Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate

Genetic parameter changes and age-age correlations in Pinus koraiensis growth over 40-year progeny testing

BACKGROUND

Early selection in tree breeding could be achieved by addressing the longevity of tree improvement activities. Genetic parameter changes and age-age correlations are essential for determining the optimal timing of early selection. Practical tracking of genetic parameters of Pinus koraiensis, a major timber species with economic and ecological value, has become feasible as its progeny testing has entered the mid-term age in Korea. However, research on the age-age correlation of P. koraiensis as progeny trials approach rotation age is limited. This study aimed to investigate genetic parameter trends and age-age correlations in P. koraiensis progeny. P. koraiensis progeny were assessed at two sites using a linear mixed-effects model with two-dimensional spatial autoregressive structure. Height, diameter, and volume growth were measured in 11 assessments over 40 years.

RESULTS

Genetic parameters, such as height and diameter, showed different patterns of change. The heritability ranged for the three growth traits in 0.083-0.710, 0.288-0.781, and 0.299-0.755 across the sites and age. Height heritability and its coefficient of variance decreased, whereas the diameter and volume estimates remained relatively constant. Correlations with Age 40 for phenotypic, genetic, and rank of breeding values ranged between 0.16 and 0.92, 0.594 and 0.988, and 0.412 and 0.965, respectively. These correlations generally increased as the age approached Age 40, with particularly high levels observed at Age 26 and Age 30.

CONCLUSION

The observed genetic trends in P. koraiensis progeny testing offer valuable insights for early and precise selection. Notably, selecting superior genotypes at Ages 26-30 is supported by discernible genetic gains and robust correlations. Future research should integrate unbalanced data for selecting mother trees or families and conduct a comprehensive economic analysis of early selection to validate its practical benefits.

Efficient genomics-based 'end-to-end' selective tree breeding framework

Since their initiation in the 1950s, worldwide selective tree breeding programs followed the recurrent selection scheme of repeated cycles of selection, breeding (mating), and testing phases and essentially remained unchanged to accelerate this process or address environmental contingencies and concerns. Here, we introduce an "end-to-end" selective tree breeding framework that: (1) leverages strategically preselected GWAS-based sequence data capturing trait architecture information, (2) generates unprecedented resolution of genealogical relationships among tested individuals, and (3) leads to the elimination of the breeding phase through the utilization of readily available wind-pollinated (OP) families. Individuals' breeding values generated from multi-trait multi-site analysis were also used in an optimum contribution selection protocol to effectively manage genetic gain/co-ancestry trade-offs and traits' correlated response to selection. The proof-of-concept study involved a 40-year-old spruce OP testing population growing on three sites in British Columbia, Canada, clearly demonstrating our method's superiority in capturing most of the available genetic gains in a substantially reduced timeline relative to the traditional approach. The proposed framework is expected to increase the efficiency of existing selective breeding programs, accelerate the start of new programs for ecologically and environmentally important tree species, and address climate-change caused biotic and abiotic stress concerns more effectively.

Optimization of In Vitro Embryo Rescue and Development of a Kompetitive Allele-Specific PCR (KASP) Marker Related to Stenospermocarpic Seedlessness in Grape (Vitis vinifera L.)

Seedlessness is one of the highest valued agronomic traits in grapes. Embryo rescue in combination with marker-assisted selection have been widely applied in seedless grape breeding due to the advantages of increasing the ratio of seedless progenies and shortening the breeding cycle. However, the large number of deformed seedlings produced during embryo rescue and the lack of fast, efficient, and low-cost markers severely inhibit the process of seedless grape breeding. In this study, a total of eighty-three grape cultivars (51 seedless and 32 seeded) with diverse genetic backgrounds and two populations derived from embryo rescue, including 113 F1 hybrid individuals (60 seedless and 53 seeded), were utilized. We screened suitable media for converting malformed seedlings into normal seedlings, analyzed the association between the SNP in VviAGL11 and seeded/seedless phenotype, and developed a KASP marker related to stenospermocarpic seedlessness. Our results indicated that the transformation rate of 37.8% was obtained with MS medium supplemented with 2.0 mg·L-1 of 6-BA and 0.5 mg·L-1 of IBA. The presence of an A nucleotide allele at position chr18:26889437 was further confirmed to be fully associated with the stenospermocarpic seedlessness phenotype. The developed KASP marker, based on the verified SNP locus in VviAGL11, successfully distinguished the seedless and seeded genotypes with high precision and throughput. The results will contribute to enhancing the efficiency of embryo rescue and facilitate parent selection and early selection of seedless offspring with molecular markers, thereby accelerating the breeding process in seedless table grapes.

Comparative transcriptomics reveals divergence in pathogen response gene families amongst 20 forest tree species

Forest trees provide critical ecosystem services for humanity that are under threat due to ongoing global change. Measuring and characterizing genetic diversity are key to understanding adaptive potential and developing strategies to mitigate negative consequences arising from climate change. In the area of forest genetic diversity, genetic divergence caused by large-scale changes at the chromosomal level has been largely understudied. In this study, we used the RNA-seq data of 20 co-occurring forest trees species from genera including Acer, Alnus, Amelanchier, Betula, Cornus, Corylus, Dirca, Fraxinus, Ostrya, Populus, Prunus, Quercus, Ribes, Tilia, and Ulmus sampled from Upper Peninsula of Michigan. These data were used to infer the origin and maintenance of gene family variation, species divergence time, as well as gene family expansion and contraction. We identified a signal of common whole genome duplication events shared by core eudicots. We also found rapid evolution, namely fast expansion or fast contraction of gene families, in plant-pathogen interaction genes amongst the studied diploid species. Finally, the results lay the foundation for further research on the genetic diversity and adaptive capacity of forest trees, which will inform forest management and conservation policies.

Comparative Analysis of Transposable Elements in Strawberry Genomes of Different Ploidy Levels

Transposable elements (TEs) make up a large portion of plant genomes and play a vital role in genome structure, function, and evolution. Cultivated strawberry (Fragaria x ananassa) is one of the most important fruit crops, and its octoploid genome was formed through several rounds of genome duplications from diploid ancestors. Here, we built a pan-genome TE library for the Fragaria genus using ten published strawberry genomes at different ploidy levels, including seven diploids, one tetraploid, and two octoploids, and performed comparative analysis of TE content in these genomes. The TEs comprise 51.83% (F. viridis) to 60.07% (F. nilgerrensis) of the genomes. Long terminal repeat retrotransposons (LTR-RTs) are the predominant TE type in the Fragaria genomes (20.16% to 34.94%), particularly in F. iinumae (34.94%). Estimating TE content and LTR-RT insertion times revealed that species-specific TEs have shaped each strawberry genome. Additionally, the copy number of different LTR-RT families inserted in the last one million years reflects the genetic distance between Fragaria species. Comparing cultivated strawberry subgenomes to extant diploid ancestors showed that F. vesca and F. iinumae are likely the diploid ancestors of the cultivated strawberry, but not F. viridis. These findings provide new insights into the TE variations in the strawberry genomes and their roles in strawberry genome evolution.

