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Beneficial interactions with microorganisms are pivotal for crop performance and resilience. However, it remains unclear how heritable the microbiome is with respect to the host plant genotype and to what extent host genetic mechanisms can modulate plant–microbiota interactions in the face of environmental stresses. Here we surveyed 3,168 root and rhizosphere microbiome samples from 129 accessions of locally adapted Zea, sourced from diverse habitats and grown under control and different stress conditions. We quantified stress treatment and host genotype effects on the microbiome. Plant genotype and source environment were predictive of microbiome abundance. Genome-wide association analysis identified host genetic variants linked to both rhizosphere microbiome abundance and source environment. We identified transposon insertions in a candidate gene linked to both the abundance of a keystone bacterium Massilia in our controlled experiments and total soil nitrogen in the source environment. Isolation and controlled inoculation of Massilia alone can contribute to root development, whole-plant biomass production and adaptation to low nitrogen availability. We conclude that locally adapted maize varieties exert patterns of genetic control on their root and rhizosphere microbiomes that follow variation in their home environments, consistent with a role in tolerance to prevailing stress.

Phenolic acids (PAs) secreted by donor plants suppress the growth of their susceptible plant neighbours. However, how structurally diverse ensembles of PAs are perceived by plants to mediate interspecific competition remains a mystery. Here we show that a plant stress granule (SG) marker, RNA-BINDING PROTEIN 47B (RBP47B), is a sensor of PAs in Arabidopsis. PAs, including salicylic acid, 4-hydroxybenzoic acid, protocatechuic acid and so on, directly bind RBP47B, promote its phase separation and trigger SG formation accompanied by global translation inhibition. Salicylic acid-induced global translation inhibition depends on RBP47 family members. RBP47s regulate the proteome rather than the absolute quantity of SG. The rbp47 quadruple mutant shows a reduced sensitivity to the inhibitory effect of the PA mixture as well as to that of PA-rich rice when tested in a co-culturing ecosystem. In this Article, we identified the long sought-after PA sensor as RBP47B and illustrated that PA-induced SG-mediated translational inhibition was one of the PA perception mechanisms.

The Mediterranean olive cyst nematode, Heterodera mediterranea, is a pest of olive trees that is found in Spain, Italy, and Tunisia. In this paper, conventional and real-time PCR assays for the identification of H. mediterranea was developed. The hsp90 gene fragment was used to design a species-specific primer and a TaqMan probe. The specificity of the primer/probe set was tested in singleplex or multiplex reactions against Mediterranean olive cyst nematode and non-target nematodes. In multiplex real-time PCR experiments with the specific and universal primer/probe sets, fluorescent signals were simultaneously monitored for hsp90 and D3 of 28S rRNA target genes. The results of the experiments showed that the assays with species-specific primer/probe were sensitive enough to detect the DNA from 0.03 of a second-stage juvenile (J2) H. mediterranea in a reaction tube.

Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB deriv

Water conservation efforts for California’s agricultural industry are critical to its sustainability through severe droughts like the current one and others experienced over the last two decades. This is most critical for perennial crops, such as vineyards and orchards, which are costly to plant and maintain and constitute a significant fraction of the regional water use. It is no longer feasible to access groundwater for irrigation to replace deficit surface water resources during drought due to a significant overdraft of aquifers and new regulation limiting its use. To achieve significant water savings, the actual crop water use or evapotranspiration (ET) needs to be mapped from field to regional scales on a daily basis. This can only be achieved using remote sensing-based models, particularly thermal-based energy balance models that are sensitive to deficit irrigation conditions. The two-source energy balance (TSEB) model has been successfully applied over vineyards in California, but challenges still remain. In particular, much of the irrigated cropland in the California Central Valley is affected by advection of hot dry air masses from surrounding non-irrigated areas and the TSEB model appears to need modifications to adequately estimate ET under such conditions, as well as the partitioning between evaporation and transpiration. This study investigates the application of the TSEB model, using local observations in a vineyard having significant advection. Four versions of the transpiration algorithm in TSEB are applied and evaluated with tower eddy covariance measurements spanning 4 growing seasons. The results suggest the performance of the original transpiration algorithm based on Priestley–Taylor used in TSEB is satisfactory in all but the most extreme advective conditions, while a transpiration algorithm based on Shuttleworth–Wallace with a canopy resistance formula, which relates maximum stomata conductance to vapor pressure deficit (VPD), performs well in

