An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage–related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

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India is considered to be the secondary center of diversity of chilli pepper, especially of Capsicum annuum. Simple sequence repeats (SSRs) are the most widely used marker system for plant variety characterization and diversity analysis especially in cultivated species which have low levels of polymorphism. The diversity analysis of 64 chilli pepper accessions, mostly of Indian origin, was performed using 50 SSR markers. Twenty seven (27) Using the given set of primers, it was possible to characterize all but two pairs of accessions from each other. The analysis allowed grouping of the test germplasm into nine clusters. Based on diversity analysis, genotypes were identified for developing mapping populations, produce heterotic F 1 hybrids and attempt crosses for genetic improvement of the crop.

Particularly PIN1, PIN protein-mediated rate-limiting auxin distribution plays a critical role in plant differentiation. Although well-characterized in Arabidopsis, little is known about the structural and functional relationship of the PIN1 gene among other plants. Here, we report that the gene structure remained conserved among bryophytes and angiosperms while the gene size varied by ~ 17%. Although the positions were conserved, highly variable intron phase suggests preference for specific regions in the gene sequence for independent events of intron insertion. Significant variation was observed across gene length for insertions and deletions that were mainly localized to the exonic regions flanking intron 1, possibly demarcating the sequences prone to deletions/duplications. The N and C-terminals showed a higher protein sequence similarity (~ 80%) compared to the central hydrophilic loop (~ 26%). In addition to the signature domains and motifs, we identified four novel uncharacterized motifs in the central divergent loop of PIN1 protein. Three different homo-loci, one each on chromosome groups 4, 6, and 7, were identified in wheat each showing dramatically different expression patterns during different plant developmental stages. Virus-induced gene silencing of the TaPIN1 gene resulted up to 26% reduction in plant height. Because of its direct role in controlling plant height along with a higher expression during stem elongation, the TaPIN1 gene can be manipulated to regulate plant height.

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Rusts are plant diseases caused by obligate fungi parasites. They are usually host-specific and cause greater losses of yields in crops, trees, and ornamental plants. Wheat is a staple food crop bearing losses specifically due to three species of rust fungi namely leaf rust (Puccinia triticina), stem rust (Puccinia graminis), and yellow rust (Puccinia striiformis). These diseases are usually inspected manually by a human being but at a large scale, this process is labor-intensive, time-consuming, and prone to human errors. Therefore, there is a need for an effective and efficient system that helps in the identification and classification of these diseases at early stages. In the present study, a deep learning-based CNN (i.e., VGG16) transfer learning model has been utilized for wheat disease classification on the CGIAR image dataset, containing two classes of wheat rust disease (leaf rust and stem rust), and one class of healthy wheat images. The deep learning models produced the best results by tuning the various hyper-parameters such as batch size, number of epochs, and learning rate. The proposed model has reported the best classification accuracy rate of 99.54% on 80 epochs using an initial learning rate from 0.01 and decayed to 0.0001.

High NUE (nitrogen use efficiency) has great practical significance for sustainable crop production. Wheat is one of the main cultivated crops worldwide for human food and nutrition. However, wheat grain productivity is dependent upon cultivars with high NUE in addition to the application of nitrogen fertilizers. In order to understand the molecular mechanisms exhibiting a high NUE response, a comparative transcriptomics study was carried out through RNA-seq analysis to investigate the gene expression that regulates NUE, in root and shoot tissue of N-efficient (PBW677) and N-inefficient (703) cultivars under optimum and nitrogen (N) stress. Differentially expressed gene analysis revealed a total of 2,406 differentially expressed genes (DEGs) present in both the contrasting cultivars under N stress. The efficient genotype PBW677 had considerably more abundant DEGs with 1,653 (903 roots +750 shoots) compared to inefficient cultivar PBW703 with 753 (96 roots +657 shoots). Gene ontology enrichment and pathway analysis of these DEGs suggested that the two cultivars differed in terms of adaptive mechanism. Gene enrichment analysis revealed that among the upregulated and downregulated genes the overrepresented and underrepresented gene categories belonged to biological processes like DNA binding, response to abiotic stimulus, photosynthesis, carbon fixation, carbohydrate metabolic process, nitrogen compound metabolic process, nitrate transport, and translation in cultivar PBW677, while the enriched biological processes were nucleosome assembly, chromatin remodeling, DNA packaging, lipid transport, sulfur compound metabolic process, protein modifications, and protein folding and refolding in N inefficient cultivar PBW703. We found several transcription factors (MYB, WRKY, RING finger protein, zinc finger protein, transporters, NRT1, amino acid transporters, sugar), protein kinases, and genes involved in N absorption, transportation, and assimilation to be highly expressed in high NUE cultivar PBW677. In our study, we report 13 potential candidate genes which showed alternate gene expression in the two contrasting cultivars under study. These genes could serve as potential targets for future breeding programs.

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