The haplotype-resolved T2T reference genome highlights structural variation underlying agronomic traits of melon

Melon(Cucumis melo L.)is an important vegetable crop that has an extensive history of cultivation.However,the genome of wild and semi-wild melon types that can be used for the analysis of agronomic traits is not yet available.Here we report a chromosome-level T2T genome assembly for 821(C.melo ssp.agrestis var.acidulus),a semi-wild melon with two haplotypes of∼373 Mb and∼364 Mb,respectively.Comparative genome analysis discovered a significant number of structural variants(SVs)between melo(C.melo ssp.melo)and agrestis(C.melo ssp.agrestis)genomes,including a copy number variation located in the ToLCNDV resistance locus on chromosome 11.Genome-wide association studies detected a significant signal associated with climacteric ripening and identified one candidate gene CM_ac12g14720.1(CmABA2),encoding a cytoplasmic short chain dehydrogenase/reductase,which controls the biosynthesis of abscisic acid.This study provides valuable genetic resources for future research on melon breeding.

Attention sports fans! The far-reaching contributions of bud sport mutants to horticulture and plant biology

A bud sport is a lateral shoot,inflorescence or single flower/fruit with a visibly different phenotype from the rest of the plant.The new phenotype is often caused by a stable somatic mutation in a single cell that is passed on to its clonal descendants and eventually populates part or all of a meristem.In many cases,a bud sport can be vegetatively propagated,thereby preserving the novel phenotype without sexual reproduction.Bud sports provide new characteristics while retaining the desirable qualities of the parent plant,which is why many bud sports have been developed into popular cultivars.We present an overview of the history of bud sports,the causes and methods of detecting somaclonal variation,and the types of mutant phenotypes that have arisen spontaneously.We focus on examples where the molecular or cytological changes causing the phenotype have been identified.Analysis of these sports has provided valuable insight into developmental processes,gene function and regulation,and in some cases has revealed new information about layer-specific roles of some genes.Examination of the molecular changes causing a phenotype and in some cases reversion back to the original state has contributed to our understanding of the mechanisms that drive genomic evolution.

Genetic dissection of climacteric fruit ripening in a melon population segregating for ripening behavior

Melon is as an alternative model to understand fruit ripening due to the coexistence of climacteric and non-climacteric varieties within the same species,allowing the study of the processes that regulate this complex trait with genetic approaches.We phenotyped a population of recombinant inbred lines(RILs),obtained by crossing a climacteric(Védrantais,cantalupensis type)and a non-climcteric variety(Piel de Sapo T111,inodorus type),for traits related to climacteric maturation and ethylene production.Individuals in the RIL population exhibited various combinations of phenotypes that differed in the amount of ethylene produced,the early onset of ethylene production,and other phenotypes associated with ripening.We characterized a major QTL on chromosome 8,ETHQV8.1,which is sufficient to activate climacteric ripening,and other minor QTLs that may modulate the climacteric response.The ETHQV8.1 allele was validated by using two reciprocal introgression line populations generated by crossing Védrantais and Piel de Sapo and analyzing the ETHQV8.1 region in each of the genetic backgrounds.A Genome-wide association study(GWAS)using 211 accessions of the ssp.melo further identified two regions on chromosome 8 associated with the production of aromas,one of these regions overlapping with the 154.1 kb interval containing ETHQV8.1.The ETHQV8.1 region contains several candidate genes that may be related to fruit ripening.This work sheds light into the regulation mechanisms of a complex trait such as fruit ripening.

Almond population genomics and non-additive GWAS reveal new insights into almond dissemination history and candidate genes for nut traits and blooming time

Domestication drastically changed crop genomes,fixing alleles of interest and creating different genetic populations.Genome-wide association studies(GWASs)are a powerful tool to detect these alleles of interest(and so QTLs).In this study,we explored the genetic structure as well as additive and non-additive genotype-phenotype associations in a collection of 243 almond accessions.Our genetic structure analysis strongly supported the subdivision of the accessions into five ancestral groups,all formed by accessions with a common origin.One of these groups was formed exclusively by Spanish accessions,while the rest were mainly formed by accessions from China,Italy,France,and the USA.These results agree with archaeological and historical evidence that separate modern almond dissemination into four phases:Asiatic,Mediterranean,Californian,and southern hemisphere.In total,we found 13 independent QTLs for nut weight,crack-out percentage,double kernels percentage,and blooming time.Of the 13 QTLs found,only one had an additive effect.Through candidate gene analysis,we proposed Prudul26A013473 as a candidate gene responsible for the main QTL found in crack-out percentage,Prudul26A012082 and Prudul26A017782 as candidate genes for the QTLs found in double kernels percentage,and Prudul26A000954 as a candidate gene for the QTL found in blooming time.Our study enhances our knowledge of almond dissemination history and will have a great impact on almond breeding.

