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

Molecular Plant, Journal Year: 2022, Volume and Issue: 15(11), P. 1664 - 1695

Published: Sept. 7, 2022

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

Language: Английский

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Fast-forward breeding for a food-secure world

Trends in Genetics, Journal Year: 2021, Volume and Issue: 37(12), P. 1124 - 1136

Published: Sept. 14, 2021

The rapid advances in plant genome sequencing and phenotyping have enhanced trait mapping gene discovery crops.Increasing adoption of machine learning algorithms is crucial to derive meaningful inferences from complex multidimensional data.Emerging breeding approaches like optimal contribution selection, alone or combination with genomic will enhance the genetic base programs while accelerating gain.Integrating speed new-age technologies holds promise relieve long-standing bottleneck lengthy crop cycles.Haplotype-based breeding, prediction, editing hasten targeted assembly superior alleles future cultivars for sustainable agricultural development long-term food security. Crop production systems need expand their outputs sustainably feed a burgeoning human population. Advances combined efficient procedures accelerate availability beneficial research. Enhanced interoperability between different omics platforms, leveraged by evolving tools, help provide mechanistic explanations traits. Targeted using optimized strategies precise techniques could deliver ideal crops future. Realizing desired productivity gains field imperative securing an adequate supply 10 billion people. Safeguarding person's right nutritious requires intensive research efforts innovative solutions breed improved resilience [1.Siddique K.H.M. et al.Re-discovering Asia's forgotten fight chronic hidden hunger.Nat. Plants. 2021; 7: 116-122Crossref PubMed Scopus (10) Google Scholar]. However, major challenge uneven distribution resources, resulting huge gap demand food. harvest are access modern infrastructure technologies, including varieties, agronomic practices, machinery farm preparation, harvest, processing, marketing. Regions high populations low should be studied address these challenges equitable opportunities. Lessons learned pandemic highlight self-sustainability, less dependence on imports, especially agriculture. For instance, vast portion entire global population resides low-income deficit countries (32.23%), least developed (12%), net food-importing developing (20.15%)i,ii. Therefore, enhancing addressing worldwide zero hunger nutrition security through infrastructure, soil improvement remains essential. A high-quality reference (see Glossary) prerequisite genomics studies given attain accurate results performance [2.Varshney R.K. al.5Gs improvement.Curr. Opin. Plant Biol. 2020; 56: 190-196Crossref (46) High-confidence variant calling facilitated genome, such as manipulation. 'Democratization' concert advanced informatics tools has contiguity completeness existing assemblies. Since single cannot capture all variations species, increased number gold- platinum-standard genomes become available several crops. Long-read linked-read PacBio, 10X Chromium, Oxford Nanopore, supplemented short reads next-generation (NGS), allow long contigs base-to-base precision (Figure 1). Hi-C [3.Belton J.M. al.Hi-C: comprehensive technique conformation genomes.Methods. 2012; 58: 268-276Crossref (418) Scholar] Bionano Genomics Optical Mapping [4.Pendleton M. al.Assembly diploid architecture individual via single-molecule technologies.Nat. Methods. 2015; 12: 780-786Crossref (310) assemblies greater dramatically improving haplotype phasing scaffolding, polyploid [5.Zhuang W. al.The cultivated peanut provides insight into legume karyotypes, evolution domestication.Nat. Genet. 2019; 51: 865-876Crossref (174) Due reduction costs, high-density genotyping now affordable assaying large samples [6.Huang B.E. al.MAGIC crops: current status prospects.Theor. Appl. 128: 999-1017Crossref (136) suite platforms (e.g., Affymetrix Axiom, GeneChip, Illumina Infinium BeadChip) varying nucleotide polymorphisms (SNPs) most species [7.Rasheed A. al.Crop chips platforms: progress, challenges, perspectives.Mol. Plant. 2017; 10: 1047-1064Abstract Full Text PDF (206) Several genome-wide integrating deep reduced representation methods, genotyping-by-sequencing, restriction site associated DNA sequencing, double-digest RAD, fragment led innovations marker various Compared array-based NGS whole resequencing can simultaneously detect known uncatalogued SNPs structural (SVs), presence/absence (PAVs) copy (CNVs). Concurrent driven mainly image sensor cost- time-efficient acquisition massive spatial temporal data, predictive phenomics [8.Mir R.R. al.Integrated genomics, physiology drought tolerance crops.Theor. 125: 625-645Crossref (274) Automated equipped plant-to-sensor sensor-to-plant modes monitor dynamic response at organ, plant, scales 3D imaging applications, X-ray computed tomography, situ root system architecture, alleviating underground bottlenecks. growing nondestructively real world fully automated field-based facilities. In contrast, aerial include unmanned vehicles, manned satellites levels payload capacity resolution 1) [9.Jin X. al.High-throughput estimation traits: review ground platforms.IEEE Trans. Geosci. Remote Sens. 9: 200-231Crossref (54) Fewer than 20% mechanized established infrastructures [10.Yang high-throughput phenotyping: past decades, 13: 187-214Abstract (159) African countries, instead specialized facilities, setting up stations surveying local pathogens regional, opposed international foundation, needs considered. Fast-tracking mining resources (PGRs), wild relatives landraces conserved genebanks, ensuring supplies. Current accumulated traits suitable agriculture consumption human-mediated domestication species. dissection, range populations, biparental multiple parental multi-parent generation inter-cross (MAGIC) nested association been many Scholar,11.Scott M.F. al.Multi-parent toolbox breeding.Heredity. 