The narrow genetic base and limited genetic information on Arachis species have hindered the process of marker-assisted selection of peanut cultivars. However, recent developments in sequencing ...technologies have expanded opportunities to exploit genetic resources, and at lower cost. To use the genetic information for Arachis species available at the transcriptome level, it is important to have a good quality reference transcriptome. The available Tifrunner 454 FLEX transcriptome sequences have an assembly with 37,000 contigs and low N50 values of 500-751 bp. Therefore, we generated de novo transcriptome assemblies, with about 38 million reads in the tetraploid cultivar OLin, and 16 million reads in each of the diploids, A. duranensis K38901 and A. ipaënsis KGBSPSc30076 using three different de novo assemblers, Trinity, SOAPdenovo-Trans and TransAByss. All these assemblers can use single kmer analysis, and the latter two also permit multiple kmer analysis. Assemblies generated for all three samples had N50 values ranging from 1278-1641 bp in Arachis hypogaea (AABB), 1401-1492 bp in Arachis duranensis (AA), and 1107-1342 bp in Arachis ipaënsis (BB). Comparison with legume ESTs and protein databases suggests that assemblies generated had more than 40% full length transcripts with good continuity. Also, on mapping the raw reads to each of the assemblies generated, Trinity had a high success rate in assembling sequences compared to both TransAByss and SOAPdenovo-Trans. De novo assembly of OLin had a greater number of contigs (67,098) and longer contig length (N50 = 1,641) compared to the Tifrunner TSA. Despite having shorter read length (2 × 50) than the Tifrunner 454FLEX TSA, de novo assembly of OLin proved superior in comparison. Assemblies generated to represent different genome combinations may serve as a valuable resource for the peanut research community.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Single-nucleotide polymorphisms, which can be identified in the thousands or millions from comparisons of transcriptome or genome sequences, are ideally suited for making high-resolution genetic ...maps, investigating population evolutionary history, and discovering marker–trait linkages. Despite significant results from their use in human genetics, progress in identification and use in plants, and particularly polyploid plants, has lagged. As part of a long-term project to identify and use SNPs suitable for these purposes in cultivated peanut, which is tetraploid, we generated transcriptome sequences of four peanut cultivars, namely OLin, New Mexico Valencia C, Tamrun OL07 and Jupiter, which represent the four major market classes of peanut grown in the world, and which are important economically to the US southwest peanut growing region. CopyDNA libraries of each genotype were used to generate 2 × 54 paired-end reads using an Illumina GAIIx sequencer. Raw reads were mapped to a custom reference consisting of Tifrunner 454 sequences plus peanut ESTs in GenBank, compromising 43,108 contigs; 263,840 SNP and indel variants were identified among four genotypes compared to the reference. A subset of 6 variants was assayed across 24 genotypes representing four market types using KASP chemistry to assess the criteria for SNP selection. Results demonstrated that transcriptome sequencing can identify SNPs usable as selectable DNA-based markers in complex polyploid species such as peanut. Criteria for effective use of SNPs as markers are discussed in this context.
At the cellular level, membrane damage is a fundamental cause of yield loss at high temperatures (HT). We report our investigations on a subset of a peanut (
) recombinant inbred line population, ...demonstrating that the membrane lipid remodeling occurring at HT is consistent with homeoviscous adaptation to maintain membrane fluidity. A major alteration in the leaf lipidome at HT was the reduction in the unsaturation levels, primarily through reductions of 18:3 fatty acid chains, of the plastidic and extra-plastidic diacyl membrane lipids. In contrast, levels of 18:3-containing triacylglycerols (TGs) increased at HT, consistent with a role for TGs in sequestering fatty acids when membrane lipids undergo remodeling during plant stress. Polyunsaturated acyl chains from membrane diacyl lipids were also sequestered as sterol esters (SEs). The removal of 18:3 chains from the membrane lipids decreased the availability of susceptible molecules for oxidation, thereby minimizing oxidative damage in membranes. Our results suggest that transferring 18:3 chains from membrane diacyl lipids to TGs and SEs is a key feature of lipid remodeling for HT adaptation in peanut. Finally, QTL-seq allowed the identification of a genomic region associated with heat-adaptive lipid remodeling, which would be useful for identifying molecular markers for heat tolerance.
