects of each trait were analyzed. BLAST analysis showed that 23 QTLs for different kernel-related traits were first time mapped and five of them were major and stable QTLs for kernel diameter ratio (121.34-126.83 cM on 4BS), spike number per square meter (71.32-73.84 cM on 2DS), kernel weight per spike (71.32-75.26 cM on 2DS), and kernel length (16.78-31.64 cM on 6A and 51.63-58.40 cM on 3D), respectively. Fifteen QTL clusters that contained 58 QTLs were also detected, and all most stable QTLs were contained in these QTL clusters. Significant correlations between different traits were detected and discussed. These results lay the foundation for fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Genome wide identification of QTL associated with yield and yield components in two popular wheat cultivars TAM 111 and TAM 112

Two drought-tolerant wheat cultivars, ‘TAM 111’ and ‘TAM 112’, have been widely grown in the Southern Great Plains of the U.S. and used as parents in many wheat breeding programs worldwide. This study aimed to reveal genetic control of yield and yield components in the two cultivars under both dryland and irrigated conditions. A mapping population containing 124 F_5:7 recombinant inbred lines (RILs) was developed from the cross of TAM 112/TAM 111. A set of 5,948 SNPs from the wheat 90K iSelect array and double digest restriction-site associated DNA sequencing was used to construct high-density genetic maps. Data for yield and yield components were obtained from 11 environments. QTL analyses were performed based on 11 individual environments, across all environments, within and across mega-environments. Thirty-six unique consistent QTL regions were distributed on 13 chromosomes including 1A, 1B, 1D, 2A, 2D, 3D, 4B, 4D, 6A, 6B, 6D, 7B, and 7D. Ten unique QTL with pleiotropic effects were identified on four chromosomes and eight were in common with the consistent QTL. These QTL increased dry biomass grain yield by 16.3 g m^-2, plot yield by 28.1 g m^-2, kernels spike^-1 by 0.7, spikes m^-2 by 14.8, thousand kernel weight by 0.9 g with favorable alleles from either parent. TAM 112 alleles mainly increased spikes m^-2 and thousand kernel weight while TMA 111 alleles increased kernels spike^-1, harvest index and grain yield. The saturated genetic map and markers linked to significant QTL from this study will be very useful in developing high throughput genotyping markers for tracking the desirable haplotypes of these important yield-related traits in popular parental cultivars.

A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat

A novel, stably expressed, and plant height-independent QTL for spike extension length on 5AS was identified and validated in different populations using a newly developed and tightly linked KASP marker. As an important component of plant height (PH), spike extension length (SEL) plays a significant role in formation of an ideotype in wheat. Despite the fact that numerous loci for SEL in wheat have been reported, our knowledge on PH-independent loci remains to be limited. In this study, two recombinant inbred line (RIL) populations genotyped using the Wheat55K SNP were used to detect quantitative trait loci (QTL) controlling SEL across six environments. A total of 30 QTL for SEL were detected in these two RIL populations, and four of them, i.e., QSEL.sicau-2CN-4D, QSEL.sicau-2SY-4B.2, QSEL.sicau-2SY-4D.1, and QSEL.sicau-2CN-5A, were stably expressed. Genetic and conditional QTL analysis showed that the first three were significantly associated with PH, while the last one, QSEL.sicau-2CN-5A, is independent of PH. Comparison of genetic and physical maps suggested that only QSEL.sicau-2CN-5A located on chromosome arm 5AS is likely a novel QTL. A Kompetitive Allele-Specific PCR (KASP) marker, KASP-AX-110413733, tightly linked to this novel QTL was developed to successfully confirm its effect in three different genetic populations. Further, in the interval where QSEL.sicau-2CN-5A was located on 'Chinese Spring' wheat reference genome, three promising genes mainly expressed in wheat stem were predicated and they all encode the cytochrome P450 that was demonstrated to be closely associated with SEL elongation in rice. In addition, significant correlations between SEL and PH, spikelet number per spike, and thousand-grain weight were also detected. Altogether, our results broaden our understanding on genetic basis of SEL and will be useful for marker-based selection of lines with different SELs and fine mapping the novel and PH-independent QTL QSEL.sicau-2CN-5A.

