Aditya Pratap

Achievements and prospects of genomics-assisted breeding in three legume crops of the semi-arid tropics

Advances in next-generation sequencing and genotyping technologies have enabled generation of large-scale genomic resources such as molecular markers, transcript reads and BAC-end sequences (BESs) in chickpea, pigeonpea and groundnut, three major legume crops of the semi-arid tropics. Comprehensive transcriptome assemblies and genome sequences have either been developed or underway in these crops. Based on these resources, dense genetic maps, QTL maps as well as physical maps for these legume species have also been developed. As a result, these crops have graduated from orphan or less-studied crops to genomic resources rich crops. This article summarizes the above-mentioned advances in genomics and genomics-assisted breeding applications in the form of marker-assisted selection (MAS) for hybrid purity assessment in pigeonpea; marker-assisted backcrossing (MABC) for introgressing QTL region for drought-tolerance related traits, Fusarium wilt (FW) resistance and Ascochyta blight (AB) resistance in chickpea; late leaf spot (LLS), leaf rust and nematode resistance in groundnut. We critically present the case of use of other modern breeding approaches like marker-assisted recurrent selection (MARS) and genomic selection (GS) to utilize the full potential of genomics-assisted breeding for developing superior cultivars with enhanced tolerance to various environmental stresses. In addition, this article recommends the use of advanced-backcross (AB-backcross) breeding and development of specialized populations such as multi-parents advanced generation intercross (MAGIC) for creating new variations that will help in developing superior lines with broadened genetic base. In summary, we propose the use of integrated genomics and breeding approach in these legume crops to enhance crop productivity in marginal environments ensuring food security in developing countries.

Biology and breeding of food legumes

1. History, Origin and Evolution 2. Biology and Floral Morphology 3. Domestication 4. Breeding for Improvement of Cool Season Food Legumes 5. Breeding for Improvement of Warm-season Food Legumes 6. Distant Hybridization and Alien Gene Introgression 7. Polyploidy 8. Cytology and Molecular Cytogenetics 9. Molecular Cytogenetics in Physical Mapping of Alien Introgressions 10. In vitro techniques 11. Microsporogenesis and Haploidy Breeding 12. Genetic Transformation 13. Male Sterility and Hybrid Production Technology 14. Mutagenesis 15. Breeding for Biotic Stresses 16. Breeding for Abiotic Stresses 17. Legume Improvement in the Acidic and less Fertile Soils 18. Genomic Approaches for Management of Abiotic Stresses 19. Molecular Breeding and Marker-assisted Selection 20. Underutilized Food Legumes 21. Legumes as a Model Plant Family 22. Plant Genetic Resources and Conservation of Biodiversity 23. Seed Dormancy and Viability 24. Post Harvest Technology 25. Value Addition and Trade.

Genomic resources for improving food legume crops

SUMMARY Food legumes are the main source of dietary protein for a large part of the world’s population, and also play an important role in maintaining soil fertility through nitrogen fixation. However, legume yields and production are often limited by large genotype×environment (G×E) interactions that influence the expression of agronomically important, complex quantitative traits. Consequently, genetic improvement has been slower than expected. Molecular marker technology enables genetic dissection of such complex traits, allowing breeders to identify genomic regions on the chromosome that have main effects or interactive effects. A number of genomic resources have been developed in several legume species during the last two decades, and provide a platform for exploiting marker technology. The present paper reviews the available genomic resources in food legumes: linkage maps, high-throughput sequencing technologies, expression sequence tag (EST) databases, genome sequences, DNA chips, targeting induced local lesions in genomes (TILLING), bacterial artificial chromosome (BAC) libraries and others. It also describes how these resources are being used to tag and map genes/quantitative trait loci (QTLs) for domesticated and other agronomically important traits. This information is important to genetic improvement efforts aiming at improving food and nutrition security worldwide.

Characterization of a new begomovirus and a beta satellite associated with the leaf curl disease of French bean in northern India.