This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic ...research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.
Peanut (Arachis hypogaea L.) plants respond to drought stress through changes in morpho-physiological and agronomic characteristics that breeders can use to improve the drought tolerance of this ...crop. Although agronomic traits, such as plant height, lateral growth, and yield, are easily measured, they may have low heritability due to environmental dependencies, including the soil type and rainfall distribution. Morpho-physiological characteristics, which may have high heritability, allow for optimal genetic gain. However, they are challenging to measure accurately at the field scale, hindering the confident selection of drought-tolerant genotypes. To this end, aerial imagery collected from unmanned aerial vehicles (UAVs) may provide confident phenotyping of drought tolerance. We selected a subset of 28 accessions from the U.S. peanut mini-core germplasm collection for in-depth evaluation under well-watered (rainfed) and water-restricted conditions in 2018 and 2019. We measured morpho-physiological and agronomic characteristics manually and estimated them from aerially collected vegetation indices. The peanut genotype and water regime significantly (p < 0.05) affected all the plant characteristics (RCC, SLA, yield, etc.). Manual and aerial measurements correlated with r values ranging from 0.02 to 0.94 (p < 0.05), but aerially estimated traits had a higher broad sense heritability (H2) than manual measurements. In particular, CO2 assimilation, stomatal conductance, and transpiration rates were efficiently estimated (R2 ranging from 0.76 to 0.86) from the vegetation indices, indicating that UAVs can be used to phenotype drought tolerance for genetic gains in peanut plants.
To test the hypothesis that the cultivated peanut species possesses almost no molecular variability, we sequenced a diverse panel of 22 Arachis accessions representing Arachis hypogaea botanical ...classes, A-, B-, and K- genome diploids, a synthetic amphidiploid, and a tetraploid wild species. RNASeq was performed on pools of three tissues, and de novo assembly was performed. Realignment of individual accession reads to transcripts of the cultivar OLin identified 306,820 biallelic SNPs. Among 10 naturally occurring tetraploid accessions, 40,382 unique homozygous SNPs were identified in 14,719 contigs. In eight diploid accessions, 291,115 unique SNPs were identified in 26,320 contigs. The average SNP rate among the 10 cultivated tetraploids was 0.5, and among eight diploids was 9.2 per 1000 bp. Diversity analysis indicated grouping of diploids according to genome classification, and cultivated tetraploids by subspecies. Cluster analysis of variants indicated that sequences of B genome species were the most similar to the tetraploids, and the next closest diploid accession belonged to the A genome species. A subset of 66 SNPs selected from the dataset was validated; of 782 SNP calls, 636 (81.32%) were confirmed using an allele-specific discrimination assay. We conclude that substantial genetic variability exists among wild species. Additionally, significant but lesser variability at the molecular level occurs among accessions of the cultivated species. This survey is the first to report significant SNP level diversity among transcripts, and may explain some of the phenotypic differences observed in germplasm surveys. Understanding SNP variants in the Arachis accessions will benefit in developing markers for selection.
Identification of peanut cultivars for distinct phenotypic or genotypic traits whether using visual characterization or laboratory analysis requires substantial expertise, time, and resources. A less ...subjective and more precise method is needed for identification of peanut germplasm throughout the value chain. In this proof-of-principle study, the accuracy of Raman spectroscopy (RS), a non-invasive, non-destructive technique, in peanut phenotyping and identification is explored. We show that RS can be used for highly accurate peanut phenotyping
surface scans of peanut leaves and the resulting chemometric analysis: On average 94% accuracy in identification of peanut cultivars and breeding lines was achieved. Our results also suggest that RS can be used for highly accurate determination of nematode resistance and susceptibility of those breeding lines and cultivars. Specifically, nematode-resistant peanut cultivars can be identified with 92% accuracy, whereas susceptible breeding lines were identified with 81% accuracy. Finally, RS revealed substantial differences in biochemical composition between resistant and susceptible peanut cultivars. We found that resistant cultivars exhibit substantially higher carotenoid content compared to the susceptible breeding lines. The results of this study show that RS can be used for quick, accurate, and non-invasive identification of genotype, nematode resistance, and nutrient content. Armed with this knowledge, the peanut industry can utilize Raman spectroscopy for expedited breeding to increase yields, nutrition, and maintaining purity levels of cultivars following release.