Identification of quantitative trait loci for carbon isotope ratio (δ13C) in a recombinant inbred population of soybean

KEY MESSAGE

QTL analysis identified 16 QTLs, grouped in eight loci on seven soybean chromosomes that were associated with carbon isotope ratio (δ13C) in a biparental recombinant inbred population. Drought is a major limitation to soybean yield, and the frequency of drought stress is likely to increase under future climatic scenarios. Water use efficiency (WUE) is associated with drought tolerance, and carbon isotope ratio (δ13C) is positively correlated with WUE. In this study, 196 F6-derived recombinant inbred lines from a cross of PI 416997 (high WUE) × PI 567201D (low WUE) were evaluated in four environments to identify genomic regions associated with δ13C. There were positive correlations of δ13C values between different environments (0.67 ≤ r ≤ 0.78). Genotype, environment, and genotype × environment interactions had significant effects on δ13C. Narrow sense heritability of δ13C was 90% when estimated across environments. There was a total of 16 QTLs on seven chromosomes with individual QTLs explaining between 2.5 and 29.9% of the phenotypic variation and with additive effects ranging from 0.07 to 0.22‰. These 16 QTLs likely identified eight loci based on their overlapping confidence intervals. Of these eight loci, two loci on chromosome 20 (Gm20) were detected in at least three environments and were considered as stable QTLs. Additive QTLs on Gm20 showed epistatic interactions with 10 QTLs present across nine chromosomes. Five QTLs were identified across environments and showed significant QTL × environment interactions. These findings demonstrate that additive QTLs and QTL × QTL interactions play significant roles in genetic control of the δ13C trait. Markers flanking identified QTLs may facilitate marker-assisted selection to accumulate desirable QTLs to improve WUE and drought tolerance in soybean.

Genome-wide Association Study (GWAS) for Mesocotyl Elongation in Rice (Oryza sativa L.) under Multiple Culture Conditions

Mesocotyl is a crucial organ for pushing buds out of soil, which plays a vital role in seedling emergence and establishment in dry direct-seeded rice. However, the genetic mechanisms of mesocotyl elongation remains unclear. In our study, 208 rice accessions were used to identify the SNPs significantly associated with mesocotyl length under various culture conditions, including sand, water and soil. The mesocotyl length ranges from 0 to 4.88 cm, 0 to 3.99 cm and 0 to 4.51 cm in sand, water and soil covering, respectively. A total of 2,338,336 SNPs were discovered by re-sequencing of 208 rice accessions. Genome-wide association study (GWAS) based on mixed linear model (MLM) was conducted and 16 unique loci were identified on chromosomes 1, 2 (2), 3, 4, 5 (2), 6 (2), 7, 8, 9 (2) and 12 (3), respectively, explaining phenotypic variations ranging from 6.3 to 15.9%. Among these loci, 12 were stable across two or more environments. Ten out of the sixteen loci coincided with known genes or quantitative trait locus (QTL), whereas the other six were potentially novel loci. Furthermore, five high-confidence candidate genes related to mesocotyl elongation were identified on chromosomes 1, 3, 5, 9 and 12. Moreover, qRT-PCR analysis showed that all the five genes showed significant expression difference between short-mesocotyl accessions and long-mesocotyl accessions. This study provides new insights into the genetic architecture of rice mesocotyl, the associated SNPs and germplasms with long mesocotyl could be useful in the breeding of mechanized dry direct-seeded rice.

