16S metagenomics dataset of Zea mays and Triticum aestivum rhizosphere from Kallar Syedan Punjab, Pakistan.

Plant microbiome referred to as plant second genome, plays pivotal role in determination of vigor and productivity of plant. Current high-throughput sequence technologies provide remarkable insight into microbial diversity and host microbe interaction. The obtained dataset aimed to reveal the core bacterial community residing the rhizosphere of two leading cereal crops Zea mays and Triticum aestivum grown in different seasons at the same geographical area. The rhizosphere bacterial communities were explored via amplicon sequencing of V3-V4 region of 16S rRNA region using IonS5™XL sequencing platform. The classified tags for 16S rRNA from both the samples were clustered into 1502 Microbial operational taxonomic units (OTUs) at 97% similarity with 1340 OTUs in Zea mays and 1337 OTUs in Triticum aestivum. Ten bacterial phyla predominant in the rhizosphere were Proteobacteria, Actinobacteria, Firmicutes, Acidobacteria, Bacteroidetes, Chloroflexi, Gemmatimonadetes, Verrucomicrobia, Nitrospirae and Thermomicrobia. These bacterial phyla accounted for 98% and 98.9% of the OTUs in Zea mays and Triticum aestivum, respectively. Statistical analysis depicted the presence of slight variations in the relative abundance of bacterial groups residing the rhizosphere of Zea mays and Triticum aestivum. The community data produced in the present work can be used for meta-analysis studies to understand rhizosphere bacterial community of two major cereal crops. Furthermore, bacterial composition and diversity data is prerequisite for rhizosphere engineering to enhance cereal production to cope with upcoming global challenges of climate change and population growth.

Characterization of bacterial community structure in the rhizosphere of Triticum aestivum L.

The plant microbiome influence plant health, yield and vigor and has attained a considerable attention in the present era. In the current study, native bacterial community composition and diversity colonizing Triticum aestivum L. rhizosphere at two distant geographical locations including Mirpur Azad Kashmir and Islamabad was elucidated. Based on IonS5™XL platform sequencing of respective samples targeting 16S rRNA gene that harbor V3-V4 conserved region revealed 1364 and 1254 microbial operational taxonomic units (OTUs) at ≥97% similarity and were classified into 23, 20 phyla; 70, 65 classes; 101, 87 orders; 189,180 families; 275, 271 genera and 94, 95 species. Respective predominant phyla accounting for 97.90% and 98.60% of bacterial community were Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, Firmicutes, Chloroflexi and Gemmatimonadetes. Diversity indices revealed variations in relative abundance of bacterial taxa owing to distant geographical locations however predominant bacterial taxa at both locations were similar. These findings paved a way to dissect consequence of associated microbiota on future wheat production system.

Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat.

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_11 ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.

Resistance associated metabolite profiling of Aspergillus leaf spot in cotton through non-targeted metabolomics.

Aspergillus tubingensis is an important pathogen of economically important crops. Different biotic stresses strongly influence the balance of metabolites in plants. The aim of this study was to understand the function and response of resistance associated metabolites which, in turn are involved in many secondary metabolomics pathways to influence defense mechanism of cotton plant. Analysis of non-targeted metabolomics using ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) revealed abundant accumulation of key metabolites including flavonoids, phenylpropanoids, terpenoids, fatty acids and carbohydrates, in response to leaf spot of cotton. The principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and partial least squares discriminant analysis (PLS-DA) score plots illustrated the evidences of variation between two varieties of cotton under mock and pathogen inoculated treatments. Primary metabolism was affected by the up regulation of pyruvate and malate and by the accumulation of carbohydrates like cellobiose and inulobiose. Among 241 resistance related (RR) metabolites, 18 were identified as resistance related constitutive (RRC) and 223 as resistance related induced (RRI) metabolites. Several RRI metabolites, identified in the present study were the precursors for many secondary metabolic pathways. These included phenylpropanoids (stilbenes and furanocoumarin), flavonoids (phlorizin and kaempferol), alkaloids (indolizine and acetylcorynoline) and terpenoids (azelaic acid and oleanolic acid). Our results demonstrated that secondary metabolism, primary metabolism and energy metabolism were more active in resistant cultivar, as compared to sensitive cultivar. Differential protein and fatty acid metabolism was also depicted in both cultivars. Accumulation of these defense related metabolites in resistant cotton cultivar and their suppression in susceptible cotton cultivar revealed the reason of their respective tolerance and susceptibility against A. tubingensis.

The diversity of Rhizobia, Sinorhizobia and novel non-Rhizobial Paenibacillus nodulating wild herbaceous legumes.

The objective of the present study was to isolate and characterize nodulating bacteria associated with wild legumes. For this purpose, we recovered twenty isolates from root nodules of five wild legume species: Melilotus alles, Melilotus officinalis, Trifolium pratense, Trifolium repens and Medicago sp. Most of the isolates were morphologically analogous with only few exceptions in colony shape, appearance and incubation time. All isolates were Gram negative except T.P2-4. Random amplification of polymorphic DNA showed genetic variation among isolates. The 16S rRNA sequence analysis revealed these isolates as Rhizobium, Sinorhizobium and Paenibacillus. Each of these was also screened for nod D and nod F genes with marked variation at these loci; however, the nucleotide sequence analysis confirmed the presence of nod genes. The assignment of strains to their hosts revealed a unique symbiotic association of Paenibacillus sp. nodulating T .pratense which is being reported here for the first time.