Candidate genes conferring ethylene-response in cultivated peanuts determined by BSA-seq and fine-mapping

Ethylene plays essential roles in plant growth,development and stress responses.The ethylene signaling pathway and molecular mechanism have been studied extensively in Arabidopsis and rice but limited in peanuts.Here,we established a sand-culture method to screen pingyangmycin mutagenized peanut lines based on their specific response to ethylene(“triple response”).An ethylene-insensitive mutant,inhibition of peanut hypocotyl elongation 1(iph1),was identified that showed reduced sensitivity to ethylene in both hypocotyl elongation and root growth.Through bulked segregant analysis sequencing,a major gene related to iph1,named AhIPH1,was preliminarily mapped at the chromosome Arahy.01,and further narrowed to a 450-kb genomic region through substitution mapping strategy.A total of 7014 genes were differentially expressed among the ACC treatment through RNA-seq analysis,of which only the Arahy.5BLU0Q gene in the candidate mapping interval was differentially expressed between WT and mutant iph1.Integrating sequence variations,functional annotation and transcriptome analysis revealed that a predicated gene,Arahy.5BLU0Q,encoding SNF1 protein kinase,may be the candidate gene for AhIPH1.This gene contained two single-nucleotide polymorphisms at promoter region and was more highly expressed in iph1 than WT.Our findings reveal a novel ethylene-responsive gene,which provides a theoretical foundation and new genetic resources for the mechanism of ethylene signaling in peanuts.

Trehalose:A sugar molecule involved in temperature stress management in plants

Trehalose(Tre)is a non-reducing disaccharide found in many species,including bacteria,fungi,invertebrates,yeast,and even plants,where it acts as an osmoprotectant,energy source,or protein/membrane protector.Despite relatively small amounts in plants,Tre concentrations increase following exposure to abiotic stressors.Trehalose-6-phosphate,a precursor of Tre,has regulatory functions in sugar metabolism,crop production,and stress tolerance.Among the various abiotic stresses,temperature extremes(heat or cold stress)are anticipated to impact crop production worldwide due to ongoing climate changes.Applying small amounts of Tre can mitigate negative physiological,metabolic,and molecular responses triggered by temperature stress.Trehalose also interacts with other sugars,osmoprotectants,amino acids,and phytohormones to regulate metabolic reprogramming that underpins temperature stress adaptation.Transformed plants expressing Tre-synthesis genes accumulate Tre and show improved stress tolerance.Genome-wide studies of Tre-encoding genes suggest roles in plant growth,development,and stress tolerance.This review discusses the functions of Tre in mitigating temperature stress—highlighting genetic engineering approaches to modify Tre metabolism,crosstalk,and interactions with other molecules—and in-silico approaches for identifying novel Tre-encoding genes in diverse plant species.We consider how this knowledge can be used to develop temperature-resilient crops essential for sustainable agriculture.

Development of an Agrobacterium-mediated CRISPR/Cas9 system in pea(Pisum sativum L.)

Pea(Pisum sativum L.)is an annual cool-season legume crop.Owing to its role in sustainable agriculture as both a rotation and a cash crop,its global market is expanding and increased production is urgently needed.For both technical and regulatory reasons,neither conventional nor transgenic breeding techniques can keep pace with the demand for increased production.In answer to this challenge,CRISPR/Cas9 genome editing technology has been gaining traction in plant biology and crop breeding in recent years.However,there are currently no reports of the successful application of the CRISPR/Cas9 genome editing technology in pea.We developed a transient transformation system of hairy roots,mediated by Agrobacterium rhizogenes strain K599,to validate the efficiency of a CRISPR/Cas9 system.Further optimization resulted in an efficient vector,PsU6.3-tRNA-PsPDS3-en35S-PsCas9.We used this optimized CRISPR/Cas9 system to edit the pea phytoene desaturase(PsPDS)gene,causing albinism,by Agrobacterium-mediated genetic transformation.This is the first report of successful generation of gene-edited pea plants by this route.