QTLs position of some important ornamental traits in recently developed OO lily population

Lilium L. is a perennial ornamental bulbous species, belonging to Liliaceae family, which consists of about 100 species. One of the most important hybrids in Lilium L. is the Oriental hybrid lily. Different cross combinations have been done in the lily family such as AA (Asiatic × Asiatic), AL (Asiatic × Longiflorum), and OT (Oriental × Trumpet). The OO (Oriental × Oriental) combination is a new one. SSR and AFLP markers were used to overlap each other and the genetic linkage groups were created according to the haploid number of lily chromosomes (12 linkage groups). In this experiment, the final F₁ population, which creates a genetic linkage group, was 100 individuals. For map construction, JOINMAP 4.0 software by treating segregation data of markers as a CP (out breeder full-sib family) model was used. After evaluation of ornamental traits, MapQTL 4.0 software was also used to find possible QTLs on these linkage maps. A total of 940 primers were tested and the best ones, which were 172 primer pairs (96 AFLP and 76 SSR markers), were used for map construction and the total of 616 loci (465 loci for AFLP marker and 151 loci for SSR marker) were scored. The entire mapped length was 2144.2 cM. 8 QTLs were obtained for flower number which is an important trait in lily. Each QTL locus explained the phenotypic variation of 2.4-89.5%. The highest amount of LOD (35.21) was found in LG-F1P2 for FN4 QTL. For leaf number, one-QTL was mapped with LOD of 7.08 between 2 markers on the LG-M10 of maternal maps. The QTL for petal length was placed on the LG-F1P2 of the F1 hybrid maps on the E-CGC/M-CGC-4 primer combination. The petal width QTLs also were mapped on the E-CGC/M-CGC-4. Qualitative locus named LN was mapped on the LG-M10 of the maternal maps. PW2 QTL was also localized on the LG-F4 of the paternal maps. In this experiment, 5 QTLs also were mapped for spot number in all F₁ hybrids and paternal and maternal maps, and spot size. Moreover, one QTL with the length of 51 cM was measured on the LG-M8 of the maternal maps. Plant height QTL with the LOD of 12.54 was mapped on the primer combination of E-CGC/M-CGC-4 on the LG-F1P2 of the F₁ hybrid maps.

Genetic Dissection of Resistance to the Three Fungal Plant Pathogens Blumeria graminis, Zymoseptoria tritici, and Pyrenophora tritici-repentis Using a Multiparental Winter Wheat Population

Bread wheat (Triticum aestivum L.) is one of the world’s most important crop species. The development of new varieties resistant to multiple pathogens is an ongoing task in wheat breeding, especially in times of increasing demand for sustainable agricultural practices. Despite this, little is known about the relations between various fungal disease resistances at the genetic level, and the possible consequences for wheat breeding strategies. As a first step to fill this gap, we analyzed the genetic relations of resistance to the three fungal diseases – powdery mildew (PM), septoria tritici blotch (STB), and tan spot (TS) – using a winter wheat multiparent advanced generation intercross population. Six, seven, and nine QTL for resistance to PM, STB, and TS, respectively, were genetically mapped. Additionally, 15 QTL were identified for the three agro-morphological traits plant height, ear emergence time, and leaf angle distribution. Our results suggest that resistance to STB and TS on chromosome 2B is conferred by the same genetic region. Furthermore, we identified two genetic regions on chromosome 1AS and 7AL, which are associated with all three diseases, but not always in a synchronal manner. Based on our results, we conclude that parallel marker-assisted breeding for resistance to the fungal diseases PM, STB, and TS appears feasible. Knowledge of the genetic co-localization of alleles with contrasting effects for different diseases, such as on chromosome 7AL, allows the trade-offs of selection of these regions to be better understood, and ultimately determined at the genic level.