396-416Crossref (38) With new sequencing/genotyping PGRs assayed evaluated environments seasons Superior genes/alleles interest identified pangenomics (Box (GWAS) (Table S1 supplemental information online, Figure Concerning modernizing addressed identify conserve germplasm undertake improvement.Box 1Pangenomics bring genes back pastSequencing popularized 'pangenome' set present within core individuals dispensable absent one individual. literature provided strong evidence SVs, evolutionary processes that shaped adaptive diversity plants. plants, PAVs 7.8% rice [80.Schatz M.C. al.Whole de novo three divergent strains rice, Oryza sativa, document novel space aus indica.Genome 2014; 15: 506PubMed 40% wheat [81.Montenegro J.D. pangenome hexaploid bread wheat.Plant J. 90: 1007-1013Crossref (170) Scholar], plants having ~30–50% variable [82.Gao L. tomato pan-genome uncovers rare allele regulating fruit flavor.Nat. 1044-1051Crossref (190) De accessions enabled called 'super-pangenome' [83.Khan A.W. al.Super-pangenome side accelerated improvement.Trends Sci. 25: 148-158Abstract (70) Scholar].Gene environmental adaptation, domestication, [84.Tan S. al.Variation among Arabidopsis populations.BMC Evol. 86Crossref (31) annotations pangenomes often enriched traits, biotic abiotic stress. Many lost during bottlenecks; identifying characterizing support reintroduction programs. Calling across domesticated lines helps retrace impact pangenome; negative effects decrease frequency those benefits increase effective size ineffective recombination, may drift bottlenecks.Knowledge enables us fine-tune outcomes constructing content variety. This building species-wide even genus-wide super-pangenomes representing allelic variants next Pangenomes teach which haplotypes combine produce combinations, enabling breeders shift useful when planning important selective elite varieties. knowledge quickly phenotypic attributes simply backcrossing Alternatively, GE molecular modify key drivers domestication; alta (CCDD) was achieved six agronomically [85.Yu H. al.A route allotetraploid rice.Cell. 184: 1156-1170Abstract (65) Sequencing Gene Knowledge Transcriptomics, proteomics, metabolomics, epigenomics windows variation beyond actual interpretable they contain [12.Weckwerth al.PANOMICS meets germplasm.Plant Biotechnol. 18: 1507-1525Crossref (25) Scholar,13.Pazhamala L.T. al.Systems biology improvement: prospects challenges.Plant Genome. 14e20098Crossref (12) These closer phenotype, narrow phenome divide, independent sets markers complement 2). Associative transcriptomics examines correlations both sequence transcript abundance [14.Harper A.L. al.Associative Brassica napus.Nat. 30: 798-802Crossref (219) maize, cis expression QTLs (eQTLs) contribute adaptation [15.Lemmon Z.H. role regulatory maize domestication.PLoS 10e1004745Crossref (79) Expression read depth GWAS transcriptome-wide test associations mRNA [16.Lin al.Substantial transcription factors revealed eRD-GWAS.Genome 192Crossref (27) Scholar,17.Kremling K.A.G. al.Transcriptome-wide supplements Zea mays.G3 (Bethesda). 3023-3033Crossref (29) Unlike variants, linkage disequilibrium genome; methods insights mechanisms enable better prioritization causal candidate [17.Kremling Proteomics also used ways refining underlying 2).Box 2Proteomics refine traitsProteomics, based mass spectrometry identification peptides matching them translated sequences, resolving ways:1.Reference proteomes compared predicted evaluate genotype-specific protein differences orthology [86.Ghatak al.Proteomics survey Solanaceae family: ahead.J. Proteome. 169: 41-57Crossref Scholar,87.Hooper C.M. al.CropPAL discovering subcellular location divergence breeding.Plant 104: 812-827Crossref (4) INDELS (missing additional proteins) genotypes.2.Quantitative proteomics same way discoveries specific [88.Hoehenwarter al.MAPA distinguishes variability highly similar isoforms potato tuber.J. Proteome Res. 2011; 2979-2991Crossref not other means because difficult structure due post-transcriptional modification [89.Millar A.H. scope, functions, dynamics posttranslational modifications.Annu. Rev. 70: 119-151Crossref (76) Scholar].3.Major proteomics-based protein–protein interaction maps coexpression link products functional units responses [90.Duncan O. al.Resource: Triticum aestivum proteome.Plant 89: 601-616Crossref (32) reduce solution resolve underlie QTL fail reach statistical significance its own [91.Weckwerth al.Differential metabolic networks unravel silent phenotypes.Proc. Natl Acad. USA. 2004; 101: 7809-7814Crossref (306) Scholar].4.Specific traditionally poorly accessible analysis postharvest seed germination traits) sought proteome tissues critical timing [92.Vanderschuren model species: status, limitations strategic improvement.J. 2013; 93: 5-19Crossref (56) Scholar].5.Traits involving post-translational processes, cascades activation/deactivation kinases/phosphatases degradation studies, usually resolved loci alone, needing direct phosphopeptides [93.Chen Y. Weckwerth Mass untangles membrane signaling networks.Trends 930-944Abstract (14) turnover [94.Nelson C.J. Millar Protein biology.Nat. 1: 15017Crossref (49) Such analyses potential maintaining target stabilizing protein, overexpression protein) altering (phosphomimic alterations), breeding.6.Proteomics offers data-independent hundreds thousands [e.g., sequential window theoretical ion spectra (SWATH) multiple-reaction monitoring (MRM)] directly assess line selection cycles Jacoby al. [95.Jacoby R.P. al.Application selected reaction field-grown dissection stress tolerance.Front. 4: 20Crossref (16) Scholar]). Proteomics, Alterations attributed heritable epigenetic changes do involve methylation, histone modification, noncoding RNAs [18.Hu al.Prediction height thaliana methylation data.Genetics. 201: 779-793Crossref (40) Recent NGS-based protocols, methylated immunoprecipitation bisulfite large-scale levels, common form polymorphisms. there modifications regulation. High-throughput screen cycles, metabolomics reached technical standard application studies. Specific metabolomic gas chromatography liquid chromatography, coupled mas