Abiotic stress tolerance:Genetics,genomics,and breeding

1.Tenth anniversary of The Crop Journal The Crop Journal will be 10 years old in October 2023.The journal is sponsored by the Crop Science Society of China,the Institute of Crop Sciences,Chinese Academy of Agricultural Sciences,and China Science Publishing&Media Group Ltd.(Science Press).It is published by Science Press and Ke Ai (founded by China Science Publishing&Media Ltd.and Elsevier).

Advances in the functional study of glutamine synthetase in plant abiotic stress tolerance response

Plant glutamine synthetase(GS,EC6.3.1.2)catalyzes the synthesis of glutamine from glutamate and ammonium ions and acts as a key enzyme in the nitrogen metabolic pathway in organisms.Nitrogen is an essential element for plant growth and development and plays an important role in crop yield and quality formation.Therefore,GS is crucial in many physiological processes in plants.Currently,nitrogen regulation by GS in plants is well-studied in terms of its effect on plant growth and development.This article reviews the regulatory role of plant GS and its molecular mechanism in mitigating stress injury,such as low or high temperature,salinity,drought and oxidation.The function of plant GS in stress tolerance response is focused.The review aims to provide a reference for the utilization of plant GS in crop stress tolerance breeding.

Non-escaping frost tolerant QTL linked genetic loci at reproductive stage in six wheat DH populations

Reproductive stage frost poses a major constraint for wheat production in countries such as Australia.However,little progress has been made in identifying key genes to overcome the constraint.In the present study,a severe frost event hit two large-scale field trials consisting of six doubled haploid(DH)wheat populations at reproductive stage(young microspore stage)in Western Australia,leading to the identification of 30 robust frost QTL on 17 chromosomes.The major 18 QTL with the phenotype variation over 9.5%were located on 13 chromosomes including 2 A,2 B,2 D,3 A,4 A,4 B,4 D,5 A,5 D,6 D,7 A,7 B and7 D.Most frost QTL were closely linked to the QTL of anthesis,maturity,Zadok stages as well as linked to anthesis related genes.Out of those,six QTL were repetitively detected on the homologous regions on 2 B,4 B,4 D,5 A,5 D,7 A in more than two populations.Results showed that the frost damage is associated with alleles of Vrn-A1 a,Vrn-D1 a,Rht-B1 b,Rht-D1 b,and the high copy number of Ppd-B1.However,anthesis QTL and anthesis related genes of Vrn-B1 a and Ta FT3-1 B on chromosomes 5 B and 1 B did not lead to frost damage,indicating that these early-flowering phenotype related genes are compatible with frost tolerance and thus can be utilised in breeding.Our results also indicate that wild-type alleles Rht-B1 a and Rht-D1 a can be used when breeding for frost-tolerant varieties without delaying flowering time.

Fast integration and accumulation of beneficial breeding alleles through an AB–NAMIC strategy in wheat

Wheat(Triticum aestivum)is among the most important staple crops for safeguarding the food security of the growing world population.To bridge the gap between genebank diversity and breeding programs,we developed an advanced backcross-nested association mapping plus inter-crossed population(AB-NAMIC)by crossing three popular wheat cultivars as recurrent founders to 20 germplasm lines from a mini core collection.Selective backcrossing combined with selection against undesirable traits and extensive crossing within and between sub-populations created new opportunities to detect unknown genes and increase the frequency of beneficial alleles in the AB-NAMIC population.We performed phenotyping of 590 AB-NAMIC lines and a natural panel of 476 cultivars for six consecutive growing seasons and genotyped these 1066 lines with a 660K SNP array.Genome-wide association studies of both panels for plant development and yield traits demonstrated improved power to detect rare alleles and loci with medium genetic effects in AB-NAMIC.Notably,genome-wide association studies in AB-NAMIC detected the candidate gene TaSWEET6-7B(TraesCS7B03G1216700),which has high homology to the rice SWEET6b gene and exerts strong effects on adaptation and yield traits.The commercial release of two derived AB-NAMIC lines attests to its direct applicability in wheat improvement.Valuable information on genome-wide association studymapping,candidate genes,and their haplotypes for breeding traits are available through WheatGAB.Our research provides an excellent framework for fast-tracking exploration and accumulation of beneficial alleles stored in genebanks.