Identification of Major QTLs Associated With First Pod Height and Candidate Gene Mining in Soybean

First pod height (FPH) is a quantitative trait in soybean [Glycine max (L.) Merr.] that affects mechanized harvesting. A compatible combination of the FPH and the mechanized harvester is required to ensure that the soybean is efficiently harvested. In this study, 147 recombinant inbred lines, which were derived from a cross between 'Dongnong594' and 'Charleston' over 8 years, were used to identify the major quantitative trait loci (QTLs) associated with FPH. Using a composite interval mapping method with WinQTLCart (version 2.5), 11 major QTLs were identified. They were distributed on five soybean chromosomes, and 90 pairs of QTLs showed significant epistatic associates with FPH. Of these, 3 were main QTL × main QTL interactions, and 12 were main QTL × non-main QTL interactions. A KEGG gene annotation of the 11 major QTL intervals revealed 8 candidate genes related to plant growth, appearing in the pathways K14486 (auxin response factor 9), K14498 (serine/threonine-protein kinase), and K13946 (transmembrane amino acid transporter family protein), and 7 candidate genes had high expression levels in the soybean stems. These results will aid in building a foundation for the fine mapping of the QTLs related to FPH and marker-assisted selection for breeding in soybean.

Adaptive selection of founder segments and epistatic control of plant height in the MAGIC winter wheat population WM-800

BACKGROUND

Multi-parent advanced generation intercross (MAGIC) populations are a newly established tool to dissect quantitative traits. We developed the high resolution MAGIC wheat population WM-800, consisting of 910 F4:6 lines derived from intercrossing eight recently released European winter wheat cultivars.

RESULTS

Genotyping WM-800 with 7849 SNPs revealed a low mean genetic similarity of 59.7% between MAGIC lines. WM-800 harbours distinct genomic regions exposed to segregation distortion. These are mainly located on chromosomes 2 to 6 of the wheat B genome where founder specific DNA segments were positively or negatively selected. This suggests adaptive selection of individual founder alleles during population development. The application of a genome-wide association study identified 14 quantitative trait loci (QTL) controlling plant height in WM-800, including the known semi-dwarf genes Rht-B1 and Rht-D1 and a potentially novel QTL on chromosome 5A. Additionally, epistatic effects controlled plant height. For example, two loci on chromosomes 2B and 7B gave rise to an additive epistatic effect of 13.7 cm.

CONCLUSION

The present study demonstrates that plant height in the MAGIC-WHEAT population WM-800 is mainly determined by large-effect QTL and di-genic epistatic interactions. As a proof of concept, our study confirms that WM-800 is a valuable tool to dissect the genetic architecture of important agronomic traits.

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Mapping QTL for Root and Shoot Morphological Traits in a Durum Wheat × T. dicoccum Segregating Population at Seedling Stage

A segregating population of 136 recombinant inbred lines derived from a cross between the durum wheat cv. "Simeto" and the T. dicoccum accession "Molise Colli" was grown in soil and evaluated for a number of shoot and root morphological traits. A total of 17 quantitative trait loci (QTL) were identified for shoot dry weight, number of culms, and plant height and for root dry weight, volume, length, surface area, and number of forks and tips, on chromosomes 1B, 2A, 3A, 4B, 5B, 6A, 6B, and 7B. LODs were 2.1 to 21.6, with percent of explained phenotypic variability between 0.07 and 52. Three QTL were mapped to chromosome 4B, one of which corresponds to the Rht-B1 locus and has a large impact on both shoot and root traits (LOD 21.6). Other QTL that have specific effects on root morphological traits were also identified. Moreover, meta-QTL analysis was performed to compare the QTL identified in the "Simeto" × "Molise Colli" segregating population with those described in previous studies in wheat, with three novel QTL defined. Due to the complexity of phenotyping for root traits, further studies will be helpful to validate these regions as targets for breeding programs for optimization of root function for field performance.

Genomic Prediction of Genotypic Effects with Epistasis and Environment Interactions for Yield-Related Traits of Rapeseed (Brassica napus L.)