A first draft genome of holm oak (Quercus ilex subsp. ballota), the most representative species of the Mediterranean forest and the Spanish agrosylvopastoral ecosystem "dehesa"

The holm oak (Quercus ilex subsp. ballota) is the most representative species of the Mediterranean Basin and the agrosylvopastoral Spanish "dehesa" ecosystem. Being part of our life, culture, and subsistence since ancient times, it has significant environmental and economic importance. More recently, there has been a renewed interest in using the Q. ilex acorn as a functional food due to its nutritional and nutraceutical properties. However, the holm oak and its related ecosystems are threatened by different factors, with oak decline syndrome and climate change being the most worrying in the short and medium term. Breeding programs informed by the selection of elite genotypes seem to be the most plausible biotechnological solution to rescue populations under threat. To achieve this and other downstream analyses, we need a high-quality and well-annotated Q. ilex reference genome. Here, we introduce the first draft genome assembly of Q. ilex using long-read sequencing (PacBio). The assembled nuclear haploid genome had 530 contigs totaling 842.2 Mbp (N50 = 3.3 Mbp), of which 448.7 Mb (53%) were repetitive sequences. We annotated 39,443 protein-coding genes of which 94.80% were complete and single-copy genes. Phylogenetic analyses showed no evidence of a recent whole-genome duplication, and high synteny of the 12 chromosomes between Q. ilex and Quercus lobata and between Q. ilex and Quercus robur. The chloroplast genome size was 142.3 Kbp with 149 protein-coding genes successfully annotated. This first draft should allow for the validation of omics data as well as the identification and functional annotation of genes related to phenotypes of interest such as those associated with resilience against oak decline syndrome and climate change and higher acorn productivity and nutraceutical value.

Comprehensive Time-Course Transcriptome Reveals the Crucial Biological Pathways Involved in the Seasonal Branch Growth in Siberian Elm (Ulmus pumila)

Timber, the most prevalent organic material on this planet, is the result of a secondary xylem emerging from vascular cambium. Yet, the intricate processes governing its seasonal generation are largely a mystery. To better understand the cyclic growth of vascular tissues in elm, we undertook an extensive study examining the anatomy, physiology, and genetic expressions in Ulmus pumila. We chose three robust 15-year-old elm trees for our study. The cultivars used in this study were collected from the Inner Mongolia Autonomous Region in China and nurtured in the tree farm of Shandong Normal University. Monthly samples of 2-year-old elm branches were taken from the tree from February to September. Marked seasonal shifts in elm branch vascular tissues were observed by phenotypic observation: In February, the cambium of the branch emerged from dormancy, spurring growth. By May, elms began generating secondary xylem, or latewood, recognized by its tiny pores and dense cell structure. From June to August, there was a marked increase in the thickness of the secondary xylem. Transcriptome sequencing provides a potential molecular mechanism for the thickening of elm branches and their response to stress. In February, the tree enhanced its genetic responses to cold and drought stress. The amplified expression of CDKB, CYCB, WOX4, and ARF5 in the months of February and March reinforced their essential role in the development of the vascular cambium in elm. Starting in May, the elm deployed carbohydrates as a carbon resource to synthesize the abundant cellulose and lignin necessary for the formation of the secondary wall. Major genes participating in cellulose (SUC and CESA homologs), xylan (UGD, UXS, IRX9, IRX10, and IRX14), and lignin (PAL, C4H, 4CL, HCT, C3H, COMT, and CAD) biosynthetic pathways for secondary wall formation were up-regulated by May or/and June. In conclusion, our findings provided a foundation for an in-depth exploration of the molecular processes dictating the seasonal growth of elm timber.

Identifying genetic variation associated with environmental gradients and drought-tolerance phenotypes in ponderosa pine

As climate changes, understanding the genetic basis of local adaptation in plants becomes an ever more pressing issue. Combining genotype-environment association (GEA) with genotype-phenotype association (GPA) analysis has an exciting potential to uncover the genetic basis of environmental responses. We use these approaches to identify genetic variants linked to local adaptation to drought in Pinus ponderosa. Over 4 million Single Nucleotide Polymorphisms (SNPs) were identified using 223 individuals from across the Sierra Nevada of California. 927,740 (22.3%) SNPs were retained after filtering for proximity to genes and used in our association analyses. We found 1374 associated with five major climate variables, with the largest number (1151) associated with April 1st snowpack. We also conducted a greenhouse study with various drought-tolerance traits measured in first-year seedlings of a subset of the genotyped trees grown in the greenhouse. 796 SNPs were associated with control-condition trait values, while 1149 were associated with responsiveness of these traits to drought. While no individual SNPs were associated with both the environmental variables and the measured traits, several annotated genes were associated with both, particularly those involved in cell wall formation, biotic and abiotic stress responses, and ubiquitination. However, the functions of many of the associated genes have not yet been determined due to the lack of gene annotation information for conifers. Future studies are needed to assess the developmental roles and ecological significance of these unknown genes.

Identification of Two Flip-Over Genes in Grass Family as Potential Signature of C4 Photosynthesis Evolution

In flowering plants, C4 photosynthesis is superior to C3 type in carbon fixation efficiency and adaptation to extreme environmental conditions, but the mechanisms behind the assembly of C4 machinery remain elusive. This study attempts to dissect the evolutionary divergence from C3 to C4 photosynthesis in five photosynthetic model plants from the grass family, using a combined comparative transcriptomics and deep learning technology. By examining and comparing gene expression levels in bundle sheath and mesophyll cells of five model plants, we identified 16 differentially expressed signature genes showing cell-specific expression patterns in C3 and C4 plants. Among them, two showed distinctively opposite cell-specific expression patterns in C3 vs. C4 plants (named as FOGs). The in silico physicochemical analysis of the two FOGs illustrated that C3 homologous proteins of LHCA6 had low and stable pI values of ~6, while the pI values of LHCA6 homologs increased drastically in C4 plants Setaria viridis (7), Zea mays (8), and Sorghum bicolor (over 9), suggesting this protein may have different functions in C3 and C4 plants. Interestingly, based on pairwise protein sequence/structure similarities between each homologous FOG protein, one FOG PGRL1A showed local inconsistency between sequence similarity and structure similarity. To find more examples of the evolutionary characteristics of FOG proteins, we investigated the protein sequence/structure similarities of other FOGs (transcription factors) and found that FOG proteins have diversified incompatibility between sequence and structure similarities during grass family evolution. This raised an interesting question as to whether the sequence similarity is related to structure similarity during C4 photosynthesis evolution.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Association Mapping and Expression Analysis of the Genes Involved in the Wood Formation of Poplar

Xylogenesis is a complex and sequential biosynthetic process controlled by polygenes. Deciphering the genetic architecture of this complex quantitative trait could provide valuable information for increasing wood biomass and improving its properties. Here, we performed genomic resequencing of 64 24-year-old trees (64 hybrids of section Aigeiros and their parents) grown in the same field and conducted full-sib family-based association analyses of two growth and six woody traits using GEMMA as a choice of association model selection. We identified 1342 significantly associated single nucleotide polymorphisms (SNPs), 673 located in the region upstream and downstream of 565 protein-encoding genes. The transcriptional regulation network of secondary cell wall (SCW) biosynthesis was further constructed based on the published data of poplar miRNA, transcriptome, and degradome. These provided a certain scientific basis for the in-depth understanding of the mechanism of poplar timber formation and the molecular-assisted breeding in the future.

