Molecular Breeding and Drought Tolerance in Chickpea DOI Creative Commons

Ruchi Asati,

M. K. Tripathi, Sushma Tiwari

et al.

Life, Journal Year: 2022, Volume and Issue: 12(11), P. 1846 - 1846

Published: Nov. 11, 2022

L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to Leguminosae family. Drought utmost common abiotic factor on plants, distressing their water status limiting growth development. Chickpea genotypes have natural ability fight drought stress using certain strategies viz., escape, avoidance tolerance. Assorted breeding methods, including hybridization, mutation, marker-aided breeding, genome sequencing along with omics approaches, could be used improve chickpea germplasm lines(s) against stress. Root features, for instance depth root biomass, been recognized as beneficial morphological factors managing terminal tolerance in chickpea. Marker-aided selection, example, a genomics-assisted (GAB) strategy that can considerably increase accuracy competence. These technologies, notably marker-assisted omics, plant physiology knowledge, underlined importance of future improvement programmes generate drought-tolerant cultivars(s).

Language: Английский

Designing Future Crops: Genomics-Assisted Breeding Comes of Age DOI Creative Commons
Rajeev K. Varshney, Abhishek Bohra, Jianming Yu

et al.

Trends in Plant Science, Journal Year: 2021, Volume and Issue: 26(6), P. 631 - 649

