Shalu Jain

Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene GS3 or qGL3. Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of TaGW2 (6A) and TaGASR7 (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.

Comparative Transcriptome Analysis of Resistant and Susceptible Common Bean Genotypes in Response to Soybean Cyst Nematode Infection

Soybean cyst nematode (SCN; Heterodera glycines Ichinohe) reproduces on the roots of common bean (Phaseolus vulgaris L.) and can cause reductions in plant growth and seed yield. The molecular changes in common bean roots caused by SCN infection are unknown. Identification of genetic factors associated with SCN resistance could help in development of improved bean varieties with high SCN resistance. Gene expression profiling was conducted on common bean roots infected by SCN HG type 0 using next generation RNA sequencing technology. Two pinto bean genotypes, PI533561 and GTS-900, resistant and susceptible to SCN infection, respectively, were used as RNA sources eight days post inoculation. Total reads generated ranged between ~ 3.2 and 5.7 million per library and were mapped to the common bean reference genome. Approximately 70–90% of filtered RNA-seq reads uniquely mapped to the reference genome. In the inoculated roots of resistant genotype PI533561, a total of 353 genes were differentially expressed with 154 up-regulated genes and 199 down-regulated genes when compared to the transcriptome of non- inoculated roots. On the other hand, 990 genes were differentially expressed in SCN-inoculated roots of susceptible genotype GTS-900 with 406 up-regulated and 584 down-regulated genes when compared to non-inoculated roots. Genes encoding nucleotide-binding site leucine-rich repeat resistance (NLR) proteins, WRKY transcription factors, pathogenesis-related (PR) proteins and heat shock proteins involved in diverse biological processes were differentially expressed in both resistant and susceptible genotypes. Overall, suppression of the photosystem was observed in both the responses. Furthermore, RNA-seq results were validated through quantitative real time PCR. This is the first report describing genes/transcripts involved in SCN-common bean interaction and the results will have important implications for further characterization of SCN resistance genes in common bean.

Isolation and Characterization of Novel EST-Derived Genic Markers in Pisum sativum (Fabaceae)

Premise of the study: Novel markers were developed for pea (Pisum sativum) from pea expressed sequence tags (ESTs) having significant homology to Medicago truncatula gene sequences to investigate genetic diversity, linkage mapping, and cross-species transferability. Methods and Results: Seventy-seven EST-derived genic markers were developed through comparative mapping between M. truncatula and P. sativum in which 75 markers produced PCR products and 33 were polymorphic among 16 pea genotypes. Conclusions: The novel markers described here will be useful for future genetic studies of P. sativum; their amplification in lentil (Lens culinaris) demonstrates their potential for use in closely related species.

Chapter 11 – Virus Resistance Breeding in Cool Season Food Legumes: Integrating Traditional and Molecular Approaches

In cool season food legumes, a large number of viral diseases cause severe yield losses. The description of disease symptoms is crucial for distinguishing various viruses; however, different virus species cannot be distinguished reliably by symptoms in many of the legumes, and infection by mixtures of viruses is common. That is why identification of viruses by serological and nucleic-acid-based techniques is important for making early and informed decisions on disease management strategies. Generally, breeders develop improved cultivars for yield and quality which may not possess resistance to various diseases. Protection from virus infection can be obtained by deploying either resistance genes present in the existing germplasm, or from non-host resistant sources. Screening of germplasm collections for virus resistance has provided breeders with genetic variation not found in available cultivars or enhanced germplasm. Inheritance of virus resistance can be monogenic or multigenic and may be either dominant or recessive. Availability of high-density molecular genetic maps has allowed identification of closely linked markers for a trait of interest and has therefore allowed marker-assisted selection (MAS) for improving concerned traits in breeding programs. However, little known information about closely linked markers for selection of virus-resistant genotypes has become a major limitation for exercising MAS in cool season food legume breeding programs. Development of markers based on genomic information from model species has great potential to facilitate efficient selection of virus resistance genes but may not be accomplished easily because of the relatively larger genome sizes of cool season food legumes. Here, the present state of the art concerning molecular breeding for resistance to these viruses is reviewed, and future perspectives for gene isolation and breeding at allelic level are briefly discussed.

Molecular and phenotypic characterization of variation related to pea enation mosaic virus resistance in lentil (Lens culinaris Medik.)