The role of forests in the EU climate policy: are we on the right track?

BACKGROUND

The European Union (EU) has committed to achieve climate neutrality by 2050. This requires a rapid reduction of greenhouse gas (GHG) emissions and ensuring that any remaining emissions are balanced through CO₂ removals. Forests play a crucial role in this plan: they are currently the main option for removing CO₂ from the atmosphere and additionally, wood use can store carbon durably and help reduce fossil emissions. To stop and reverse the decline of the forest carbon sink, the EU has recently revised the regulation on land use, land-use change and forestry (LULUCF), and set a target of - 310 Mt CO₂e net removals for the LULUCF sector in 2030.

RESULTS

In this study, we clarify the role of common concepts in forest management - net annual increment, harvest and mortality - in determining the forest sink. We then evaluate to what extent the forest sink is on track to meet the climate goals of the EU. For this assessment we use data from the latest national GHG inventories and a forest model (Carbon Budget Model). Our findings indicate that on the EU level, the recent decrease in increment and the increase in harvest and mortality are causing a rapid drop in the forest sink. Furthermore, continuing the past forest management practices is projected to further decrease the sink. Finally, we discuss options for enhancing the sinks through forest management while taking into account adaptation and resilience.

CONCLUSIONS

Our findings show that the EU forest sink is quickly developing away from the EU climate targets. Stopping and reversing this trend requires rapid implementation of climate-smart forest management, with improved and more timely monitoring of GHG fluxes. This enhancement is crucial for tracking progress towards the EU's climate targets, where the role of forests has become - and is expected to remain - more prominent than ever before.

Investigation of mutation load and rate in androgenic mutant lines of rapeseed in early generations evaluated by high-density SNP genotyping

Oilseed rape (Brassica napus) is an important oil crop distributed worldwide with a broad adaptation to different climate zones. The cultivation of rapeseed is one of the most commercially viable areas in crop production. Altogether 269,093 ha of rapeseed are cultivated in Kazakhstan. However, all rapeseed cultivars and lines cultivated in Kazakhstan on an industrial scale predominantly belong to the foreign breeding system. Therefore, the formation of a diverse genetic pool for breeding new, highly productive cultivars adopted to the environmental conditions of Kazakhstan is the most important goal in country selection programs. In this work, we have developed ethyl methanesulfonate (EMS) doubled haploid mutant lines from plant material of cultivars 'Galant' and 'Kris' to broad diversity of rapeseed in Kazakhstan. The development of mutant lines was performed via embryo callusogenesis or embryo secondary callusogenesis. Mutants were investigated by Brassica90k SNP array, and we were able to locate 24,657 SNPs from 26,256 SNPs filtered by quality control on the genome assembly (Bra_napus_v2.0). Only 18,831 SNPs were assigned to the available annotated genomic features. The most frequent combination of mutations according to reference controls was adenine with guanine (70%), followed by adenine with cytosine (28.8%), and only minor fractions were cytosine with guanine (0.54%) and adenine with thymine (0.59%). We revealed 5606.27 markers for 'Kris' and 4893.01 markers for 'Galant' by mutation occurrence. Most mutation occurrences were occupied by double mutations where progenitors and offspring were homozygous by different alleles, enabling the selection of appropriate genotypes in a short period of time. Regarding the biological impact of mutations, 861 variants were reported as having a low predicted impact, with 1042 as moderate and 121 as high; all others were reported as belonging to non-coding sequences, intergenic regions, and other features with the effect of modifiers. Protein encoding genes, such as wall-associated receptor kinase-like protein 5, TAO1-like disease resistance protein, receptor-like protein 12, and At5g42460-like F-box protein, contained more than two variable positions, with an impact on their biological activities. Nevertheless, the obtained mutant lines were able to survive and reproduce. Mutant lines, which include moderate and high impact mutations in encoding genes, are a perfect pool not only for MAS but also for the investigation of the fundamental basis of protein functions. For the first time, a collection of mutant lines was developed in our country to improve the selection of local rapeseed cultivars.

Evolution and Expression Patterns of the Fructose 1,6-Bisphosptase Gene Family in a Miracle Tree (Neolamarckia cadamba)

Neolamarckia cadamba (N. cadamba) is a fast-growing tree species with tremendous economic and ecological value; the study of the key genes regulating photosynthesis and sugar accumulation is very important for the breeding of N. cadamba. Fructose 1,6-bisphosptase (FBP) gene has been found to play a key role in plant photosynthesis, sugar accumulation and other growth processes. However, no systemic analysis of FBPs has been reported in N. cadamba. A total of six FBP genes were identifed and cloned based on the N. cadamba genome, and these FBP genes were sorted into four groups. The characteristics of the NcFBP gene family were analyzed such as phylogenetic relationships, gene structures, conserved motifs, and expression patterns. A cis-acting element related to circadian control was first found in the promoter region of FBP gene. Phylogenetic and quantitative real-time PCR analyses showed that NcFBP5 and NcFBP6 may be chloroplast type 1 FBP and cytoplasmic FBP, respectively. FBP proteins from N. cadamba and 22 other plant species were used for phylogenetic analyses, indicating that FBP family may have expanded during the evolution of algae to mosses and differentiated cpFBPase1 proteins in mosses. This work analyzes the internal relationship between the evolution and expression of the six NcFBPs, providing a scientific basis for the evolutionary pattern of plant FBPs, and promoting the functional studies of FBP genes.

Improving Coconut Using Modern Breeding Technologies: Challenges and Opportunities

Coconut (Cocos nucifera L.) is a perennial palm with a wide range of distribution across tropical islands and coastlines. Multitude use of coconut by nature is important in the socio-economic fabric framework among rural smallholders in producing countries. It is a major source of income for 30 million farmers, while 60 million households rely on the coconut industry directly as farm workers and indirectly through the distribution, marketing, and processing of coconut and coconut-based products. Stagnant production, inadequate planting materials, the effects of climate change, as well as pests and diseases are among the key issues that need to be urgently addressed in the global coconut industry. Biotechnology has revolutionized conventional breeding approaches in creating genetic variation for trait improvement in a shorter period of time. In this review, we highlighted the challenges of current breeding strategies and the potential of biotechnological approaches, such as genomic-assisted breeding, next-generation sequencing (NGS)-based genotyping and genome editing tools in improving the coconut. Also, combining these technologies with high-throughput phenotyping approaches and speed breeding could speed up the rate of genetic gain in coconut breeding to solve problems that have been plaguing the industry for decades.

