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.

Identification of genomic regions associated with cereal cyst nematode (Heterodera avenae Woll.) resistance in spring and winter wheat.

Cereal cyst nematode (CCN) is a major threat to cereal crop production globally including wheat (Triticum aestivum L.). In the present study, single-locus and multi-locus models of Genome-Wide Association Study (GWAS) were used to find marker trait associations (MTAs) against CCN (Heterodera avenae) in wheat. In total, 180 wheat accessions (100 spring and 80 winter types) were screened against H. avenae in two independent years (2018/2019 "Environment 1" and 2019/2020 "Environment 2") under controlled conditions. A set of 12,908 SNP markers were used to perform the GWAS. Altogether, 11 significant MTAs, with threshold value of -log10 (p-values) ≥ 3.0, were detected using 180 wheat accessions under combined environment (CE). A novel MTA (wsnp_Ex_c53387_56641291) was detected under all environments (E1, E2 and CE) and considered to be stable MTA. Among the identified 11 MTAs, eight were novel and three were co-localized with previously known genes/QTLs/MTAs. In total, 13 putative candidate genes showing differential expression in roots, and known to be involved in plant defense mechanisms were reported. These MTAs could help us to identify resistance alleles from new sources, which could be used to identify wheat varieties with enhanced CCN resistance.

GWAS scans of cereal cyst nematode (Heterodera avenae) resistance in Indian wheat germplasm.

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (-log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods.

QTL mapping for resistance against cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.).

The resistance to cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.) was studied using 114 doubled haploid lines from a novel ITMI mapping population. These lines were screened for nematode infestation in a controlled environment for two years. QTL-mapping analyses were performed across two years (Y1 and Y2) as well as combining two years (CY) data. On the 114 lines that were screened, a total of 2,736 data points (genotype, batch or years, and replication combinations) were acquired. For QTL analysis, 12,093 markers (11,678 SNPs and 415 SSRs markers) were used, after filtering the genotypic data, for the QTL mapping. Composite interval mapping, using Haley-Knott regression (hk) method in R/QTL, was used for QTL analysis. In total, 19 QTLs were detected out of which 13 were novel and six were found to be colocalized or nearby to previously reported Cre genes, QTLs or MTAs for H. avenae or H. filipjevi. Nine QTLs were detected across all three groups (Y1, Y2 and CY) including a significant QTL "QCcn.ha-2D" on chromosome 2D that explains 23% of the variance. This QTL colocalized with a previously identified Cre3 locus. Novel QTL, QCcn.ha-2A, detected in the present study could be the possible unreported homeoloci to QCcn.ha-2D, QCcn.ha-2B.1 and QCcn.ha-2B.2. Six significant digenic epistatic interactions were also observed. In addition, 26 candidate genes were also identified including genes known for their involvement in PPNs (plant parasitic nematodes) resistance in different plant species. In-silico expression of putative candidate genes showed differential expression in roots during specific developmental stages. Results obtained in the present study are useful for wheat breeding to generate resistant genetic resources against H. avenae.

GWAS for main effects and epistatic interactions for grain morphology traits in wheat.

In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-022-01164-w.

WheatQTLdb V2.0: a supplement to the database for wheat QTL.

We recently developed a database for hexaploid wheat QTL (WheatQTLdb; www.wheatqtldb.net), which included 11,552 QTL affecting various traits of economic importance. However, that database did not include valuable QTL from other wheat species and/or progenitors of hexaploid wheat. Therefore, an updated and improved version of wheat QTL database (WheatQTLdb V2.0) was developed, which now includes information on hexaploid wheat (Triticum aestivum) and the following seven other related species: T. durum, T. turgidum, T. dicoccoides, T. dicoccum, T. monococcum, T. boeoticum, and Aegilops tauschii. WheatQTLdb V2.0 includes a much-improved list of QTL, including 27,518 main effect QTL, 202 epistatic QTL, and 1321 metaQTL. This newly released WheatQTLdb V2.0 also has additional valuable options to search and choose the QTL, category-wise, and trait-wise data for their use in research or breeding programs.

Multi-locus genome-wide association mapping for spike-related traits in bread wheat (Triticum aestivum L.).