Oilseed rape (Brassica napus) is an economically important oil crop, yet the genetic architecture of its complex traits remain largely unknown. Here, genome-wide association study was conducted for eight yield-related traits to dissect the genetic architecture of additive, dominance, epistasis, and their environment interaction. Additionally, the optimal genotype combination and the breeding value of superior line, superior hybrid and existing best line in mapping population were predicted for each trait in two environments based on the predicted genotypic effects. As a result, 17 quantitative trait SNPs (QTSs) were identified significantly for target traits with total heritability varied from 58.47 to 87.98%, most of which were contributed by dominance, epistasis, and environment-specific effects. The results indicated that non-additive effects were large contributions to heritability and epistasis, and also noted that environment interactions were important variants for oilseed breeding. Our study facilitates the understanding of genetic basis of rapeseed yield trait, helps to accelerate rapeseed breading, and also offers a roadmap for precision plant breeding via marker-assisted selection.

SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments

Soybean oil content is one of main quality traits. In this study, we used the multifactor dimensionality reduction (MDR) method and a soybean high-density genetic map including 5,308 markers to identify stable single nucleotide polymorphism (SNP)—SNP interactions controlling oil content in soybean across 23 environments. In total, 36,442,756 SNP-SNP interaction pairs were detected, 1865 of all interaction pairs associated with soybean oil content were identified under multiple environments by the Bonferroni correction with p <3.55×10⁻¹¹. Two and 1863 SNP-SNP interaction pairs detected stable across 12 and 11 environments, respectively, which account around 50% of total environments. Epistasis values and contribution rates of stable interaction (the SNP interaction pairs were detected in more than 2 environments) pairs were detected by the two way ANOVA test, the available interaction pairs were ranged 0.01 to 0.89 and from 0.01 to 0.85, respectively. Some of one side of the interaction pairs were identified with previously research as a major QTL without epistasis effects. The results of this study provide insights into the genetic architecture of soybean oil content and can serve as a basis for marker-assisted selection breeding.

Induced parthenogenesis by gamma-irradiated pollen in loquat for haploid production

Successful haploid induction in loquat (Eriobotrya japonica (Thunb.) Lindl.) through in situ-induced parthenogenesis with gamma-ray irradiated pollen has been achieved. Female flowers of cultivar 'Algerie' were pollinated using pollen of cultivars 'Changhong-3', 'Cox' and 'Saval Brasil' irradiated with two doses of gamma rays, 150 and 300 Gy. The fruits were harvested 90, 105 and 120 days after pollination (dap). Four haploid plants were obtained from 'Algerie' pollinated with 300-Gy-treated pollen of 'Saval Brasil' from fruits harvested 105 dap. Haploidy was confirmed by flow cytometry and chromosome count. The haploids showed a very weak development compared to the diploid plants. This result suggests that irradiated pollen can be used to obtain parthenogenetic haploids.

Genome-wide association analysis reveals new targets for carotenoid biofortification in maize

KEY MESSAGE

Genome-wide association analysis in CIMMYT's association panel revealed new favorable native genomic variations in/nearby important genes such as hydroxylases and CCD1 that have potential for carotenoid biofortification in maize. Genome-wide association studies (GWAS) have been used extensively to identify allelic variation for genes controlling important agronomic and nutritional traits in plants. Provitamin A (proVA) enhancing alleles of lycopene epsilon cyclase (LCYE) and β-carotene hydroxylase 1 (CRTRB1), previously identified through candidate-gene based GWAS, are currently used in CIMMYT's maize breeding program. The objective of this study was to identify genes or genomic regions controlling variation for carotenoid concentrations in grain for CIMMYT's carotenoid association mapping panel of 380 inbred maize lines, using high-density genome-wide platforms with ~476,000 SNP markers. Population structure effects were minimized by adjustments using principal components and kinship matrix with mixed models. Genome-wide linkage disequilibrium (LD) analysis indicated faster LD decay (3.9 kb; r (2) = 0.1) than commonly reported for temperate germplasm, and therefore the possibility of achieving higher mapping resolution with our mostly tropical diversity panel. GWAS for various carotenoids identified CRTRB1, LCYE and other key genes or genomic regions that govern rate-critical steps in the upstream pathway, such as DXS1, GGPS1, and GGPS2 that are known to play important roles in the accumulation of precursor isoprenoids as well as downstream genes HYD5, CCD1, and ZEP1, which are involved in hydroxylation and carotenoid degradation. SNPs at or near all of these regions were identified and may be useful target regions for carotenoid biofortification breeding efforts in maize; for example a genomic region on chromosome 2 explained ~16% of the phenotypic variance for β-carotene independently of CRTRB1, and a variant of CCD1 that resulted in reduced β-cryptoxanthin degradation was found in lines that have previously been observed to have low proVA degradation rates.