Begomoviruses are emerging as serious threat to many crops throughout the world particularly in tropical and sub-tropical regions. A leaf curl disease with symptoms typical of infection by many begomoviruses was observed in French bean (Phaseolus vulgaris) at Kanpur, India, during 2010–2012. The disease caused downward leaf curling and made the plants unproductive. The disease was transmitted from infected to healthy plants through whitefly (Bemisia tabaci). The products of five samples digested with EcoRI yielded DNA fragments of about 2.7xa0kb. The complete sequence of the Fb1 sample comprised 2,741 nucleotides with genome organization typical of begomoviruses having two ORFs in virion-sense and five ORFs in complementary-sense separated by an intergenic region with begomovirus conserved nonanucleotide sequence, TAATATTAC. The complete DNA-A sequence homology was most closely related to Cotton leaf curl Bangalore virus with 80xa0% nucleotide sequence identity. Based on the demarcation criteria for identifying a begomovirus species, Fb1 is considered as a distinct begomovirus species, named French bean leaf curl virus and designated as FbLCV-[IN:Knp:12]. The complete sequence of associated satellite DNA-β comprises 1,379 nucleotides with single ORF and has 80xa0% identity with Papaya leaf curl beta satellite. There was no evidence of recombination in DNA-A of FbLCV and associated beta satellite DNA molecule.

Phenomics in crop plants : trends, options and limitations

1. Plant Phenomics: An Overview.- 2. Traits for Phenotyping.- 3. High Precision Phenotyping under Controlled versus Natural Environments.- 4. Towards Digital and Image Based Phenotyping.- 5. Imaging Methods for Phenotyping of Plant Traits.- 6. Screening for Plant Features.- 7. Phenotyping Crop Plants for Drought and Heat Related Traits.- 8. Phenotyping for Root Traits.- 9. Phenotyping for Soil Problems.- 10. Phenotyping Methods of Fungal Diseases, Parasitic Nematodes and Weeds in Cool Season Food Legumes.- 11. Advances in Phenotyping of Functional Traits.- 12. Role of Fluorescence Approaches to Understand Functional Traits of Photosynthesis.- 13. Identification of Subcellular Structural and Metabolic Changes through NMR.- 14. Precision Nutrient Management and Crop Sensing.- 15. Phenotyping Nutritional and Anti-Nutritional Traits.- 16. Experimental Designs for Precision in Phenotyping.- 17. Biometrical Approaches for Analysis of Phenotypic Data of Complex Traits.- 18. Harnessing Genomics through Phenomics.- 19. High Throughput Plant Phenotyping Platforms.

THE SYNTHESIS OF TiO2 NANOPARTICLES BY WET-CHEMICAL METHOD AND THEIR PHOTOLUMINESCENCE, THERMAL AND VIBRATIONAL CHARACTERIZATIONS: EFFECT OF GROWTH CONDITION

Low temperature calcination methods have been developed to obtain anatase TiO2 nanocrystals using three different synthesis routes. The DSC thermograms have been used to set the annealing temperature. Various size of TiO2 nanocrystals ranging from 8 nm to 16.5 nm have been used to synthesize by setting up the annealing temperature and time. The X-ray diffraction (XRD) and Raman spectrum have been used to identify and confirm the anatase crystal structure having long range ordering. The photoluminescence (PL) spectra have been recorded as a function of particle size and excitation power, which is attributed to the defects inside the grain that can migrate into the grain surface region during annealing. In a typical TiO2 nanocrystals (sample TN12), luminescence efficiency increases with the decrease in size due to e-/h+ recombination process.

Marker-assisted introgression of resistance to fusarium wilt race 2 in Pusa 256, an elite cultivar of desi chickpea

Fusarium wilt caused by F. oxysporum f. sp. ciceris causes extensive damage to chickpea (Cicer arietinum L.) in many parts of the world. In the central part of India, pathogen race 2 (Foc 2) causes severe yield losses. We initiated molecular marker-assisted backcrossing (MABC) using desi cultivar, Vijay, as a donor to introgress resistance to this race (Foc2) in Pusa 256, another elite desi cultivar of chickpea. To confirm introgression of resistance for this race, foreground selection was undertaken using two SSR markers (TA 37 and TA110), with background selection to observe the recovery of recurrent parent genome using 45 SSRs accommodated in 8 multiplexes. F1 plants were confirmed with molecular markers and backcrossed with Pusa 256, followed by cycles of foreground and background selection at each stage to generate 161 plants in BC3F2 during the period 2009–2013. Similarly, 46 BC3F1 plants were also generated in another set during the same period. On the basis of foreground selection, 46 plants were found homozygotes in BC3F2. Among them, 17 plants recorded >91% background recovery with the highest recovery percentage of 96%. In BC3F1 also, 14 hybrid plants recorded a background recovery of >85% with the highest background recovery percentage of >94%. The identified plants were selfed to obtain 1341 BC3F3 and 2198 BC3F2 seeds which were screened phenotypically for resistance to fusarium wilt (race 2) besides doing marker analysis. Finally, 17 BC3F4 and 11 BC3F3 lines were obtained which led to identification of 5 highly resistant lines of Pusa 256 with Foc 2 gene introgressed in them. Development of these lines will help in horizontal as well as vertical expansion of chickpea in central part of India.