Hemp (Cannabis sativa L. ssp. sativa) has a long history of domestication due to its versatile use. Recently, different sectors in the economy are investigating hemp cultivation to increase agronomic ...production and to limit delta-9-tetrahydrocannabinol (THC). Despite the rapid growth of hemp literature in recent years, it is still uncertain whether the knowledge gained from higher latitude regions is applicable to low latitude and tropical regions where hemp has not been grown traditionally. This review provides a comprehensive and updated survey of hemp agronomy, focusing on environmental and management factors influencing the growth and yield of hemp, methods of cannabinoids detection and quantification, and hemp breeding. This review suggests that some previous claims about hemp as a low input crop may not hold true in low-latitude regions. Additional research strategies, such as the integration of experimentation and modeling efforts, are encouraged to hasten new discoveries. Furthermore, to effectively increase the outputs of value products (cannabinoids, seeds, fiber and biomass, etc.) while limiting the THC level, new collaborations between hemp agronomists and economists may streamline the production process by increasing the efficiency of the total production system of hemp as a multifaceted crop.
Water deficit and salinity are two major abiotic stresses that have tremendous effect on crop yield worldwide. Timely identification of these stresses can help limit associated yield loss. ...Confirmatory detection and identification of water deficit stress can also enable proper irrigation management. Traditionally, unmanned aerial vehicle (UAV)‐based imaging and satellite‐based imaging, together with visual field observation, are used for diagnostics of such stresses. However, these approaches can only detect salinity and water deficit stress at the symptomatic stage. Raman spectroscopy (RS) is a noninvasive and nondestructive technique that can identify and detect plant biotic and abiotic stress. In this study, we investigated accuracy of Raman‐based diagnostics of water deficit and salinity stresses on two greenhouse‐grown peanut accessions: tolerant and susceptible to water deficit. Plants were grown for 76 days prior to application of the water deficit and salinity stresses. Water deficit treatments received no irrigation for 5 days, and salinity treatments received 1.0 L of 240‐mM salt water per day for the duration of 5‐day sampling. Every day after the stress was imposed, plant leaves were collected and immediately analyzed by a hand‐held Raman spectrometer. RS and chemometrics could identify control and stressed (either water deficit or salinity) susceptible plants with 95% and 80% accuracy just 1 day after treatment. Water deficit and salinity stressed plants could be differentiated from each other with 87% and 86% accuracy, respectively. In the tolerant accessions at the same timepoint, the identification accuracies were 66%, 65%, 67%, and 69% for control, combined stresses, water deficit, and salinity stresses, respectively. The high selectivity and specificity for presymptomatic identification of abiotic stresses in the susceptible line provide evidence for the potential of Raman‐based surveillance in commercial‐scale agriculture and digital farming.
Highlights
We show that Raman spectroscopy can be used for presymptomatic diagnosis of water deficit and salinity stresses in two peanut accessions. We found that the accuracy of stress detection and identification directly depends on the plant sensitivity to the stress imposed.
•Elevated CO2 increased peanut photosynthesis by 58% and yield by 39%.•Elevated CO2 reduced leaf nitrogen content by 16%.•Elevated CO2 increased leaf-level transpiration efficiency by 73%.•There was ...minimal photosynthetic down-regulation to elevated CO2.•Elevated CO2 reduced the negative effects of water stress on peanut.
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.
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