A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.)

This study identified 333 genomic regions associated to 28 traits related to nitrogen use efficiency in European winter wheat using genome-wide association in a 214-varieties panel experimented in eight environments. Improving nitrogen use efficiency is a key factor to sustainably ensure global production increase. However, while high-throughput screening methods remain at a developmental stage, genetic progress may be mainly driven by marker-assisted selection. The objective of this study was to identify chromosomal regions associated with nitrogen use efficiency-related traits in bread wheat (Triticum aestivum L.) using a genome-wide association approach. Two hundred and fourteen European elite varieties were characterised for 28 traits related to nitrogen use efficiency in eight environments in which two different nitrogen fertilisation levels were tested. The genome-wide association study was carried out using 23,603 SNP with a mixed model for taking into account parentage relationships among varieties. We identified 1,010 significantly associated SNP which defined 333 chromosomal regions associated with at least one trait and found colocalisations for 39 % of these chromosomal regions. A method based on linkage disequilibrium to define the associated region was suggested and discussed with reference to false positive rate. Through a network approach, colocalisations were analysed and highlighted the impact of genomic regions controlling nitrogen status at flowering, precocity, and nitrogen utilisation on global agronomic performance. We were able to explain 40 ± 10 % of the total genetic variation. Numerous colocalisations with previously published genomic regions were observed with such candidate genes as Ppd-D1, Rht-D1, NADH-Gogat, and GSe. We highlighted selection pressure on yield and nitrogen utilisation discussing allele frequencies in associated regions.

Genetic analysis of root morphological traits in wheat

Traits related to root architecture are of great importance for yield performance of crop species, although they remain poorly understood. The present study is aimed at identifying the genomic regions involved in the control of root morphological traits in durum wheat (Triticum durum Desf.). A set of 123 recombinant inbred lines derived from the durum wheat cross of cvs. 'Creso' × 'Pedroso' were grown hydroponically to two growth stages, and were phenotypically evaluated for a number of root traits. In addition, meta-(M)QTL analysis was performed that considered the results of other root traits studies in wheat, to compare with the 'Creso' × 'Pedroso' cross and to increase the QTL detection power. Eight quantitative trait loci (QTL) for traits related to root morphology were identified on chromosomes 1A, 1B, 2A, 3A, 6A and 6B in the 'Creso' × 'Pedroso' segregating population. Twenty-two MQTL that comprised from two to six individual QTL that had widely varying confidence intervals were found on 14 chromosomes. The data from the present study provide a detailed analysis of the genetic basis of morphological root traits in wheat. This study of the 'Creso' × 'Pedroso' durum-wheat population has revealed some QTL that had not been previously identified.

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Drought resistance - is it really a complex trait?

Drought resistance is being increasingly labelled as being a 'complex trait', especially with the recent expansion of research into its genomics. There is a danger that this label may turn into an axiom that is liable to damage education on the subject as well as research and the delivery of solutions to the farmer. This opinionated review examines whether there is grounds for such an axiom. Drought resistance is labelled as a 'complex trait' mainly when viewed by molecular biologists from the gene discovery platform. This platform is capable of expressing hundreds and thousands of drought-responsive genes, which are up- or down-regulated under dehydration stress according to growth stage, plant organ or even time of day. Sorting out the 'grain out of the chaff' in order to identify the function of the candidate genes towards drought resistance is difficult and, thus, the idea that drought resistance is complex is raised. However, when drought resistance is viewed from the physiological and agronomic whole-plant and crop platform, it appears much simpler; its control, whether constitutive or adaptive, is rather obvious with respect to manipulation in breeding and crop management. The most important and common drought resistance traits function to maintain plant hydration under drought stress due to effective use of water (EUW). The state of our knowledge and the achievements in breeding for drought resistance do not support labelling drought resistance as a complex trait. The genomics road towards drought resistance is complex but we already know that the destination is much simpler.

