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Epigenetic regulation of the activity of defense genes during onset of diseases or resistance against diseases in plants is an active area of research. In the present study, a pair of wheat NILs for leaf rust resistance gene Lr28 (R) in the background of an Indian cultivar HD2329 (S) was used for a study of DNA methylation mediated regulation of gene expression. Leaf samples were collected at 0 h before (S0 and R0) and 96 h after inoculation (S96 and R96). The DNA samples were subjected to BS-Seq and sequencing data were used for identification of differentially methylated/demethylated regions/genes (DMRs and DMGs). Following four pairs of comparisons were used for this purpose: S0 vs S96; S0 vs R0; R0 vs R96; S96 vs R96. Major role of CHH methylation relative to that of CG and CHG methylation was observed. Some important observations include the following: (i) abundance of CHH methylation among DMRs; (ii) predominance of DMRs in intergenic region, relative to other genomic regions (promoters, exons, introns, TSS and TTS); (iii) abundance of transposable elements (TEs) in DMRs with CHH context; (iv) demethylation mediated high expression of genes during susceptible reaction (S0 vs S96) and methylation mediated low expression of genes during resistant reaction (R0 vs R96 and S96 vs R96); (v) major genes under regulation encode proteins, which differ from those encoded by genes regulated during susceptible reaction and (vi) ~ 500 DMGs carried differential binding sites for H3K4/K27me3 marks suggesting joint involvement of DNA and H3 methylation. Thus, CHH methylation either alone or in combination with histone methylation plays a major role in regulating the expression of genes involved in wheat-leaf rust interaction.

Majority of cereals are deficient in essential micronutrients including grain iron (GFe) and grain zinc (GZn), which are therefore the subject of research involving biofortification. In the present study, 11 meta-QTLs (MQTLs) including nine novel MQTLs for GFe and GZn contents were identified in wheat. Eight of these 11 MQTLs controlled both GFe and GZn. The confidence intervals of the MQTLs were narrower (0.51–15.75 cM) relative to those of the corresponding QTLs (0.6 to 55.1 cM). Two ortho-MQTLs involving three cereals (wheat, rice and maize) were also identified. Results of MQTLs were also compared with the results of earlier genome wide association studies (GWAS). As many as 101 candidate genes (CGs) underlying MQTLs were also identified. Twelve of these CGs were prioritized; these CGs encoded proteins with important domains (zinc finger, RING/FYVE/PHD type, flavin adenine dinucleotide linked oxidase, etc.) that are involved in metal ion binding, heme binding, iron binding, etc. qRT-PCR analysis was conducted for four of these 12 prioritized CGs using genotypes which have differed for GFe and GZn. Significant differential expression in these genotypes was observed at 14 and 28 days after anthesis. The MQTLs/CGs identified in the present study may be utilized in marker-assisted selection (MAS) for improvement of GFe/GZn contents and also for understanding the molecular basis of GFe/GZn homeostasis in wheat. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-022-01149-9.

The genetic architecture of nitrogen use efficiency (NUE) and its two component traits i.e. NUpE (N uptake efficiency) and NUtE (N utilization efficiency) was studied using a bi-parental RIL mapping population derived from a cross HUW468 (high NUE)/C306 (low NUE). The mapping population, two parental genotypes and three check genotypes were evaluated under four different N levels (0, 60, 120, and 180 kg/ha) over three years. A genetic map containing 456 SNP markers (2,571.38 cM length) was used for QTL analysis. Thirty six main effect QTLs (17 QTLs for NUE, 13 NUpE and 6QTLs for NUtE) distributed on 12 chromosomes (1B, 1D, 2A, 2B, 3A, 4B, 5A, 5B, 5D, 6A, 6D, and 7A) were identified at 2.52 to 9.27 LOD scores. Individual QTLs explained 6.65–22.89% phenotypic variation. Multi-traits QTLs (Mt-QTLs) and and epistatic QTLs involving first order epistatic (QTL x QTL) interactions were also discovered. Candidate genes (CGs, as many as 737) were mined from QTL regions which were mainly involved in metabolic process, cellular process and catalytic activity, etc; differential expression was observed for 49 genes in roots and 34 CGs in shoots. The CGs encoded important transcription factors, transporters etc. having a role in NUE. QTLs and CGs reported in this study enriched the available knowledge. Seven QTLs (including three Mt-QTLs) and QTLs involved in six epistatic interactions were recommended for MAS for improvement of NUE in wheat.