Deep learning based classification of sheep behaviour from accelerometer data with imbalance

Classification of sheep behaviour from a sequence of tri-axial accelerometer data has the potential to enhance sheep management.Sheep behaviour is inherently imbalanced(e.g.,more ruminating than walking)resulting in underperforming classification for the minority activities which hold importance.Existing works have not addressed class imbalance and use traditional machine learning techniques,e.g.,Random Forest(RF).We investigated Deep Learning(DL)models,namely,Long Short Term Memory(LSTM)and Bidirectional LSTM(BLSTM),appropriate for sequential data,from imbalanced data.Two data sets were collected in normal grazing conditions using jaw-mounted and earmounted sensors.Novel to this study,alongside typical single classes,e.g.,walking,depending on the behaviours,data samples were labelled with compound classes,e.g.,walking_-grazing.The number of steps a sheep performed in the observed 10 s time window was also recorded and incorporated in the models.We designed several multi-class classification studies with imbalance being addressed using synthetic data.DL models achieved superior performance to traditional ML models,especially with augmented data(e.g.,4-Class+Steps:LSTM 88.0%,RF 82.5%).DL methods showed superior generalisability on unseen sheep(i.e.,F1-score:BLSTM 0.84,LSTM 0.83,RF 0.65).LSTM,BLSTM and RF achieved sub-millisecond average inference time,making them suitable for real-time applications.The results demonstrate the effectiveness of DL models for sheep behaviour classification in grazing conditions.The results also demonstrate the DL techniques can generalise across different sheep.The study presents a strong foundation of the development of such models for real-time animal monitoring.

Expression profile of CYP402C1 and its role in resistance to imidacloprid in the whitefly, Bemisia tabaci

Bemisia tabaci(Gennadius)(Hemiptera:Aleyrodidae)is a cosmopolitan insect pest causing serious damage to crop production.Cytochromes P450(CYPs)of B.tabaci are widely known to be involved in the metabolic resistance to a variety of insecticides,continuously increasing the difficulty in controlling this pest.In this study,four P450 genes(CYP6CMI,CYP6CXl,CYP6CX3,and CYP402CI)in B.tabaci exhibited correlations with the resistance to imidacloprid.We have focused on trying to understand the function and metabolism capacity of CYP402C1.The expression profiles of CYP402C1 were examined by reverse transcription quantitative real-time PCR and fluorescence in situ hybridizations.Its role in resistance to imidacloprid was investigated by RNA interference,transgenic Drosophila melanogaster,and heterologous expression.The results showed that CYP402CI was highly expressed in the active feeding stages of B.tabaci,such as nymphs and female adults.CYP402C1 was mainly expressed in midguts of nymphs and adults,especially in the filter chamber.Knockdown of CYP402CI significantly decreased the resistance of B.tabaci to imidacloprid by 3.96-fold(50%lethal concentration:186.46 versus 47.08 mg/L).Overexpression of CYP402CI in a transgenic D.melanogaster line(Gal4>UAS-CYP402CI)significantly increased the resistance to imidacloprid from 12.68-to 14.92-fold(129.01 and 151.80 mg/L versus 1925.14 mg/L).The heterologous expression of CYP402CI showed a metabolism ability of imidacloprid(imidacloprid decreased by 12.51%within 2 h).This study provides new insights for CYP402C1 function in B.tabaci and will help develop new strategies in B.tabaci control and its insecticide resistance.

A survey of image-based computational learning techniques for frost detection in plants

Frost damage is one of the major concerns for crop growers as it can impact the growth of the plants and hence,yields.Early detection of frost can help farmers mitigating its impact.In the past,frost detection was a manual or visual process.Image-based techniques are increasingly being used to understand frost development in plants and automatic assessment of damage resulting from frost.This research presents a comprehensive survey of the state-of the-art methods applied to detect and analyse frost stress in plants.We identify three broad computational learning approaches i.e.,statistical,traditional machine learning and deep learning,applied to images to detect and analyse frost in plants.We propose a novel taxonomy to classify the existing studies based on several attributes.This taxonomy has been developed to classify the major characteristics of a significant body of published research.In this survey,we profile 80 relevant papers based on the proposed taxonomy.We thoroughly analyse and discuss the techniques used in the various approaches,i.e.,data acquisition,data preparation,feature extraction,computational learning,and evaluation.We summarise the current challenges and discuss the opportunities for future research and development in this area including in-field advanced artificial intelligence systems for real-time frost monitoring.

