Venkateswara R. Sripathi

Introduction: Soil microorganisms play a crucial role in plant development, while biopolymers, such as cork and Extracellular Polymeric Substances/Exopolysaccharides (EPS), can enhance soil health. However, these amendments may affect DNA extraction and microbial analysis, necessitating the validation of the extraction method before conducting next-generation sequencing (NGS).Methods: This study evaluated 48 soil samples from Decatur, Alabama (Silt loam) that underwent four treatments: unamended soil (soil.control), soil with cork (soil.cork), soil with EPS (soil.EPS), and soil with both cork and EPS (soil.cork.EPS). Samples were collected at four time intervals (0-, 24-, 48-, and 72-hours post-treatment), with three biological replicates for each treatment. The FastDNA Spin Kit proved the most effective among the six DNA extraction methods tested.Results and discussion: Amplicon sequencing of the 16S rRNA gene identified 62,996 amplicon sequence variants (ASVs), with 513 ASVs shared across all time points and 467 ASVs shared among the different treatments. The microbial community was primarily composed of Actinobacteria, Proteobacteria, and Acidobacteria, with Actinobacteria being the most abundant phylum. Actinobacteria, Alphaproteobacteria, Bacilli, and Betaproteobacteria contributed to microbial diversity at the class level. Notable families such as Bacillaceae, Gaiellaceae, Micromonosporaceae, and Streptomycetaceae showed treatment-dependent variations. Core microbiome analysis revealed Bacillus and Gaiella as the dominant genera, which play vital roles in soil ecosystem stability and nutrient cycling. These microbes contribute to carbon sequestration, nitrogen fixation, and phosphorus solubilization, improving soil fertility and plant-microbe interactions. These findings offer valuable insights into microbial dynamics in amended soils, providing information that can improve soil quality and agricultural productivity.

Introduction: Plant roots, nematodes, and soil microorganisms have a complex interaction in the rhizosphere by exchanging or communicating through biomolecules or chemicals or signals. Some rhizospheric (including endophytic) microbes process such compounds via biogeochemical cycles to improve soil fertility, promote plant growth and development, and impart stress tolerance in plants. Some rhizospheric microbes can affect negatively on plant parasitic nematodes (PPNs) thus hindering the ability of nematodes in parasitizing the plant roots. Next-generation sequencing is one of the most widely used and cost-effective ways of determining the composition and diversity of microbiomes in such complex environmental samples.Methods: This study employed amplicon sequencing (Illumina/NextSeq) of 16S ribosomal RNA (16S rRNA) for bacteria and Internal Transcribed Spacer (ITS2) region for fungi to profile the soil microbiome in the rhizosphere of cotton grown in North Alabama. We isolated DNA (ZymoBIOMICS) from soil samples in triplicates from four representative locations of North Alabama. Based on the level of Reniform Nematode (RN) Infestation, these locations were classified as Group A-RN Not-Detected (ND), Group B-RN Low Infestation (LI), Group C-RN Medium Infestation (MI), and Group D-RN High Infestation (HI) and determined using sieving method and microscopic examination.Results and discussion: Our analyses identified 47,893 bacterial and 3,409 fungal Amplicon Sequence Variants (ASVs) across all groups. Among the bacterial ASVs, 12,758, 10,709, 12,153, and 11,360 unique ASVs were determined in Groups A, B, C, and D, respectively. While 663, 887, 480, and 326 unique fungal ASVs were identified in Groups A, B, C, and D, respectively. Also, the five most abundant rhizospheric bacterial genera identified were Gaiella, Conexibacter, Bacillus, Blastococcus, Streptomyces. Moreover, five abundant fungal genera belonging to Fusarium, Aspergillus, Gibberella, Cladosporium, Lactera were identified. The tight clustering of bacterial nodes in Actinobacteria, Acidobacteria, and Proteobacteria shows they are highly similar and often found together. On the other hand, the close association of Ascomycota and Basidiomycota suggesting that they have different ecological roles but occupy similar niches and contribute similar functions within the microbial community. The abundant microbial communities identified in this study had a role in nutrient recycling, soil health, plant resistance to some environmental stress and pests including nematodes, and biogeochemical cycles. Our findings will aid in broadening our understanding of how microbial communities interact with crops and nematodes in the rhizosphere, influencing plant growth and pest management.

