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.

Triticum aestivum L. Zea mays L. Rhizosphere 16S rRNA IonS5 tm XL sequencing Bacterial community a b s t r a c t 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 TM 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. ©

Value of the Data
• The myriad of rhizosphere bacteria regulates growth and development of plant. Unraveling the rhizosphere bacterial community using metagenomics provides a deeper understanding of rhizosphere setting. • The dataset unraveled taxonomic composition of bacterial community from the rhizosphere of two leading cereal crops Zea mays and Triticum aestivum grown in different seasons at the same geographical area. • The crop researchers working on rhizosphere microbiome can use the dataset to interlink taxonomic information with potential functional description. Functional networking of rhizosphere microbiome will help researchers in improving crop yield under adverse conditions to meet future food demand.
• The crop scientists can use dataset to perform meta-analysis studies to correlate present findings with rhizosphere microbiome research outcomes available in literature to answer the questions regarding cereal crops growth, yield and adaptability. • The dataset produce is a baseline for further studies on plant type and seasonal shift role in modeling bacterial composition and diversity of rhizosphere.

.1. Tags statistics
The amplicon sequencing of V3-V4 region of 16S rRNA was used to explore the core bacterial community structure residing the rhizosphere of Zea mays and Triticum aestivum . A total of 70,208 high-quality reads (total tags) were obtained from rhizosphere of Zea mays . Of the high quality reads, 33,971 were taxon tags (classified tags) and 36,237 were unique tags (unique reads). Whereas the total tags obtained from the rhizosphere of Triticum aestivum were 73,174. Of the total effective tags, 32,783 were taxon tags and 40,391 were unique tags.

Classified tags
Of the total 70,208 high quality bacterial tags obtained from the rhizosphere of Zea mays , 33,971, 33,904, 33,357, 30,137, 27,070, 19,230 and 4169 were assigned to kingdom, phylum, class, order, family, genus and species rank, respectively. Whereas of the total 73,174 bacterial tags obtained from rhizospheric soil of Triticum aestivum , 32,738, 32,493, 30,507, 28,086, 21,131 and 3521 were assigned to phylum, class, order, family, genus and species, respectively.

Bacterial operational taxonomic units
The bacterial tags 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 . The OTUs obtained from Zea mays were classified into 22 phyla, 66 classes, 91 orders, 188 families and 284 genera. The OTUs obtained from Triticum aestivum were classified into 21 phyla, 65 classes, 88 orders, 184 families and 279 genera. The OTUs clustering elucidated the presence of 1175 OTUs in the rhizosphere soils of both the crops, whereas 165 and 162 OTUs were unique in the rhizosphere of Zea mays and Triticum aestivum , respectively. The OTUs found in both the rhizosphere belonged to 21 phyla, 59 classes, 80 orders, 169 families and 254 genera ( Fig. 1 A and B, Supplementary Table S1 ).  approximately 98 and 98.9% of the bacterial OTUs in Zea mays and Triticum aestivum respectively ( Fig. 2 A).
The major bacterial genera found in the rhizosphere of Zea mays and Triticum aestivum were Bacillus, Microvirga, Sphingomonas, Nocardioides, Bryobacter, Solirubrobacter, Rubrobacter, Marmoricola, Gaiella and Devosia ( Fig. 2 E). The ten predominant genera accounted for 22% and 22.6% of the bacterial community in the rhizosphere of Zea mays and Triticum aestivum .

Alpha diversity
Alpha diversity was measured using observed species, chao1, abundance based coverage estimator (ACE), shannon, shannon-pielou, simpson and diversity inverse simpson. The observed species, chao1 and ACE indices reflected species richness. Whereas Shannon, Shannonpielou, simpson and diversity inverse simpson indices depicted species diversity, accounting both species richness and species evenness. The results showed the presence of great diversity of bacteria in rhizosphere of Zea mays and Triticum aestivum . Slight variations were observed in the alpha diversity indices of bacterial communities of Zea mays and Triticum aestivum rhizosphere ( Table 2 ).

Comparison of the rhizospheric microbiome profiles between two crops
Correlation test revealed positive correlation between Zea mays and Triticum aestivum bacterial communities ( Fig. 3 ). Principal Component Analysis depicted variation in the core bacterial communities colonizing the rhizosphere of Zea mays and Triticum aestivum ( Fig. 4 ).

