Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom^®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.

Unravelling the genetic architecture underlying yield components and agronomic traits is important for enhancing crop productivity. Here, a recombinant inbred line (RIL) population, developed from ICC 4958 and DCP 92–3 cross, was used for constructing linkage map and QTL mapping analysis. The RIL population was genotyped using a high-throughput Axiom^®CicerSNParray, which enabled the development of a high-density genetic map consisting of 3,818 SNP markers and spanning a distance of 1064.14 cM. Analysis of phenotyping data for yield, yield components and agronomic traits measured across three years together with genetic mapping data led to the identification of 10 major-effect QTLs and six minor-effect QTLs explaining up to 59.70% phenotypic variance. The major-effect QTLs identified for 100-seed weight, and plant height possessed key genes, such as C3HC4 RING finger protein, pentatricopeptide repeat (PPR) protein, sugar transporter, leucine zipper protein and NADH dehydrogenase, amongst others. The gene ontology studies highlighted the role of these genes in regulating seed weight and plant height in crop plants. The identified genomic regions for yield, yield components, and agronomic traits, and the closely linked markers will help advance genetics research and breeding programs in chickpea.

Clusterbean (Cyamopsis tetragonoloba L. Taub), is an important industrial, vegetable and forage crop. This crop owes its commercial importance to the presence of guar gum (galactomannans) in its endosperm which is used as a lubricant in a range of industries. Despite its relevance to agriculture and industry, genomic resources available in this crop are limited. Therefore, the present study was undertaken to generate RNA-Seq based transcriptome from leaf, shoot, and flower tissues. A total of 145 million high quality Illumina reads were assembled using Trinity into 127,706 transcripts and 48,007 non-redundant high quality (HQ) unigenes. We annotated 79% unigenes against Plant Genes from the National Center for Biotechnology Information (NCBI), Swiss-Prot, Pfam, gene ontology (GO) and KEGG databases. Among the annotated unigenes, 30,020 were assigned with 116,964 GO terms, 9984 with EC and 6111 with 137 KEGG pathways. At different fragments per kilobase of transcript per millions fragments sequenced (FPKM) levels, genes were found expressed higher in flower tissue followed by shoot and leaf. Additionally, we identified 8687 potential simple sequence repeats (SSRs) with an average frequency of one SSR per 8.75 kb. A total of 28 amplified SSRs in 21 clusterbean genotypes resulted in polymorphism in 13 markers with average polymorphic information content (PIC) of 0.21. We also constructed a database named ‘ClustergeneDB’ for easy retrieval of unigenes and the microsatellite markers. The tissue specific genes identified and the molecular marker resources developed in this study is expected to aid in genetic improvement of clusterbean for its end use.

Methane is produced by various natural processes that directly or indirectly contribute to the entire Earth’s methane budget. If the Earth’s overall methane budget becomes imbalanced, CH₄ has an impact on climate change. Wetlands, rice fields, animals, factories, and fossil fuels are major sources of methane emissions. Among all the resources, wetlands and rice fields are more prominent factors in methane emission, dependent on the water table, temperature, and vegetation. Our study employed the GIS remote sensing technique to analyze methane emissions from 2003 to 2021 in the northern part of India, East Uttar Pradesh and Bihar, and the northeast region of India that is Assam. We also predicted the water table, temperature, and vegetation as raw materials for methane creation. Water table, temperature, and vegetation are essential for wetland ecosystem life, particularly for methanogenic organisms; however, the water table and temperature are critical for rice plant growth and development. With the help of GIS remote sensing, India’s monthly rainfall pattern and the water table, vegetation, and temperature pattern over 41 years were analyzed. Our key findings highlight the importance of GIS remote-sensing-based monitoring of methane gas emissions from wetlands and rice fields for their management.

Pigeonpea is one of the important pulse crops grown in many states of India and plays a major role in sustainable food and nutritional security for the smallholder farmers. In order to overcome the productivity barrier the Translational Pigeonpea Genomics Consortium (TPGC) was established, representing research institutes from six different states (Andhra Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Telangana, and Uttar Pradesh) of India. To enhance pigeonpea productivity and production the team has been engaged in deploying modern genomics approaches in breeding and popularizing modern varieties in farmers’ fields. For instance, new genetic stock has been developed for trait mapping and molecular breeding initiated for enhancing resistance to fusarium wilt and sterility mosaic disease in 11 mega varieties of pigeonpea. In parallel, genomic segments associated with cleistogamous flower, shriveled seed, pods per plant, seeds per pod, 100 seed weight, and seed protein content have been identified. Furthermore, 100 improved lines were evaluated for yield and desirable traits in multi-location trials in different states. Furthermore, a total of 303 farmers’ participatory varietal selection (FPVS) trials have been conducted in 129 villages from 15 districts of six states with 16 released varieties/hybrids. Additionally, one line (GRG 152 or Bheema) from multi-location trials has been identified by the All India Coordinated Research Project on Pigeonpea (AICRP-Pigeonpea) and released for cultivation by the Central Variety Release Committee (CVRC). In summary, the collaborative efforts of several research groups through TPGC is accelerating genetics gains in breeding plots and is expected to deliver them to pigeonpea farmers to enhance their income and improve livelihood.