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Sesame (Sesamum indicum L.) also known as Queen of oilseeds is being cultivated worldwide for its oil content for nutritional and medicinal value. Low productivity is one of the major constraints of sesame cultivation. Systematic efforts are made using induced mutagenesis to increase its productivity and realize earliness and alteration in genetic architecture. Sodium Azide was used as a chemical mutagen in the present study. Nine sesame varieties viz., TMV 3, TMV 4, TMV 5, TMV 6, TMV (Sv) 7, CO 1, VRI 1, VRI(Sv) 2 and Paiyur 1 released from Tamil Nadu Agricultural University, Coimbatore, India were subjected to mutation at three different concentrations of Sodium Azide viz., 5 mM, 10 mM and 15 mM. An extra early mutant that matured on 70 DAS was identified in M4 generation of TMV 5 at 15 mM. This mutant (TVS 1401) was forwarded to subsequent generations with confirmed earliness. After confirming the superior performance of the mutant TVS 1401 for yield attributes in station trials, it was evaluated in MLT for two seasons. During Rabi 2017 MLT, it recorded 521 kg/ha of seed yield with the duration of 72 days. During Kharif 2018, it recorded 683 kg/ha of seed yield which was 21.96% higher yield than the popular check TMV 7 and matured 16 days earlier. This extra early mutant has white seed coat colour with 1000 seed weight of 3.22 g. Dissection of fatty acid profile of this mutant also confirmed its superiority. Distinctness of TVS1401 in molecular level was also established through RAPD markers viz., OPC03550 and OPA04550.

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01041-y.

The caloric needs of the global population are solely dependent on only 30 crops including rice, wheat, and maize. It is important to diversify and ensure the global food supply by enhancing the wide adaptation of nutritionally important vegetable crops. Focusing on the underutilized and locally available vegetable crops would meet the need of eradicating malnutrition and food security for the local population and small-hold farmers. With the advent of long-read sequencing technologies, several orphan crops and crops with complex genetic nature are being explored and genome resources are made available for crop improvement. Moringa oliefera is a well-known medicinal and nutritive plant which is getting adequate attention in recent years. Functional analytical tools including genome, transcriptome, metabolome, and proteome were made available for moringa; besides diversity analysis, evolutionary and syntenic studies were also reported. With an objective of exploring the available resources of an important nutritive crop and evaluating the need to enhance the functional studies further, this chapter reviews the application of long-read sequencing and their application in moringa genomics for its wider utilization in pharma industries.

MAS can be simply defined as selection for a trait based on the genotype of an associated marker rather than the trait itself. In essence, the associated marker is used as an indirect selection criterion. The potential of MAS as a tool for crop improvement has been extensively explored in different plant species. This chapter elaborates what would be the future of molecular breeding strategies in several crops.

Conventional plant breeding is largely dependent on selection of desirable plants which is highly decided by the genotype and environment interaction. Selecting plants in a segregating progeny that contains appropriate combinations of genes is a critical component of plant breeding. Usually, breeders improve crops by crossing plants with desired traits, such as high yield or disease resistance, and selecting the best offspring over multiple generations of testing under multilocation trials. However, the selection process is limited by several factors, as explained in this chapter. Besides, this chapter describes the role of marker-assisted selection (MAS) in the above said breeding process and elaborates how MAS can be done to increase the efficiency of the breeding program.

Incidence of vector-transmitted virus diseases and the damage caused to vegetable crops by these diseases are reported to be increasing in countries with tropical and subtropical conditions. Virus-resistant crops and an integrated approach to crop management including appropriate control of plant-virus insect-vectors could reduce the problem. However, in developing countries, such a strategy is rarely applied effectively. We surveyed 800 growers of chili, tomato and mungbean in India, Thailand and Vietnam to understand what farmers know about plant viruses, their perceptions about yield damage, the control methods they choose to apply and the perceived effectiveness of these. Farmers regarded their economic losses from pests and diseases to be very substantial. Only a minority of them knew that certain disease symptoms were probably being caused by a plant virus and even fewer knew about the role of insect vectors in its spread. Farmers mostly relied on synthetic pesticides to manage the virus disease symptoms they observed. If farmers had better knowledge about plant viruses, their insect vectors, and cost-effective, safer means of control, then use of synthetic pesticides could be reduced substantially. Building knowledge among farmers is therefore an important way to address the diseases caused by plant viruses, while the development of virus-resistant varieties and simple and effective methods of vector control offer longer-term solutions.

