Fertilizing Nature: A Tragedy of Excess in the Commons

Why has nitrogen fertilizer use declined in some countries while increasing in others, despite significant environmental harm? Proper crop management strategies offer environmental and economic benefits without sacrificing yields

Integrated physical, genetic and genome map of chickpea (Cicer arietinum L.)

Physical map of chickpea was developed for the reference chickpea genotype (ICC 4958) using bacterial artificial chromosome (BAC) libraries targeting 71,094 clones (~12× coverage). High information content fingerprinting (HICF) of these clones gave high-quality fingerprinting data for 67,483 clones, and 1,174 contigs comprising 46,112 clones and 3,256 singletons were defined. In brief, 574 Mb genome size was assembled in 1,174 contigs with an average of 0.49 Mb per contig and 3,256 singletons represent 407 Mb genome. The physical map was linked with two genetic maps with the help of 245 BAC-end sequence (BES)-derived simple sequence repeat (SSR) markers. This allowed locating some of the BACs in the vicinity of some important quantitative trait loci (QTLs) for drought tolerance and reistance to Fusarium wilt and Ascochyta blight. In addition, fingerprinted contig (FPC) assembly was also integrated with the draft genome sequence of chickpea. As a result, ~965 BACs including 163 minimum tilling path (MTP) clones could be mapped on eight pseudo-molecules of chickpea forming 491 hypothetical contigs representing 54,013,992 bp (~54 Mb) of the draft genome. Comprehensive analysis of markers in abiotic and biotic stress tolerance QTL regions led to identification of 654, 306 and 23 genes in drought tolerance “QTL-hotspot” region, Ascochyta blight resistance QTL region and Fusarium wilt resistance QTL region, respectively. Integrated physical, genetic and genome map should provide a foundation for cloning and isolation of QTLs/genes for molecular dissection of traits as well as markers for molecular breeding for chickpea improvement

A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200–250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34 % combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6–27.3 % PVE at 5.4–11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41 % combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea

Genomic Approaches to Enhance Stress Tolerance for Productivity Improvements in Pearl Millet

Pearl millet [Pennisetum glaucum (L.) R. Br.], the sixth most important cereal crop (after rice, wheat, maize, barley, and sorghum), is grown as a grain and stover crop by the small holder farmers in the harshest cropping environments of the arid and semiarid tropical regions of sub-Saharan Africa and South Asia. Millet is grown on ~31 million hectares globally with India in South Asia; Nigeria, Niger, Burkina Faso, and Mali in western and central Africa; and Sudan, Uganda, and Tanzania in Eastern Africa as the major producers. Pearl millet provides food and nutritional security to more than 500 million of the world’s poorest and most nutritionally insecure people. Global pearl millet production has increased over the past 15 years, primarily due to availability of improved genetics and adoption of hybrids in India and expanding area under pearl millet production in West Africa. Pearl millet production is challenged by various biotic and abiotic stresses resulting in a significant reduction in yields. The genomics research in pearl millet lagged behind because of multiple reasons in the past. However, in the recent past, several efforts were initiated in genomic research resulting into a generation of large amounts of genomic resources and information including recently published sequence of the reference genome and re-sequencing of almost 1000 lines representing the global diversity. This chapter reviews the advances made in generating the genetic and genomics resources in pearl millet and their interventions in improving the stress tolerance to improve the productivity of this very important climate-smart nutri-cereal

Chickpea

The narrow genetic base of cultivated chickpea warrants systematic collection, documentation and evaluation of chickpea germplasm and particularly wild Cicer species for effective and efficient use in chickpea breeding programmes. Limiting factors to crop production, possible solutions and ways to overcome them, importance of wild relatives and barriers to alien gene introgression and strategies to overcome them and traits for base broadening have been discussed. It has been clearly demonstrated that resistance to major biotic and abiotic stresses can be successfully introgressed from the primary gene pool comprising progenitor species. However, many desirable traits including high degree of resistance to multiple stresses that are present in the species belonging to secondary and tertiary gene pools can also be introgressed by using special techniques to overcome pre- and post-fertilization barriers. Besides resistance to various biotic and abiotic stresses, the yield QTLs have also been introgressed from wild Cicer species to cultivated varieties. Status and importance of molecular markers, genome mapping and genomic tools for chickpea improvement are elaborated. Because of major genes for various biotic and abiotic stresses, the transfer of agronomically important traits into elite cultivars has been made easy and practical through marker-assisted selection and marker-assisted backcross. The usefulness of molecular markers such as SSR and SNP for the construction of high-density genetic maps of chickpea and for the identification of genes/QTLs for stress resistance, quality and yield contributing traits has also been discussed

Assessment of nutrient use in annual and perennial crops: a functional concept for analyzing nitrogen use efficiency

The use of more nutrient-efficient crops is important for maintaining yields while enhancing environmental sustainability. Various approaches are being applied to evaluate aspects of plant nutrient use efficiency, among them ecological concepts based on accumulation and losses of biomass and nutrients, agronomic concepts with a major focus on agricultural crops and harvested products, and physiological approaches assessing single physiological processes important for nutrient use. Unfortunately, the various approaches are often not compatible. Here we propose, with the example of nitrogen (N) use efficiency (NUE) of cereals, to integrate the functionally important components of NUE in a common conceptual framework. We link productivity to N in crops and seeds and consider the whole life-cycle of the crop (including seeds). Three major components of NUE are separated: The N uptake efficiency, grain-specific N efficiency and grain N concentration. The three components combine to a measure of overall NUE in terms of the N yield in harvested grain per unit of N in seed grain or soil N. The concept can be applied for both annual and perennial plants, which is demonstrated with the examples of winter wheat and a perennial energy crop (Salix) grown in Central Sweden