Genome–Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome–environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat–based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change.

“I shall endeavor to find out how nature’s forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature” Alexander von Humboldt—Letter to Karl Freiesleben, June 1799.

Genetic variability for vigor and yield of robusta coffee (Coffea canephora) clones in Ghana

Effectiveness of plant improvement programs, especially in perennial crops like coffee, may be improved by knowing the level of genetic variation which exist within a breeding population coupled with the knowledge of estimates of genetic parameters for key agronomic traits. Thus, this study was conducted to evaluate C. canephora clones for growth (stem diameter, number of laterals and span) and yield traits; estimate genetic parameters of these traits; and determine the phenotypic and genetic associations between these traits to guide future crop improvement efforts. The productivity of 56 coffee clones was assessed from 2012 to 2020 in a clonal experiment planted in a randomized complete block design with three replicates. Each plot consisted of eight plants spaced at 2 × 3 m at the Cocoa Research Institute of Ghana. There were significant (p < 0.001) differences among clones for all the traits assessed. Broad sense heritability was low-to-moderate for all the traits evaluated with the highest (0.34) observed for cumulative yield (CY). Cumulative yield was genetically correlated (p < 0.001) with span and number of laterals (NOL). For the growth traits, NOL was the most strongly associated with CY (r_g = 0.49, p < 0.001). The results revealed that selection based on early years’ yield (MY1) could be as effective as selection based on CY (r_g = 0.87, p < 0.001). Our findings indicate that there is significant genetic variation among the test clones for the parameters assessed and presents a good opportunity for future variety development.

A Machine-Learning Method to Assess Growth Patterns in Plants of the Family Lemnaceae

Numerous new technologies have been implemented in image analysis methods that help researchers draw scientific conclusions from biological phenomena. Plants of the family Lemnaceae (duckweeds) are the smallest flowering plants in the world, and biometric measurements of single plants and their growth rate are highly challenging. Although the use of software for digital image analysis has changed the way scientists extract phenomenological data (also for studies on duckweeds), the procedure is often not wholly automated and sometimes relies on the intervention of a human operator. Such a constraint can limit the objectivity of the measurements and generally slows down the time required to produce scientific data. Herein lies the need to implement image analysis software with artificial intelligence that can substitute the human operator. In this paper, we present a new method to study the growth rates of the plants of the Lemnaceae family based on the application of machine-learning procedures to digital image analysis. The method is compared to existing analogical and computer-operated procedures. The results showed that our method drastically reduces the time consumption of the human operator while retaining a high correlation in the growth rates measured with other procedures. As expected, machine-learning methods applied to digital image analysis can overcome the constraints of measuring growth rates of very small plants and might help duckweeds gain worldwide attention thanks to their strong nutritional qualities and biological plasticity.

Delving the Role of Caralluma fimbriata: An Edible Wild Plant to Mitigate the Biomarkers of Metabolic Syndrome

Metabolic syndrome (MS), commonly known as syndrome X or insulin resistance syndrome, is a collection of risk factors for cardiovascular diseases and type II diabetes. MS is believed to impact over a billion individuals worldwide. It is a medical condition defined by visceral obesity, insulin resistance, high blood pressure, and abnormal cholesterol levels, according to the World Health Organization. The current dietary trends are more focused on the use of functional foods and nutraceuticals that are well known for their preventive and curative role against such pathological disorders. Caralluma fimbriata is one such medicinal plant that is gaining popularity. It is a wild, edible, succulent roadside shrub with cactus-like leaves. Besides its main nutrient contents, various bioactive constituents have been identified and linked with positive health outcomes of appetite-suppressing, hypolipidemic, antioxidant, hepatoprotective, and anticancer potentials. Hence, such properties make C. fimbriata an invaluable plant against MS. The current review compiles recent available literature on C. fimbriata's nutritional composition, safety parameters, and therapeutic potential for MS. Summarized data in this review reveals that C. fimbriata remains a neglected plant with limited food and therapeutic applications. Yet various studies explored here do prove its positive health-ameliorating outcomes.

Genome-Wide Identification of the LHC Gene Family in Kiwifruit and Regulatory Role of AcLhcb3.1/3.2 for Chlorophyll a Content

Light-harvesting chlorophyll a/b-binding (LHC) protein is a superfamily that plays a vital role in photosynthesis. However, the reported knowledge of LHCs in kiwifruit is inadequate and poorly understood. In this study, we identified 42 and 45 LHC genes in Actinidia chinensis (Ac) and A. eriantha (Ae) genomes. Phylogenetic analysis showed that the kiwifruit LHCs of both species were grouped into four subfamilies (Lhc, Lil, PsbS, and FCII). Expression profiles and qRT-PCR results revealed expression levels of LHC genes closely related to the light, temperature fluctuations, color changes during fruit ripening, and kiwifruit responses to Pseudomonas syringae pv. actinidiae (Psa). Subcellular localization analysis showed that AcLhcb1.5/3.1/3.2 were localized in the chloroplast while transient overexpression of AcLhcb3.1/3.2 in tobacco leaves confirmed a significantly increased content of chlorophyll a. Our findings provide evidence of the characters and evolution patterns of kiwifruit LHCs genes in kiwifruit and verify the AcLhcb3.1/3.2 genes controlling the chlorophyll a content.

JAZ1-3 and MYC2-1 Synergistically Regulate the Transformation from Completely Mixed Flower Buds to Female Flower Buds in Castanea mollisima

Chestnut (Castanea mollisima) is an important woody food crop, but its yield has been low in cultivation, mainly due to the problems of fewer female flowers and more male flowers. Therefore, regulating the transition of chestnut flowers and effectively balancing the proportion of male and female to improve the yield are key factor to be solved in production. In this study, the chestnut floral buds in pre- and post-winter were used as materials. The data of metabolites, hormones, and gene expression during flower bud differentiation of chestnut were analyzed by transcriptomics and metabolomics to preliminarily reveal the possible reason of male and female flower bud transformation in pre- and post-winter. The analysis of Differentially Expressed Genes (DEGs) showed that there were 6323 DEGs in the Complete mixed flower bud (CMF) group in pre- and post-winter, of which 3448 genes were up-regulated and 2875 genes were down-regulated. There were 8037 DEGs in the Incomplete mixed flower bud (IMF) in pre- and post-winter, of which 4546 genes were up-regulated and 3491 genes were down-regulated. A total of 726 genes from the two flower buds were enriched into 251 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in post winter, of which plant hormone signal transduction accounted for 4.13%. The analysis results of differential metabolites showed that the differential metabolites of the two flower buds were mainly concentrated in the secondary metabolic synthesis pathway. The difference of hormone content showed that the content of Gibberellin 9 (GA9) and GA19 in CMF was higher than that in IMF in pre-winter, but the opposite in post-winter. Methyl jasmonate (MeJA) content was only very high in CMF in pre-winter, while Jasmonoyl-(l)-Isoleucine (JA-ILE) showed high content in CMF in post-winter. In post-winter, higher concentration of JA-ILE was positively correlated with the expression of Flowering Locus T (CmFT), and CmFT gene was significantly positively correlated with the expression levels of MYC2-1, MYC2-2 and LFY 3 (LEAFY 3). The higher concentration of JA-ILE was negatively correlated with the transcription level of JAZ1-3. In vitro experiments further verified that Jasmonate-Zim 1–3 (JAZ 1–3) combined with MYC2-1 inhibited the transcription of CmFT gene, while MYC2-1 alone promoted the expression of FT. The results suggested that a higher concentration of GA is conducive to breaking the dormancy of flower buds and promoting the development of male flower buds, while a lower concentration of GA and a higher concentration of JA-ILE are conducive to the differentiation and formation of female flower buds in post-winter, in which JAZ1-3 and MYC2-1 play a key role in the differentiation of female flower buds of chestnut.