Gametic embryogenesis and haploid technology as valuable support to plant breeding

Plant breeding is focused on continuously increasing crop production to meet the needs of an ever-growing world population, improving food quality to ensure a long and healthy life and address the problems of global warming and environment pollution, together with the challenges of developing novel sources of biofuels. The breeders' search for novel genetic combinations, with which to select plants with improved traits to satisfy both farmers and consumers, is endless. About half of the dramatic increase in crop yield obtained in the second half of the last century has been achieved thanks to the results of genetic improvement, while the residual advance has been due to the enhanced management techniques (pest and disease control, fertilization, and irrigation). Biotechnologies provide powerful tools for plant breeding, and among these ones, tissue culture, particularly haploid and doubled haploid technology, can effectively help to select superior plants. In fact, haploids (Hs), which are plants with gametophytic chromosome number, and doubled haploids (DHs), which are haploids that have undergone chromosome duplication, represent a particularly attractive biotechnological method to accelerate plant breeding. Currently, haploid technology, making possible through gametic embryogenesis the single-step development of complete homozygous lines from heterozygous parents, has already had a huge impact on agricultural systems of many agronomically important crops, representing an integral part in their improvement programmes. The aim of this review was to provide some background, recent advances, and future prospective on the employment of haploid technology through gametic embryogenesis as a powerful tool to support plant breeding.

Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat

Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F(8:9) recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht-B1, Rht-D1 and Rht13, respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate.

Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat

A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from a different crossover event and distinct from all other recombinants in the proportions of rye and wheat chromatin present. It provides a simple and powerful approach to detect even small QTL effects using fewer progeny. A promising empirical Bayes method was applied to estimate additive and epistatic effects for all possible marker pairs simultaneously in a single model. This method has an advantage for QTL analysis in minimizing the error variance and detecting interaction effects between loci with no main effect. A total of 15 QTL effects, 6 additive and 9 epistatic, were detected for different traits of root length and root weight in 1RS wheat. Epistatic interactions were further partitioned into inter-genomic (wheat and rye alleles) and intra-genomic (rye-rye or wheat-wheat alleles) interactions affecting various root traits. Four common regions were identified involving all the QTL for root traits. Two regions carried QTL for almost all the root traits and were responsible for all the epistatic interactions. Evidence for inter-genomic interactions is provided. Comparison of mean values supported the QTL detection.

Mapping QTL associated with photoperiod sensitivity and assessing the importance of QTL×environment interaction for flowering time in maize

Background

An understanding of the genetic determinism of photoperiod response of flowering is a prerequisite for the successful exchange of germplasm across different latitudes. In order to contribute to resolve the genetic basis of photoperiod sensitivity in maize, a set of 201 recombinant inbred lines (RIL), derived from a temperate and tropical inbred line cross were evaluated in 5 field trials spread in short- and long-day environments.

Methodology/Principal Findings

Firstly, QTL analyses for flowering time and photoperiod sensitivity in maize were conducted in individual photoperiod environments separately, and then, the total genetic effect was partitioned into additive effect (A) and additive-by-environment interaction effect (AE) by using a mixed-model-based composite interval mapping (MCIM) method.

Conclusions/Significance

Seven putative QTL were found associated with DPS thermal time based on the data estimated in individual environments. Nine putative QTL were found associated with DPS thermal time across environments and six of them showed significant QTL×enviroment (QE) interactions. Three QTL for photoperiod sensitivity were identified on chromosome 4, 9 and 10, which had the similar position to QTL for DPS thermal time in the two long-day environment. The major photoperiod sensitive loci qDPS10 responded to both short and long-day photoperiod environments and had opposite effects in different photoperiod environment. The QTL qDPS3, which had the greatest additive effect exclusively in the short-day environment, were photoperiod independent and should be classified in autonomous promotion pathway.