Language: Английский

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Breeding More Crops in Less Time: A Perspective on Speed Breeding

Biology, Journal Year: 2022, Volume and Issue: 11(2), P. 275 - 275

Published: Feb. 10, 2022

Breeding crops in a conventional way demands considerable time, space, inputs for selection, and the subsequent crossing of desirable plants. The duration seed-to-seed cycle is one crucial bottlenecks progress plant research breeding. In this context, speed breeding (SB), relying mainly on photoperiod extension, temperature control, early seed harvest, has potential to accelerate rate improvement. Well demonstrated case long-day plants, SB protocols are being extended short-day plants reduce generation interval time. Flexibility allows them align integrate with diverse purposes including population development, genomic phenotyping, editing. review, we discuss different methodologies their application hasten future Though been extensively used phenotyping pyramiding multiple traits development new crop varieties, certain challenges limitations hamper its widespread across crops. However, existing constraints can be resolved by further optimization critical food efficient integration pipelines.

Language: Английский

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Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Genes, Journal Year: 2023, Volume and Issue: 14(7), P. 1484 - 1484

Published: July 21, 2023

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The is posing increased demand for food, thereby pushing an acceleration in agricultural production. Furthermore, anthropogenic activities have resulted environmental pollution such as water soil degradation well alterations the composition concentration of gases. These affecting not only biodiversity loss but also physio-biochemical processes crop plants, resulting a stress-induced decline yield. To overcome problems ensure supply food material, consistent efforts being made develop strategies techniques increase yield enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication initially remained dependent on phenotype-based selection improvement. But it has grown through cytological biochemical methods, newer contemporary methods based DNA-marker-based help agronomically useful traits. now supported by high-end molecular biology tools like PCR, high-throughput genotyping phenotyping, data from morpho-physiology, statistical tools, bioinformatics, machine learning. After establishing its worth animal breeding, genomic (GS), improved variant marker-assisted (MAS), way into crop-breeding programs powerful tool. novel innovative marker-based models genetic evaluation, GS makes use markers. can amend complex traits shorten period, making advantageous over pedigree (MAS). It reduces time resources required plant while allowing gain attributes. been taken new heights integrating advanced technologies speed learning, environmental/weather further harness potential, approach known integrated (IGS). This review highlights IGS strategies, procedures, approaches, associated emerging issues, with special emphasis cereal crops. In this domain, highlight potential cutting-edge innovation climate-smart crops endure abiotic stresses motive keeping production quality at par global demand.