Published: April 21, 2021

Availability of reference genomes and genome-wide surveys on comprehensive diversity panels pave the way to associate allelic variation with phenotypes.Methods are now available evaluate genetic worth vast resources archived in gene banks streamline application these crop improvement programs.Precise genome editing technologies concert enhanced trait architectures enable innovative solutions engineer complex variation.High-throughput phenotyping methods beginning alleviate challenge accurate, precise, large-scale measurements plant performance.Optimized speed breeding protocols remain crucial accelerating advance when applied genomic approaches.Sustaining gains from seeks fast-tracking exploitation minor effect alleles, accumulation favorable purging deleterious alleles. Over past decade, genomics-assisted (GAB) has been instrumental harnessing potential modern characterizing exploiting for germplasm enhancement cultivar development. Sustaining GAB future (GAB 2.0) will rely upon a suite new approaches that fast-track targeted manipulation creating novel facilitate their rapid efficient incorporation programs. Genomic strategies optimize beneficial alleles be indispensable designing crops. In coming decades, 2.0 is expected play role more climate-smart cultivars higher nutritional value cost-effective timely manner. Ensuring sustainable increase global food production finite an increasing human population great challenge. wake enormous advances, 15 years back we proposed concept [1.Varshney R.K. et al.Genomics-assisted improvement.Trends Plant Sci. 2005; 10: 621-630Abstract Full Text PDF PubMed Scopus (392) Google Scholar]. Interestingly, proposition coincided release high-quality sequence assembly rice (Oryza sativa), representing first any [2.International Rice Genome Sequencing Project The map-based genome.Nature. 436: 793-800Crossref (2692) Subsequently, array tools have become applications (Table 1). Parallel advancements technologies, designs based multi-parent synthetic populations were implemented discovery impart benefits both association mapping linkage analysis, such as diversity, controlled structure, greater power quantitative locus (QTL) detection improved accuracy [3.Kover P.X. al.A multiparent advanced generation inter-cross fine-map traits Arabidopsis thaliana.PLoS Genet. 2009; 5e1000551Crossref (361) Scholar,4.Yu J. al.Genetic design statistical nested maize.Genetics. 2008; 178: 539-551Crossref (627) Scholar].Table 1Genome Resources Ten Topmost Food CropsaAbbreviation: n.d., no data.CropArea (mha)bSource: http://www.fao.org/faostat/en/#data/QC.Production (mmt)bSource: http://www.fao.org/faostat/en/#data/QC.Assembled (Mb)SNP arrayGenomic databasesGene expression atlasPan-genomeWheat(Triticum aestivum)215.9765.714 500[61.International Wheat Consortium (IWGSC) Shifting limits wheat research using fully annotated genome.Science. 2018; 361eaar7191Crossref (891) Scholar]Wheat 9K iSelect [62.Cavanagh C.R. al.Genome-wide comparative uncovers multiple targets selection hexaploid landraces cultivars.Proc. Natl. Acad. U. S. A. 2013; 110: 20Crossref (601) 90K [63.Wang Y. al.Simultaneous three homoeoalleles bread confers heritable resistance powdery mildew.Nat. Biotechnol. 2014; 32: 947-951Crossref (839) 660K Axiom HD genotyping [64.Winfield M.O. al.High-density SNP its secondary tertiary pool.Plant 2016; 14: 1195-1206Crossref (44) breeder's (Affymetrix 35K) [65.Allen A.M. al.Characterization breeders' suitable high-throughput accessions (Triticum aestivum).Plant 2017; 15: 390-401Crossref (0) Variation Database (WGVD) [66.Wang al.WGVD: integrated web-database selective signatures.Database. 2020; 2020baaa090Crossref Scholar]WheatExp [67.Pearce al.WheatExp: RNA-seq database polyploid wheat.BMC Biol. 2015; 299Crossref (59) Scholar]18 Cultivars [68.Montenegro J.D. al.The pangenome wheat.Plant 90: 1007-1013Crossref (111) Scholar]Maize(Zea mays)197.21148.42048[69.Schnable P.S. B73 maize genome: complexity, dynamics.Science. 326: 1112-1115Crossref (2568) Scholar]MaizeSNP50 BeadChip (llumina Infinium 50K) [70.Ganal M.W. large (Zea mays L.) array: development genotyping, compare genome.PLoS One. 2011; 6e28334Crossref Scholar]Subset MaizeSNP50 (Illumina 3K) [71.Rousselle al.Study essential derivation maize: III. Selection evaluation panel single nucleotide polymorphism loci use European North American germplasm.Crop 55: 1170-1180Crossref (3) Scholar]Axiom 600K [72.Unterseer powerful tool analysis high density 600 K array.BMC Genomics. 823Crossref 55K [73.Xu C. al.Development 55 coverage molecular breeding.Mol. Breed. 37: Scholar]MaizeSNPDB [74.Zhou W. al.MaizeSNPDB: retrieve SNPs among 1210 lines.Comput. Struct. 2019; 17: 1377-1383Crossref Scholar]36 207 Genes [75.Hoopes G.M. al.An updated atlas reveals organ-specific stress-induced genes.Plant 97: 1154-1167Crossref (29) Scholar]503 Inbred lines [76.Hirsch C.N. al.Insights into pan-genome pan-transcriptome.Plant Cell. 26: 121-135Crossref (226) Scholar]Rice(Oryza sativa)162755.4371[2.International Scholar]Affymetrix (1M) [77.McCouch S.R. assays rice.Breed. 