BACKGROUND: Bread wheat (Triticum aestivum L.) is one of the most important cereal food crops for the global population. Spike-layer uniformity (the consistency of the spike distribution in the vertical space)-related traits (SLURTs) are quantitative and have been shown to directly affect yield potential by modifying the plant architecture. Therefore, these parameters are important breeding targets for wheat improvement. The present study is the first genome-wide association study (GWAS) targeting SLURTs in wheat. In this study, a set of 225 diverse spring wheat accessions were used for multi-locus GWAS to evaluate SLURTs, including the number of spikes per plant (NSPP), spike length (SL), number of spikelets per spike (NSPS), grain weight per spike (GWPS), lowest tiller height (LTH), spike-layer thickness (SLT), spike-layer number (SLN) and spike-layer uniformity (SLU). RESULTS: In total, 136 significant marker trait associations (MTAs) were identified when the analysis was both performed individually and combined for two environments. Twenty-nine MTAs were detected in environment one, 48 MTAs were discovered in environment two and 59 MTAs were detected using combined data from the two environments. Altogether, 15 significant MTAs were found for five traits in one of the two environments, and four significant MTAs were detected for the two traits, LTH and SLU, in both environments i.e. E1, E2 and also in combined data from the two environments. In total, 279 candidate genes (CGs) were identified, including Chaperone DnaJ, ABC transporter-like, AP2/ERF, SWEET sugar transporter, as well as genes that have previously been associated with wheat spike development, seed development and grain yield. CONCLUSIONS: The MTAs detected through multi-locus GWAS will be useful for improving SLURTs and thus yield in wheat production through marker-assisted and genomic selection.

WheatQTLdb: a QTL database for wheat.

During the last three decades, QTL analysis in wheat has been conducted for a variety of individual traits, so that thousands of QTL along with the linked markers, their genetic positions and contribution to phenotypic variation (PV) for concerned traits are now known. However, no exhaustive database for wheat QTL is currently available at a single platform. Therefore, the present database was prepared which is an exhaustive information resource for wheat QTL data from the published literature till May, 2020. QTL data from both interval mapping and genome-wide association studies (GWAS) have been included for the following classes of traits: (i) morphological traits, (ii) N and P use efficiency, (iii) traits for biofortification (Fe, K, Se, and Zn contents), (iv) tolerance to abiotic stresses including drought, water logging, heat stress, pre-harvest sprouting and salinity, (v) resistance to biotic stresses including those due to bacterial, fungal, nematode and insects, (vi) quality traits, and (vii) a variety of physiological traits, (viii) developmental traits, and (ix) yield and its related traits. For the preparation of the database, literature was searched for data on QTL/marker-trait associations (MTAs), curated and then assembled in the form of WheatQTLdb. The available information on metaQTL, epistatic QTL and candidate genes, wherever available, is also included in the database. Information on QTL in this WheatQTLdb includes QTL names, traits, associated markers, parental genotypes, crosses/mapping populations, association mapping panels and other useful information. To our knowledge, WheatQTLdb prepared by us is the largest collection of QTL (11,552), epistatic QTL (107) and metaQTL (330) data for hexaploid wheat to be used by geneticists and plant breeders for further studies involving fine mapping, cloning, and marker-assisted selection (MAS) during wheat breeding.

Genome-wide association study in hexaploid wheat identifies novel genomic regions associated with resistance to root lesion nematode (Pratylenchus thornei).

Root lesion nematode (RLN; Pratylenchus thornei) causes extensive yield losses in wheat worldwide and thus pose serious threat to global food security. Reliance on fumigants (such as methyl bromide) and nematicides for crop protection has been discouraged due to environmental concerns. Hence, alternative environment friendly control measures like finding and deployment of resistance genes against Pratylenchus thornei are of significant importance. In the present study, genome-wide association study (GWAS) was performed using single-locus and multi-locus methods. In total, 143 wheat genotypes collected from pan-Indian wheat cultivation states were used for nematode screening. Genotypic data consisted of  > 7K SNPs with known genetic positions on the high-density consensus map was used for association analysis. Principal component analysis indicated the existence of sub-populations with no major structuring of populations due to the origin. Altogether, 25 significant marker trait associations were detected with - log10 (p value) > 4.0. Three large linkage disequilibrium blocks and the corresponding haplotypes were found to be associated with significant SNPs. In total, 37 candidate genes with nine genes having a putative role in disease resistance (F-box-like domain superfamily, Leucine-rich repeat, cysteine-containing subtype, Cytochrome P450 superfamily, Zinc finger C2H2-type, RING/FYVE/PHD-type, etc.) were identified. Genomic selection was conducted to investigate how well one could predict the phenotype of the nematode count without performing the screening experiments. Prediction value of r = 0.40 to 0.44 was observed when 56 to 70% of the population was used as a training set. This is the first report where GWAS has been conducted to find resistance against root lesion nematode (P. thornei) in Indian wheat germplasm.

Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat.

A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01240-1.

Genetic diversity and population structure analysis of Indian garlic (Allium sativum L.) collection using SSR markers.