This study identified proteomic changes in the seeds of two tolerant (SB-DT3 and SB-DT2) and two sensitive (Merlot and Stampede) common bean genotypes in response to terminal drought stress. Differentially expressed proteins (DEPs) were abundant in the susceptible genotype compared to the tolerant line. DEPs associated with starch biosynthesis, protein–chromophore linkage, and photosynthesis were identified in both genotypes, while a few DEPs and enriched biological pathways exhibited genotype-specific differences. The tolerant genotypes uniquely showed DEPs related to sugar metabolism and plant signaling, while the sensitive genotypes displayed more DEPs involved in plant–pathogen interaction, proteasome function, and carbohydrate metabolism. DEPs linked with chaperone and signal transduction were significantly altered between both genotypes. In summary, our proteomic analysis revealed both conserved and genotype-specific DEPs that could be used as targets in selective breeding and developing drought-tolerant common bean genotypes.

Around 300 different plant species are infected by the plant-parasitic reniform nematode (Rotylenchulus reniformis), including cotton. This is a devasting nematode with a preference for cotton; it is commonly found in Alabama farms and causes severe reduction in yields. Its first internal transcribed spacer (ITS1) region can be sequenced, and potential mutations can be found in order to study the population dynamics of the reniform nematode. The goal of our study was to sequence the ITS1 rDNA region in male and female RNs that were collected from BelleMina, Hamilton, and Lamons locations in Alabama. After separating the single male and female RNs from the samples collected from the three selected listed sites above, the ITS1 region was amplified selectively using specific primers, and the resulting products were cloned and sequenced. Two distinct bands were observed after DNA amplification of male and female nematodes at 550 bp and 730 bp, respectively. The analysis of sequenced fragments among the three populations showed variation in average nucleotide frequencies of female and male RNs. Singletons within the female and male Hamilton populations ranged from 7.8% to 10%, and the variable sites ranged from 13.4% to 26%. However, female and male BelleMina populations had singletons ranging from 7.1% to 19.7% and variable regions in the range of 13.9% to 49.3%. The female and male Lamons populations had singletons ranging from 2.5% to 8.7% and variable regions in the range of 2.9% to 14.2%. Phylogenetic (neighbor-joining) analysis for the two ITS1 fragments (ITS-550 and ITS-730) showed relatively high intra-nematode variability. Different clone sequences from an individual nematode often had greater similarity with other nematodes than with their own sequences. RNA fold analysis of the ITS1 sequences revealed varied stem and loop structures, suggesting both conserved and variable regions in the variants identified from female and male RNs, thus underscoring the presence of significant intra- and inter-nematodal variation among RN populations in Alabama.

The cotton crop is economically important and primarily grown for its fiber. Although the genus Gossypium consists of over 50 species, only four domesticated species produce spinnable fiber. However, the genes determine the molecular phenotype of fiber, and variation in their expression primarily contributes to associated phenotypic changes. Transcriptome analyses can elucidate the similarity or variation in gene expression (GE) among organisms at a given time or a circumstance. Even though several algorithms are available for analyzing such high-throughput data generated from RNA Sequencing (RNA-Seq), a reliable pipeline that includes a combination of tools such as an aligner for read mapping, an assembler for quantitating full-length transcripts, a differential gene expression (DGE) package for identifying differences in the transcripts across the samples, a gene ontology tool for assigning function, and enrichment and pathway mapping tools for finding interrelationships between genes based on their associated functions are needed. Therefore, this chapter first introduces the cotton crop, fiber phenotype, transcriptome, then discusses the basic RNA-Seq pipeline and later emphasizes various transcriptome analyses studies focused on genes associated with fiber quality and its attributes.

RNA sequencing (RNA-Seq) is the leading, routine, high-throughput, and cost-effective next-generation sequencing (NGS) approach for mapping and quantifying transcriptomes, and determining the transcriptional structure. The transcriptome is a complete collection of transcripts found in a cell or tissue or organism at a given time point or specific developmental or environmental or physiological condition. The emergence and evolution of RNA-Seq chemistries have changed the landscape and the pace of transcriptome research in life sciences over a decade. This chapter introduces RNA-Seq and surveys its recent food and agriculture applications, ranging from differential gene expression, variants calling and detection, allele-specific expression, alternative splicing, alternative polyadenylation site usage, microRNA profiling, circular RNAs, single-cell RNA-Seq, metatranscriptomics, and systems biology. A few popular RNA-Seq databases and analysis tools are also presented for each application. We began to witness the broader impacts of RNA-Seq in addressing complex biological questions in food and agriculture.

