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.

With an aim of enhancing drought tolerance using a marker-assisted backcrossing (MABC) approach, we introgressed the "QTL-hotspot" region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought-tolerance related traits into three elite Indian chickpea (Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92-3. Of eight simple sequence repeat (SSR) markers in the QTLhotspot region, two to three polymorphic markers were used for foreground selection with respective cross-combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92-3, respectively. In total, 61 ILs (20 BC 3 F 3 in Pusa 372; 20 BC 2 F 3 in Pusa 362, and 21 BC 3 F 3 in DCP 92-3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4-14), IPC(L4-16), and IPC(L19-1) in DCP 92-3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central SubCommittees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL-hotspot

In the context of climate change, heat stress during the reproductive stages of chickpea (Cicer arietinum L.) leads to significant yield losses. In order to identify the genomic regions responsible for heat stress tolerance, a recombinant inbred line population derived from DCP 92-3 (heat sensitive) and ICCV 92944 (heat tolerant) was genotyped using the genotyping-by-sequencing approach and evaluated for two consecutive years (2017 and 2018) under normal and late sown or heat stress environments. A high-density genetic map comprising 788 single-nucleotide polymorphism markers spanning 1,125 cM was constructed. Using composite interval mapping, a total of 77 QTLs (37 major and 40 minor) were identified for 12 of 13 traits. A genomic region on CaLG07 harbors quantitative trait loci (QTLs) explaining >30% phenotypic variation for days to pod initiation, 100 seed weight, and for nitrogen balance index explaining >10% PVE. In addition, we also reported for the first time major QTLs for proxy traits (physiological traits such as chlorophyll content, nitrogen balance index, normalized difference vegetative index, and cell membrane stability). Furthermore, 32 candidate genes in the QTL regions that encode the heat shock protein genes, heat shock transcription factors, are involved in flowering time regulation as well as pollen-specific genes. The major QTLs reported in this study, after validation, may be useful in molecular breeding for developing heat-tolerant superior lines or varieties.

An upland rice variety, Nagina22 (N22) and its 137 ethyl methanesulfonate (EMS)-induced mutants, along with a sensitive variety, Jaya, was screened both in low phosphorus (P) field (Olsen P 1.8) and in normal field (Olsen P 24) during dry season. Based on the grain yield (YLD) of plants in normal field and plants in low P field, 27 gain of function (high-YLD represented as hy) and 9 loss of function (low-YLD represented as ly) mutants were selected and compared with N22 for physiological and genotyping studies. In low P field, hy mutants showed higher P concentration in roots, leaves, grains, and in the whole plant than in ly mutants at harvest. In low P conditions, Fv/Fm and qN were 24% higher in hy mutants than in ly mutants. In comparison with ly mutants, the superoxide dismutase (SOD) activity in the roots and leaves of hy mutants in low P fields was 9% and 41% higher at the vegetative stage, respectively, but 51% and 14% lower in the roots and leaves at the reproductive stage, respectively. However, in comparison with ly mutants, the catalase (CAT) activity in the roots and leaves of hy mutants in low P fields was 35% higher at the vegetative stage and 15% and 17% higher at the reproductive stage, respectively. Similarly, hy mutants in low P field showed 20% and 80% higher peroxidase (POD) activity in the roots and leaves at the vegetative stage, respectively, but showed 14% and 16% lower POD activity at the reproductive stage in the roots and leaves, respectively. Marker trait association analysis using 48 simple sequence repeat (SSR) markers and 10 Pup1 gene markers showed that RM3648 and RM451 in chromosome 4 were significantly associated with grain YLD, tiller number (TN), SOD, and POD activities in both the roots and leaves in low P conditions only. Similarly, RM3334 and RM6300 in chromosome 5 were associated with CAT activity in leaves in low P conditions. Notably, grain YLD was positively and significantly correlated with CAT activity in the roots and shoots, Fv/Fm and qN in low P conditions, and the shoots’ P concentration and qN in normal conditions. Furthermore, CAT activity in shoots was positively and significantly correlated with TN in both low P and normal conditions. Thus, chromosomal regions and physiological traits that have a role in imparting tolerance to low P in the field were identified.

No abstract