Back to wild relatives for future breeding through super-pangenome

Crop wild relatives(CWRs)deliver untapped genetic diversity,as they contain valuable breeding traits absent in the cultivated pool,e.g.,traits imparting climate resilience.Facilitating genetic material from CWRs to breeding programs can advance effective traits and broaden the genetic base of cultivated crops(Bohra et al.,2022).The availability of genetic diversity in crop breeding programs is important for accelerating crop production while safeguarding food safety and agricultural sustainability.Crop domestication and artificial selection have paved the way for crop cultivars tailored to evolving human requirements and modern cultivation practices.However,domestication and breeding have significantly reduced genetic diversity in modern crops(Khan et al.,2020;Bohra et al.,2022).Owing to the extensive genetic and phenotypic variability,CWRs serve as valuable genetic reservoirs for crop improvement(Bohra et al.,2022;Li et al.,2023).The use of CWRs in breeding programs is not that straightforward,as linkage drags often remain difficult to overcome.

Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction

The first paradigm of plant breeding involves direct selection-based phenotypic observation,followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and,more recently,by incorporation of molecular marker genotypes.However,plant performance or phenotype(P)is determined by the combined effects of genotype(G),envirotype(E),and genotype by environment interaction(GEI).Phenotypes can be predicted more precisely by training a model using data collected from multiple sources,including spatiotemporal omics(genomics,phenomics,and enviromics across time and space).Integration of 3D information profiles(G-P-E),each with multidimensionality,provides predictive breeding with both tremendous opportunities and great challenges.Here,we first review innovative technologies for predictive breeding.We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy,particularly envirotypic data,which have largely been neglected in data collection and are nearly untouched in model construction.We propose a smart breeding scheme,integrated genomic-enviromic prediction(iGEP),as an extension of genomic prediction,using integrated multiomics information,big data technology,and artificial intelligence(mainly focused on machine and deep learning).We discuss how to implement iGEP,including spatiotemporal models,environmental indices,factorial and spatiotemporal structure of plant breeding data,and cross-species prediction.A strategy is then proposed for prediction-based crop redesign at both the macro(individual,population,and species)and micro(gene,metabolism,and network)scales.Finally,we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives.We call for coordinated efforts in smart breeding through iGEP,institutional partnerships,and innovative technological support.

AGRONOMIC AND ENVIRONMENTAL BENEFITS OF REINTRODUCING HERB-AND LEGUME-RICH MULTISPECIES LEYS INTO ARABLE ROTATIONS:A REVIEW

Agricultural intensification and the subsequent decline of mixed farming systems has led to an increase in continuous cropping with only a few fallow or break years,undermining global soil health.Arable-ley rotations incorporating temporary pastures(leys) lasting 1–4 years may alleviate soil degradation by building soil fertility and improving soil structure.However,the majority of previous research on arable-ley rotations has utilized either grass or grassclover leys within ungrazed systems.Multispecies leys,containing a mix of grasses,legumes,and herbs,are rapidly gaining popularity due to their promotion in agri-environment schemes and potential to deliver greater ecosystem services than conventional grass or grass-clover leys.Livestock grazing in arable-ley rotations may increase the economic resilience of these systems,despite limited research of the effects of multispecies leys on ruminant health and greenhouse gas emissions.This review aims to evaluate previous research on multispecies leys,highlighting areas for future research and the potential benefits and disbenefits on soil quality and livestock productivity.The botanical composition of multispecies leys is crucial,as legumes,deep rooted perennial plants(e.g.,Onobrychis viciifolia and Cichorium intybus) and herbs(e.g.,Plantago lanceolata) can increase soil carbon,improve soil structure,reduce nitrogen fertilizer requirements,and promote the recovery of soil fauna(e.g.,earthworms) in degraded arable soils while delivering additional environmental benefits(e.g.,biological nitrification inhibition and enteric methane reduction).Multispecies leys have the potential to deliver biologically driven regenerative agriculture,but more long-term research is needed to underpin evidence-based policy and farmer guidance.