Jain, S., Porter, L. D., Kumar, A., Mir, R. R., Eigenbrode, S. D. and McPhee, K. E. 2014. Molecular and phenotypic characterization of variation related to pea enation mosaic virus resistance in lentil (Lens culinaris Medik.). Can. J. Plant Sci. 94: 1333-1344. Identification of genetically diverse lentil germplasm with resistance to pea enation mosaic virus (PEMV) through the combined approach of molecular marker analysis and phenotyping could prove useful in breeding programs. A total of 44 lentil (Lens culinaris Medik.) accessions, were screened for resistance to PEMV. Two accessions (PI 431663 and PI 432028) were identified with resistance to PEMV in field tests while several accessions were found resistant in greenhouse screenings. Thirty-six polymorphic simple sequence repeat (SSR) markers which produced 43 loci with 2 to 12 alleles per locus were used for genetic diversity analysis. The polymorphic information content (PIC) values for these markers ranged from 0.22-0.85 with a mean of 0.55 per marker. Using allelic data of 36 SSR primer pairs, dissimilarity ranging from 0.12 to 0.74 was calculated. Cluster analysis performed using the unweighted pair group method with arithmetic mean (UPGMA) determined that most of PEMV-resistant accessions were grouped in one cluster along with other accessions from Iran, Chile, Ethiopia, India, Pakistan, Turkey, Afghanistan and Lebanon. All the adapted cultivars originating from North and South America were grouped in another cluster along with some European accessions. The 44 accessions were classified into 4 subpopulations using Structure 2.2 software complimenting the results of UPGMA analysis and indicated the effect of geographical origin on the grouping of accessions. The results of this study can be used to select genetically diverse PEMV-resistant accessions for lentil improvement programs.

An Overview of QTL Identification and Marker-Assisted Selection for Grain Protein Content in Wheat

Grain protein content (GPC) is one of the most important traits in both the hexaploid and durum wheat. It plays an important role in end-use quality and thus determines the economic value of the crop. Improvement in GPC is a major objective in wheat breeding programs around the world. Therefore, in the past two decades, numerous studies on genetic dissection of this trait have been conducted in wheat. These studies have identified numerous quantitative trait loci (QTL) and markers associated with GPC in wheat. The available information about the marker trait associations for GPC offer great opportunities for marker-assisted breeding for this complex quantitative trait. In this article, we summarize the information available about the molecular genetic dissection of GPC and the progresses and prospects of application of marker-assisted breeding for improvement of this trait in wheat. We also reviewed the genetic relationship between GPC and grain yield. Strategies were also suggested to improve GPC in wheat based on available genetic and genomic resources.

Enhancing Abiotic Stress Tolerance

The banana is one of the most important staple fruit crop which feed millions of people around the globe. In the era of climate change, banana cultivation and production is seriously hampered by different biotic and abiotic constraints. Abiotic stresses arise from adverse environmental conditions which can hinder yield stability every cropping season, thus reducing food security adversely. Improved genetic material and breeding methods can help in solving the abiotic stress, challenges such as drought, salinity and temperature stress. Scientific advancements in the twenty-first century through advanced molecular technology and approaches have been made for a robust banana improvement programme. The development of climate resilient crops can be achieved by combining traditional breeding, tissue culture, and biotechnological approaches. This chapter reviews some of the basic aspects related to genetic transformation of banana along with some advanced techniques for further improvement. Embracing modern biotechnological tools combined with tissue culture and breeding techniques is imperative for developing abiotic stress-tolerant/stress-resistant banana.

Harnessing Genomics Through Phenomics

Plant genetics and genomics have revolutionized agricultural research, and a vast amount of genomics resources have been developed in crop plants. However, these genomics resources could not be utilized with their full potential in genetic improvement of crop plants especially for the improvement of complex quantitative traits related to biotic and abiotic stresses and the outcome is still far from satisfactory. Among several reasons, the lack of availability of precise and high-throughput phenotyping tools are cited as the major one, as poor phenotyping has led to poor results in gene/QTL discovery for genomics-assisted breeding applications. During the recent past, high-throughput precise phenotyping tools and techniques have been developed, which led to development of a number of phenomics platforms. These phenomics platforms can help us to collect high-quality accurate phenotyping data necessary for harnessing the potentiality of genomics resources through genetic dissection of complex quantitative traits including discovery of new gene/QTL, identification of gene function, and genomics selection. This chapter focuses on recent developments in the area of phenomics and provides an overview on the practical use of genomics through crop phenomics.