One of the major problems in the U.S. and global cotton production is the damage caused by the reniform nematode, Rotylenchulus reniformis. Amplification of DNA from single nematodes for further molecular analysis can be challenging sometimes. In this research, two whole-genome amplification (WGA) methods were evaluated for their efficiencies in DNA amplification from a single reniform nematode. The WGA was carried out using both REPLI-g Mini and Midi kits, and the GenomePlex single cell whole-genome amplification kit. Sequence analysis produced 4Mb and 12Mb of genomic sequences for the reniform nematode using REPLI-g and SIGMA libraries. These sequences were assembled into 28,784 and 24,508 contigs, respectively, for REPLI-g and SIGMA libraries. The highest repeats in both libraries were of low complexity, and the lowest for the REPLI-g library were for satellites and for the SIGMA library, RTE/BOV-B. The same kind of repeats were observed for both libraries; however, the SIGMA library had four other repeat elements (Penelope (long interspersed nucleotide element (LINE)), RTE/BOV-B (LINE), PiggyBac, and Mirage/P-element/Transib), which were not seen in the REPLI-g library. DNA transposons were also found in both libraries. Both reniform nematode 18S rRNA variants (RN_VAR1 and RN_VAR2) could easily be identified in both libraries. This research has therefore demonstrated the ability of using both WGA methods, in amplification of gDNA isolated from single reniform nematodes.

Histone modifications play a significant role in the regulation of transcription and various biological processes, such as development and regeneration. Though a few genomic (including DNA methylation patterns) and transcriptomic studies are currently available in switchgrass, the genome-wide distribution of histone modifications has not yet been studied to help elucidate gene regulation and its application to switchgrass improvement. This study provides a comprehensive epigenomic analyses of two contrasting switchgrass ecotypes, lowland (AP13) and upland (VS16), by employing chromatin immunoprecipitation sequencing (ChIP-Seq) with two histone marks (suppressive- H3K9me2 and active- H4K12ac). In this study, most of the histone binding was in non-genic regions, and the highest enrichment was seen between 0 and 2 kb regions from the transcriptional start site (TSS). Considering the economic importance and potential of switchgrass as a bioenergy crop, we focused on genes, transcription factors (TFs), and pathways that were associated with C4-photosynthesis, biomass, biofuel production, biotic stresses, and abiotic stresses. Using quantitative real-time PCR (qPCR) the relative expression of five genes selected from the phenylpropanoid-monolignol pathway showed preferential binding of acetylation marks in AP13 rather than in VS16. The genome-wide histone modifications reported here can be utilized in understanding the regulation of genes important in the phenylpropanoid–monolignol biosynthesis pathway, which in turn, may help understand the recalcitrance associated with conversion of biomass to biofuel, a major roadblock in utilizing lignocellulosic feedstocks.

Cotton (Gossypium spp.) produces naturally soft, single-celled trichomes as fiber on the seed coat supplying the main source of natural raw material for the textile industry. It is economically considered as one of the most leading cash crops in the world and evolutionarily very important as a model system for detailed scientific investigations. Cotton production is going through a big transition stage such as losing the market share in competition with the synthetic fibers, high popularity of Bt and herbicide resistance genes in cotton cultivars, and the recent shift of fiber demands to meet the standard fiber quality due to change of textile technologies to produce high superior quality of fibers in the global market. Recently, next-generation sequencing technologies through high-throughput sequencing at greatly reduced costs provided opportunities to sequence the diploid and tetraploid cotton genomes. With the availability of large volume of literatures on molecular mapping, new genomic resources, characterization of cotton genomes, discoveries of many novel genes, regulatory elements including small and microRNAs and new genetic tools such as gene silencing or gene editing technique for genome manipulation, this report attempted to provide the readers a comprehensive review on the recent advances of cotton fiber genomics research.

Common bean (Phaseolus vulgaris L.) is an important legume, useful for its high protein and dietary fiber. The fungal pathogen Uromyces appendiculatus (Pers.) Unger can cause major loss in susceptible varieties of the common bean. The Ur-3 locus provides race specific resistance to virulent strains or races of the bean rust pathogen along with Crg, (Complements resistance gene), which is required for Ur-3-mediated rust resistance. In this study, we inoculated two common bean genotypes (resistant “Sierra” and susceptible crg) with rust race 53 of U. appendiculatus, isolated leaf RNA at specific time points, and sequenced their transcriptomes. First, molecular markers were used to locate and identify a 250 kb deletion on chromosome 10 in mutant crg (which carries a deletion at the Crg locus). Next, we identified differential expression of several disease resistance genes between Mock Inoculated (MI) and Inoculated (I) samples of “Sierra” leaf RNA within the 250 kb delineated region. Both marker assisted molecular profiling and RNA-seq were used to identify possible transcriptomic locations of interest regarding the resistance in the common bean to race 53. Identification of differential expression among samples in disease resistance clusters in the bean genome may elucidate significant genes underlying rust resistance. Along with preserving favorable traits in the crop, the current research may also aid in global sustainability of food stocks necessary for many populations.