We recently developed a database for hexaploid wheat QTL (WheatQTLdb; www.wheatqtldb.net) that 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 bread wheat. Therefore, an updated and wider version of wheat QTL database (WheatQTLdb V2.0) was developed in this study which now includes information on hexaploid wheat (Triticum aestivum) as well as 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, so that V2.0 now has 27,518 main-effect QTL, 202 epistatic QTL, and 1,321 metaQTL. This newly released WheatQTLdb V2.0 will provide plant breeders and geneticists much more valuable options to search and choose the category-wise and trait-wise data for their research or breeding programmes.

In wheat, a genome-wide association study (GWAS) combined with a study of genomic prediction (GP) was conducted for pre-harvest sprouting tolerance (PHST). For GWAS, a panel of 190 accessions was phenotyped for the three parameters of PHST (sprouting score, falling number and grain color) over two years and genotyped with 9,904 DArT-seq SNP markers. GWAS for main-effect quantitative trait nucleotides (M-QTNs) was performed using the following three models: CMLM, SUPER, and FarmCPU. A total of 171 M-QTNs (CMLM, 47; SUPER, 70; FarmCPU, 54) were detected, suggesting differences in efficiencies of the three models. As many as 15 epistatic QTNs (E-QTNs) involved in 20 first order epistatic interactions were also identified using PLINK v1.07. A total of 26 PHS-responsive genomic regions (each 5 Mbp in size) that spread over 16 chromosomes were demarcated, which overlapped the previously mapped QTLs, MTAs, cloned genes and the M-QTNs reported in the present study. As many as 20 definitive and stable QTNs were recommended for use in marker-assisted recurrent selection (MARS) for improvement of PHST. Candidate genes associated with different M-QTNs revealed key role of some QTNs in abscisic acid pathway involved in PHST. Genomic prediction accuracies (based on cross-validation approach) using three different models ranged from 0.41 to 055, which are comparable to the results of previous studies. In summary, the results of the present study improved our understanding of the genetic architecture of PHST in wheat and provided novel genomic resources for wheat breeding based on MARS and GP.

Meta-QTL (MQTL) analysis for drought tolerance was undertaken in bread wheat to identify consensus and robust MQTLs using 340 known QTLs from 11 earlier studies; 13 MQTLs located on 6 chromosomes (1D, 3B, 5A, 6D, 7A and 7D) were identified, with maximum of 4 MQTLs on chromosome 5A. Mean confidence intervals for MQTLs were much narrower (mean, 6.01 cM; range 2.07–19.46 cM), relative to those in original QTLs (mean, 13.6 cM; range, 1.0–119.1 cM). Two MQTLs, namely MQTL4 and MQTL12, were major MQTLs with potential for use in marker-assisting breeding. As many as 228 candidate genes (CGs) were also identified using 6 of the 13 MQTLs. In-silico expression analysis of these 228 CGs allowed identification of 14 important CGs, with + 3 to − 8 fold change in expression under drought (relative to normal conditions) in a tolerant cv. named TAM107. These CGs encoded proteins belonging to the following families: NAD-dependent epimerase/dehydratase, protein kinase, NAD(P)-binding domain protein, heat shock protein 70 (Hsp70), glycosyltransferase 2-like, etc. Important MQTLs and CGs identified in the present study should prove useful for future molecular breeding and for the study of molecular basis of drought tolerance in cereals in general and wheat in particular.