Plant Phenomics: An Overview

Precise and accurate measurement of traits plays an important role in the genetic improvement of crop plants. Therefore, a lot of development has taken place in the area of phenomics in the recent past. Both forward and reverse phenomics have been evolved, which can help in identification of either the best genotype having the desirable traits or mechanism and genes that make a genotype the best. This includes development of high throughput non-invasive imaging technologies including colour imaging for biomass, plant structure, phenology and leaf health (chlorosis, necrosis); near infrared imaging for measuring tissue and soil water contents; far infrared imaging for canopy/leaf temperature; fluorescence imaging for physiological state of photosynthetic machinery; and automated weighing and watering for water usage imposing drought/salinity. These phenomics tools and techniques are paving the way in harnessing the potentiality of genomic resources in genetic improvement of crop plants. These techniques have become much more advanced and have now entered the era of high throughput integrated phenotyping platforms to provide a solution to genomics-enabled improvement and address our need of precise and efficient phenotyping of crop plants.

High-Throughput Plant Phenotyping Platforms

To meet the ever-increasing demand of food and feed for the burgeoning population, we need to double our food production by 2050 with a growth rate of about 2.4 %. This needs input-responsive, resource-use-efficient and short-duration genotypes which are stable and can perform well in an array of situations. For this, integrated breeding efforts connecting genomics and phenomics together are required. While a giant leap has been made in crop genotyping in the last two decades, especially with the development of next-generation DNA sequencing, the latest developments in automation, robotics, accurate environmental control and remote sensing facilities have offered opportunities for precise field phenotyping of crop plants through state-of-the-art high-throughput plant phenotyping platforms (HTPPs). Although the initially developed platforms had limitations with regard to accuracy, speed and ground clearance, the latest HTPPs are capable of taking multiple trait measurements simultaneously that have improved data acquisition as well as provide high-throughput phenotypic data required for crop breeding programmes. A number of analysis pipelines have also been developed which are equipped with high-speed computing. This chapter describes some of the most popular HTPPs and their specific features to achieve precision phenotypes in crop plants.

Genome scanning of Asiatic Vigna species for discerning population genetic structure based on microsatellite variation

AbstractnWild relatives are important genetic resources for crop improvement. However, basic information about their population structure, genetic diversity, species relationships and distribution of variation in a gene pool remains scanty in Vigna species. The level of genetic diversity and population genetic structure of representative accessions of cultivated and wild Asiatic Vigna species collected from diversity-rich endemic areas of India have been investigated using both microsatellite markers and morphological descriptors. Forty-one wild and 12 cultivated accessions of 13 Vigna species were genotyped using 53 polymorphic microsatellite markers. A total of 539 alleles were detected among 53 accessions at all loci with an average 10.16 alleles per locus. The major allele frequency varied from 0.16 to 0.65 (meanxa0=xa00.30), while polymorphism information content of polymorphic markers ranged from 0.47 to 0.89 (meanxa0=xa00.79). The UPGMA revealed five major clusters accommodating ~96xa0% of the accessions. The largest cluster accommodated 19 (36xa0%), while the smallest cluster had only two accessions. Two accessions, JAP/10-5 and JAP/10-9 of V. trilobata, did not group with any other accession. The model-based population structure analysis also showed almost similar pattern and grouped 53 accessions of Vigna into five genetically distinct sub-populations (Kxa0=xa05) based on maximum ∆K values. Duncan’s multiple range test revealed significant difference between five genetic and one admixture group developed through population structure analysis with 22 morphological descriptors. Analysis of variance for morphological data revealed significant difference in 12 qualitative and quantitative traits including growth habit, terminal leaflet length, colour of petiole base, petiole length, leaf senescence, length of peduncle, raceme position, calyx colour, colour of VSI pod, pod pubescence, pod curvature and 100-seed weight, indicating their significance in distinguishing population groups. The information on genetic diversity and population structure of wild and cultivated accessions of Asiatic Vigna will be tremendously useful to accelerate their use in trait improvement.n