Genetic diversity was assessed among 53 Indian garlic accessions using SSR markers. Initially, 24 SSR primer pairs were used for screening three selected garlic accessions. Out of 24 SSR primer pairs, 10 primer pairs which consistently showed good amplification and polymorphism were selected for DNA profiling. SSR primer pairs showed PIC values ranging from 0.30 to 0.99. Based on AMOVA we found that the greater part of the genetic diversity was expected due to intra population with 84% variation and only 16% of variation was due to among populations suggesting presence of genetic structure. The results of cluster analysis and principal component analysis largely correspond to each other. Population structure analysis revealed genetic differentiation of accessions. The results of present study revealed existence of significant variability in Indian garlic germplasm.

Assessment of genetic diversity and population structure in gladiolus (Gladiolus hybridus Hort.) by ISSR markers.

ISSR (Inter simple sequence repeat) markers were used to assess the genetic diversity and population structure in 53 indigenous and exotic genotypes of gladiolus (Gladiolus hybridus Hort.). Molecular markers analysis showed PIC ranges from 0.42 (ISSR 861) to 0.99 (ISSR 855, ISSR 856 and ISSR 889) with an average 0.812, marker index ranged from 0.99 (ISSR 889) to 9.26 (ISSR 851) with an average 4.66 and resolving power of the primers ranged from 0.03 (ISSR 889) to 11.58 (ISSR 861) with an average value 3.80. The dendrogram based UPGMA clustering showed that all the 53 genotypes grouped into three main clusters. Nei's gene diversity (Na) varied from 0.929 to 1.717, effective number of alleles (Ne) varied from 1.262 to 1.369, Shannon's information index (I) ranged from 0.251 to 0.359 and gene diversity (He) was in the range from 0.167 to 0.229. Population structure analysis revealed three groups in which 32 genotypes were admixture types.

Comparative QTL analysis of root lesion nematode resistance in barley.

KEY MESSAGE: This study demonstrates for the first time that resistance to different root lesion nematodes ( P. neglectus and P. penetrans ) is controlled by a common QTL. A major resistance QTL ( Rlnnp6H ) has been mapped to chromosome 6H using two independent barley populations. Root lesion nematodes (Pratylenchus spp.) are important pests in cereal production worldwide. We selected two doubled haploid populations of barley (Igri × Franka and Uschi × HHOR 3073) and infected them with Pratylenchus penetrans and Pratylenchus neglectus. Nematode multiplication rates were measured 7 or 10 weeks after infection. In both populations, continuous phenotypic variations for nematode multiplication rates were detected indicating a quantitative inheritance of resistance. In the Igri × Franka population, four P. penetrans resistance QTLs were mapped with 857 molecular markers on four linkage groups (2H, 5H, 6H and 7H). In the Uschi × HHOR 3073 population, eleven resistance QTLs (P. penetrans and P. neglectus) were mapped with 646 molecular markers on linkage groups 1H, 3H, 4H, 5H, 6H and 7H. A major resistance QTL named Rlnnp6H (LOD score 6.42-11.19) with a large phenotypic effect (27.5-36.6 %) for both pests was mapped in both populations to chromosome 6H. Another resistance QTL for both pests was mapped on linkage group 5H (Igri × Franka population). These data provide first evidence for common resistance mechanisms against different root lesion nematode species. The molecular markers are a powerful tool for the selection of resistant barley lines among segregating populations because resistance tests are time consuming and laborious.

MutMap+: genetic mapping and mutant identification without crossing in rice.

Advances in genome sequencing technologies have enabled researchers and breeders to rapidly associate phenotypic variation to genome sequence differences. We recently took advantage of next-generation sequencing technology to develop MutMap, a method that allows rapid identification of causal nucleotide changes of rice mutants by whole genome resequencing of pooled DNA of mutant F2 progeny derived from crosses made between candidate mutants and the parental line. Here we describe MutMap+, a versatile extension of MutMap, that identifies causal mutations by comparing SNP frequencies of bulked DNA of mutant and wild-type progeny of M3 generation derived from selfing of an M2 heterozygous individual. Notably, MutMap+ does not necessitate artificial crossing between mutants and the wild-type parental line. This method is therefore suitable for identifying mutations that cause early development lethality, sterility, or generally hamper crossing. Furthermore, MutMap+ is potentially useful for gene isolation in crops that are recalcitrant to artificial crosses.

Deployment of the Burkholderia glumae type III secretion system as an efficient tool for translocating pathogen effectors to monocot cells.