Improved accuracy of evapotranspiration (ET) estimation, including its partitioning between transpiration (T) and surface evaporation (E), is key to monitor agricultural water use in vineyards, especially to enhance water use efficiency in semi-arid regions such as California, USA. Remote-sensing methods have shown great utility in retrieving ET from surface energy balance models based on thermal infrared data. Notably, the two-source energy balance (TSEB) has been widely and robustly applied in numerous landscapes, including vineyards. However, vineyards add an additional complexity where the landscape is essentially made up of two distinct zones: the grapevine and the interrow, which is often seasonally covered by an herbaceous cover crop. Therefore, it becomes more complex to disentangle the various contributions of the different vegetation elements to total ET, especially through TSEB, which assumes a single vegetation source over a soil layer. As such, a remote-sensing-based three-source energy balance (3SEB) model, which essentially adds a vegetation source to TSEB, was applied in an experimental vineyard located in California’s Central Valley to investigate whether it improves the depiction of the grapevine-interrow system. The model was applied in four different blocks in 2019 and 2020, where each block had an eddy-covariance (EC) tower collecting continuous flux, radiometric, and meteorological measurements. 3SEB’s latent and sensible heat flux retrievals were accurate with an overall RMSD ~ 50 W/m2 compared to EC measurements. 3SEB improved upon TSEB simulations, with the largest differences being concentrated in the spring season, when there is greater mixing between grapevine foliage and the cover crop. Additionally, 3SEB’s modeled ET partitioning (T/ET) compared well against an EC T/ET retrieval method, being only slightly underestimated. Overall, these promising results indicate 3SEB can be of great utility to vineyard irrigation management, especially

[Background]: Energy landscapes provide an approach to the mechanistic basis of spatial ecology and decision-making in animals. This is based on the quantification of the variation in the energy costs of movements through agiven environment, as well as how these costs vary in time and for different animal populations. Organisms asdiverse as fish, mammals, and birds will move in areas of the energy landscape that result in minimised costs andmaximised energy gain. Recently, energy landscapes have been used to link energy gain and variable energy costsof foraging to breeding success, revealing their potential use for understanding demographic changes., [Methods]: Using GPS-temperature-depth and tri-axial accelerometer loggers, stable isotope and molecular analysesof the diet, and leucocyte counts, we studied the response of gentoo (Pygoscelis papua) and chinstrap (Pygoscelisantarcticus) penguins to different energy landscapes and resources. We compared species and gentoo penguinpopulations with contrasting population trends., [Results]: Between populations, gentoo penguins from Livingston Island (Antarctica), a site with positive populationtrends, foraged in energy landscape sectors that implied lower foraging costs per energy gained compared withthose around New Island (Falkland/Malvinas Islands; sub-Antarctic), a breeding site with fluctuating energy costs offoraging, breeding success and populations. Between species, chinstrap penguins foraged in sectors of the energylandscape with lower foraging costs per bottom time, a proxy for energy gain. They also showed lowerphysiological stress, as revealed by leucocyte counts, and higher breeding success than gentoo penguins. In termsof diet, we found a flexible foraging ecology in gentoo penguins but a narrow foraging niche for chinstraps., [Conclusions]: The lower foraging costs incurred by the gentoo penguins from Livingston, may favour a higherbreeding success that would explain the species’positive population trend in the Antarctic Peninsula. The lowerforaging costs in chinstrap penguins may also explain their higher breeding success, compared to gentoos fromAntarctica but not their negative population trend. Altogether, our results suggest a link between energylandscapes and breeding success mediated by the physiological condition.

