Ramesh Buyyarapu

SNP Markers and Their Impact on Plant Breeding

The use of molecular markers has revolutionized the pace and precision of plant genetic analysis which in turn facilitated the implementation of molecular breeding of crops. The last three decades have seen tremendous advances in the evolution of marker systems and the respective detection platforms. Markers based on single nucleotide polymorphisms (SNPs) have rapidly gained the center stage of molecular genetics during the recent years due to their abundance in the genomes and their amenability for high-throughput detection formats and platforms. Computational approaches dominate SNP discovery methods due to the ever-increasing sequence information in public databases; however, complex genomes pose special challenges in the identification of informative SNPs warranting alternative strategies in those crops. Many genotyping platforms and chemistries have become available making the use of SNPs even more attractive and efficient. This paper provides a review of historical and current efforts in the development, validation, and application of SNP markers in QTL/gene discovery and plant breeding by discussing key experimental strategies and cases exemplifying their impact.

Development of a 63K SNP Array for Cotton and High-Density Mapping of Intraspecific and Interspecific Populations of Gossypium spp.

High-throughput genotyping arrays provide a standardized resource for plant breeding communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), complex trait dissection, and studying patterns of genomic diversity among cultivars and wild accessions. We have developed the CottonSNP63K, an Illumina Infinium array containing assays for 45,104 putative intraspecific single nucleotide polymorphism (SNP) markers for use within the cultivated cotton species Gossypium hirsutum L. and 17,954 putative interspecific SNP markers for use with crosses of other cotton species with G. hirsutum. The SNPs on the array were developed from 13 different discovery sets that represent a diverse range of G. hirsutum germplasm and five other species: G. barbadense L., G. tomentosum Nuttal × Seemann, G. mustelinum Miers × Watt, G. armourianum Kearny, and G. longicalyx J.B. Hutchinson and Lee. The array was validated with 1,156 samples to generate cluster positions to facilitate automated analysis of 38,822 polymorphic markers. Two high-density genetic maps containing a total of 22,829 SNPs were generated for two F2 mapping populations, one intraspecific and one interspecific, and 3,533 SNP markers were co-occurring in both maps. The produced intraspecific genetic map is the first saturated map that associates into 26 linkage groups corresponding to the number of cotton chromosomes for a cross between two G. hirsutum lines. The linkage maps were shown to have high levels of collinearity to the JGI G. raimondii Ulbrich reference genome sequence. The CottonSNP63K array, cluster file and associated marker sequences constitute a major new resource for the global cotton research community.

Generation and analysis of expressed sequence tags (ESTs) for marker development in yam (Dioscorea alata L.)

BackgroundAnthracnose (Colletotrichumgloeosporioides) is a major limiting factor in the production of yam (Dioscorea spp.) worldwide. Availability of high quality sequence information is necessary for designing molecular markers associated with resistance. However, very limited sequence information pertaining to yam is available at public genome databases. Therefore, this collaborative project was developed for genetic improvement and germplasm characterization of yams using molecular markers. The current investigation is focused on studying gene expression, by large scale generation of ESTs, from one susceptible (TDa 95-0310) and two resistant yam genotypes (TDa 87-01091, TDa 95-0328) challenged with the fungus. Total RNA was isolated from young leaves of resistant and susceptible genotypes and cDNA libraries were sequenced using Roche 454 technology.ResultsA total of 44,757 EST sequences were generated from the cDNA libraries of the resistant and susceptible genotypes. Greater than 56% of ESTs were annotated using MapMan Mercator tool and Blast2GO search tools. Gene annotations were used to characterize the transcriptome in yam and also perform a differential gene expression analysis between the resistant and susceptible EST datasets. Mining for SSRs in the ESTs revealed 1702 unique sequences containing SSRs and 1705 SSR markers were designed using those sequences.ConclusionWe have developed a comprehensive annotated transcriptome data set in yam to enrich the EST information in public databases. cDNA libraries were constructed from anthracnose fungus challenged leaf tissues for transcriptome characterization, and differential gene expression analysis. Thus, it helped in identifying unique transcripts in each library for disease resistance. These EST resources provide the basis for future microarray development, marker validation, genetic linkage mapping and QTL analysis in Dioscorea species.

Genomics-Assisted Plant Breeding in the 21st Century: Technological Advances and Progress

One of the key global challenges of the 21st century is the production of enough food for the increasing world population. As per some recent reports the global population will continue to grow with some 9 billion people by the middle of the current century and the world will need 70 to 100% more food by that time (Godfray et al., 2010 and references therein). Agricultural productivity needs to be increased while addressing the issues of scarcity of arable land and water, impact of changing climate and preservation of natural resources. Improvement of crop yields on available agricultural land requires concerted efforts using modern scientific and technological advances in multiple disciplines (Hubert et al., 2010). Two such disciplines that have revolutionized crop improvement in the recent decades are molecular breeding and plant genomics. While the availability and application of molecular markers have accelerated the pace and precision of plant genetics and breeding, the introduction of a multitude of “omics” tools has provided unprecedented ability to dissect the molecular and genetic basis of traits as well as the characterization of whole genomes.

Wild Relatives of Maize, Rice, Cotton, and Soybean: Treasure Troves for Tolerance to Biotic and Abiotic Stresses

Global food demand is expected to nearly double by 2050 due to an increase in the worlds population. The Green Revolution has played a key role in the past century by increasing agricultural productivity worldwide, however, limited availability and continued depletion of natural resources such as arable land and water will continue to pose a serious challenge for global food security in the coming decades. High yielding varieties with proven tolerance to biotic and abiotic stresses, superior nutritional profiles, and the ability to adapt to the changing environment are needed for continued agricultural sustainability. The narrow genetic base of modern cultivars is becoming a major bottleneck for crop improvement efforts and, therefore, the use of crop wild relatives (CWRs) is a promising approach to enhance genetic diversity of cultivated crops. This article provides a review of the efforts to date on the exploration of CWRs as a source of tolerance to multiple biotic and abiotic stresses in four global crops of importance; maize, rice, cotton, and soybean. In addition to the overview of the repertoire and geographical spread of CWRs in each of the respective crops, we have provided a comprehensive discussion on the morphological and/or genetic basis of the traits along with some examples, when available, of the research in the transfer of traits from CWRs to cultivated varieties. The emergence of modern molecular and genomic technologies has not only accelerated the pace of dissecting the genetics underlying the traits found in CWRs, but also enabled rapid and efficient trait transfer and genome manipulation. The potential and promise of these technologies has also been highlighted in this review.