A diagnostic marker kit for Fusarium wilt and sterility mosaic diseases resistance in pigeonpea

Agroinfiltration-mediated transient assay for rapid evaluation of constructs in pigeonpea

The process of generating stable transformants is time-consuming, labor-intensive, and genotype-dependent. In contrast, transient gene expression techniques, such as agroinfiltration, offer a rapid assessment of gene function and expression. Agroinfiltration, widely employed for studying gene function, has been extensively applied in leaf tissues of Nicotiana benthamiana and various other plant species. Despite its broad utility in various plants, to our knowledge, no prior investigation has been reported in pigeonpea. In this study, we developed an agroinfiltration method for transiently expressing a green fluorescent protein (mGFP5) reporter gene in four pigeonpea genotypes using syringe infiltration at the seedling stage under greenhouse conditions. The expression of the reporter gene mGFP5 was assessed at 72-, 96-, and 120 h post-infiltration (hpi). Additionally, we assessed the effect of morphogenic genes, specifically growth-regulating factor 4 (GRF4) and GRF-interacting factor 1 (GIF1), from both rice and pigeonpea on the expression of mGFP5 in four pigeonpea genotypes. Our findings demonstrate that OsGRF4-GIF1 led to enhanced mGFP5 expression compared to CcGRF4-GIF1 in four diverse pigeonpea genotypes. Fluorescence could be detected till 120 hpi. Furthermore, PCR, RT-PCR, and fluorescence quantification confirmed the presence and expression of mGFP5 at 72 hpi. Our results highlight the efficacy of agroinfiltration in quickly evaluating candidate genes in four genetically diverse pigeonpea genotypes, thereby reducing the time required for the initial assessment of constructs suitable for diverse molecular biology analyses.

Sterility Mosaic Disease of Pigeonpea (Cajanus cajan (L.) Huth): Current Status, Disease Management Strategies, and Future Prospects

Pigeonpea (Cajanus cajan) is one of the important grain legume crops cultivated in the semi-arid tropics, playing a crucial role in the economic well-being of subsistence farmers. India is the major producer of pigeonpea, accounting for over 75% of the world's production. Sterility mosaic disease (SMD), caused by Pigeonpea sterility mosaic virus (PPSMV) and transmitted by the eriophyid mite (Aceria cajani), is a major constraint to pigeonpea cultivation in the Indian subcontinent, leading to potential yield losses of up to 100%. The recent characterization of another Emaravirus associated with SMD has further complicated the etiology of this challenging viral disease. This review focuses on critical areas, including the current status of the disease, transmission and host-range, rapid phenotyping techniques, as well as available disease management strategies. The review concludes with insights into the future prospects, offering an overview and direction for further research and management strategies.

Identification of QTLs for Reduced Susceptibility to Rose Rosette Disease in Diploid Roses

Resistance to rose rosette disease (RRD), a fatal disease of roses (Rosa spp.), is a high priority for rose breeding. As RRD resistance is time-consuming to phenotype, the identification of genetic markers for resistance could expedite breeding efforts. However, little is known about the genetics of RRD resistance. Therefore, we performed a quantitative trait locus (QTL) analysis on a set of inter-related diploid rose populations phenotyped for RRD resistance and identified four QTLs. Two QTLs were found in multiple years. The most consistent QTL is qRRV_TX2WSE_ch5, which explains approximately 20% and 40% of the phenotypic variation in virus quantity and severity of RRD symptoms, respectively. The second, a QTL on chromosome 1, qRRD_TX2WSE_ch1, accounts for approximately 16% of the phenotypic variation for severity. Finally, a third QTL on chromosome 3 was identified only in the multiyear analysis, and a fourth on chromosome 6 was identified in data from one year only. In addition, haplotypes associated with significant changes in virus quantity and severity were identified for qRRV_TX2WSE_ch5 and qRRD_TX2WSE_ch1. This research represents the first report of genetic determinants of resistance to RRD. In addition, marker trait associations discovered here will enable better parental selection when breeding for RRD resistance and pave the way for marker-assisted selection for RRD resistance.

Salient Findings on Host Range, Resistance Screening, and Molecular Studies on Sterility Mosaic Disease of Pigeonpea Induced by Pigeonpea sterility mosaic viruses (PPSMV-I and PPSMV-II)

Two distinct emaraviruses, Pigeonpea sterility mosaic virus-I (PPSMV-I) and Pigeonpea sterility mosaic virus-II (PPSMV-II) were found to be associated with sterility mosaic disease (SMD) of pigeonpea [Cajanus cajan (L.) Millsp.]. The host range of both these viruses and their vector are narrow, confined to Nicotiana benthamiana identified through mechanical transmission, and to Phaseolus vulgaris cvs. Top Crop, Kintoki, and Bountiful (F: Fabaceae) through mite transmission. A weed host Chrozophora rottleri (F: Euphorbiaceae) was also infected and tested positive for both the viruses in RT-PCR. Among the wild Cajanus species tested, Cajanus platycarpus accessions 15661, 15668, and 15671, and Cajanus scarabaeoides accessions 15683, 15686, and 15922 were infected by both the viruses and mite vector suggesting possible sources of SMD inoculum. Though accession 15666 of C. platycarpus, 15696 of C. scarabaeoides, and 15639 of Cajanus lanceolatus were infected by both the viruses, no mite infestation was observed on them. Phylogenetic analysis of nucleotide sequences of RNA-1 and RNA-2 of PPSMV-I and PPSMV-II isolates in southern India revealed significant divergence especially PPSMV-II, which is closely related to the Fig mosaic virus (FMV) than PPSMV-I. In multilocation testing of pigeonpea genotypes for their broad-based resistance to SMD for two consecutive years, genotypes ICPL-16086 and ICPL-16087 showed resistance reaction (<10% incidence) in all three locations studied. Overall, the present study gives a clear idea about the host range of PPSMV-I and PPSMV-II, their molecular relationship, and sources of resistance. This information is critical for the development of reliable diagnostic tools and improved disease management strategies.

Genomic resources in plant breeding for sustainable agriculture

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.