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

Identification of Genomic Regions Associated with Vine Growth and Plant Height of Soybean

Vining growth (VG) and high plant height (PH) are the physiological traits of wild soybean that preclude their utilization for domesticated soybean breeding and improvement. To identify VG- and PH-related quantitative trait loci (QTLs) in different genetic resources, two populations of recombinant inbred lines (RILs) were developed by crossing a cultivated soybean, Zhonghuang39 (ZH39), with two wild soybean accessions, NY27-38 and NY36-87. Each line from the two crosses was evaluated for VG and PH. Three QTLs for VG and three for PH, detected in the ZH39 × NY27-38 population of the RILs, co-located on chromosomes 2, 17 and 19. The VG- and PH-related QTL in the ZH39 × NY36-87 population co-located on chromosome 19. A common QTL shared by the two populations was located on chromosome 19, suggesting that this major QTL was consistently selected for in different genetic backgrounds. The results suggest that different loci are involved in the domestication or adaptations of soybean of various genetic backgrounds. The molecular markers presented here would benefit the fine mapping and cloning of candidate genes underlying the VG and PH co-localized regions and thus facilitate the utilization of wild resources in breeding by avoiding undesirable traits.

Chasing genetic correlation breakers to stimulate population resilience to climate change

Global climate change introduces new combinations of environmental conditions, which is expected to increase stress on plants. This could affect many traits in multiple ways that are as yet unknown but will likely require the modification of existing genetic relationships among functional traits potentially involved in local adaptation. Theoretical evolutionary studies have determined that it is an advantage to have an excess of recombination events under heterogeneous environmental conditions. Our study, conducted on a population of radiata pine (Pinus radiata D. Don), was able to identify individuals that show high genetic recombination at genomic regions, which potentially include pleiotropic or collocating QTLs responsible for the studied traits, reaching a prediction accuracy of 0.80 in random cross-validation and 0.72 when whole family was removed from the training population and predicted. To identify these highly recombined individuals, a training population was constructed from correlation breakers, created through tandem selection of parents in the previous generation and their consequent mating. Although the correlation breakers showed lower observed heterogeneity possibly due to direct selection in both studied traits, the genomic regions with statistically significant differences in the linkage disequilibrium pattern showed higher level of heretozygosity, which has the effect of decomposing unfavourable genetic correlation. We propose undertaking selection of correlation breakers under current environmental conditions and using genomic predictions to increase the frequency of these ’recombined’ individuals in future plantations, ensuring the resilience of planted forests to changing climates. The increased frequency of such individuals will decrease the strength of the population-level genetic correlations among traits, increasing the opportunity for new trait combinations to be developed in the future.

Whole Transcriptome Sequencing Unveils the Genomic Determinants of Putative Somaclonal Variation in Mint (Mentha L.)

Mint (Mentha L., Lamiaceae) is a strongly scented herb of the family Lamiaceae that is grown mostly by clonal propagation, making it a valuable species for the study of somaclonal variation and its phenotypic consequences. The recent introduction of a few species of mint in South America, followed by a presumably rampant propagation, make this region particularly ideal for studying the extent of somaclonal genetic diversity. Hence, the objective of this work was to offer a preliminary characterization of somaclonal genetically coding diversity of the mint in the northern Andes in order to address the question of whether somaclonal variants may have emerged despite relatively recent introductions in a region where mint is not native. A total of 29 clonally propagated specimens, collected in mint export farms in the province of Antioquia, a major region for mint production in the northwest Andes of Colombia, were genotyped using RNA sequencing (RNA-Seq). SNP calling was carried out from the leaves’ transcriptome profiles of each plant by combining the GATK4 and TRINITY protocols, obtaining a total of 2033 loci across 912 transcripts with a minimum read depth of 20X and 4% of missing data. Unsupervised machine learning algorithms considered the K-means, AGNES and UPGMA approaches, all of which suggested three genetic clusters for M. spicata and a unique cluster for M. × piperita. The results indicate that at least two different origins of M. spicata reached the eastern region of the Antioquia province, clonally propagated in the locality ever since for local consumption and export. One of these ancestries had more population structure, possibly due to environmental or anthropological pressures that intervened in the fragmentation of this genetic group or to a higher somaclonal mutation rate. This work offers a first step into the study of the accumulation and transmission of presumably quasi-neutral somatic mutations at coding regions in an herbaceous clonally propagated scented species such as mint, likely favored by an expected population expansion after its Andean introduction. These ad hoc hypotheses warrant further study as part of future research.

Deciphering Pleiotropic Signatures of Regulatory SNPs in Zea mays L. Using Multi-Omics Data and Machine Learning Algorithms

Maize is one of the most widely grown cereals in the world. However, to address the challenges in maize breeding arising from climatic anomalies, there is a need for developing novel strategies to harness the power of multi-omics technologies. In this regard, pleiotropy is an important genetic phenomenon that can be utilized to simultaneously enhance multiple agronomic phenotypes in maize. In addition to pleiotropy, another aspect is the consideration of the regulatory SNPs (rSNPs) that are likely to have causal effects in phenotypic development. By incorporating both aspects in our study, we performed a systematic analysis based on multi-omics data to reveal the novel pleiotropic signatures of rSNPs in a global maize population. For this purpose, we first applied Random Forests and then Markov clustering algorithms to decipher the pleiotropic signatures of rSNPs, based on which hierarchical network models are constructed to elucidate the complex interplay among transcription factors, rSNPs, and phenotypes. The results obtained in our study could help to understand the genetic programs orchestrating multiple phenotypes and thus could provide novel breeding targets for the simultaneous improvement of several agronomic traits.

