Longitudinal genome-wide association study reveals early QTL that predict biomass accumulation under cold stress in sorghum.

Introduction: Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy due to its high biomass yields. However, early growth phases of sorghum are sensitive to cold stress, limiting its planting in temperate environments. Cold adaptability is crucial for cultivating bioenergy and grain sorghum at higher latitudes and elevations, or for extending the growing season. Identifying genes and alleles that enhance biomass accumulation under early cold stress can lead to improved sorghum varieties through breeding or genetic engineering. Methods: We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP includes diverse accessions with dense genotyping and varied racial, geographical, and phenotypic backgrounds. Daily, non-destructive imaging allowed temporal analysis of growth-related traits and water use efficiency (WUE). A genome-wide association study (GWAS) was performed to identify genomic intervals and genes associated with cold stress response. Results: The GWAS identified transient quantitative trait loci (QTL) strongly associated with growth-related traits, enabling an exploration of the genetic basis of cold stress response at different developmental stages. This analysis of daily growth traits, rather than endpoint traits, revealed early transient QTL predictive of final phenotypes. The study identified both known and novel candidate genes associated with growth-related traits and temporal responses to cold stress. Discussion: The identified QTL and candidate genes contribute to understanding the genetic mechanisms underlying sorghum's response to cold stress. These findings can inform breeding and genetic engineering strategies to develop sorghum varieties with improved biomass yields and resilience to cold, facilitating earlier planting, extended growing seasons, and cultivation at higher latitudes and elevations.

Natural variation in Brachypodium distachyon responses to combined abiotic stresses.

The demand for agricultural production is becoming more challenging as climate change increases global temperature and the frequency of extreme weather events. This study examines the phenotypic variation of 149 accessions of Brachypodium distachyon under drought, heat, and the combination of stresses. Heat alone causes the largest amounts of tissue damage while the combination of stresses causes the largest decrease in biomass compared to other treatments. Notably, Bd21-0, the reference line for B. distachyon, did not have robust growth under stress conditions, especially the heat and combined drought and heat treatments. The climate of origin was significantly associated with B. distachyon responses to the assessed stress conditions. Additionally, a GWAS found loci associated with changes in plant height and the amount of damaged tissue under stress. Some of these SNPs were closely located to genes known to be involved in responses to abiotic stresses and point to potential causative loci in plant stress response. However, SNPs found to be significantly associated with a response to heat or drought individually are not also significantly associated with the combination of stresses. This, with the phenotypic data, suggests that the effects of these abiotic stresses are not simply additive, and the responses to the combined stresses differ from drought and heat alone.

Phytochromes transmit photoperiod information via the evening complex in Brachypodium.

BACKGROUND: Daylength is a key seasonal cue for animals and plants. In cereals, photoperiodic responses are a major adaptive trait, and alleles of clock genes such as PHOTOPERIOD1 (PPD1) and EARLY FLOWERING3 (ELF3) have been selected for in adapting barley and wheat to northern latitudes. How monocot plants sense photoperiod and integrate this information into growth and development is not well understood. RESULTS: We find that phytochrome C (PHYC) is essential for flowering in Brachypodium distachyon. Conversely, ELF3 acts as a floral repressor and elf3 mutants display a constitutive long day phenotype and transcriptome. We find that ELF3 and PHYC occur in a common complex. ELF3 associates with the promoters of a number of conserved regulators of flowering, including PPD1 and VRN1. Consistent with observations in barley, we are able to show that PPD1 overexpression accelerates flowering in short days and is necessary for rapid flowering in response to long days. PHYC is in the active Pfr state at the end of the day, but we observe it undergoes dark reversion over the course of the night. CONCLUSIONS: We propose that PHYC acts as a molecular timer and communicates information on night-length to the circadian clock via ELF3.

Wireless Fixed Camera Network for Greenhouse-Based Plant Phenotyping.