Prior to the availability of whole-genome sequences, our understanding of the structural and functional aspects of Prunus tree genomes was limited mostly to molecular genetic mapping of important traits and development of EST resources. With public release of the peach genome and others that followed, significant advances in our knowledge of Prunus genomes and the genetic underpinnings of important traits ensued. In this review, we highlight key achievements in Prunus genetics and breeding driven by the availability of these whole-genome sequences. Within the structural and evolutionary contexts, we summarize: (1) the current status of Prunus whole-genome sequences; (2) preliminary and ongoing work on the sequence structure and diversity of the genomes; (3) the analyses of Prunus genome evolution driven by natural and man-made selection; and (4) provide insight into haploblocking genomes as a means to define genome-scale patterns of evolution that can be leveraged for trait selection in pedigree-based Prunus tree breeding programs worldwide. Functionally, we summarize recent and ongoing work that leverages whole-genome sequences to identify and characterize genes controlling 22 agronomically important Prunus traits. These include phenology, fruit quality, allergens, disease resistance, tree architecture, and self-incompatibility. Translationally, we explore the application of sequence-based marker-assisted breeding technologies and other sequence-guided biotechnological approaches for Prunus crop improvement. Finally, we present the current status of publically available Prunus genomics and genetics data housed mainly in the Genome Database for Rosaceae (GDR) and its updated functionalities for future bioinformatics-based Prunus genetics and genomics inquiry.

Potato cyst nematodes (PCNs), Globodera rostochiensis and G. pallida, cause important economic losses. They are hard to manage because of their ability to remain dormant in soil for many years. Although general knowledge about these plant parasitic nematodes has considerably increased over the past decades, very little is known about molecular events involved in cyst dormancy and hatching, two key steps of their development. Here, we have studied the progression of PCN transcriptomes from dry cysts to hatched juveniles using RNA-Seq. We found that several cell detoxification-related genes were highly active in the dry cysts. Many genes linked to an increase of calcium and water uptake were up-regulated during transition from dormancy to hydration. Exposure of hydrated cysts to host plant root exudates resulted in different transcriptional response between species. After 48 h of exposure, G. pallida cysts showed no significant modulation of gene expression while G. rostochiensis had 278 differentially expressed genes. The first G. rostochiensis significantly up-regulated gene was observed after 8 h and was coding for a transmembrane metalloprotease. This enzyme is able to activate/inactivate peptide hormones and could be involved in a cascade of events leading to hatching. Several known effector genes were also up-regulated during hatching.

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Ticks transmit more pathogens to humans and animals than any other arthropod. We describe the 2.1 Gbp nuclear genome of the tick, Ixodes scapularis (Say), which vectors pathogens that cause Lyme disease, human granulocytic anaplasmosis, babesiosis and other diseases. The large genome reflects accumulation of repetitive DNA, new lineages of retro-transposons, and gene architecture patterns resembling ancient metazoans rather than pancrustaceans. Annotation of scaffolds representing ∼57% of the genome, reveals 20,486 protein-coding genes and expansions of gene families associated with tick–host interactions. We report insights from genome analyses into parasitic processes unique to ticks, including host ‘questing’, prolonged feeding, cuticle synthesis, blood meal concentration, novel methods of haemoglobin digestion, haem detoxification, vitellogenesis and prolonged off-host survival. We identify proteins associated with the agent of human granulocytic anaplasmosis, an emerging disease, and the encephalitis-causing Langat virus, and a population structure correlated to life-history traits and transmission of the Lyme disease agent.

Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.

Background The size and complexity of conifer genomes has, until now, prevented full genome sequencing and assembly. The large research community and economic importance of loblolly pine, Pinus taeda L., made it an early candidate for reference sequence determination, Results We develop a novel strategy to sequence the genome of loblolly pine that combines unique aspects of pine reproductive biology and genome assembly methodology. We use a whole genome shotgun approach relying primarily on next generation sequence generated from a single haploid seed megagametophyte from a loblolly pine tree, 20-1010, that has been used in industrial forest tree breeding. The resulting sequence and assembly was used to generate a draft genome spanning 23.2 Gbp and containing 20.1 Gbp with an N50 scaffold size of 66.9 kbp, making it a significant improvement over available conifer genomes. The long scaffold lengths allow the annotation of 50,172 gene models with intron lengths averaging over 2.7 kbp and sometimes exceeding 100 kbp in length. Analysis of orthologous gene sets identifies gene families that may be unique to conifers. We further characterize and expand the existing repeat library based on the de novo analysis of the repetitive content, estimated to encompass 82% of the genome, Conclusions In addition to its value as a resource for researchers and breeders, the loblolly pine genome sequence and assembly reported here demonstrates a novel approach to sequencing the large and complex genomes of this important group of plants that can now be widely applied

