Genome-wide analyses of cassava Pathogenesis-related (PR) gene families reveal core transcriptome responses to whitefly infestation, salicylic acid and jasmonic acid.

BACKGROUND:Whiteflies are a threat to cassava (Manihot esculenta), an important staple food in many tropical/subtropical regions. Understanding the molecular mechanisms regulating cassava's responses against this pest is crucial for developing control strategies. Pathogenesis-related (PR) protein families are an integral part of plant immunity. With the availability of whole genome sequences, the annotation and expression programs of the full complement of PR genes in an organism can now be achieved. An understanding of the responses of the entire complement of PR genes during biotic stress and to the defense hormones, salicylic acid (SA) and jasmonic acid (JA), is lacking. Here, we analyze the responses of cassava PR genes to whiteflies, SA, JA, and other biotic aggressors. RESULTS:The cassava genome possesses 14 of the 17 plant PR families, with a total of 447 PR genes. A cassava PR gene nomenclature is proposed. Phylogenetic relatedness of cassava PR proteins to each other and to homologs in poplar, rice and Arabidopsis identified cassava-specific PR gene family expansions. The temporal programs of PR gene expression in response to the whitefly (Aleurotrachelus socialis) in four whitefly-susceptible cassava genotypes showed that 167 of the 447 PR genes were regulated after whitefly infestation. While the timing of PR gene expression varied, over 37% of whitefly-regulated PR genes were downregulated in all four genotypes. Notably, whitefly-responsive PR genes were largely coordinately regulated by SA and JA. The analysis of cassava PR gene expression in response to five other biotic stresses revealed a strong positive correlation between whitefly and Xanthomonas axonopodis and Cassava Brown Streak Virus responses and negative correlations between whitefly and Cassava Mosaic Virus responses. Finally, certain associations between PR genes in cassava expansions and response to biotic stresses were observed among PR families. CONCLUSIONS:This study represents the first genome-wide characterization of PR genes in cassava. PR gene responses to six biotic stresses and to SA and JA are demonstrably different to other angiosperms. We propose that our approach could be applied in other species to fully understand PR gene regulation by pathogens, pests and the canonical defense hormones SA and JA

Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

Citation: Serba, D. D., Uppalapati, S. R., Krom, N., Mukherjee, S., Tang, Y. H., Mysore, K. S., & Saha, M. C. (2016). Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency. Bmc Genomics, 17, 14. doi:10.1186/s12864-016-3377-8Background: Switchgrass, a warm-season perennial grass studied as a potential dedicated biofuel feedstock, is classified into two main taxa - lowland and upland ecotypes - that differ in morphology and habitat of adaptation. But there is limited information on their inherent molecular variations. Results: Transcriptome analysis by RNA-sequencing (RNA-Seq) was conducted for lowland and upland ecotypes to document their gene expression variations. Mapping of transcriptome to the reference genome (Panicum virgatum v1. 1) revealed that the lowland and upland ecotypes differ substantially in sets of genes transcribed as well as levels of expression. Differential gene expression analysis exhibited that transcripts related to photosynthesis efficiency and development and photosystem reaction center subunits were upregulated in lowlands compared to upland genotype. On the other hand, catalase isozymes, helix-loop-helix, late embryogenesis abundant group I, photosulfokinases, and S-adenosyl methionine synthase gene transcripts were upregulated in the upland compared to the lowlands. At >= 100x coverage and >= 5% minor allele frequency, a total of 25,894 and 16,979 single nucleotide polymorphism (SNP) markers were discovered for VS16 (upland ecotype) and K5 (lowland ecotype) against the reference genome. The allele combination of the SNPs revealed that the transition mutations are more prevalent than the transversion mutations. Conclusions: The gene ontology (GO) analysis of the transcriptome indicated lowland ecotype had significantly higher representation for cellular components associated with photosynthesis machinery controlling carbon fixation. In addition, using the transcriptome data, SNP markers were detected, which were distributed throughout the genome. The differentially expressed genes and SNP markers detected in this study would be useful resources for traits mapping and gene transfer across ecotypes in switchgrass breeding for increased biomass yield for biofuel conversion