Language: Английский

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Temperature‐smart plants: A new horizon with omics‐driven plant breeding

Physiologia Plantarum, Journal Year: 2024, Volume and Issue: 176(1)

Published: Jan. 1, 2024

Abstract The adverse effects of mounting environmental challenges, including extreme temperatures, threaten the global food supply due to their impact on plant growth and productivity. Temperature extremes disrupt genetics, leading significant issues eventually damaging phenotypes. Plants have developed complex signaling networks respond tolerate temperature stimuli, genetic, physiological, biochemical, molecular adaptations. In recent decades, omics tools other strategies rapidly advanced, offering crucial insights a wealth information about how plants adapt stress. This review explores potential an integrated omics‐driven approach understanding temperatures. By leveraging cutting‐edge methods, genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, alongside power machine learning speed breeding data, we can revolutionize practices. These advanced techniques offer promising pathway developing climate‐proof varieties that withstand fluctuations, addressing increasing demand for high‐quality in face changing climate.

Language: Английский

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Past and future of cytoplasmic male sterility and heterosis breeding in crop plants

Plant Cell Reports, Journal Year: 2025, Volume and Issue: 44(2)

Published: Jan. 22, 2025

Language: Английский

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Salinity stress tolerance and omics approaches: revisiting the progress and achievements in major cereal crops

Heredity, Journal Year: 2022, Volume and Issue: 128(6), P. 497 - 518

Published: March 5, 2022

Language: Английский

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Speed Breeding for Crop Improvement and Food Security

Crops, Journal Year: 2023, Volume and Issue: 3(4), P. 276 - 291

Published: Nov. 3, 2023

Amid a rapidly growing global population and increasing threats to crop yields, this review focuses on Speed Breeding (SB) in genetics. It traces SB’s development from carbon arc lamp experiments 150 years ago its modern use with LED technology which significantly accelerates breeding cycles. SB has applications genetic mapping, modification, trait stacking, enhancing resilience by leveraging allelic diversity. aligns well methods like single plant selection seed descent. The integration of gene editing, genotyping, genomic holds great promise. However, faces challenges related infrastructure, genotypic variations, potential stress responses. In summary, is powerful promising approach address food security concerns advancing

Language: Английский

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Superior haplotypes of key drought-responsive genes reveal opportunities for the development of climate-resilient rice varieties

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Jan. 12, 2024

Abstract Haplotype-based breeding is an emerging and innovative concept that enables the development of designer crop varieties by exploiting exploring superior alleles/haplotypes among target genes to create new traits in programs. In this regard, whole-genome re-sequencing 399 genotypes (landraces lines) from 3000 rice genomes panel (3K-RG) mined identify haplotypes for 95 drought-responsive candidate genes. Candidate gene-based association analysis reveals 69 marker-trait associations (MTAs) 16 single plant yield (SPY) under drought stress. Haplo-pheno these identifies seven associated with higher SPY Our study performance lines possessing significantly (p ≤ 0.05) as measured (SPY), OsGSK1 -H4, OsDSR2- H3, OsDIL1- H22 , OsDREB1C -H3, ASR3- H88, DSM3- H4 ZFP182 -H4 compared without haplotypes. The validation results indicate a haplotype DREB transcription factor ( ) present all drought-tolerant varieties, while it was notably absent susceptible varieties. These carrying can be used potential donors haplotype-based develop high-yielding

Language: Английский

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Genomics-Assisted Breeding: A Powerful Breeding Approach for Improving Plant Growth and Stress Resilience

Agronomy, Journal Year: 2024, Volume and Issue: 14(6), P. 1128 - 1128

Published: May 25, 2024

Climate change biotic and abiotic stressors lead to unpredictable crop yield losses, threatening global food nutritional security. In the past, traditional breeding has been instrumental in fulfilling demand; however, owing its low efficiency, dependence on environmental conditions, labor intensity, time consumption, it fails maintain demand face of a rapidly changing environment an expanding population. this regard, plant breeders need integrate multiple disciplines technologies, such as genotyping, phenotyping, envirotyping, order produce stress-resilient high-yielding crops shorter time. With technological revolution, undergone various reformations, for example, artificial selection breeding, hybrid molecular precise which have developing modern agriculture. Marker-assisted selection, also known marker-assisted emerged game changer evolved over into genomics-assisted (GAB). It involves genomic information speed up develop crops. The combination with phenomic resources enabled identification quantitative trait loci (QTLs)/genes quickly, thereby accelerating improvement efforts. review, we provided update rapid advancement mainly GAB, efficient improvements. We highlighted importance GAB improving stress tolerance well productivity different systems. Finally, discussed how expansion omics-assisted (OAB) will contribute development future resilient

Language: Английский

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