An indoor wireless fixed camera network was developed for an efficient, cost-effective method of extracting informative plant phenotypes in a controlled greenhouse environment. Deployed at the Donald Danforth Plant Science Center (DDPSC), this fixed camera platform implements rapid and automated plant phenotyping. The platform uses low-cost Raspberry Pi computers and digital cameras to monitor aboveground morphological and developmental plant phenotypes. The Raspberry Pi is a readily programmable, credit card-sized computer board with remote accessibility. A standard camera module connects to the Raspberry Pi computer board and generates eight-megapixel resolution images. With a fixed array, or "bramble," of Raspberry Pi computer boards and camera modules placed strategically in a greenhouse, we can capture automated, high-resolution images for 3D reconstructions of individual plants on timescales ranging from minutes to hours, capturing temporal changes in plant phenotypes.

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum.

We explore the use of deep convolutional neural networks (CNNs) trained on overhead imagery of biomass sorghum to ascertain the relationship between single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the phenotypes they control. We consider both CNNs trained explicitly on the classification task of predicting whether an image shows a plant with a reference or alternate version of various SNPs as well as CNNs trained to create data-driven features based on learning features so that images from the same plot are more similar than images from different plots, and then using the features this network learns for genetic marker classification. We characterize how efficient both approaches are at predicting the presence or absence of a genetic markers, and visualize what parts of the images are most important for those predictions. We find that the data-driven approaches give somewhat higher prediction performance, but have visualizations that are harder to interpret; and we give suggestions of potential future machine learning research and discuss the possibilities of using this approach to uncover unknown genotype × phenotype relationships.

Genome Wide Association Study Uncovers the QTLome for Osmotic Adjustment and Related Drought Adaptive Traits in Durum Wheat.

Osmotic adjustment (OA) is a major component of drought resistance in crops. The genetic basis of OA in wheat and other crops remains largely unknown. In this study, 248 field-grown durum wheat elite accessions grown under well-watered conditions, underwent a progressively severe drought treatment started at heading. Leaf samples were collected at heading and 17 days later. The following traits were considered: flowering time (FT), leaf relative water content (RWC), osmotic potential (ψs), OA, chlorophyll content (SPAD), and leaf rolling (LR). The high variability (3.89-fold) in OA among drought-stressed accessions resulted in high repeatability of the trait (h2 = 72.3%). Notably, a high positive correlation (r = 0.78) between OA and RWC was found under severe drought conditions. A genome-wide association study (GWAS) revealed 15 significant QTLs (Quantitative Trait Loci) for OA (global R2 = 63.6%), as well as eight major QTL hotspots/clusters on chromosome arms 1BL, 2BL, 4AL, 5AL, 6AL, 6BL, and 7BS, where a higher OA capacity was positively associated with RWC and/or SPAD, and negatively with LR, indicating a beneficial effect of OA on the water status of the plant. The comparative analysis with the results of 15 previous field trials conducted under varying water regimes showed concurrent effects of five OA QTL cluster hotspots on normalized difference vegetation index (NDVI), thousand-kernel weight (TKW), and/or grain yield (GY). Gene content analysis of the cluster regions revealed the presence of several candidate genes, including bidirectional sugar transporter SWEET, rhomboid-like protein, and S-adenosyl-L-methionine-dependent methyltransferases superfamily protein, as well as DREB1. Our results support OA as a valuable proxy for marker-assisted selection (MAS) aimed at enhancing drought resistance in wheat.

The recent evolutionary rescue of a staple crop depended on over half a century of global germplasm exchange.

Rapid environmental change can lead to population extinction or evolutionary rescue. The global staple crop sorghum (Sorghum bicolor) has recently been threatened by a global outbreak of an aggressive new biotype of sugarcane aphid (SCA; Melanaphis sacchari). We characterized genomic signatures of adaptation in a Haitian breeding population that had rapidly adapted to SCA infestation, conducting evolutionary population genomics analyses on 296 Haitian lines versus 767 global accessions. Genome scans and geographic analyses suggest that SCA adaptation has been conferred by a globally rare East African allele of RMES1, which spread to breeding programs in Africa, Asia, and the Americas. De novo genome sequencing revealed potential causative variants at RMES1. Markers developed from the RMES1 sweep predicted resistance in eight independent commercial and public breeding programs. These findings demonstrate the value of evolutionary genomics to develop adaptive trait technology and highlight the benefits of global germplasm exchange to facilitate evolutionary rescue.