Rosaceae is the most important fruit-producing clade, and its key commercially relevant genera (Fragaria, Rosa, Rubus and Prunus) show broadly diverse growth habits, fruit types and compact diploid genomes. Peach, a diploid Prunus species, is one of the best genetically characterized deciduous trees. Here we describe the high-quality genome sequence of peach obtained from a completely homozygous genotype. We obtained a complete chromosome-scale assembly using Sanger whole-genome shotgun methods. We predicted 27,852 protein-coding genes, as well as noncoding RNAs. We investigated the path of peach domestication through whole-genome resequencing of 14 Prunus accessions. The analyses suggest major genetic bottlenecks that have substantially shaped peach genome diversity. Furthermore, comparative analyses showed that peach has not undergone recent whole-genome duplication, and even though the ancestral triplicated blocks in peach are fragmentary compared to those in grape, all seven paleosets of paralogs from the putative paleoancestor are detectable.

The pig, Sus scrofa, is a foreign species to the American continent. Although pigs originally introduced in the Americas should be related to those from the Iberian Peninsula and Canary islands, the phylogeny of current creole pigs that now populate the continent is likely to be very complex. Because of the extreme climates that America harbors, these populations also provide a unique example of a fast evolutionary phenomenon of adaptation. Here, we provide a genome wide study of these issues by genotyping, with a 60k SNP chip, 206 village pigs sampled across 14 countries and 183 pigs from outgroup breeds that are potential founders of the American populations, including wild boar, Iberian, international and Chinese breeds. Results show that American village pigs are primarily of European ancestry, although the observed genetic landscape is that of a complex conglomerate. There was no correlation between genetic and geographical distances, neither continent wide nor when analyzing specific areas. Most populations showed a clear admixed structure where the Iberian pig was not necessarily the main component, illustrating how international breeds, but also Chinese pigs, have contributed to extant genetic composition of American village pigs. We also observe that many genes related to the cardiovascular system show an increased differentiation between altiplano and genetically related pigs living near sea level.

Single nucleotide polymorphisms (SNPs) are a fundamental source of genomic variation. Large SNP panels have been developed for Prunus species. Fruit quality traits are essential peach breeding program objectives since they determine consumer acceptance, fruit consumption, industry trends and cultivar adoption. For many cultivars, these traits are negatively impacted by cold storage, used to extend fruit market life. The major symptoms of chilling injury are lack of flavor, off flavor, mealiness, flesh browning, and flesh bleeding. A set of 1,109 SNPs was mapped previously and 67 were linked with these complex traits. The prediction of the effects associated with these SNPs on downstream products from the ‘peach v1.0’ genome sequence was carried out. A total of 2,163 effects were detected, 282 effects (non-synonymous, synonymous or stop codon gained) were located in exonic regions (13.04 %) and 294 placed in intronic regions (13.59 %). An extended list of genes and proteins that could be related to these traits was developed. Two SNP markers that explain a high percentage of the observed phenotypic variance, UCD_SNP_1084 and UCD_SNP_46, are associated with zinc finger (C3HC4-type RING finger) family protein and AOX1A (alternative oxidase 1a) protein groups, respectively. In addition, phenotypic variation suggests that the observed polymorphism for SNP UCD_SNP_1084 [A/G] mutation could be a candidate quantitative trait nucleotide affecting quantitative trait loci for mealiness. The interaction and expression of affected proteins could explain the variation observed in each individual and facilitate understanding of gene regulatory networks for fruit quality traits in peach