An integrated approach for increasing breeding efficiency in apple and peach in Europe

Despite the availability of whole genome sequences of apple and peach,there has been a considerable gap between genomics and breeding.To bridge the gap,the European Union funded the FruitBreedomics project(March 2011 to August 2015)involving 28 research institutes and private companies.Three complementary approaches were pursued:(i)tool and software development,(ii)deciphering genetic control of main horticultural traits taking into account allelic diversity and(iii)developing plant materials,tools and methodologies for breeders.Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding,development of new,dense SNP arrays in apple and peach,new phenotypic methods for some complex traits,software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis(PBA).This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies(GWAS)on several European genebank collections.FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities.Through FruitBreedomics,significant progresses were made in the field of apple and peach breeding,genetics,genomics and bioinformatics of which advantage will be made by breeders,germplasm curators and scientists.A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public.This review covers the scientific discoveries made in this major endeavour,and perspective in the apple and peach breeding and genomics in Europe and beyond.

The apple REFPOP—a reference population for genomics-assisted breeding in apple

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates.Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs,and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions.Here we present an apple reference population:the apple REFPOP,a large collection formed of 534 genotypes planted in six European countries,as a unique tool to accelerate apple breeding.The population consisted of 269 accessions and 265 progeny from 27 parental combinations,representing the diversity in cultivated apple and current European breeding material,respectively.A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95.Based on the genotypic data,linkage disequilibrium was low and population structure was weak.Two well-studied phenological traits of horticultural importance were measured.We found marker–trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date,respectively.With decreasing SNP density,the detection of significant marker–trait associations varied depending on trait architecture.Regardless of the trait,10,000 SNPs sufficed to maximize genomic prediction ability.We confirm the suitability of the apple REFPOP design for genomics-assisted breeding,especially for breeding programs using related germplasm,and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.

Fine mapping and identification of candidate genes for the peach powdery mildew resistance gene Vr3

Powdery mildew is one of the major diseases of peach(Prunus persica),caused by the ascomycete Podosphaera pannosa.Currently,it is controlled through calendar-based fungicide treatments starting at petal fall,but an alternative is to develop resistant peach varieties.Previous studies mapped a resistance gene(Vr3)in interspecific populations between almond(‘Texas’)and peach(‘Earlygold’).To obtain molecular markers highly linked to Vr3 and to reduce the number of candidate genes,we fine-mapped Vr3 to a genomic region of 270 kb with 27 annotated genes.To find evidence supporting one of these positional candidate genes as being responsible of Vr3,we analyzed the polymorphisms of the resequences of both parents and used near-isogenic lines(NILs)for expression analysis of the positional candidate genes in symptomatic or asymptomatic leaves.Genes differentially expressed between resistant and susceptible individuals were annotated as a Disease Resistance Protein RGA2(Prupe2G111700)or an Eceriferum 1 protein involved in epicuticular wax biosynthesis(Prupe2G112800).Only Prupe2G111700 contained a variant predicted to have a disruptive effect on the encoded protein,and was overexpressed in both heterozygous and homozygous individuals containing the Vr3 almond allele,compared with susceptible individuals.This information was also useful to identify and validate molecular markers tightly linked and flanking Vr3.In addition,the NILs used in this work will facilitate the introgression of this gene into peach elite materials,alone or pyramided with other known resistance genes such as peach powdery mildew resistance gene Vr2.

Corrigendum to “Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry”

In the article titled“Automatic Fruit Morphology Phenome and Genetic Analysis:An Application in the Octoploid Strawberry”[1],some funding information was omitted.The funding DOI“10.13039/501100011033”was missing.The corrected Acknowledgements section is provided below.