Drought is a major limitation for rice production in rainfed ecosystems. Identifying quantitative trait loci (QTLs) linked to drought resistance provides opportunity to breed high yielding rice varieties suitable for drought-prone areas. Although considerable efforts were made in mapping QTLs associated with drought-resistance traits in rice, most of the studies involved indica × japonica crosses and hence, the drought-resistance alleles were contributed mostly by japonica ecotypes. It is desirable to look for genetic variation within indica ecotypes adapted to target environment (TE) as the alleles from japonica ecotype may not be expressed under lowland conditions. A subset of 250 recombinant inbred lines (RILs) of F8 generation derived from two indica rice lines (IR20 and Nootripathu) with contrasting drought-resistance traits were used to map the QTLs for morpho-physiological and plant production traits under drought stress in the field in TE. A genetic linkage map was constructed using 101 polymorphic PCR-based markers distributed over the 12 chromosomes covering a total length of 1,529 cM in 17 linkage groups with an average distance of 15.1 cM. Composite interval mapping analysis identified 22 QTLs, which individually explained 4.8–32.2% of the phenotypic variation. Consistent QTLs for drought-resistance traits were detected using locally adapted indica ecotypes, which may be useful for rainfed rice improvement.

Many of the world's rice-growing regions lack adequate irrigation facilities, and drought frequently reduces yield. This paper reviews drought-resistance traits in rice and their quantitative trait loci (QTLs), with emphasis on CT9993/IR62266, one of the most widely studied mapping populations, and suggests ways to develop cultivars that will perform well in drought-prone environments. Information about the type of drought faced in the target region – particularly the timing of the drought (late season terminal drought, early stage vegetative drought, and intermittent drought) and the intensity of the drought – are important in determining the specific plant traits required to improve drought resistance in rice. Most of these traits are related to drought avoidance strategy, so that the drought-resistant genotypes are able to maintain better internal water status, either by taking up more water through a better root system or by reducing the rate of plant water use. We identified and listed a number of QTLs for many drought-resistance traits, such as deep roots. We identified four key genomic regions on chromosomes 1, 4, 8, and 9 on which are co-located a number of QTLs for traits considered to be directly or indirectly responsible for grain yield under stress. These regions, once they have been more finely mapped, appear promising for eventual use in marker-assisted selection for development of drought-resistant rice varieties. In addition to selecting for specific traits or specific genomic regions, screening under managed drought conditions on the basis of yield itself or on spikelet fertility adjusted for flowering time appears useful, because of the relatively high degrees of heritability of these characters, for the development of drought-resistant rice cultivars, and it is currently practiced in some breeding programs.

Drought stress is a major constraint for rice (Oryza sativa L.) production and yield stability in rainfed ecosystems. Identifying genomic regions (QTLs) contributing in drought resistance will help to develop rice cultivars suitable for water-limiting environments through marker-assisted breeding. QTLs linked to physio-morphological and plant production traits under drought stress in the field were mapped by evaluating 177 F6 recombinant inbred (RI) lines of Bala × Azucena under rainfed conditions in the target environment (TE). The rice lines were subjected to severe drought stress during reproductive phase due to a natural rainfall failure event. The RI lines showed significant variation in physio-morphological and plant production traits under stress. A total of 24 QTLs were identified for various traits under stress, which individually explained 4.6 to 22.3% phenotypic variation. Composite interval mapping detected three markers viz., RM3894, RG409 and G1073 on chromosomes 3 and 8 linked to grain yield under drought stress in TE, respectively explaining 22..3, 17.1 and 10.9% of phenotypic variation. QTLs for leaf drying, days to 50% flowering and number of productive tillers under drought stress co-located at certain of these regions. Further, QTLs for several root traits overlapped with QTLs for grain yield under stress in these RI lines, indicating the pleiotropic effects of root trait QTLs on rice performance under stress. Correlation coefficients between potential root traits determined in another study and plant production under stress in this study were not significant in these RI lines. Consistent QTLs for drought resistance traits and yield under drought stress in TE were detected and might be useful for rainfed rice improvement.