Genomic patterns of structural variation among diverse genotypes of Sorghum bicolor and a potential role for deletions in local adaptation.

Genomic structural mutations, especially deletions, are an important source of variation in many species and can play key roles in phenotypic diversification and evolution. Previous work in many plant species has identified multiple instances of structural variations (SVs) occurring in or near genes related to stress response and disease resistance, suggesting a possible role for SVs in local adaptation. Sorghum [Sorghum bicolor (L.) Moench] is one of the most widely grown cereal crops in the world. It has been adapted to an array of different climates as well as bred for multiple purposes, resulting in a striking phenotypic diversity. In this study, we identified genome-wide SVs in the Biomass Association Panel, a collection of 347 diverse sorghum genotypes collected from multiple countries and continents. Using Illumina-based, short-read whole-genome resequencing data from every genotype, we found a total of 24,648 SVs, including 22,359 deletions. The global site frequency spectrum of deletions and other types of SVs fit a model of neutral evolution, suggesting that the majority of these mutations were not under any types of selection. Clustering results based on single nucleotide polymorphisms separated the genotypes into eight clusters which largely corresponded with geographic origins, with many of the large deletions we uncovered being unique to a single cluster. Even though most deletions appeared to be neutral, a handful of cluster-specific deletions were found in genes related to biotic and abiotic stress responses, supporting the possibility that at least some of these deletions contribute to local adaptation in sorghum.

DCT4-A New Member of the Dicarboxylate Transporter Family in C4 Grasses.

Malate transport shuttles atmospheric carbon into the Calvin-Benson cycle during NADP-ME C4 photosynthesis. Previous characterizations of several plant dicarboxylate transporters (DCT) showed that they efficiently exchange malate across membranes. Here, we identify and characterize a previously unknown member of the DCT family, DCT4, in Sorghum bicolor. We show that SbDCT4 exchanges malate across membranes and its expression pattern is consistent with a role in malate transport during C4 photosynthesis. SbDCT4 is not syntenic to the characterized photosynthetic gene ZmDCT2, and an ortholog is not detectable in the maize reference genome. We found that the expression patterns of DCT family genes in the leaves of Zea mays, and S. bicolor varied by cell type. Our results suggest that subfunctionalization, of members of the DCT family, for the transport of malate into the bundle sheath plastids, occurred during the process of independent recurrent evolution of C4 photosynthesis in grasses of the PACMAD clade. We also show that this subfunctionalization is lineage independent. Our results challenge the dogma that key C4 genes must be orthologues of one another among C4 species, and shed new light on the evolution of C4 photosynthesis.

Escalation in the host-pathogen arms race: A host resistance response corresponds to a heightened bacterial virulence response.

The zig-zag model of host-pathogen interaction describes the relative strength of defense response across a spectrum of pathogen-induced plant phenotypes. A stronger defense response results in increased resistance. Here, we investigate the strength of pathogen virulence during disease and place these findings in the context of the zig-zag model. Xanthomonas vasicola pv. holcicola (Xvh) causes sorghum bacterial leaf streak. Despite being widespread, this disease has not been described in detail at the molecular level. We divided diverse sorghum genotypes into three groups based on disease symptoms: water-soaked lesions, red lesions, and resistance. Bacterial growth assays confirmed that these three phenotypes represent a range of resistance and susceptibility. To simultaneously reveal defense and virulence responses across the spectrum of disease phenotypes, we performed dual RNA-seq on Xvh-infected sorghum. Consistent with the zig-zag model, the expression of plant defense-related genes was strongest in the resistance interaction. Surprisingly, bacterial virulence genes related to the type III secretion system (T3SS) and type III effectors (T3Es) were also most highly expressed in the resistance interaction. This expression pattern was observed at multiple time points within the sorghum-Xvh pathosystem. Further, a similar expression pattern was observed in Arabidopsis infected with Pseudomonas syringae for effector-triggered immunity via AvrRps4 but not AvrRpt2. Specific metabolites were able to repress the Xvh virulence response in vitro and in planta suggesting a possible signaling mechanism. Taken together, these findings reveal multiple permutations of the continually evolving host-pathogen arms race from the perspective of host defense and pathogen virulence responses.