Genetic improvement along with widened crop base necessitates for the detailed understanding of the genetic diversity and population structure in wheat. The present investigation reports the discovery of a total of 182 alleles by assaying 52 simple sequence repeats (SSRs) on 40 genotypes of bread wheat. Unweighted neighbour-joining method grouped these genotypes into two main clusters. Highly heat tolerant and intermediate tolerant cultivars were grouped in the same cluster, whereas remaining genotypes, particularly sensitive ones, were assigned different cluster. Similarly, the entire population was structured into two sub-populations (K = 2), closely corresponding with the other distance-based clustering patterns. The marker-trait association was discovered for four important physiological parameters, viz. canopy temperature depression, membrane thermostability index (MSI), normalized difference vegetation index and heat susceptibility index, indicating for heat stress (HS) tolerance in wheat. Both general and mixed linear models of association studies during 2017 and 2018, revealed the association of SSR markers, wmc222 (17.60%, PV) and gwm34 (20.70%, PV) with the mean phenotypic value of MSI. Likewise, SSR markers barc183, gwm75, gwm11 and cfd7 revealed a unique relationship with four selected physiological traits. Candidate genes discovered using in silico tools had nine SSR markers within the genic regions reported to play a role in heat and drought stress responses in plants. The information generated about these genic regions may be explored further in expression studies in-vivo to impart HS tolerance in bread wheat.

In wheat, a major yield QTL (Qyld.csdh.7AL) contributing ~ 20% to the variation for grain yield under drought was introgressed into each of the four Indian wheat cultivars (HUW234, HUW468, K307 and DBW17) with an objective to develop high yielding drought tolerant genotypes. The marker Xwmc273.3 linked to the yield QTL was used for marker assisted foreground selection, which was followed by phenotypic selection leading to the development of 55 advanced lines. These lines were evaluated during the crop seasons 2015–2016 and 2016–2017 under irrigated and rainfed conditions at two locations (Meerut and Niphad), which differed for agro-climatic conditions. Under irrigated condition at Niphad, three lines gave 14.9–25.7% higher yield relative to the corresponding genotypes HUW234 and DWB17 that were used for introgression. Similarly, under rainfed condition at Meerut, one line gave 25.5% higher yield relative to the corresponding genotype HUW234. The high yield in the selected lines was attributed to number of grains per ear, grain weight, tiller number, biomass and lower canopy temperature. The line giving higher yield under rainfed condition also had low stress sensitivity index suggesting its ability to tolerate water-stress. The high yielding lines may be used for testing in a variety development programme. The study is yet another example of the successful use of MAS in combination with phenotypic selection for development of high yielding wheat genotypes for rainfed and irrigated conditions.

In bread wheat, meta-QTL analysis was conducted using 353 QTLs that were available from earlier studies. When projected onto a dense consensus map comprising 76,753 markers, only 184 QTLs with the required information, could be utilized leading to identification of 61 MQTLs spread over 18 of the 21 chromosomes (barring 5D, 6D and 7D). The range for mean R2 (PVE %) was 1.9% to 48.1%, and that of CI was 0.02 to 11.47 cM; these CIs also carried 37 Yr genes. Using these MQTLs, 385 candidate genes (CGs) were also identified. Out of these CGs, 241 encoded known R proteins and 120 showed differential expression due to stripe rust infection at the seedling stage; the remaining 24 CGs were common in the sense that they encoded R proteins as well as showed differential expression. The proteins encoded by CGs carried the following widely known domains: NBS-LRR domain, WRKY domains, ankyrin repeat domains, sugar transport domains, etc. Thirteen breeders’ MQTLs (PVE > 20%) including four pairs of closely linked MQTLs are recommended for use in wheat molecular breeding, for future studies to understand the molecular mechanism of stripe rust resistance and for gene cloning.