Single nucleotide polymorphisms (SNPs) were used to construct an integrated SNP linkage map of peach (Prunus persica (L.) Batsch). A set of 1,536 SNPs were evaluated with the GoldenGate® Genotyping assay in two mapping populations, Pop-DF, and Pop-DG. After genotyping and filtering, a final set of 1,400 high quality SNPs in Pop-DF and 962 in Pop-DG with full map coverage were selected and used to construct two linkage maps with JoinMap®4.0. The Pop-DF map covered 422 cM of the peach genome and included 1,037 SNP markers, and Pop-DG map covered 369 cM and included 738 SNPs. A consensus map was constructed with 588 SNP markers placed in eight linkage groups (n = 8 for peach), with map coverage of 454 cM and an average distance of 0.81 cM/marker site. Placements of SNPs on the “peach v1.0” physical map were compared to placement on the linkage maps and several differences were observed. Using the SNP linkage map of Pop-DG and phenotypic data collected for three harvest seasons, a QTL analysis for fruit quality traits and chilling injury symptoms was carried out with the mapped SNPs. Significant QTL effects were detected for mealiness (M) and flesh bleeding (FBL) QTLs on linkage group 4 and flesh browning (FBr) on linkage group 5. This study represents one of the first examples of QTL detection for quality traits and chilling injury symptoms using a high-density SNP map in a single peach F1 family

Background The application of next generation sequencing technologies and bioinformatic scripts to identify high frequency SNPs distributed throughout the peach genome is described. Three peach genomes were sequenced using Roche 454 and Illumina/Solexa technologies to obtain long contigs for alignment to the draft 'Lovell' peach sequence as well as sufficient depth of coverage for 'in silico' SNP discovery, Description The sequences were aligned to the 'Lovell' peach genome released April 01, 2010 by the International Peach Genome Initiative (IPGI). 'Dr. Davis', 'F8, 1-42' and 'Georgia Belle' were sequenced to add SNPs segregating in two breeding populations, Pop DF ('Dr. Davis' × 'F8, 1-42') and Pop DG ('Dr. Davis' × 'Georgia Belle'). Roche 454 sequencing produced 980,000 total reads with 236 Mb sequence for 'Dr. Davis' and 735,000 total reads with 172 Mb sequence for 'F8, 1-42'. 84 bp × 84 bp paired end Illumina/Solexa sequences yielded 25.5, 21.4, 25.5 million sequences for 'Dr. Davis', 'F8, 1-42' and 'Georgia Belle', respectively. BWA/SAMtools were used for alignment of raw reads and SNP detection, with custom PERL scripts for SNP filtering. Velvet's Columbus module was used for sequence assembly. Comparison of aligned and overlapping sequences from both Roche 454 and Illumina/Solexa resulted in the selection of 6654 high quality SNPs for 'Dr. Davis' vs. 'F8, 1-42' and 'Georgia Belle', distributed on eight major peach genome scaffolds as defined from the 'Lovell' assembly, Conclusion The eight scaffolds contained about 215-225 Mb of peach genomic sequences with one SNP/~ 40,000 bases. All sequences from Roche 454 and Illumina/Solexa have been submitted to NCBI for public use in the Short Read Archive database. SNPs have been deposited in the NCBI SNP database

A genome-wide framework physical map of peach was constructed using high-information content fingerprinting (HICF) and FPC software. The resulting HICF assembly contained 2,138 contigs composed of 15,655 clones (4.3× peach genome equivalents) from two complementary bacterial artificial chromosome libraries. The total physical length of all contigs is estimated at 303 Mb or 104.5% of the peach genome. The framework physical map is anchored on the Prunus genetic reference map and integrated with the peach transcriptome map. The physical length of anchored contigs is estimated at 45.0 Mb or 15.5% of the genome. Altogether, 2,636 markers, i.e., genetic markers, peach unigene expressed sequence tags, and gene-specific and overgo probes, were incorporated into the physical framework and supported the accuracy of contig assembly.