Farmers, in the given geographical region, cultivate only a small set of crop varieties for a long period of time. Modern plant breeding programs also resulted in severe genetic bottleneck. As a consequence, reduction in genetic diversity is widespread among crop plants, and it is considered as a detrimental feature to the future farming process. This is because continuous use of same cultivars usually leads to at least (1) extensive existence of (as well as emergence of new) pest and diseases to the given crop species and (2) loss of landraces and wild species of the given crop plants (which is otherwise referred to as genetic erosion). Due to ever increasing population growth and continuous shrinking of farming lands, farmers are forced to cultivate crop plants under a wide range of latitudes and longitudes. This requires crop plants which can tolerate variations in light, temperature, water and nutrients besides occurrence of peculiar pest and diseases that challenge crop production in these environments. Conventional breeding approaches such as desirable phenotypic selection among the breeding materials have considerably contributed in genetic improvement of crops. However, only a few genetically improved lines are available to meet such challenges. The main limitations that prevent the further progress through conventional breeding methods are lack of adequate genetic/biochemical/molecular knowledge on expression of traits that are beneficial to the crop cultivation and production. Most of the agronomically and economically important traits are quantitative in nature and having complex inheritance. Thanks to the developments in nucleic acid characterisation and manipulation, it is now possible to genetically analyse and manipulate such quantitative traits using quantitative trait loci (QTL) mapping and marker-assisted selection (MAS). Thus, advances in molecular marker technologies have opened the door to new techniques for construction and screening of breeding populations, increase the efficiency of selection and accelerate the rates of genetic gain. By employing genetic and QTL mapping, a marker can either be located within the gene of interest or be linked to a gene determining a trait of interest. Consequently, MAS can be executed as a selection for a trait based on genotype using associated markers rather than the phenotype of the trait. This book is designed to describe the basics of genetic and QTL mapping using molecular markers and practicing MAS in crop plants with step-by-step procedures. In general, MAS scheme in genetic improvement of crop plants for the given trait involves (1) characterisation of germplasm for the trait of interest, (2) selection of extremely diverse parents, (3) development of mapping population, (4) selection of appropriate combinations of molecular markers and genotyping of parents and mapping population, (5) construction of genetic or linkage map, (6) phenotyping of mapping population for the selected trait, (7) QTL analysis by combining the data obtained from step 5 and 6, (8) fine mapping and validation of QTLs and (9) executing MAS for the target trait. Therefore, this first chapter of this book is keen to describe the leading vital step in MAS: characterisation of germplasm.

MAS can be simply defined as selection for a trait based on the genotype of an associated marker rather than the trait itself. In essence, the associated marker is used as an indirect selection criterion. The potential of MAS as a tool for crop improvement has been extensively explored in different plant species. Major applications of MAS include (1) tracing favourable alleles and pyramiding them in desirable genetic backgrounds (foreground MAS), (2) eliminating unwanted genetic backgrounds (background MAS) or undesirable plant material in early breeding generations and identifying the most desirable gene combinations or individuals in segregating populations and (3) breaking the undesirable linkages between favourable and unfavourable alleles (reducing linkage drag). The success of MAS in plant breeding is often assessed on the basis of these three components. In theory, MAS can reduce the cost and increase the precision and efficiency of selection and breeding. However, MAS is not a ‘silver bullet’, and it can be more effective than conventional phenotype-based selection only under certain situations, including when (1) trait-based selection is not feasible (e.g. lack of selection environment or pathogen), (2) such selection is costly or ineffective, (3) trait expression is developmentally regulated or phenotypically not obvious until late in the season, (4) the trait is governed by recessive or incompletely dominant gene(s), (5) trait heritability is low rendering conventional phenotypic selection is ineffective, (6) there are too much G × E interactions, (7) multiple trait selection is desired, (8) conducting gene introduction/pyramiding from different sources and (9) transferring genes/QTLs from wild genetic backgrounds. Furthermore, in a backcross-breeding programme, MAS allows reduction of linkage drag by selecting against the undesirable donor genome and for desirable recurrent parent genome (background selection) while also selecting for desirable donor alleles (foreground selection). Moreover, with MAS, it is possible to conduct multiple rounds of selection in a year, allowing approximately two generations of selection per year, compared to one in phenotypic selection methods.

Conventional plant breeding is largely dependent on selection of desirable plants which is highly decided by the genotype and environment interaction. Selecting plants in a segregating progeny that contain appropriate combinations of genes is a critical component of plant breeding. Usually, breeders improve crops by crossing plants with desired traits, such as high yield or disease resistance, and selecting the best offspring over multiple generations of testing under multi-location trials. Thus, to develop a new variety, it may take 10–15 years. Any technique that may speed up this process or make it more efficient is really a boon to breeders.

Plant breeding programme’s key goal revolves in generation of elite crop plants that are having combination of superior genes/alleles. However, the critical limitation is lack of understanding of what most genes do in terms of the desired phenotype expression (e.g. pest resistance, salt tolerance and yield increase) in plants. We do know that all the agronomically important traits are quite complex. For example, in halophytes, we know that salt tolerance depends on the ability to compartmentalise ions, which in turn depends on regulation of transpiration, the tight control of leakage of ions through the root apoplast, the nature of the membranes in the leaf vacuoles, synthesis of compatible solutes such as glycine betaine and the ability to tolerate low K and Na ratios in the cytoplasm of mature cells or the ability of protein synthesis to operate at low K:Na ratios in the cells, etc. Under such conditions, how QTL mapping might be useful in increasing the yield under those unfavourable environments? In order to have efficient knowledge-based MAS, it is necessary to understand the techniques that are being used to unravel the function of genes, and such knowledge should be incorporated to the QTL mapping procedure. This chapter provides the state-of-the-art techniques in molecular, biochemical and physiological studies and their potential role in MAS.