Stripe rust caused by Puccinia striiformis f. sp. tritici Eriks. & E. Henn (Pst) is one of the most prevalent wheat diseases causing upto 70% yield losses worldwide. The present study was conducted in wheat for the first time to identify important meta-QTL (MQTL) regions for their use in developing stripe rust resistant wheat cultivars and to understand the genetic architecture of stripe rust resistance in wheat. For this purpose, a dense consensus map consisting of 76,753 markers was constructed and 353 QTLs from earlier studies were projected on this consensus map. As many as 61 MQTLs were identified using 184 (out of 353) original QTLs. Ten important genomic regions including six breeders’ MQTLs (PVE >20%) and four MQTL hotspots were selected to be used by wheat breeders. As many as 409 important candidate genes (CGs) were also identified, which either encoded known R proteins (265) or showed differential expression (144) due to stripe rust infection. These included genes encoding the following proteins: NBS-LRR, WRKY domains, ankyrin repeat domains, sugar transporters, etc. Overall, the present study provided robust MQTLs and underlying CGs which may be potential targets for molecular breeding for development of stripe rust resistant wheat cultivars or may be the target for future molecular studies to understand the mechanism of stripe rust resistance.

The review outlines past failures, present status and future prospects of hybrid wheat, and includes information on CMS/CHA/transgenic approaches for male sterility, heterotic groups and cost-effective hybrid seed production. Hybrid varieties give increased yield and improved grain quality in both cross- and self-pollinated crops. However, hybrid varieties in self-pollinated crops (particularly cereals) have not been very successful, except for hybrid rice in China. In case of hybrid wheat, despite the earlier failures, renewed efforts in recent years have been made and hybrid varieties with desirable attributes have been produced and marketed in some European countries. This review builds upon previous reviews, with a new outlook and improved knowledge base, not covered in earlier reviews. New technologies have been described, which include the Hordeum chilense-based CMS-fertility restorer system, chromosomal XYZ-4E-ms system and the following transgenic technologies: (1) conditional male sterility involving use of tapetum-specific expression of a gene that converts a pro-toxin into a phytotoxin causing male sterility; (2) barnase-barstar SeedLink system of Bayer CropScience; (3) split-barnase system that obviates the need of a barstar-based male restorer line; and (4) seed production technology of DuPont-Pioneer that makes use of transgenes in production of male-sterile lines, but gives hybrid seed with no transgenes. This review also includes a brief account of studies for discovery of heterotic QTL, genomic prediction of hybrid vigour and the development of heterotic groups/patterns and their importance in hybrid wheat production. The problem of high cost of hybrid seed due to required high seed rate in wheat relative to hybrid rice has also been addressed. The review concludes with a brief account of the current efforts and future possibilities in making hybrid wheat a commercial success.

SWEET proteins represent one of the largest sugar transporter family in the plant kingdom and play crucial roles in plant development and stress responses. In the present study, a total of 108 TaSWEET genes distributed on all the 21 wheat chromosomes were identified using the latest whole genome sequence (as against 59 genes reported in an earlier report). These 108 genes included 14 of the 17 types reported in Arabidopsis and also included three novel types. Tandem duplications (22) and segmental duplications (5) played a significant role in the expansion of TaSWEET family. A number of cis-elements were also identified in the promoter regions of TaSWEET genes, indicating response of TaSWEET genes during development and also during biotic/abiotic stresses. The TaSWEET proteins carried 4-7 trans-membrane helices (TMHs) showing diversity in structure. Phylogenetic analysis using SWEET proteins of wheat and 8 other species gave four well-known clusters. Expression analysis involving both in silico and in planta indicated relatively higher expression of TaSWEET genes in water/heat sensitive and leaf rust resistant genotypes. The results provided insights into the functional role of TaSWEETs in biotic and abiotic stresses, which may further help in planning strategies to develop high yielding wheat varieties tolerant to environmental stresses.

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.