Comparative evolutionary genetics of deleterious load in sorghum and maize.

Sorghum and maize share a close evolutionary history that can be explored through comparative genomics1,2. To perform a large-scale comparison of the genomic variation between these two species, we analysed ~13 million variants identified from whole-genome resequencing of 499 sorghum lines together with 25 million variants previously identified in 1,218 maize lines. Deleterious mutations in both species were prevalent in pericentromeric regions, enriched in non-syntenic genes and present at low allele frequencies. A comparison of deleterious burden between sorghum and maize revealed that sorghum, in contrast to maize, departed from the domestication-cost hypothesis that predicts a higher deleterious burden among domesticates compared with wild lines. Additionally, sorghum and maize population genetic summary statistics were used to predict a gene deleterious index with an accuracy greater than 0.5. This research represents a key step towards understanding the evolutionary dynamics of deleterious variants in sorghum and provides a comparative genomics framework to start prioritizing these variants for removal through genome editing and breeding.

Genome and time-of-day transcriptome of Wolffia australiana link morphological minimization with gene loss and less growth control.

Rootless plants in the genus Wolffia are some of the fastest growing known plants on Earth. Wolffia have a reduced body plan, primarily multiplying through a budding type of asexual reproduction. Here, we generated draft reference genomes for Wolffia australiana (Benth.) Hartog & Plas, which has the smallest genome size in the genus at 357 Mb and has a reduced set of predicted protein-coding genes at about 15,000. Comparison between multiple high-quality draft genome sequences from W. australiana clones confirmed loss of several hundred genes that are highly conserved among flowering plants, including genes involved in root developmental and light signaling pathways. Wolffia has also lost most of the conserved nucleotide-binding leucine-rich repeat (NLR) genes that are known to be involved in innate immunity, as well as those involved in terpene biosynthesis, while having a significant overrepresentation of genes in the sphingolipid pathways that may signify an alternative defense system. Diurnal expression analysis revealed that only 13% of Wolffia genes are expressed in a time-of-day (TOD) fashion, which is less than the typical ∼40% found in several model plants under the same condition. In contrast to the model plants Arabidopsis and rice, many of the pathways associated with multicellular and developmental processes are not under TOD control in W. australiana, where genes that cycle the conditions tested predominantly have carbon processing and chloroplast-related functions. The Wolffia genome and TOD expression data set thus provide insight into the interplay between a streamlined plant body plan and optimized growth.

Expansion of the circadian transcriptome in Brassica rapa and genome-wide diversification of paralog expression patterns.

An important challenge of crop improvement strategies is assigning function to paralogs in polyploid crops. Here we describe the circadian transcriptome in the polyploid crop Brassica rapa. Strikingly, almost three-quarters of the expressed genes exhibited circadian rhythmicity. Genetic redundancy resulting from whole genome duplication is thought to facilitate evolutionary change through sub- and neo-functionalization among paralogous gene pairs. We observed genome-wide expansion of the circadian expression phase among retained paralogous pairs. Using gene regulatory network models, we compared transcription factor targets between B. rapa and Arabidopsis circadian networks to reveal evidence for divergence between B. rapa paralogs that may be driven in part by variation in conserved non-coding sequences (CNS). Additionally, differential drought response among retained paralogous pairs suggests further functional diversification. These findings support the rapid expansion and divergence of the transcriptional network in a polyploid crop and offer a new approach for assessing paralog activity at the transcript level.

