In India, the registration and protection of new and notified/extant plant varieties are based on the criteria of distinctness, uniformity and stability (DUS) of morphological characteristics. However, these morphological traits have not been helpful in resolving closely related genotypes. The molecular markers can very well support the DUS testing in such cases. Therefore, in the present study, 20 accessions of bottle gourd were fingerprinted using 20 simple sequence repeat (SSR) primers. Of these, ten primers exhibited polymorphic profiles, while nine exhibited monomorphic patterns and one revealed a null allele. The number of alleles ranged from 2 to 4 with an average of 2.6 alleles per locus. Unique DNA profiles of all the accessions could be created using a set of five polymorphic primers. Therefore, SSR markers used in the present study could precisely distinguish all the 20 accessions from each other, and these SSR markers can be further used to differentiate the future genotypes from the existing ones. The dendrogram depicting the genetic relationships as revealed by NTSYS-pc 2.02 and the tree diagram generated using the DARwin 5.0 program classified the accessions into two main clusters. There is no strong association between the clustering pattern and geographical origin of these accessions. This SSR marker-based diversity would facilitate the implementation of marker-assisted breeding schemes for efficient introduction of the desired traits into bottle gourd.

In India, Protection of Plant Varieties and Farmer's Rights Act (PPV&FRA, 2001) requires the registration and protection of new and notified/extant plant varieties based on the criteria of distinctness, uniformity and stability (DUS) of morphological characteristics. However, these morphological traits have not been able to resolve closely related genotypes. The molecular markers can very well support the DUS testing in such cases. In the present study, therefore, 14 varieties of rice cultivated in Punjab state of India were fingerprinted using 75 simple sequence repeat (SSR) primers. Out of these, 58 primers produced polymorphic profiles, while 13 were monomorphic, 2 revealed null allele and the remaining 2 amplified only from super basmati. In a screen of 7 cultivars, 16 SSR loci produced 17 rare/unique alleles, which provided an opportunity for their unambiguous identification. Cluster analysis based on SSR data clearly distinguished the cultivars into two dist inct groups: comprising non-basmati (group I) and basmati (group II). The cluster pattern was consistent with the pedigree and breeding history of the cultivars.

Bitter gourd (Momordica charantia L.) is an important vegetable crop having numerous medicinal properties. Earliness and yield related traits are main aims of bitter gourd breeding program. High resolution quantitative trait loci (QTLs) mapping can help in understanding the molecular basis of phenotypic variation of these traits and thus facilitate marker-assisted breeding. The aim of present study was to identify genetic loci controlling earliness, fruit, and seed related traits. To achieve this, genotyping-by-sequencing (GBS) approach was used to genotype 101 individuals of F4 population derived from a cross between an elite cultivar Punjab-14 and PAUBG-6. This population was phenotyped under net-house conditions for three years 2018, 2019, and 2021. The linkage map consisting of 15 linkage groups comprising 3,144 single nucleotide polymorphism (SNP) markers was used to detect the QTLs for nine traits. A total of 50 QTLs for these traits were detected which were distributed on 11 chromosomes. The QTLs explained 5.09–29.82% of the phenotypic variance. The highest logarithm of the odds (LOD) score for a single QTL was 8.68 and the lowest was 2.50. For the earliness related traits, a total of 22 QTLs were detected. For the fruit related traits, a total of 16 QTLs and for seed related traits, a total of 12 QTLs were detected. Out of 50 QTLs, 20 QTLs were considered as frequent QTLs (FQ-QTLs). The information generated in this study is very useful in the future for fine-mapping and marker-assisted selection for these traits in bitter gourd improvement program.

Various pathogenic microorganisms (such as fungi, bacteria, viruses and nematodes) affect plant viability and productivity. However, plants combat these pathogens by inducing their defense mechanism to sustain their fitness. The aggregation of pathogenesis-related (PR) proteins in response to invading pathogens is a crucial component of a plant’s self-defense mechanism. PR proteins induce innate resistance in plants through fungal cell wall disintegration, membrane permeabilization, transcriptional suppression, and ribosome inactivation. Earlier studies have demonstrated their crucial role in determining resistance against phytopathogens, making them a promising candidate for developing disease-resistant crop varieties. Plant genetic engineering is a potential approach for developing disease-resistant transgenic crops by employing several PR genes (thaumatin, osmotin-like proteins, chitinases, glucanases, defensins, thionins, oxalate oxidase, oxalate oxidases like proteins/germin-like proteins and LTPs). Furthermore, the overexpression of PR proteins enhances the resistance against phytopathogens. As a result, this chapter gives an overview of PR proteins, including their classification, functional characterization, signaling pathways, mode of action and role in defense against various phytopathogens. It also highlights genetic engineering advances in utilizing these genes singly or synergistically against various phytopathogens to impart disease resistance. Various challenges faced with the products of transgenic technology and synergistic expression of different groups of PR proteins were also discussed.

Yellow mosaic disease (YMD) in bitter gourd (Momordica charantia) is a devastating disease that seriously affects its yield. Although there is currently no effective method to control the disease, breeding of resistant varieties is the most effective and economic option. Moreover, quantitative trait locus (QTL) associated with resistance to YMD has not yet been reported. With the objective of mapping YMD resistance in bitter gourd, the susceptible parent “Punjab-14” and the resistant parent “PAUBG-6” were crossed to obtain F4 mapping population comprising 101 individuals. In the present study, the genotyping by sequencing (GBS) approach was used to develop the genetic linkage map. The map contained 3,144 single nucleotide polymorphism (SNP) markers, consisted of 15 linkage groups, and it spanned 2415.2 cM with an average marker distance of 0.7 cM. By adopting the artificial and field inoculation techniques, F4:5 individuals were phenotyped for disease resistance in Nethouse (2019), Rainy (2019), and Spring season (2020). The QTL analysis using the genetic map and phenotyping data identified three QTLs qYMD.pau_3.1, qYMD.pau_4.1, and qYMD.pau_5.1 on chromosome 3, 4, and 5 respectively. Among these, qYMD.pau_3.1, qYMD.pau_4.1 QTLs were identified during the rainy season, explaining the 13.5 and 21.6% phenotypic variance respectively, whereas, during the spring season, qYMD.pau_4.1 and qYMD.pau_5.1 QTLs were observed with 17.5 and 22.1% phenotypic variance respectively. Only one QTL qYMD.pau_5.1 was identified for disease resistance under nethouse conditions with 15.6% phenotypic variance. To our knowledge, this is the first report on the identification of QTLs associated with YMD resistance in bitter gourd using SNP markers. The information generated in this study is very useful in the future for fine-mapping and marker-assisted selection for disease resistance.