Differential DNA methylation due to APR gene Lr48 for leaf rust resistance in wheat cv. CSP44 was examined at pre-adult plant (P-AP) susceptible stage and adult plant (AP) resistant stage. As many as 52,872 differentially methylated regions (DMRs) carrying 897 differentially methylated genes (DMGs) and many intergenic regions were identified. DMGs included exons/introns, promoters and UTRs. Little less than half of DMGs, were also compared with transcriptome data based on RNA-sEq. Susceptibility (at P-AP) was found to be governed by activation (due to hypomethylation) of relatively more genes, whereas resistance (at AP) involved silencing of relatively large number of genes. Using GO terms, DMGs were found to belong to a variety of biological processes including transcription regulation, protein synthesis, signal transduction, defense, photosynthesis, lipid and carbohydrate metabolism. The results of the present study improved our understanding of the epigenetic control of leaf rust APR in 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.

Meta-QTL (MQTL) analysis for drought tolerance was undertaken in bread wheat to identify consensus and robust MQTLs using 340 known QTLs from 11 earlier studies; 13 MQTLs located on 6 chromosomes (1D, 3B, 5A, 6D, 7A and 7D) were identified, with maximum of 4 MQTLs on chromosome 5A. Mean confidence intervals for MQTLs were much narrower (mean, 6.01 cM; range 2.07–19.46 cM), relative to those in original QTLs (mean, 13.6 cM; range, 1.0–119.1 cM). Two MQTLs, namely MQTL4 and MQTL12, were major MQTLs with potential for use in marker-assisting breeding. As many as 228 candidate genes (CGs) were also identified using 6 of the 13 MQTLs. In-silico expression analysis of these 228 CGs allowed identification of 14 important CGs, with + 3 to − 8 fold change in expression under drought (relative to normal conditions) in a tolerant cv. named TAM107. These CGs encoded proteins belonging to the following families: NAD-dependent epimerase/dehydratase, protein kinase, NAD(P)-binding domain protein, heat shock protein 70 (Hsp70), glycosyltransferase 2-like, etc. Important MQTLs and CGs identified in the present study should prove useful for future molecular breeding and for the study of molecular basis of drought tolerance in cereals in general and wheat in particular. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12298-020-00847-6) contains supplementary material, which is available to authorized users.

In common wheat, genes/QTL for a number of traits including grain quality and resistance against all the three rusts were pyramided in the background of an erstwhile elite Indian wheat cv. PBW343. For this purpose, two improved lines (P1 and P2) each in the background of PBW343 were crossed; these two lines were earlier developed using marker-assisted selection (MAS). The genes carried by line “P1” included Yr70/Lr76 + Lr37/Yr17/Sr38, and the genes carried by line “P2” included Gpc-B1/Yr36+QPhs.ccsu-3A.1+QGw.ccsu-1A.3+Lr24/Sr24+Glu-A1-1/Glu-A1-2. Following foreground MAS in F2 and F3 and SDS-PAGE analysis in F5, 23 lines were selected, each carrying all the genes/QTL for grain quality and resistance to three rusts in homozygous condition. Eleven of the selected lines had relatively higher grain protein content (along with one or more other traits) and were also resistant to five pathotypes of Puccinia triticina (Pt), seven pathotypes of Puccinia graminis f. sp. tritici (Pgt), and two pathotypes (78S84 and 47S103) of Puccinia striiformis f. sp. tritici (Pst) that occur in major wheat-growing areas of India. One line (CCSU-7) out of these 11 selected lines had significantly higher grain yield as well as grain protein content compared with check cv. PBW343, which should prove useful in future wheat breeding programs for improving not only the grain quality but also the durability of resistance against all three rusts.