Like animals, plants have internal biological clocks that allow them to adapt to daily and yearly changes, such as day-night cycles or seasons turning. Unlike animals, however, plants cannot move when their environment becomes different, so they need to be able to weather these changes by adjusting which genes they switch on and off. To do this, plants keep track of how long days are using external cues such as light or temperature. One of the effects of climate change is that these cues become less reliable, making it harder for plants to adapt to their environment and survive. This is a potential problem for crop species, like Brassica rapa. This plant has many edible forms, including Chinese cabbage, oilseed, pak choi, and turnip. It is also a close relative of the well-studied model plant, Arabidopsis. Since evolving away from Arabidopsis, the genome of B. rapa tripled, meaning it has one, two, or three copies of each gene. This has allowed the extra gene copies to mutate and adapt to different purposes. The question is, what impact has this genome expansion had on the plant's biological clock? One way to find out is to perform RNA-sequencing experiments, which record the genes a plant is using at any one time. Here, Greenham, Sartor et al. report the results of a series of RNA-sequencing experiments performed every two hours across two days. Plants were first exposed to light-dark or temperature cycles and then samples were taken when the plants were in constant light and temperature. This revealed which genes B. rapa turned on and off in response to signals from the internal biological clock. It turns out that the biological clock of B. rapa controls close to three quarters of its genes. These genes showed distinct phases, increasing or decreasing in regular patterns. But the different copies of duplicated and triplicated genes did not necessarily all behave in the same way. Many of the copies had different rhythms, and some increased and decreased in patterns totally opposite to their counterparts. Not only did the daily patterns differ, but responses to stressors like drought were also altered. Comparing these patterns to the patterns seen in Arabidopsis revealed that often, one B. rapa gene behaved just like its Arabidopsis equivalent, while its copies had evolved new behaviors. The different behaviors of the copies of each gene in B. rapa relative to its biological clock allow this plant to grow in different environments with varying temperatures and day lengths. Understanding how these adaptations work opens new avenues of research into how plants detect and respond to environmental signals. This could help to guide future work into targeting genes to improve crop growth and stress resilience.

Chlorophyll fluorescence imaging captures photochemical efficiency of grain sorghum (Sorghum bicolor) in a field setting.

BACKGROUND: Photosynthesis is one of the most important biological reactions and forms the basis of crop productivity and yield on which a growing global population relies. However, to develop improved plant cultivars that are capable of increased productivity, methods that can accurately and quickly quantify photosynthetic efficiency in large numbers of genotypes under field conditions are needed. Chlorophyll fluorescence imaging is a rapid, non-destructive measurement that can provide insight into the efficiency of the light-dependent reactions of photosynthesis. RESULTS: To test and validate a field-deployed fluorescence imaging system on the TERRA-REF field scanalyzer, leaves of potted sorghum plants were treated with a photosystem II inhibitor, DCMU, to reduce photochemical efficiency (FV/FM). The ability of the fluorescence imaging system to detect changes in fluorescence was determined by comparing the image-derived values with a handheld fluorometer. This study demonstrated that the imaging system was able to accurately measure photochemical efficiency (FV/FM) and was highly correlated (r = 0.92) with the handheld fluorometer values. Additionally, the fluorescence imaging system was able to track the decrease in photochemical efficiency due to treatment of DCMU over a 7 day period. CONCLUSIONS: The system's ability to capture the temporal dynamics of the plants' response to this induced stress, which has comparable dynamics to abiotic and biotic stressors found in field environments, indicates the system is operating correctly. With the validation of the fluorescence imaging system, physiological and genetic studies can be undertaken that leverage the fluorescence imaging capabilities and throughput of the field scanalyzer.

Exceptional subgenome stability and functional divergence in the allotetraploid Ethiopian cereal teff.

Teff (Eragrostis tef) is a cornerstone of food security in the Horn of Africa, where it is prized for stress resilience, grain nutrition, and market value. Here, we report a chromosome-scale assembly of allotetraploid teff (variety Dabbi) and patterns of subgenome dynamics. The teff genome contains two complete sets of homoeologous chromosomes, with most genes maintaining as syntenic gene pairs. TE analysis allows us to estimate that the teff polyploidy event occurred ~1.1 million years ago (mya) and that the two subgenomes diverged ~5.0 mya. Despite this divergence, we detect no large-scale structural rearrangements, homoeologous exchanges, or biased gene loss, in contrast to many other allopolyploids. The two teff subgenomes have partitioned their ancestral functions based on divergent expression across a diverse expression atlas. Together, these genomic resources will be useful for accelerating breeding of this underutilized grain crop and for fundamental insights into polyploid genome evolution.