Comparative Transcriptomic Analysis Provides Insight into the Key Regulatory Pathways and Differentially Expressed Genes in Blueberry Flower Bud Endo- and Ecodormancy Release

Endodormancy is the stage that perennial plants must go through to prepare for the next seasonal cycle, and it is also an adaptation that allows plants to survive harsh winters. Blueberries (Vaccinium spp.) are known to have high nutritional and commercial value. To better understand the molecular mechanisms of bud dormancy release, the transcriptomes of flower buds from the southern highbush blueberry variety “O’Neal” were analyzed at seven time points of the endo- and ecodormancy release processes. Pairwise comparisons were conducted between adjacent time points; five kinds of phytohormone were identified via these processes. A total of 12,350 differentially expressed genes (DEGs) were obtained from six comparisons. Gene Ontology analysis indicated that these DEGs were significantly involved in metabolic processes and catalytic activity. KEGG pathway analysis showed that these DEGs were predominantly mapped to metabolic pathways and the biosynthesis of secondary metabolites in endodormancy release, but these DEGs were significantly enriched in RNA transport, plant hormone signal transduction, and circadian rhythm pathways in the process of ecodormancy release. The contents of abscisic acid (ABA), salicylic acid (SA), and 1-aminocyclopropane-1-carboxylate (ACC) decreased in endo- and ecodormancy release, and the jasmonic acid (JA) level first decreased in endodormancy release and then increased in ecodormancy release. Weighted correlation network analysis (WGCNA) of transcriptomic data associated with hormone contents generated 25 modules, 9 of which were significantly related to the change in hormone content. The results of this study have important reference value for elucidating the molecular mechanism of flower bud dormancy release.

Improving lodgepole pine genomic evaluation using spatial correlation structure and SNP selection with single-step GBLUP

Modeling environmental spatial heterogeneity can improve the efficiency of forest tree genomic evaluation. Furthermore, genotyping costs can be lowered by reducing the number of markers needed. We investigated the impact on variance components, breeding value accuracy, and bias of two phenotypic data adjustments (experimental design and autoregressive spatial models), and a relationship matrix calculated from a subset of markers selected for their ability to infer ancestry. Using a multiple-trait multiple-site single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) approach, four scenarios (2 phenotype adjustments × 2 marker sets) were applied to diameter at breast height (DBH), height (HT), and resistance to western gall rust (WGR) in four open-pollinated progeny trials of lodgepole pine, with 1490 (out of 11,188) trees genotyped with 25,099 SNPs. As a control, we fitted the conventional ABLUP model using pedigree information. The highest heritability estimates were achieved for the ABLUP followed closely by the ssGBLUP with the full marker set and using the spatial phenotype adjustments. The highest predictive ability was obtained by using a reduced marker subset (8000 SNPs) when either the spatial (DBH: 0.429, and WGR: 0.513) or design (HT: 0.467) phenotype corrections were used. No significant difference was detected in prediction bias among the six fitted models, and all values were close to 1 (0.918-1.014). Results demonstrated that selecting informative markers, such as those capturing ancestry, can improve the predictive ability. The use of spatial correlation structure increased traits' heritability and reduced prediction bias, while increases in predictive ability were trait-dependent.

From Genome Sequencing to CRISPR-Based Genome Editing for Climate-Resilient Forest Trees

Due to the economic and ecological importance of forest trees, modern breeding and genetic manipulation of forest trees have become increasingly prevalent. The CRISPR-based technology provides a versatile, powerful, and widely accepted tool for analyzing gene function and precise genetic modification in virtually any species but remains largely unexplored in forest species. Rapidly accumulating genetic and genomic resources for forest trees enabled the identification of numerous genes and biological processes that are associated with important traits such as wood quality, drought, or pest resistance, facilitating the selection of suitable gene editing targets. Here, we introduce and discuss the latest progress, opportunities, and challenges of genome sequencing and editing for improving forest sustainability.

Inheritance of Yield Components and Morphological Traits in Avocado cv. Hass From "Criollo" "Elite Trees" via Half-Sib Seedling Rootstocks

Grafting induces precocity and maintains clonal integrity in fruit tree crops. However, the complex rootstock × scion interaction often precludes understanding how the tree phenotype is shaped, limiting the potential to select optimum rootstocks. Therefore, it is necessary to assess (1) how seedling progenies inherit trait variation from elite 'plus trees', and (2) whether such family superiority may be transferred after grafting to the clonal scion. To bridge this gap, we quantified additive genetic parameters (i.e., narrow sense heritability-h ², and genetic-estimated breeding values-GEBVs) across landraces, "criollo", "plus trees" of the super-food fruit tree crop avocado (Persea americana Mill.), and their open-pollinated (OP) half-sib seedling families. Specifically, we used a genomic best linear unbiased prediction (G-BLUP) model to merge phenotypic characterization of 17 morpho-agronomic traits with genetic screening of 13 highly polymorphic SSR markers in a diverse panel of 104 avocado "criollo" "plus trees." Estimated additive genetic parameters were validated at a 5-year-old common garden trial (i.e., provenance test), in which 22 OP half-sib seedlings from 82 elite "plus trees" served as rootstocks for the cv. Hass clone. Heritability (h ²) scores in the "criollo" "plus trees" ranged from 0.28 to 0.51. The highest h ² values were observed for ribbed petiole and adaxial veins with 0.47 (CI 95%0.2-0.8) and 0.51 (CI 0.2-0.8), respectively. The h ² scores for the agronomic traits ranged from 0.34 (CI 0.2-0.6) to 0.39 (CI 0.2-0.6) for seed weight, fruit weight, and total volume, respectively. When inspecting yield variation across 5-year-old grafted avocado cv. Hass trees with elite OP half-sib seedling rootstocks, the traits total number of fruits and fruits' weight, respectively, exhibited h ² scores of 0.36 (± 0.23) and 0.11 (± 0.09). Our results indicate that elite "criollo" "plus trees" may serve as promissory donors of seedling rootstocks for avocado cv. Hass orchards due to the inheritance of their outstanding trait values. This reinforces the feasibility to leverage natural variation from "plus trees" via OP half-sib seedling rootstock families. By jointly estimating half-sib family effects and rootstock-mediated heritability, this study promises boosting seedling rootstock breeding programs, while better discerning the consequences of grafting in fruit tree crops.

Evolutionary Genetics of Crop-Wild Complexes

Since Darwin's time, the role of crop wild relatives (CWR), landraces, and cultivated genepools in shaping plant diversity and boosting food resources has been a major question [...].