Present study revealed a complex relationship among histone H3 methylation (examined using H3K4/K27me3 marks), cytosine DNA methylation and differential gene expression during Lr28 mediated leaf rust resistance in wheat. During the present study, genome-wide histone modifications were examined in a pair of near isogenic lines (NILs) (with and without Lr28 in the background of cv. HD2329). The two histone marks used included H3K4me3 (an activation mark) and H3K27me3 (a repression mark). The results were compared with levels of expression (using RNA-seq) and DNA methylation (MeDIP) data obtained using the same pair of NILs. Some of the salient features of the present study include the following: (i) large scale differential binding sites (DBS) were available for only H3K4me3 in the susceptible cultivar, but for both H3K4me3 and H3K27me3 in its resistant NIL; (ii) DBSs for H3K27me3 mark were more abundant (> 80%) in intergenic regions, whereas DBSs for H3K4me3 were distributed in all genomic regions including exons, introns, intergenic, TTS (transcription termination sites) and promoters; (iii) fourteen (14) genes associated with DBSs showed co-localization for both the marks; (iv) only a small fraction (7% for H3K4me3 and 12% for H3K27me3) of genes associated with DBSs matched with the levels of gene expression inferred from RNA-seq data; (v) validation studies using qRT-PCR were conducted on 26 selected representative genes; results for only 11 genes could be validated. The proteins encoded by important genes involved in promoting infection included domains generally carried by R gene proteins such as Mlo like protein, protein kinases and purple acid phosphatase. Similarly, proteins encoded by genes involved in resistance included those carrying domains for lectin kinase, R gene, aspartyl protease, etc. Overall, the results suggest a very complex network of downstream genes that are expressed during compatible and incompatible interactions; some of the genes identified during the present study may be used in future validation studies involving RNAi/overexpression approaches.

Differential DNA methylation due to APR gene Lr48 for leaf rust resistance in wheat cv. CSP44 was examined at pre-adult plant (P-AP) susceptible stage and adult plant (AP) resistant stage. As many as 52,872 differentially methylated regions (DMRs) carrying 897 differentially methylated genes (DMGs) and many intergenic regions were identified. A proportion of individual DMGs involved in methylation included exons/introns, promoters and UTRs. DMGs were also compared with transcriptome data based on RNA-seq. Susceptibility (at P-AP) was found to be governed by activation (due to hypomethylation) of relatively more genes, whereas resistance (at AP) involved silencing of relatively large number of genes. Using GO terms, DMGs were assigned to a variety of functions belonging to biological processes including transcription regulation, protein synthesis, signal transduction, defense, photosynthesis, lipid and carbohydrate metabolism. The results of the present study improved our understanding of the epigenetic control of APR to leaf rust in wheat.

Differential DNA methylation due to Lr28 was examined in susceptible (S) wheat cv. HD2329 and its resistant (R) near isogenic line (NIL) (HD2329+Lr28) using two approaches: methylation sensitive amplified polymorphism (MSAP) and methylated DNA immunoprecipitation (MeDIP). S/R lines each had a large number of hypomethylated genes and relatively fewer hypermethylated genes at 96 hai (hours after inoculation) relative to 0 hbi (hours before inoculation), suggesting activation of many genes during the passage of time (96 hai), although identity of genes may differ in S and R lines. When R NIL was compared with S cultivar, there were many hypermethylated and fewer hypomethylated genes in R NIL relative to S cultivar, suggesting that many genes that are active in S cultivar are silenced in R NIL, both at 0 hbi and at 96 hai. Level of methylation was generally abundant in intergenic regions followed by that in promoters, transcription termination sites (TTSs) and exons/introns. Hypermethylation in promoter and gene body regions was not always associated with inhibition of gene expression and vice-versa, indicating that more than one regulatory mechanisms may control the expression of genes due to pathogen attack in presence and absence of Lr28. MSAP analysis also showed abundance of mCG methylation in S cultivar and that of mCCG methylation in R NIL (at 96 hai), suggesting differences in methylation context in NILs with and without Lr28. The results of the present study improved our understanding of the epigenetic control of leaf rust resistance in wheat.