Genome wide association mapping for agronomic, fruit quality, and root architectural traits in tomato under organic farming conditions

[EN] Background Opportunity and challenges of the agriculture scenario of the next decades will face increasing demand for secure food through approaches able to minimize the input to cultivations. Large panels of tomato varieties represent a valuable resource of traits of interest under sustainable cultivation systems and for genome-wide association studies (GWAS). For mapping loci controlling the variation of agronomic, fruit quality, and root architecture traits, we used a heterogeneous set of 244 traditional and improved tomato accessions grown under organic field trials. Here we report comprehensive phenotyping and GWAS using over 37,300 SNPs obtained through double digest restriction-site associated DNA (dd-RADseq). Results A wide range of phenotypic diversity was observed in the studied collection, with highly significant differences encountered for most traits. A variable level of heritability was observed with values up to 69% for morphological traits while, among agronomic ones, fruit weight showed values above 80%. Genotype by environment analysis highlighted the strongest genotypic effect for aboveground traits compared to root architecture, suggesting that the hypogeal part of tomato plants has been a minor objective for breeding activities. GWAS was performed by a compressed mixed linear model leading to 59 significantly associated loci, allowing the identification of novel genes related to flower and fruit characteristics. Most genomic associations fell into the region surrounding SUN, OVATE, and MYB gene families. Six flower and fruit traits were associated with a single member of the SUN family (SLSUN31) on chromosome 11, in a region involved in the increase of fruit weight, locules number, and fruit fasciation. Furthermore, additional candidate genes for soluble solids content, fruit colour and shape were found near previously reported chromosomal regions, indicating the presence of synergic and multiple linked genes underlying the variation of these traits. Conclusions Results of this study give new hints on the genetic basis of traits in underexplored germplasm grown under organic conditions, providing a framework for the development of markers linked to candidate genes of interest to be used in genomics-assisted breeding in tomato, in particular under low-input and organic cultivation conditions.This research was supported by the European Union Horizon 2020 Research and Innovation program for funding this research under grant agreement No 774244 (Breeding for Resilient, Efficient and Sustainable Organic Vegetable Production; BRESOV) and by 'RGV-FAO'project funded by the Italian Ministry of Agriculture, Food and Forestry. The funding bodies were not involved in the design of the study, collection, analysis, and interpretation of data, and in writing the manuscript.Tripodi, P.; Soler Aleixandre, S.; Campanelli, G.; Díez Niclós, MJTDJ.; Esposito, S.; Sestili, S.; Figás-Moreno, MDR.... (2021). Genome wide association mapping for agronomic, fruit quality, and root architectural traits in tomato under organic farming conditions. BMC Plant Biology. 21(1):1-22. https://doi.org/10.1186/s12870-021-03271-412221

Functionally informed fine-mapping and polygenic localization of complex trait heritability

Fine-mapping aims to identify causal variants impacting complex traits. We propose PolyFun, a computationally scalable framework to improve fine-mapping accuracy by leveraging functional annotations across the entire genome-not just genome-wide-significant loci-to specify prior probabilities for fine-mapping methods such as SuSiE or FINEMAP. In simulations, PolyFun + SuSiE and PolyFun + FINEMAP were well calibrated and identified >20% more variants with a posterior causal probability >0.95 than identified in their nonfunctionally informed counterparts. In analyses of 49 UK Biobank traits (average n = 318,000), PolyFun + SuSiE identified 3,025 fine-mapped variant-trait pairs with posterior causal probability >0.95, a >32% improvement versus SuSiE. We used posterior mean per-SNP heritabilities from PolyFun + SuSiE to perform polygenic localization, constructing minimal sets of common SNPs causally explaining 50% of common SNP heritability; these sets ranged in size from 28 (hair color) to 3,400 (height) to 2 million (number of children). In conclusion, PolyFun prioritizes variants for functional follow-up and provides insights into complex trait architectures. PolyFun is a computationally scalable framework for functionally informed fine-mapping that makes full use of genome-wide data. It prioritizes more variants than previous methods when applied to 49 complex traits from UK Biobank.Peer reviewe