Phylogenomic and Microsynteny Analysis Provides Evidence of Genome Arrangements of High-Affinity Nitrate Transporter Gene Families of Plants

Nitrate transporter 2 (NRT2) and NRT3 or nitrate-assimilation-related 2 (NAR2) proteins families form a two-component, high-affinity nitrate transport system, which is essential for the acquisition of nitrate from soils with low N availability. An extensive phylogenomic analysis across land plants for these families has not been performed. In this study, we performed a microsynteny and orthology analysis on the NRT2 and NRT3 genes families across 132 plants (Sensu lato) to decipher their evolutionary history. We identified significant differences in the number of sequences per taxonomic group and different genomic contexts within the NRT2 family that might have contributed to N acquisition by the plants. We hypothesized that the greater losses of NRT2 sequences correlate with specialized ecological adaptations, such as aquatic, epiphytic, and carnivory lifestyles. We also detected expansion on the NRT2 family in specific lineages that could be a source of key innovations for colonizing contrasting niches in N availability. Microsyntenic analysis on NRT3 family showed a deep conservation on land plants, suggesting a high evolutionary constraint to preserve their function. Our study provides novel information that could be used as guide for functional characterization of these gene families across plant lineages.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Fab Advances in Fabaceae for Abiotic Stress Resilience: From 'Omics' to Artificial Intelligence

Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely impacted. Our limited understanding of genetic determinants and novel variants associated with the abiotic stress response in food legume crops restricts its amelioration. Therefore, it is imperative to understand different molecular approaches in food legume crops that can be utilized in crop improvement programs to minimize the economic loss. 'Omics'-based molecular breeding provides better opportunities over conventional breeding for diversifying the natural germplasm together with improving yield and quality parameters. Due to molecular advancements, the technique is now equipped with novel 'omics' approaches such as ionomics, epigenomics, fluxomics, RNomics, glycomics, glycoproteomics, phosphoproteomics, lipidomics, regulomics, and secretomics. Pan-omics-which utilizes the molecular bases of the stress response to identify genes (genomics), mRNAs (transcriptomics), proteins (proteomics), and biomolecules (metabolomics) associated with stress regulation-has been widely used for abiotic stress amelioration in food legume crops. Integration of pan-omics with novel omics approaches will fast-track legume breeding programs. Moreover, artificial intelligence (AI)-based algorithms can be utilized for simulating crop yield under changing environments, which can help in predicting the genetic gain beforehand. Application of machine learning (ML) in quantitative trait loci (QTL) mining will further help in determining the genetic determinants of abiotic stress tolerance in pulses.

Integrative Pre-Breeding for Biotic Resistance in Forest Trees

Climate change is unleashing novel biotic antagonistic interactions for forest trees that may jeopardize populations' persistence. Therefore, this review article envisions highlighting major opportunities from ecological evolutionary genomics to assist the identification, conservation, and breeding of biotic resistance in forest tree species. Specifically, we first discuss how assessing the genomic architecture of biotic stress resistance enables us to recognize a more polygenic nature for a trait typically regarded Mendelian, an expectation from the Fisherian runaway pathogen-host concerted arms-race evolutionary model. Secondly, we outline innovative pipelines to capture and harness natural tree pre-adaptations to biotic stresses by merging tools from the ecology, phylo-geography, and omnigenetics fields within a predictive breeding platform. Promoting integrative ecological genomic studies promises a better understanding of antagonistic co-evolutionary interactions, as well as more efficient breeding utilization of resistant phenotypes.

Induced Genetic Variations in Fruit Trees Using New Breeding Tools: Food Security and Climate Resilience

Fruit trees provide essential nutrients to humans by contributing to major agricultural outputs and economic growth globally. However, major constraints to sustainable agricultural productivity are the uncontrolled proliferation of the population, and biotic and abiotic stresses. Tree mutation breeding has been substantially improved using different physical and chemical mutagens. Nonetheless, tree plant breeding has certain crucial bottlenecks including a long life cycle, ploidy level, occurrence of sequence polymorphisms, nature of parthenocarpic fruit development and linkage. Genetic engineering of trees has focused on boosting quality traits such as productivity, wood quality, and resistance to biotic and abiotic stresses. Recent technological advances in genome editing provide a unique opportunity for the genetic improvement of woody plants. This review examines application of the CRISPR-Cas system to reduce disease susceptibility, alter plant architecture, enhance fruit quality, and improve yields. Examples are discussed of the contemporary CRISPR-Cas system to engineer easily scorable PDS genes, modify lignin, and to alter the flowering onset, fertility, tree architecture and certain biotic stresses.

Molecular Cloning, Transcriptional Profiling, Subcellular Localization, and miRNA-Binding Site Analysis of Six SCL9 Genes in Poplar

The SCL9 subfamily is a key member of the GRAS family that regulates plant development and stress responses. Nevertheless, the functional role of these genes in the growth and development of poplar still unclear. Here, we reported the six SCL9 genes, which were found to be differentially expressed during poplar adventitious root formation. The full-length sequences of PeSCL9 genes of ‘Nanlin895’ poplar (Populus deltoids × Populus euramericana) were cloned by the RACE technique All PeSCL9 genes lacked introns. RT-qPCR revealed that PeSCL9 genes displayed a dynamic expression pattern in the adventitious root of poplar, according to RT-qPCR data. A series of comprehensive genes characteristics analysis were carried out for six genes by bioinformation. Meanwhile, transient expression analysis of the Populus protoplasts showed that all the PeSCL9 proteins were localized in the nucleus. In addition, the degradome and sRNA of ‘Nanlin895’ poplar in combination were used to predict miRNAs that regulate PeSCL9. It was found that miR396a and miR396c may affect PeSCL9 expression via cleavage, which was further verified by a transient expression experiment in Populus protoplasts. Overall, the development of poplar adventitious root and other tissues was closely related to these six SCL9 genes, and they serve as a starting point for further research into the mechanisms regulating poplar growth and development.

Overexpression Populus d-Type Cyclin Gene PsnCYCD1;1 Influences Cell Division and Produces Curved Leaf in Arabidopsis thaliana

d-type cyclins (CYCDs) are a special class of cyclins and play extremely important roles in plant growth and development. In the plant kingdom, most of the existing studies on CYCDs have been done on herbaceous plants, with few on perennial woody plants. Here, we identified a Populus&nbsp;d-type cyclin gene, PsnCYCD1;1, which is mainly transcribed in leaf buds and stems. The promoter of PsnCYCD1;1 activated GUS gene expression and transgenic Arabidopsis lines were strongly GUS stained in whole seedlings and mature anthers. Moreover, subcellular localization analysis showed the fluorescence signal of PsnCYCD1;1-GFP fusion protein is present in the nucleus. Furthermore, overexpression of the PsnCYCD1;1 gene in Arabidopsis can promote cell division and lead to small cell generation and cytokinin response, resulting in curved leaves and twisted inflorescence stems. Moreover, the transcriptional levels of endogenous genes, such as ASs, KNATs, EXP10, and PHB, were upregulated by PsnCYCD1;1. Together, our results indicated that PsnCYCD1;1 participates in cell division by cytokinin response, providing new information on controlling plant architecture in woody plants.

Harnessing Crop Wild Diversity for Climate Change Adaptation

Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.

Allelic Diversity at Abiotic Stress Responsive Genes in Relationship to Ecological Drought Indices for Cultivated Tepary Bean, Phaseolus acutifolius A. Gray, and Its Wild Relatives

Some of the major impacts of climate change are expected in regions where drought stress is already an issue. Grain legumes are generally drought susceptible. However, tepary bean and its wild relatives within Phaseolus acutifolius or P. parvifolius are from arid areas between Mexico and the United States. Therefore, we hypothesize that these bean accessions have diversity signals indicative of adaptation to drought at key candidate genes such as: Asr2, Dreb2B, and ERECTA. By sequencing alleles of these genes and comparing to estimates of drought tolerance indices from climate data for the collection site of geo-referenced, tepary bean accessions, we determined the genotype x environmental association (GEA) of each gene. Diversity analysis found that cultivated and wild P. acutifolius were intermingled with var. tenuifolius and P. parvifolius, signifying that allele diversity was ample in the wild and cultivated clade over a broad sense (sensu lato) evaluation. Genes Dreb2B and ERECTA harbored signatures of directional selection, represented by six SNPs correlated with the environmental drought indices. This suggests that wild tepary bean is a reservoir of novel alleles at genes for drought tolerance, as expected for a species that originated in arid environments. Our study corroborated that candidate gene approach was effective for marker validation across a broad genetic base of wild tepary accessions.