Genome-wide transcriptome analysis was undertaken in a leaf-rust resistant bread wheat line CSP44 (selected from Australian cv. Condor) carrying the adult plant resistance (APR) gene Lr48. Two pre-adult plant (P-AP) susceptible stages (S48 and S96) and two adult plant (AP) resistant stages (R48 and R96) were used for RNA-seq. At the susceptible P-AP stage (during S48 to S96), expression increased in 2062 genes, and declined in 130 genes; 1775 of 2062 differentially expressed genes (DEGs) also exhibited high expression during early incompatible stage R48. Comparison of S96 with R96 showed that the expression of 80 genes was enhanced and that of 208 genes declined at the AP stage. At the resistant AP stage (during R48 to R96), expression of mere 25 genes increased and that of 126 genes declined. Apparently, the resistance during late adult stage (R96) is caused by regulation of the expression of relatively fewer genes, although at pre-adult stage (S48 to S96), expression of large number of genes increased; expression of majority of these genes kept on increasing during adult stage at R48 also. These and other results of the present study suggest that APR may mimic some kind of systemic acquired resistance (SAR). The host-specific DEGs belonged to 10 different classes including genes involved in defence, transport, epigenetics, photosynthesis, genes encoding some transcription factors etc. The pathogen (Puccinia triticina) specific DEGs (including three genes encoding known biotrophic effectors) seem to help the pathogen in infection/growth through large-scale stage-specific enhanced expression of host’s genes. A putative candidate gene for Lr48 containing protein kinase domain (its ortholog in rice encoding OsWAK8) was also identified.

The present study was conducted to study the genetic architecture of grain micronutrients (Zn, Fe and β-carotene contents), grain protein content and four yield traits in a spring wheat reference set comprising 246 genotypes. Phenotypic data on these traits recorded at two locations and the genotyping data for 17,937 SNP markers (obtained through outsourcing) were used for genome wide association study, which gave following results after Bonferroni correction using four methods: (1) single locus single trait analysis gave 136 marker-trait associations; (2) multi-locus mixed model gave 587 MTAs; (3) multi-trait mixed model gave 28 MTAs and (4) matrix-variate linear mixed model gave 33 MTAs. As many as 73 epistatic interactions were also detected. Keeping all the results in mind, nine most important MTAs were selected for biofortification. These markers were associated with three traits (GPC, GFeC and GYPP). These MTAs can be used in wheat improvement programs either using marker-assisted recurrent selection or pseudo-backcrossing method.

Development of leaf rust-resistant cultivars is a priority during wheat breeding, since leaf rust causes major losses in yield. Resistance against leaf rust due to Lr genes is partly controlled by epigenetic modifications including histone acetylation that is known to respond to biotic/abiotic stresses. In the present study, enrichment of H3K4ac and H3K9ac in promoters of six defense responsive genes (N-acetyltransferase, WRKY 40, WRKY 70, ASR1, Peroxidase 12 and Sarcosine oxidase) was compared with their expression in a pair of near-isogenic lines (NILs) for the gene Lr28 following inoculation with leaf rust pathotype ’77-5’; ChIP-qPCR was used for this purpose. The proximal and distal promoters of these genes contained a number of motifs that are known to respond to biotic stresses. The enrichment of two acetylation marks changed with passage of time; changes in expression of two of the six genes (N-acetyltransferase and peroxidase12), largely matched with changes in H3K4/H3K9 acetylation patterns of the two promoter regions. For example, enrichment of both the marks matched with higher expression of N-acetyltransferase gene in susceptible NIL and the deacetylation (H3K4ac) largely matched with reduced gene expression in resistant NIL. In peroxidase12, enrichment of H3K4ac and H3K9ac largely matched with higher expression in both the NILs. In the remaining four genes, changes in H3 acetylation did not always match with gene expression levels. This indicated complexity in the regulation of the expression of these remaining four genes, which may be controlled by other epigenetic/genetic regulatory mechanisms that need further analysis.