Genome sequences of plant fungal pathogens have enabled the identification of effectors that cooperatively modulate the cellular environment for successful fungal growth and suppress host defense. Identification and characterization of novel effector proteins are crucial for understanding pathogen virulence and host-plant defense mechanisms. Previous reports indicate that the Pseudomonas syringae pv. tomato DC3000 type III secretion system (T3SS) can be used to study how non-bacterial effectors manipulate dicot plant cell function using the effector detector vector (pEDV) system. Here we report a pEDV-based effector delivery system in which the T3SS of Burkholderia glumae, an emerging rice pathogen, is used to translocate the AVR-Pik and AVR-Pii effectors of the fungal pathogen Magnaporthe oryzae to rice cytoplasm. The translocated AVR-Pik and AVR-Pii showed avirulence activity when tested in rice cultivars containing the cognate R genes. AVR-Pik reduced and delayed the hypersensitive response triggered by B. glumae in the non-host plant Nicotiana benthamiana, indicative of an immunosuppressive virulence activity. AVR proteins fused with fluorescent protein and nuclear localization signal were delivered by B. glumae T3SS and observed in the nuclei of infected cells in rice, wheat, barley and N. benthamiana. Our bacterial T3SS-enabled eukaryotic effector delivery and subcellular localization assays provide a useful method for identifying and studying effector functions in monocot plants.

QTL analysis of root-lesion nematode resistance in barley: 1. Pratylenchus neglectus.

The root-lesion nematode Pratylenchus neglectus can cause severe losses in barley cultivation. Multiplication rates had been found to vary greatly between different barley accessions. Two winter barley cultivars, Igri and Franka, had been found to differ in their ability to resist this parasite. An existing Igri × Franka doubled haploid population was chosen to genetically map resistance genes after artificial inoculation with P. neglectus in the greenhouse and climate chamber. A continuous phenotypic variation was found indicating a quantitative inheritance of P. neglectus resistance. An existing map was enriched by 527 newly developed Diversity Array Technology markers (DArTs). The new genetic linkage map was comprised of 857 molecular markers that cover 1,157 cM on seven linkage groups. Using phenotypic data collected from four different experiments in 3 years, five quantitative trait loci were mapped by composite interval mapping on four (3H, 5H, 6H and 7H) linkage groups. A quantitative trait locus with a large phenotypic effect of 16% and likelihood of odds (LOD) score of 6.35 was mapped on linkage group 3H. The remaining four QTLs were classified as minor or moderate with LOD scores ranging from 2.71 to 3.55 and R (2) values ranging from 8 to 10%. The DNA markers linked to the resistance QTLs should be quite useful for marker-assisted selection in barley breeding because phenotypic selection is limited due to time constraints and labor costs.

Delineating the structural, functional and evolutionary relationships of sucrose phosphate synthase gene family II in wheat and related grasses.

BACKGROUND: Sucrose phosphate synthase (SPS) is an important component of the plant sucrose biosynthesis pathway. In the monocotyledonous Poaceae, five SPS genes have been identified. Here we present a detailed analysis of the wheat SPSII family in wheat. A set of homoeologue-specific primers was developed in order to permit both the detection of sequence variation, and the dissection of the individual contribution of each homoeologue to the global expression of SPSII. RESULTS: The expression in bread wheat over the course of development of various sucrose biosynthesis genes monitored on an Affymetrix array showed that the SPS genes were regulated over time and space. SPSII homoeologue-specific assays were used to show that the three homoeologues contributed differentially to the global expression of SPSII. Genetic mapping placed the set of homoeoloci on the short arms of the homoeologous group 3 chromosomes. A resequencing of the A and B genome copies allowed the detection of four haplotypes at each locus. The 3B copy includes an unspliced intron. A comparison of the sequences of the wheat SPSII orthologues present in the diploid progenitors einkorn, goatgrass and Triticum speltoides, as well as in the more distantly related species barley, rice, sorghum and purple false brome demonstrated that intronic sequence was less well conserved than exonic. Comparative sequence and phylogenetic analysis of SPSII gene showed that false purple brome was more similar to Triticeae than to rice. Wheat - rice synteny was found to be perturbed at the SPS region. CONCLUSION: The homoeologue-specific assays will be suitable to derive associations between SPS functionality and key phenotypic traits. The amplicon sequences derived from the homoeologue-specific primers are informative regarding the evolution of SPSII in a polyploid context.

Genetic diversity in Indian common bean (Phaseolus vulgaris L.) using random amplified polymorphic DNA markers.

Genetic diversity of twenty-six common bean (Phaseolus vulgaris L.) accessions of diverse geographical origin was studied using Random Amplified Polymorphic DNA (RAPD) markers. Fifteen out of forty four primers screened showed polymorphism across present set of genotypes. A total of 124 amplicons were scored using these 15 primers. Ninety five percent of the amplified products showed polymorphism, indicating fair amount of variation at the DNA level among these accessions. Cluster analysis delineated the genotypes in to four groups.