Identification of stress-responsive genes in an indica rice (Oryza sativa L.) using ESTs generated from drought-stressed seedlings

The impacts of drought on plant growth and development limit cereal crop production worldwide. Rice (Oryza sativa) productivity and production is severely affected due to recurrent droughts in almost all agroecological zones. With the advent of molecular and genomic technologies, emphasis is now placed on understanding the mechanisms of genetic control of the drought-stress response. In order to identify genes associated with water-stress response in rice, ESTs generated from a normalized cDNA library, constructed from drought-stressed leaf tissue of an indica cultivar, Nagina 22 were used. Analysis of 7794 cDNA sequences led to the identification of 5815 rice ESTs. Of these, 334 exhibited no significant sequence homology with any rice ESTs or full-length cDNAs in public databases, indicating that these transcripts are enriched during drought stress. Analysis of these 5815 ESTs led to the identification of 1677 unique sequences. To characterize this drought transcriptome further and to identify candidate genes associated with the drought-stress response, the rice data were compared with those for abiotic stress-induced sequences obtained from expression profiling studies in Arabidopsis, barley, maize, and rice. This comparative analysis identified 589 putative stress-responsive genes (SRGs) that are shared by these diverse plant species. Further, the identified leaf SRGs were compared to expression profiles for a drought-stressed rice panicle library to identify common sequences. Significantly, 125 genes were found to be expressed under drought stress in both tissues. The functional classification of these 125 genes showed that a majority of them are associated with cellular metabolism, signal transduction, and transcriptional regulation

Functional genomics of drought stress response in rice: transcript mapping of annotated unigenes of an indica rice (Oryza sativa L. cv. Nagina 22)

Rice being one of the widely cultivated cereals across diverse agroecological systems, is prone to high yield losses due to recurring droughts. In India, drought is a major constraint of rice production and accounts for as much as 15% of yield losses during some years. Conventional plant breeding techniques though cumbersome and time-consuming, have been immensely helpful in releasing drought-tolerant varieties. However, this is not adequate to cope up with the future demand for rice, as drought seems to spread to more regions and seasons across the country. Understanding the genes that govern rice plant architecture and response to drought stress is urgently needed to enhance breeding rice with improved drought tolerance. In order to identify genes associated with drought stress response and their temporal and spatial regulation, we took the genomic approach. By generating a large set of expressed sequence tags (ESTs) from cDNA libraries of drought-stressed seedlings and transcript profiling, we identified 589 genes presumed to be involved in drought stress. These 5814 ESTs are assembled into 2094 contigs and localized onto chromosome arms. We present here the physical map of the 2094 unigene set along with 589 annotated putative stress responsive genes of rice. Further, using ESTs, a few of drought quantitative trait loci (QTLs) have been dissected and putative candidate genes identified. This will be useful to rice researchers as ready reference source for breeding through developing candidate gene markers, molecular dissection of QTLs associated with drought stress and map-based cloning

Whole Genome Sequencing and Comparative Genomic Analysis Reveal Allelic Variations Unique to a Purple Colored Rice Landrace (Oryza sativa ssp. indica cv. Purpleputtu)

Purpleputtu (Oryza sativa ssp. indica cv. Purpleputtu) is a unique rice landrace from southern India that exhibits predominantly purple color. This study reports the underlying genetic complexity of the trait, associated domestication and de-domestication processes during its coevolution with present day cultivars. Along-with genome level allelic variations in the entire gene repertoire associated with the purple, red coloration of grain and other plant parts. Comparative genomic analysis using ‘a panel of 108 rice lines’ revealed a total of 3,200,951 variants including 67,774 unique variations in Purpleputtu (PP) genome. Multiple sequence alignment uncovered a 14 bp deletion in Rc (Red colored, a transcription factor of bHLH class) locus of PP, a key regulatory gene of anthocyanin biosynthetic pathway. Interestingly, this deletion in Rc gene is a characteristic feature of the present-day white pericarped rice cultivars. Phylogenetic analysis of Rc locus revealed a distinct clade showing proximity to the progenitor species Oryza rufipogon and O. nivara. In addition, PP genome exhibits a well conserved 4.5 Mbp region on chromosome 5 that harbors several loci associated with domestication of rice. Further, PP showed 1,387 unique when SNPs compared to 3,023 lines of rice (SNP-Seek database). The results indicate that PP genome is rich in allelic diversity and can serve as an excellent resource for rice breeding for a variety of agronomically important traits such as disease resistance, enhanced nutritional values, stress tolerance, and protection from harmful UV-B rays

Potential Application of Genomic Technologies in Breeding for Fungal and Oomycete Disease Resistance in Pea

Growth and yield of pea crops are severely affected by various fungal diseases, including root rot, Ascochyta blight, powdery mildew, and rust, in different parts of the world. Conventional breeding methods have led to enhancement of host plant resistance against these diseases in adapted cultivars, which is the primary option to minimize the yield losses. To support the breeding programs for marker-assisted selection, several successful attempts have been made to detect the genetic loci associated with disease resistance, based on SSR and SNP markers. In recent years, advances in next-generation sequencing platforms, and resulting improvements in high-throughput and economical genotyping methods, have been used to make rapid progress in identification of these loci. The first reference genome sequence of pea was published in 2019 and provides insights on the distribution and architecture of gene families associated with disease resistance. Furthermore, the genome sequence is a resource for anchoring genetic linkage maps, markers identified in multiple studies, identification of candidate genes, and functional genomics studies. The available pea genomic resources and the potential application of genomic technologies for development of disease-resistant cultivars with improved agronomic profile will be discussed, along with the current status of the arising improved pea germplasm

Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection

Gene associated SNP discovery in fine quality Indian Gossypium barbadense cotton through whole genome resequencing

262-272The present study deals with the resequencing of cultivars, Suvin and BCS-23-18-7 belonging to Gossypium barbadense which are distinctly differing in fiber qualities and seed cotton yield using Illumina Hiseq2500 sequencer. A total of 2,604,107 single nucleotide polymorphism (SNP) and 592,364 insertion and deletions (INDELs) were identified when compared with G. barbadense reference genome. Among the 14,075 preferentially expressed genes of agronomically important traits of cotton, we have identified 33,637 markers in the genic regions. Comparing between the variants of Suvin and BCS-23-18-7, among the 4,929 preferentially expressed genes in fiber, only 1,128 genes have 2,453 variants and of these 1,512 variants are non-synonymous types, leading to change at the protein level. In order to validate the presence of these markers in the expressed genes could tag the expression and/or phenotypic variation bought by alleles of Suvin/BCS- 23-18-7, among 51 fiber elongation genes, ten genes that had high effect SNPs were utilized for real-time PCR, which showed an extended period of expression up to 15 days post-anthesis (DPA) in Suvin. Hence, utilization of such markers for the construction of SNP array / linkage maps would provide greater value to quantitative trait loci (QTL) mapping instead of random genomic markers

Construction of high-density linkage maps for mapping quantitative trait loci for multiple traits in field pea (Pisum sativum L.)

Abstract Background The objective of this research was to map quantitative trait loci (QTLs) of multiple traits of breeding importance in pea (Pisum sativum L.). Three recombinant inbred line (RIL) populations, PR-02 (Orb x CDC Striker), PR-07 (Carerra x CDC Striker) and PR-15 (1–2347-144 x CDC Meadow) were phenotyped for agronomic and seed quality traits under field conditions over multiple environments in Saskatchewan, Canada. The mapping populations were genotyped using genotyping-by-sequencing (GBS) method for simultaneous single nucleotide polymorphism (SNP) discovery and construction of high-density linkage maps. Results After filtering for read depth, segregation distortion, and missing values, 2234, 3389 and 3541 single nucleotide polymorphism (SNP) markers identified by GBS in PR-02, PR-07 and PR-15, respectively, were used for construction of genetic linkage maps. Genetic linkage groups were assigned by anchoring to SNP markers previously positioned on these linkage maps. PR-02, PR-07 and PR-15 genetic maps represented 527, 675 and 609 non-redundant loci, and cover map distances of 951.9, 1008.8 and 914.2 cM, respectively. Based on phenotyping of the three mapping populations in multiple environments, 375 QTLs were identified for important traits including days to flowering, days to maturity, lodging resistance, Mycosphaerella blight resistance, seed weight, grain yield, acid and neutral detergent fiber concentration, seed starch concentration, seed shape, seed dimpling, and concentration of seed iron, selenium and zinc. Of all the QTLs identified, the most significant in terms of explained percentage of maximum phenotypic variance (PVmax) and occurrence in multiple environments were the QTLs for days to flowering (PVmax = 47.9%), plant height (PVmax = 65.1%), lodging resistance (PVmax = 35.3%), grain yield (PVmax = 54.2%), seed iron concentration (PVmax = 27.4%), and seed zinc concentration (PVmax = 43.2%). Conclusion We have identified highly significant and reproducible QTLs for several agronomic and seed quality traits of breeding importance in pea. The QTLs identified will be the basis for fine mapping candidate genes, while some of the markers linked to the highly significant QTLs are useful for immediate breeding applications

Development of a Sequence-Based Reference Physical Map of Pea (<em>Pisum sativum</em> L.)

International audienceWhole genome profiling (WGP) is a sequence-based physical mapping technology and uses sequence tags generated by next generation sequencing for construction of bacterial artificial chromosome (BAC) contigs of complex genomes. The physical map provides a framework for assembly of genome sequence and information for localization of genes that are difficult to find through positional cloning. To address the challenges of accurate assembly of the pea genome (similar to 4.2 GB of which approximately 85% is repetitive sequences), we have adopted the WGP technology for assembly of a pea BAC library. Multi-dimensional pooling of 295,680 BAC clones and sequencing the ends of restriction fragments of pooled DNA generated 1,814 million high quality reads, of which 825 million were deconvolutable to 1.11 million unique WGP sequence tags. These WGP tags were used to assemble 220,013 BACs into contigs. Assembly of the BAC clones using the modified Fingerprinted Contigs (FPC) program has resulted in 13,040 contigs, consisting of 213,719 BACs, and 6,294 singleton BACs. The average contig size is 0.33 Mbp and the N-50 contig size is 0.62 Mbp. WGP (TM) technology has proved to provide a robust physical map of the pea genome, which would have been difficult to assemble using traditional restriction digestion based methods. This sequence-based physical map will be useful to assemble the genome sequence of pea. Additionally, the 1.1 million WGP tags will support efficient assignment of sequence scaffolds to the BAC clones, and thus an efficient sequencing of BAC pools with targeted genome regions of interest

Draft genome sequence of Sclerospora graminicola, the pearl millet downy mildew pathogen

Sclerospora graminicola pathogen is the most important biotic production constraints of pearl millet in India, Africa and other parts of the world. We report a de novo whole genome assembly and analysis of pathotype 1, one of the most virulent pathotypes of S. graminicola from India. The draft genome assembly contained 299,901,251bp with 65,404 genes. This study may help understand the evolutionary pattern of pathogen and aid elucidation of effector evolution for devising effective durable resistance breeding strategies in pearl millet