Genome-wide transcriptome and physiological analyses provide new insights into peanut drought response mechanisms

Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNAseq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought-responsive genotypes

Effect of elevated CO2 on peanut performance in a semi-arid production region

With the intensification and frequency of heat waves and periods of water deficit stress, along with rising atmospheric carbon dioxide [CO2], understanding the seasonal leaf-gas-exchange responses to combined abiotic factors will be important in predicting crop performance in semi-arid production systems. In peanut (Arachis hypogaea L.), the availability of developmental stage physiological data on the response to repeated water deficit stress periods in an elevated [CO2] (EC) environment is limited and necessary to improve crop model predictions. Here, we investigated the effects of season-long EC (650 µmol CO2 m−2 s−1) on the physiology and productivity of peanut in a semi-arid environment. This study was conducted over two-growing seasons using field-based growth chambers to maintain EC conditions, and impose water-stress at three critical developmental stages. Our results showed that relative to ambient [CO2] (AC), long-term EC during water-stress episodes, increased leaf-level light-saturated CO2 assimilation (Asat), transpiration efficiency (TE), vegetative biomass, and pod yield by 58%, 73%, 58%, and 39%, respectively. Although leaf nitrogen content was reduced by 16%, there was 41% increase in maximum Rubisco carboxylation efficiency in EC, indicating that there was minimal photosynthetic down-regulation. Furthermore, long-term EC modified the short-term physiological response (Asat) to rapid changes in [CO2] during the water-stress episodes, generating a much greater change in EC (54%) compared to AC (10%). Additionally, long-term EC generated a 23% greater Asat compared to the short-term EC during the water-stress episodes. These findings indicate high levels of physiological adjustment in EC, which may increase drought resilience. We concluded that EC may reduce the negative impacts of repeated water-stress events at critical developmental stages on rain-fed peanut in semi-arid regions. These results can inform current models to improve the projections of peanut response to future climates

Genome-wide transcriptome and physiological analyses provide new insights into peanut drought response mechanisms

Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNAseq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought-responsive genotypes

Long-term repair of porcine articular cartilage using cryopreservable, clinically compatible human embryonic stem cell-derived chondrocytes.

Osteoarthritis (OA) impacts hundreds of millions of people worldwide, with those affected incurring significant physical and financial burdens. Injuries such as focal defects to the articular surface are a major contributing risk factor for the development of OA. Current cartilage repair strategies are moderately effective at reducing pain but often replace damaged tissue with biomechanically inferior fibrocartilage. Here we describe the development, transcriptomic ontogenetic characterization and quality assessment at the single cell level, as well as the scaled manufacturing of an allogeneic human pluripotent stem cell-derived articular chondrocyte formulation that exhibits long-term functional repair of porcine articular cartilage. These results define a new potential clinical paradigm for articular cartilage repair and mitigation of the associated risk of OA