2010; 60: 524-535Crossref (130) Scholar]RiceSNP50 [78.Chen analyses provide biochemical insights natural metabolism.Nat. 46: 714-721Crossref (293) Scholar]RICE6K 6K) [79.Yu H. whole-genome (RICE6K) rice.Plant 12: 28-37Crossref (101) Scholar] OsSNPnks [80.Singh N. al.Single-copy 50 chip studies rice.Sci. Rep. 5: 11600Crossref (34) Affymetrix GeneChip (44K) [81.Tung platform dissecting phenotype genotype associations spp.).Rice. 3: 205-217Crossref Scholar]SNP-Seek [82.Alexandrov al.SNP-Seek derived 3000 genomes.Nucleic Acids Res. 43: D1023-D1027Crossref (188) Scholar][83.Wang L. dynamic covering entire life cycle 61: 752-766Crossref (248) Scholar,84.Cao P. Oligonucleotide Array Database: expression.Rice. 2012; 17Crossref Scholar]66 Accessions [85.Zhao Q. al.Pan-genome highlights extent cultivated wild rice.Nat. 50: 278-284Crossref (149) Scholar]Soybean(Glycine max)120.5333.7973[86.Schmutz al.Genome palaeopolyploid soybean.Nature. 463: 7278Crossref (2570) Scholar]SoySNP50K [87.Song SoySNP50K, high-density soybean.PLoS 8e54985Crossref (292) Scholar]SoyaSNP180K [88.Lee Y.G. al.Development, validation soybean array.Plant 81: 625-636Crossref (30) Scholar]SoyKB [89.Joshi T. al.Soybean knowledge base (SoyKB): web resource integration translational genomics breeding.Nucleic 42: D1245-D1252Crossref Scholar]55 616 [90.Libault M. transcriptome model Glycine max, plants.Plant 63: 86-99PubMed Scholar]26 [91.Liu soybeans.Cell. 182: 162-176Abstract (42) Scholar]Barley(Hordeum vulgare)51.1158.94980 [92.International Barley A physical, functional barley 491: 711-716Crossref (978) Scholar]; 4790 [93.Mascher chromosome conformation capture ordered 544: 427-433Crossref (553) Scholar]9K Illumina Custom Genotyping [94.Comadr`an al.Natural homolog Antirrhinum CENTRORADIALIS contributed spring growth habit environmental adaptation barley.Nat. 44: 1388-1392Crossref (284) 50K [95.Bayer M.M. 50k array.Front. 8: 1792Crossref (74) Scholar]BarleyVarDB [96.Tan al.BarleyVarDB: variation.Database. 2020baaa091Crossref (1) Scholar]21 439 [97.Druka seed through development.Funct. Integr. 2006; 6: 202-211Crossref Scholar]20 [98.Jayakodi hidden legacy mutation breeding.Nature. 588: 284-289Crossref (6) Scholar]Sorghum(Sorghum bicolor)4057.9739 [99.Paterson A.H. Sorghum bicolor diversification grasses.Nature. 457: 551-556Crossref (1906) Scholar]3K [100.Bekele W.A. al.High-throughput sorghum: resequencing screening 11: 1112-1125Crossref (37) Scholar]SorGSD [101.Luo al.SorGSD: sorghum database.Biotechnol. Biofuels. 9: 6Crossref (21) Scholar]27 577 [102.Shakoor genotype-specific profiles vegetative tissues grain, sweet bioenergy sorghums.BMC 35Crossref (45) Scholar]n.d.Rapeseed(Brassica napus)3470.5849.7 [103.Chalhoub B. al.Early allopolyploid evolution post-Neolithic Brassica napus oilseed 345: 950-953Crossref (1027) Scholar]International (60K) [104.Clarke W.E. ancestral diploid species optimised markers allotetraploid genome.Theor. Appl. 129: 1887-1899Crossref Scholar]BnaGVD [105.Yan al.BnaGVD: rapeseed (Brassica napus).Plant Cell Physiol. 2021; (Published online January 5, 2021. https://doi.org/10.1093/pcp/pcaa169)Crossref Scholar]101 040 [106.Chao al.BrassicaEDB: crops.Int. Mol. 21: 5831Crossref (2) Scholar]8 [107.Song J.M. al.Eight reveal architecture ecotype differentiation napus.Nat. Plants. 34-45Crossref (61) Scholar]Dry beans(Phaseolus vulgaris)3328.9473 [108.Schmutz common bean dual domestications.Nat. 707-713Crossref (602) Scholar]BARCBean6K_1, BARCBean6K_2, BARCBean6K_3 [109.Song al.SNP assay map construction, anchoring sequence, other bean.G3 (Bethesda). 2285-2290Crossref (73) Scholar]PhaseolusGenes (http://phaseolusgenes.bioinformatics.ucdavis.edu/)[110.O'Rourke J.A. RNA-Seq bean.BMC 866Crossref (68) Scholar]n.d.Groundnut(Arachis hypogaea)29.648.82540 [111.Bertioli D.J. sequences Arachis duranensis ipaensis, ancestors peanut.Nat. 48: 438-446Crossref (372) 2540 [112.Zhuang peanut provides insight legume karyotypes, domestication.Nat. 51: 865-876Crossref (64) Scholar]'Axiom_Arachis' 58K [113.Pandey M.K. Axiom_Arachis 58 genetics groundnut.Sci. 7: 40577Crossref Scholar]n.d.57 344 Transcripts [114.Sinha al.Arachis hypogaea fastigiata subspecies groundnut accelerate applications.Plant 18: 2187-2200Crossref Scholar]n.d.Sugarcane(Saccharum officinarum)26.71949.3800–900 (Monoploid)76K [115.Yang X. al.Mining variations representative sugarcane accessions.BMC 594Crossref (17) 84K [116.Balsalobre T.W.A. al.GBS-based dosage QTL allow mining yield-related sugarcane.BMC 72Crossref Sugarcane100K [117.You construction identification.Theor. 13: 2829-2845Crossref Scholar]n.d.n.d.n.d.a Abbreviation: data.b Source: http://www.fao.org/faostat/en/#data/QC. Open table tab characterization underlying important agronomic processes. this article, discuss products delivered opportunities latest innovations offer sustain recent decades [i.e., or (GB)]. We highlight broad create selection. years, expedited timelines progress across range species, than 130 publicly bred different crops [5.Vogel Marker-Assisted Selection: Biotechnology Breeding Without Genetic Engineering. Greenpeace International, 2014Google majority noteworthy by variety programs include having elevated levels against diseases bacterial blight blast rust aestivum). Among biotic stresses, tolerance submergence, salinity, drought remained key target GAB. similar impact witnessed quality several (Box 1).Box 1Key Products Delivered Genomics-Assisted Some CropsGAB Biotic Stress ResistanceSimply inherited under influence strong-effect QTL, disease resistance, most preferred introgression approaches. 