Site description and sample collection
The bulk soil and rhizosphere samples were collected from Kallar Syedan, Pakistan located between 33.42 N °latitude and 73.37 E °longitude. Kallar Syedan has an average annual temperature of 22.1 °C and receives an average annual precipitation of 859 mm.
For soil analysis, 500 g of bulk soil was collected independently from 1 to 6 inches and 7 to 12 inches depths. The bulk soil samples were sent to the Soil and Water Testing Laboratory, Rawalpindi, Pakistan for analysis. The parameters analyzed were electrical conductivity, pH, organic matter, available phosphorus, potassium, saturation percentage and texture of soil.
Triticum aestivum and Zea mays rhizosphere samples were collected in April and September 2018, respectively. For sample collection, soil was dug to 10 cm and plant along with soil was taken and packed in a resealable bag. Six replicates of both Triticum aestivum and Zea mays were excised from different locations of same field at the grain filling stage. Samples were sent to Microbiology Laboratory at Allama Iqbal Open University, Islamabad, Pakistan within few hours and stored at −80 °C.

Rhizosphere sample preparation and DNA isolation
The loosely attached soil was removed by shaking the roots. The remaining attached soil was collected and sieved to remove tiny root leftovers. The cleaned rhizosphere soil was grinded to fine powder and used for DNA isolation. High quality microbial DNA was extracted using Invitrogen TM Pure Link TM Microbiome DNA Purification kit (ThermoFisher Scientific, Catalog No. A29790, Pub. No. MAN0014331). The DNA was isolated from 200 mg of the rhizosphere soil using manufacturer's protocol with some modifications. The quality and purity of DNA was monitored on 1% agarose gel. The DNA isolated from biological replicates was pooled and subjected to PCR amplification.

Amplicon generation
The V3-V4 region of 16S rRNA gene was amplified using universal primers (341F and 806R) with the barcode. The Phusion® High-Fidelity PCR Master Mix (New England Biolabs) was used for PCR reactions. The Phusion® High-Fidelity PCR Master Mix manual was followed for preparation of reaction cocktail and PCR profile. Gel electrophoresis was performed using 2% agarose gel. The products between 400 and 450 bp were chosen for purification. The PCR products were purified through Qiagen Gel Extraction Kit (Qiagen, Germany) following manufacturer's protocol.

Library preparation and sequencing
To generate sequencing libraries, NEB Next ® Ultra DNA Library Prep Kit for Illumina was used following manufacturer's instruction. The quality of the libraries was accessed via Qubit @ 2.0 Fluorometer and Agilent Bioanalyzer 2100 system. Finally, the libraries generated were sequenced using IonS5 TM XL (Thermofisher) platform.

Single-end reads, data filtration and chimera removal
Each sample was assigned single-end reads on the basis of its unique barcode. The singleend reads were truncated by cutting off primer sequence and barcode. The raw reads were filtered to obtain high-quality clean reads under specified filtering conditions using Quantitative Insights Into Microbial Ecology software (Qiime Version 1.7.0) (http://qiime.org/scripts/ split_libraries_fastq.html) [1] . To obtain the effective tags, the clean reads were compared with reference Gold database (http://drive5.com/uchime/uchime_download.html) for detection and removal of chimera sequences using UCHIME algorithm (http://www.drive5.com/usearch/ manual/uchime_algo.html) [2] .

OTU cluster and species annotation
All the effective reads were subjected to sequence analysis using Uparse software (Version 7.0.1001) (http://drive5.com/uparse/) [3] . The sequences depicting ≥ 97% similarity were assigned to same operational taxonomic units (OTUs). The representative sequence of each OTU was selected for further annotation. For representative sequences of 16S rRNA, the SSUrRNA database of SILIVA Database (http://www.arb-silva.de/) [4] was used for annotation at each taxonomic rank using Mothur software with threshold 0.8 ∼1 [5] . The Korona figures were constructed using maximum depth to visually display species annotation results [6] .

Alpha diversity
Alpha diversity was used to determine the complexity of species diversity within a sample. Alpha diversity was measured via alpha diversity indices that included observed species, chao1, abundance based coverage estimator, shannon, Shannon-pielou, simpson and diversity inverse simpson. OTUs abundance information was normalized using a standard of sequence number corresponding to the sample with the least sequences. The R-software (version 3.6.3) was used to determine the alpha diversity for each sample using the normalized data. The packages used to calculate the alpha diversity indices were phyloseq, microbiome, knitr and dplyr.

Comparison of the rhizospheric microbiome profiles between two crops
Correlation test and Principal Component Analysis were performed to reflect the correlation and variation between the microbial community composition inhabiting the rhizosphere of Zea mays and Triticum aestivum . Correlation test and Principal Component Analysis were done by XLSTAT-2021 using normalized data to compare the rhizosphere microbiome of Triticum aestivum and Zea mays . Heatmap for the top 50 OTUs was obtained via Clustalvis.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.