Leaf rust disease causes severe yield losses in wheat throughout the world. During the present study, high-throughput RNA-Seq analysis was used to gain insights into the role of Lr28 gene in imparting seedling leaf rust resistance in wheat. Differential expression analysis was conducted using a pair of near-isogenic lines (NILs) (HD 2329 and HD 2329 + Lr28) at early (0 h before inoculation (hbi), 24 and 48 h after inoculation (hai)) and late stages (72, 96 and 168 hai) after inoculation with a virulent pathotype of pathogen Puccinia triticina. Expression of a large number of genes was found to be affected due to the presence/absence of Lr28. Gene ontology analysis of the differentially expressed transcripts suggested enrichment of transcripts involved in carbohydrate and amino acid metabolism, oxidative stress and hormone metabolism, in resistant and/or susceptible NILs. Genes encoding receptor like kinases (RLKs) (including ATP binding; serine threonine kinases) and other kinases were the most abundant class of genes, whose expression was affected. Genes involved in reactive oxygen species (ROS) homeostasis and several genes encoding transcription factors (TFs) (most abundant being WRKY TFs) were also identified along with some ncRNAs and histone variants. Quantitative real-time PCR was also used for validation of 39 representative selected genes. In the long term, the present study should prove useful in developing leaf rust resistant wheat cultivars through molecular breeding.

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.

ADP-glucose pyrophosphorylase (AGPase) is a heterotetrameric enzyme with two large subunits (LS) and two small subunits (SS). It plays a critical role in starch biosynthesis. We are reporting here detailed structure, function and evolution of the genes encoding the LS and the SS among monocots and dicots. “True” orthologs of maize Sh2 (AGPase LS) and Bt2 (AGPase SS) were identified in seven other monocots and three dicots; structure of the enzyme at protein level was also studied. Novel findings of the current study include the following: (i) at the DNA level, the genes controlling the SS are more conserved than those controlling the LS; the variation in both is mainly due to intron number, intron length and intron phase distribution; (ii) at protein level, the SS genes are more conserved relative to those for LS; (iii) “QTCL” motif present in SS showed evolutionary differences in AGPase belonging to wheat 7BS, T. urartu, rice and sorghum, while “LGGG” motif in LS was present in all species except T. urartu and chickpea; SS provides thermostability to AGPase, while LS is involved in regulation of AGPase activity; (iv) heterotetrameric structure of AGPase was predicted and analyzed in real time environment through molecular dynamics simulation for all the species; (v) several cis-acting regulatory elements were identified in the AGPase promoters with their possible role in regulating spatial and temporal expression (endosperm and leaf tissue) and also the expression, in response to abiotic stresses; and (vi) expression analysis revealed downregulation of both subunits under conditions of heat and drought stress. The results of the present study have allowed better understanding of structure and evolution of the genes and the encoded proteins and provided clues for exploitation of variability in these genes for engineering thermostable AGPase.

AGPase, a key enzyme of starch biosynthetic pathway, has a significant role in crop productivity. Thermotolerant variants of AGPase in cereals may be used for developing cultivars, which may enhance productivity under heat stress. Improvement of crop productivity has always been the major goal of plant breeders to meet the global demand for food. However, crop productivity itself is influenced in a large measure by a number of abiotic stresses including heat, which causes major losses in crop productivity. In cereals, crop productivity in terms of grain yield mainly depends upon the seed starch content so that starch biosynthesis and the enzymes involved in this process have been a major area of investigation for plant physiologists and plant breeders alike. Considerable work has been done on AGPase and its role in crop productivity, particularly under heat stress, because this enzyme is one of the major enzymes, which catalyses the rate-limiting first committed key enzymatic step of starch biosynthesis. Keeping the above in view, this review focuses on the basic features of AGPase including its structure, regulatory mechanisms involving allosteric regulators, its sub-cellular localization and its genetics. Major emphasis, however, has been laid on the genetics of AGPases and its manipulation for developing high yielding cultivars that will have comparable productivity under heat stress. Some important thermotolerant variants of AGPase, which mainly involve specific amino acid substitutions, have been highlighted, and the prospects of using these thermotolerant variants of AGPase in developing cultivars for heat prone areas have been discussed. The review also includes a brief account on transgenics for AGPase, which have been developed for basic studies and crop improvement.