Time of day and network reprogramming during drought induced CAM photosynthesis in Sedum album.

Plants with facultative crassulacean acid metabolism (CAM) maximize performance through utilizing C3 or C4 photosynthesis under ideal conditions while temporally switching to CAM under water stress (drought). While genome-scale analyses of constitutive CAM plants suggest that time of day networks are shifted, or phased to the evening compared to C3, little is known for how the shift from C3 to CAM networks is modulated in drought induced CAM. Here we generate a draft genome for the drought-induced CAM-cycling species Sedum album. Through parallel sampling in well-watered (C3) and drought (CAM) conditions, we uncover a massive rewiring of time of day expression and a CAM and stress-specific network. The core circadian genes are expanded in S. album and under CAM induction, core clock genes either change phase or amplitude. While the core clock cis-elements are conserved in S. album, we uncover a set of novel CAM and stress specific cis-elements consistent with our finding of rewired co-expression networks. We identified shared elements between constitutive CAM and CAM-cycling species and expression patterns unique to CAM-cycling S. album. Together these results demonstrate that drought induced CAM-cycling photosynthesis evolved through the mobilization of a stress-specific, time of day network, and not solely the phasing of existing C3 networks. These results will inform efforts to engineer water use efficiency into crop plants for growth on marginal land.

Target Capture Sequencing Unravels Rubus Evolution.

Rubus (Rosaceae) comprises more than 500 species with additional commercially cultivated raspberries and blackberries. The most recent (> 100 years old) global taxonomic treatment of the genus defined 12 subgenera; two subgenera were subsequently described and some species were rearranged. Intra- and interspecific ploidy levels and hybridization make phylogenetic estimation of Rubus challenging. Our objectives were to estimate the phylogeny of 94 taxonomically and geographically diverse species and three cultivars using chloroplast DNA sequences and target capture of approximately 1,000 low copy nuclear genes; estimate divergence times between major Rubus clades; and examine the historical biogeography of species diversification. Target capture sequencing identified eight major groups within Rubus. Subgenus Orobatus and Subg. Anoplobatus were monophyletic, while other recognized subgenera were para- or polyphyletic. Multiple hybridization events likely occurred across the phylogeny at subgeneric levels, e.g., Subg. Rubus (blackberries) × Subg. Idaeobatus (raspberries) and Subg. Idaeobatus × Subg. Cylactis (Arctic berries) hybrids. The raspberry heritage within known cultivated blackberry hybrids was confirmed. The most recent common ancestor of the genus was most likely distributed in North America. Multiple distribution events occurred during the Miocene (about 20 Ma) from North America into Asia and Europe across the Bering land bridge and southward crossing the Panamanian Isthmus. Rubus species diversified greatly in Asia during the Miocene. Rubus taxonomy does not reflect phylogenetic relationships and subgeneric revision is warranted. The most recent common ancestor migrated from North America towards Asia, Europe, and Central and South America early in the Miocene then diversified. Ancestors of the genus Rubus may have migrated to Oceania by long distance bird dispersal. This phylogeny presents a roadmap for further Rubus systematics research. In conclusion, the target capture dataset provides high resolution between species though it also gave evidence of gene tree/species tree and cytonuclear discordance. Discordance may be due to hybridization or incomplete lineage sorting, rather than a lack of phylogenetic signal. This study illustrates the importance of using multiple phylogenetic methods when examining complex groups and the utility of software programs that estimate signal conflict within datasets.

A near complete, chromosome-scale assembly of the black raspberry (Rubus occidentalis) genome.