'Improved Samba Mahsuri' (ISM) carrying (BB) (Xanthomonas oryzae pv. oryzae) genes (Xa21, xa13, xa5) [132.Sundaram R.M. al.Marker assisted Mahsuri, elite indica variety.Euphytica. 160: 411-422Crossref Two major (Magnaporthe (Pi-2 Pi-54) BB (Xa38) further stacked 'ISM' [133.Madhavi K.R. background elite, resistant variety, Mahsuri.Euphytica. 212: 331-342Crossref (8) Scholar,134.Yugander al.Incorporation Xa38 Improved Mahsuri.PLoS 13e0198260Crossref (14) 'Pusa Basmati 1' pyramided two (Pi2+Pi5) (Pi54+Pi1+Pita) [135.Khanna near-isogenic gene(s) rice.Theor. 128: 1243-1259Crossref (57) version 1121' 6' (Pi2 Pi54) (xa13 Xa21) others [136.Ellur al.Improvement varieties marker backcross breeding.Plant 242: 330-341Crossref Scholar].A DNA improving stress response quality-related (http://maswheat.ucdavis.edu/protocols/index.htm). Examples versions hard red winter (HRWW) 'Jagger' 'Overley' Yr40/Lr57 Lr58, respectively [137.Kuraparthy V. PCR marker-assisted transfer leaf stripe Lr57 Yr40 wheats.Crop 49: 120-126Crossref 'HUW510' Lr34 [138.Vasistha al.Molecular validates spot blotch wheat.Euphytica. 213: 262Crossref (4) pearl millet, 'HHB 67-improved' represented downy mildew 67', which was released commercial cultivation India 2005 (see Rai al. [139.Rai K.N. al.Adaptation germplasm-derived parent millet.Plant Resour. Newsl. 154: 20-24Google Scholar]). Other success stories demonstrating cereal included eyespot (Rhizoctonia cerealis) Pch1, recessive rym4/ rym5 yellow mosaic viruses, mlo (Blumeria graminis f. sp. hordei).Unlike cereals, grain lagged behind terms product delivery; however, genotyping-based selections increasingly embraced For instance, pyramiding cyst nematode (Heterodera glycines) races (2, 3, 14) at USDA-ARS led registration high-yielding genotypes 'JTN 5503', 5303', 'DS 880', 5109' [140.Arelli al.Registration yielding JTN5503.Crop 2723-2724Crossref Scholar, 141.Arelli conventional JTN-4307 nematodes fungal diseases.J. Regist. 192-199Crossref 142.Arelli P.R. Young L.D. Inheritance PI 567516C LY1 infecting cv. Hartwig.Euphytica. 165: 1-4Crossref (19) 143.Smith USDA, ARS, National Program. Germplasm Information Network, 2010Google Similarly, Varshney [144.Varshney al.Marker-assisted region improve popular (Arachis L.).Theor. 127: 1771-1781Crossref (93) obtained set 20 hypogaea) showing yield increased (Puccinia arachidis) transferring susceptible ('ICGV 91114', 'JL 24', 'TAG 24'). chickpea, simultaneous wilt (Fusarium oxysporum ciceris) (Ascochyta rabiei) shown chickpea C 214 [145.Varshney backcrossing introgress Fusarium race 1 Ascochyta 214, chickpea.Plant Genome. 1-11Crossref (77) Scholar].GAB Abiotic ToleranceThe immense utility abiotic exemplified controlling submergence (sub1), salt (Saltol), introgressed them. Sub1 'Swarna', India, within short span 2 [146.Neeraja approach developing submergence-tolerant cultivars.Theor. 2007; 115: 767-776Crossref (276) Vietnam, nearly ten cross OM1490/IR64-Sub1 90–99% revival field conditions [147.Lang N.T. (MAB) Mekong delta.Omonrice. 11-21Google Higher survival rates mega-varieties, including 'Samba (BPT 5204), 'CR 1009' 'Thadokkham (TDK1) Laos, 'BR 11' Bangladesh also evident following QTL-introgression Hasan [148.Hasan backcrossing: useful method improvement.Biotechnol. Equip. 29: 237-254Crossref Scholar]).The Saltol various countries, candidate 1121', 6', 'AS 996', 'BT 7', 'Bacthom 'Q5DB', 'BRRI-Dhan 49' Waziri [149.Waziri al.Saltol salinity rice.Austin. Bioeng. 1-5Google Successful Sub1, Saltol, (Pi2, Pi9), gall midge (Orseolia (Gm1, Gm4) Tapaswini', pyramid (Xa 4, xa5, highly 'Tapaswini', demonstrated [150.Das G. al.Improved Tapaswini four six genes/QTLs, resistance/tolerance stresses 2413Crossref Scholar].Similar above-mentioned examples tolerance, major-effect QTLs 'Sabitri' (a yet drought-susceptible Nepal) yielded variants good type rain-fed areas Nepal countries South Asia [151.Dixit develop drought-tolerant Sabitri, Nepal.Euphytica. 184Crossref (11) availability stable effects facilitated well. 'QTL hotspot' 372' pulse 10216' (https://icar.org.in/content/development-two-superior-chickpea-varieties-genomics-assisted-breeding).GAB Quality TraitsOne breakthroughs plants involves introduction Gpc-B1 (grain protein content) tetra caused creation GPC viz. USA ('Farnum', 'Lassik', 'Westmore', 'Desert King-High Protein'), Canada ('Lillian', 'Somerset', 'Burnside'), Australia (improved 'Wyalkatchem', 'Gladius', 'VR 1128') Mitrofanova Khakimova [152.Mitrofanova O.P. A.G. New content.Russ. 477-487Crossref references therein). variant badh2 Wx basmati 'Manawthukha' (an Myanmar) resulted fragrance intermediate amylose content [153.Yi cooking Myanmar Manawthukha.Field Crops 113: 178-186Crossref By reducing cycles up 3 Chu [154.Chu oleic peanut.Plant 4: 110-117Crossref developed 'Tifguard High O/L' acid resistance. More recently, oil combined late (Phaeoisariopsis personata Berk. & Curtis) [155.Janila fatty desaturase mutant (ahFAD2A ahFAD2B) enhances low containing genotypes.Plant 203-213Crossref (66) Scholar,156.Yaduru Indian foliar SSR backcrossing.Crop 1-15Crossref (5) Resistance Simply bl