The Genetic Basis of Tomato Aroma

Tomato (Solanum lycopersicum L.) aroma is determined by the interaction of volatile compounds (VOCs) released by the tomato fruits with receptors in the nose, leading to a sensorial impression, such as "sweet", "smoky", or "fruity" aroma. Of the more than 400 VOCs released by tomato fruits, 21 have been reported as main contributors to the perceived tomato aroma. These VOCs can be grouped in five clusters, according to their biosynthetic origins. In the last decades, a vast array of scientific studies has investigated the genetic component of tomato aroma in modern tomato cultivars and their relatives. In this paper we aim to collect, compare, integrate and summarize the available literature on flavour-related QTLs in tomato. Three hundred and 5ifty nine (359) QTLs associated with tomato fruit VOCs were physically mapped on the genome and investigated for the presence of potential candidate genes. This review makes it possible to (i) pinpoint potential donors described in literature for specific traits, (ii) highlight important QTL regions by combining information from different populations, and (iii) pinpoint potential candidate genes. This overview aims to be a valuable resource for researchers aiming to elucidate the genetics underlying tomato flavour and for breeders who aim to improve tomato aroma.

Evaluation of Responsivity to Drought Stress Using Infrared Thermography and Chlorophyll Fluorescence in Potted Clones of Cryptomeria japonica

As climate change progresses, the breeding of drought-tolerant forest trees is necessary. Breeding drought-tolerant trees requires screening for drought stress using a large number of individuals and a high-throughput phenotyping method. The aim of this study was therefore to establish high-throughput methods for evaluating the clonal stress responses to drought stress using infrared thermography and chlorophyll fluorescence methods in Cryptomeria japonica. The stomatal conductance index (Ig), maximum photochemical quantum yield of photosystem II (Fv/Fm), and axial growth of four plus-tree clones of C. japonica planted in pots were measured weekly for 85 days after irrigation was stopped. The phenotypic trait responsivity to drought stress was estimated by a nonlinear mixed model and by introducing the cumulative water index, which considers the past history of the soil water environment. These methods and procedures enabled us to evaluate the clonal stress responses in C. japonica and could be applied to large-scale clone materials to promote the breeding program for drought tolerance.

Enviromic Assembly Increases Accuracy and Reduces Costs of the Genomic Prediction for Yield Plasticity in Maize

Quantitative genetics states that phenotypic variation is a consequence of the interaction between genetic and environmental factors. Predictive breeding is based on this statement, and because of this, ways of modeling genetic effects are still evolving. At the same time, the same refinement must be used for processing environmental information. Here, we present an "enviromic assembly approach," which includes using ecophysiology knowledge in shaping environmental relatedness into whole-genome predictions (GP) for plant breeding (referred to as enviromic-aided genomic prediction, E-GP). We propose that the quality of an environment is defined by the core of environmental typologies and their frequencies, which describe different zones of plant adaptation. From this, we derived markers of environmental similarity cost-effectively. Combined with the traditional additive and non-additive effects, this approach may better represent the putative phenotypic variation observed across diverse growing conditions (i.e., phenotypic plasticity). Then, we designed optimized multi-environment trials coupling genetic algorithms, enviromic assembly, and genomic kinships capable of providing in-silico realization of the genotype-environment combinations that must be phenotyped in the field. As proof of concept, we highlighted two E-GP applications: (1) managing the lack of phenotypic information in training accurate GP models across diverse environments and (2) guiding an early screening for yield plasticity exerting optimized phenotyping efforts. Our approach was tested using two tropical maize sets, two types of enviromics assembly, six experimental network sizes, and two types of optimized training set across environments. We observed that E-GP outperforms benchmark GP in all scenarios, especially when considering smaller training sets. The representativeness of genotype-environment combinations is more critical than the size of multi-environment trials (METs). The conventional genomic best-unbiased prediction (GBLUP) is inefficient in predicting the quality of a yet-to-be-seen environment, while enviromic assembly enabled it by increasing the accuracy of yield plasticity predictions. Furthermore, we discussed theoretical backgrounds underlying how intrinsic envirotype-phenotype covariances within the phenotypic records can impact the accuracy of GP. The E-GP is an efficient approach to better use environmental databases to deliver climate-smart solutions, reduce field costs, and anticipate future scenarios.

Inheritance of Rootstock Effects in Avocado (Persea americana Mill.) cv. Hass

Grafting is typically utilized to merge adapted seedling rootstocks with highly productive clonal scions. This process implies the interaction of multiple genomes to produce a unique tree phenotype. However, the interconnection of both genotypes obscures individual contributions to phenotypic variation (rootstock-mediated heritability), hampering tree breeding. Therefore, our goal was to quantify the inheritance of seedling rootstock effects on scion traits using avocado (Persea americana Mill.) cv. Hass as a model fruit tree. We characterized 240 diverse rootstocks from 8 avocado cv. Hass orchards with similar management in three regions of the province of Antioquia, northwest Andes of Colombia, using 13 microsatellite markers simple sequence repeats (SSRs). Parallel to this, we recorded 20 phenotypic traits (including morphological, biomass/reproductive, and fruit yield and quality traits) in the scions for 3 years (2015-2017). Relatedness among rootstocks was inferred through the genetic markers and inputted in a "genetic prediction" model to calculate narrow-sense heritabilities (h 2) on scion traits. We used three different randomization tests to highlight traits with consistently significant heritability estimates. This strategy allowed us to capture five traits with significant heritability values that ranged from 0.33 to 0.45 and model fits (r) that oscillated between 0.58 and 0.73 across orchards. The results showed significance in the rootstock effects for four complex harvest and quality traits (i.e., total number of fruits, number of fruits with exportation quality, and number of fruits discarded because of low weight or thrips damage), whereas the only morphological trait that had a significant heritability value was overall trunk height (an emergent property of the rootstock-scion interaction). These findings suggest the inheritance of rootstock effects, beyond root phenotype, on a surprisingly wide spectrum of scion traits in "Hass" avocado. They also reinforce the utility of polymorphic SSRs for relatedness reconstruction and genetic prediction of complex traits. This research is, up to date, the most cohesive evidence of narrow-sense inheritance of rootstock effects in a tropical fruit tree crop. Ultimately, our work highlights the importance of considering the rootstock-scion interaction to broaden the genetic basis of fruit tree breeding programs while enhancing our understanding of the consequences of grafting.