Background: The fragmented nature of most draft plant genomes has hindered downstream gene discovery, trait mapping for breeding, and other functional genomics applications. There is a pressing need to improve or finish draft plant genome assemblies. Findings: Here, we present a chromosome-scale assembly of the black raspberry genome using single-molecule real-time Pacific Biosciences sequencing and high-throughput chromatin conformation capture (Hi-C) genome scaffolding. The updated V3 assembly has a contig N50 of 5.1 Mb, representing an ∼200-fold improvement over the previous Illumina-based version. Each of the 235 contigs was anchored and oriented into seven chromosomes, correcting several major misassemblies. Black raspberry V3 contains 47 Mb of new sequences including large pericentromeric regions and thousands of previously unannotated protein-coding genes. Among the new genes are hundreds of expanded tandem gene arrays that were collapsed in the Illumina-based assembly. Detailed comparative genomics with the high-quality V4 woodland strawberry genome (Fragaria vesca) revealed near-perfect 1:1 synteny with dramatic divergence in tandem gene array composition. Lineage-specific tandem gene arrays in black raspberry are related to agronomic traits such as disease resistance and secondary metabolite biosynthesis. Conclusions: The improved resolution of tandem gene arrays highlights the need to reassemble these highly complex and biologically important regions in draft plant genomes. The updated, high-quality black raspberry reference genome will be useful for comparative genomics across the horticulturally important Rosaceae family and enable the development of marker assisted breeding in Rubus.

Climate-smart crops with enhanced photosynthesis.

The potential of enhanced photosynthetic efficiency to help achieve the sustainable yield increases required to meet future demands for food and energy has spurred intense research towards understanding, modeling, and engineering photosynthesis. These current efforts, largely focused on the C3 model Arabidopsis thaliana or crop plants (e.g. rice, sorghum, maize, and wheat), could be intensified and broadened using model systems closely related to our food, feed, and energy crops and that allow rapid design-build-test-learn cycles. In this outlooking Opinion, we advocate for a concerted effort to expand our understanding and improve our ability to redesign carbon uptake, allocation, and utilization. We propose two specific research directions that combine enhanced photosynthesis with climate-smart metabolic attributes: (i) engineering pathways for flexible (facultative) C3-C4 metabolism where plants will operate either C3 or C4 photosynthesis based on environmental conditions such as temperature, light, and atmospheric CO2 levels; and (ii) increasing rhizospheric sink strength for carbon utilization, including strategies that allow for augmented transport of carbon to the soil for improved soil properties and carbon storage without jeopardizing aboveground crop biomass. We argue that such ambitious undertakings be first approached and demonstrated by exploring the full genomic potential of two model grasses, the C3Brachypodium distachyon and the C4Setaria viridis. The development of climate-smart crops could provide novel and bold solutions to increase crop productivity while reducing atmospheric carbon and nitrogen emissions.

High density SNP mapping and QTL analysis for time of leaf budburst in Corylus avellana L.

The growing area of European hazelnut (Corylus avellana L.) is increasing, as well as the number of producing countries, and there is a pressing need for new improved cultivars. Hazelnut conventional breeding process is slow, due to the length of juvenile phase and the high heterozygosity level. The development of genetic linkage maps and the identification of molecular markers tightly linked to QTL (quantitative trait loci) of agronomic interest are essential tools for speeding up the selection of seedlings carrying desired traits through marker-assisted selection. The objectives of this study were to enrich a previous linkage map and confirm QTL related to time of leaf budburst, using an F1 population obtained by crossing Tonda Gentile delle Langhe with Merveille de Bollwiller. Genotyping-by-Sequencing was used to identify a total of 9,999 single nucleotide polymorphism markers. Well saturated linkage maps were constructed for each parent using the double pseudo-testcross mapping strategy. A reciprocal translocation was detected in Tonda Gentile delle Langhe between two non-homologous chromosomes. Applying a bioinformatic approach, we were able to disentangle 'pseudo-linkage' between markers, removing markers around the translocation breakpoints and obtain a linear order of the markers for the two chromosomes arms, for each linkage group involved in the translocation. Twenty-nine QTL for time of leaf budburst were identified, including a stably expressed region on LG_02 of the Tonda Gentile delle Langhe map. The stability of these QTL and their coding sequence content indicates promise for the identification of specific chromosomal regions carrying key genes involved in leaf budburst.