Genetic dissection of the developmental behaviours of plant height in wheat under diverse water regimes

Plant height (PH), a crucial trait related to yield potential in crop plants, is known to be typically quantitatively inherited. However, its full expression can be inhibited by a limited water supply. In this study, the genetic basis of the developmental behaviour of PH was assessed in a 150-line wheat (Triticum aestivum L.) doubled haploid population (Hanxuan 10 x Lumai 14) grown in 10 environments (year x site x water regime combinations) by unconditional and conditional quantitative trait locus (QTL) analyses in a mixed linear model. Genes that were expressed selectively during ontogeny were identified. No single QTL was continually active in all periods of PH growth, and QTLs with additive effects (A-QTLs) expressed in the period S1|S0 (the period from the original point to the jointing stage) formed a foundation for PH development. Additive main effects (a effects), which were mostly expressed in S1|S0, were more important than epistatic main effects (aa effects) or QTL x environment interaction (QE) effects, suggesting that S1|S0 was the most significant development period affecting PH growth. A few QTLs, such as QPh.cgb-6B.7, showed high adaptability for water-limited environments. Many QTLs, including four A-QTLs (QPh.cgb-2D.1, QPh.cgb-4B.1, QPh.cgb-4D.1, and QPh.cgb-5A.7) coincident with previously identified reduced height (Rht) genes (Rht8, Rht1, Rht2, and Rht9), interacted with more than one other QTL, indicating that the genetic architecture underlying PH development is a network of genes with additive and epistatic effects. Therefore, based on multilocus combinations in S1|S0, superior genotypes were predicted for guiding improvements in breeding for PH.

Linkage and association mapping of Arabidopsis thaliana flowering time in nature

Flowering time is a key life-history trait in the plant life cycle. Most studies to unravel the genetics of flowering time in Arabidopsis thaliana have been performed under greenhouse conditions. Here, we describe a study about the genetics of flowering time that differs from previous studies in two important ways: first, we measure flowering time in a more complex and ecologically realistic environment; and, second, we combine the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping. Our experiments involved phenotyping nearly 20,000 plants over 2 winters under field conditions, including 184 worldwide natural accessions genotyped for 216,509 SNPs and 4,366 RILs derived from 13 independent crosses chosen to maximize genetic and phenotypic diversity. Based on a photothermal time model, the flowering time variation scored in our field experiment was poorly correlated with the flowering time variation previously obtained under greenhouse conditions, reinforcing previous demonstrations of the importance of genotype by environment interactions in A. thaliana and the need to study adaptive variation under natural conditions. The use of 4,366 RILs provides great power for dissecting the genetic architecture of flowering time in A. thaliana under our specific field conditions. We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters. We show that QTL mapping increases our power to distinguish true from false associations in GWA mapping. QTL mapping also permits the identification of false negatives, that is, causative SNPs that are lost when applying GWA methods that control for population structure. Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study. Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock. Furthermore, we identified new genomic regions lacking obvious candidate genes.

Haploids in flowering plants: origins and exploitation

The first haploid angiosperm, a dwarf form of cotton with half the normal chromosome complement, was discovered in 1920, and in the ninety years since then such plants have been identified in many other species. They can occur either spontaneously or can be induced by modified pollination methods in vivo, or by in vitro culture of immature male or female gametophytes. Haploids represent an immediate, one-stage route to homozygous diploids and thence to F(1) hybrid production. The commercial exploitation of heterosis in such F(1) hybrids leads to the development of hybrid seed companies and subsequently to the GM revolution in agriculture. This review describes the range of techniques available for the isolation or induction of haploids and discusses their value in a range of areas, from fundamental research on mutant isolation and transformation, through to applied aspects of quantitative genetics and plant breeding. It will also focus on how molecular methods have been used recently to explore some of the underlying aspects of this fascinating developmental phenomenon.