GenoDrawing:An Autoencoder Framework for Image Prediction from SNP Markers

Advancements in genome sequencing have facilitated whole-genome characterization of numerous plant species,providing an abundance of genotypic data for genomic analysis.Genomic selection and neural networks(NNs),particularly deep learning,have been developed to predict complex traits from dense genotypic data.Autoencoders,an NN model to extract features from images in an unsupervised manner,has proven to be useful for plant phenotyping.This study introduces an autoencoder framework,GenoDrawing,for predicting and retrieving apple images from a low-depth single-nucleotide polymorphism(SNP)array,potentially useful in predicting traits that are difficult to define.GenoDrawing demonstrates proficiency in its task using a small dataset of shape-related SNPs.Results indicate that the use of SNPs associated with visual traits has substantial impact on the generated images,consistent with biological interpretation.While using substantial SNPs is crucial,incorporating additional,unrelated SNPs results in performance degradation for simple NN architectures that cannot easily identify the most important inputs.The proposed GenoDrawing method is a practical framework for exploring genomic prediction in fruit tree phenotyping,particularly beneficial for small to medium breeding companies to predict economically substantial heritable traits.Although GenoDrawing has limitations,it sets the groundwork for future research in image prediction from genomic markers.Future studies should focus on using stronger models for image reproduction,SNP information extraction,and dataset balance in terms of phenotypes for more precise outcomes.

Mechanical and natural ventilation systems in a greenhouse designed using computational fluid dynamics

The aim of this study was to analyse air exchange and temperature distribution in a greenhouse with combined mechanical and natural ventilation and to design more efficient mechanical ventilation systems.For this purpose,a computational fluid dynamics(CFD)model of the greenhouse was used.Three configurations were considered:Configuration 1(mechanical ventilation and closed roof ventilators),Configurations 2 and 3(mechanical ventilation and roof ventilators open 30%and 100%,respectively).After validation,the CFD model was used to improve the design of the greenhouse mechanical ventilation system in each of the three configurations analyzed.Four greenhouse lengths,28 m,50 m,75 m and 100 m,were used in the simulations.Compared to fan ventilation only,roof ventilation improved the climate of fan-ventilated greenhouses in terms of the air exchange rate(22%)and climate uniformity because the internal air was mixed better than with mechanical ventilation only.As the greenhouse length increased,more advantages were achieved with natural ventilation compared to mechanical ventilation.For most configurations,there was a strong linear correlation between temperature gradient and greenhouse length.The greenhouse whose regression line had the steepest slope was the one with closed roof ventilators.Increasing the fan capacity produced a general reduction in temperature,but the effect was less intense for the greenhouses with open roof ventilators.Compared to box inlet ventilators,an enlarged continuous inlet in the wall opposite the fans increased overall system performance because it eliminated backflow recirculation zones,which are prone to produce high temperatures.

Automatic Fruit Morphology Phenome and Genetic Analysis:An Application in the Octoploid Strawberry

Automatizing phenotype measurement will decisively contribute to increase plant breeding efficiency.Among phenotypes,morphological traits are relevant in many fruit breeding programs,as appearance influences consumer preference.Often,these traits are manually or semiautomatically obtained.Yet,fruit morphology evaluation can be enhanced using fully automatized procedures and digital images provide a cost-effective opportunity for this purpose.Here,we present an automatized pipeline for comprehensive phenomic and genetic analysis of morphology traits extracted from internal and external strawberry(Fragaria x ananassa)images.The pipeline segments,classifies,and labels the images and extracts conformation features,including linear(area,perimeter,height,width,circularity,shape descriptor,ratio between height and width)and multivariate(Fourier elliptical components and Generalized Procrustes)statistics.Internal color patterns are obtained using an autoencoder to smooth out the image.In addition,we develop a variational autoencoder to automatically detect the most likely number of underlying shapes.Bayesian modeling is employed to estimate both additive and dominance effects for all traits.As expected,conformational traits are clearly heritable.Interestingly,dominance variance is higher than the additive component for most of the traits.Overall,we show that fruit shape and color can be quickly and automatically evaluated and are moderately heritable.Although we study strawberry images,the algorithm can be applied to other fruits,as shown in the GitHub repository.