Language: Английский

Citations

372

5Gs for crop genetic improvement DOI Creative Commons
Rajeev K. Varshney, Pallavi Sinha, Vikas Kumar Singh

et al.

Current Opinion in Plant Biology, Journal Year: 2020, Volume and Issue: 56, P. 190 - 196

Published: Jan. 28, 2020

Here we propose a 5G breeding approach for bringing much-needed disruptive changes to crop improvement. These 5Gs are Genome assembly, Germplasm characterization, Gene function identification, Genomic (GB), and editing (GE). In our view, it is important have genome assemblies available each deep collection of germplasm characterized at sequencing agronomic levels identification marker-trait associations superior haplotypes. Systems biology sequencing-based mapping approaches can be used identify genes involved in pathways leading the expression trait, thereby providing diagnostic markers target traits. genes, markers, haplotypes, genome-wide data may utilized GB GE methodologies combination with rapid cycle strategy.

Language: Английский

Citations

193

Smart reprograming of plants against salinity stress using modern biotechnological tools DOI
Ali Raza, Javaria Tabassum, Ali Fakhar

et al.

Critical Reviews in Biotechnology, Journal Year: 2022, Volume and Issue: 43(7), P. 1035 - 1062

Published: Aug. 15, 2022

Climate change gives rise to numerous environmental stresses, including soil salinity. Salinity/salt stress is the second biggest abiotic factor affecting agricultural productivity worldwide by damaging physiological, biochemical, and molecular processes. In particular, salinity affects plant growth, development, productivity. Salinity responses include modulation of ion homeostasis, antioxidant defense system induction, biosynthesis phytohormones osmoprotectants protect plants from osmotic decreasing toxicity augmented reactive oxygen species scavenging. As most crop are sensitive salinity, improving salt tolerance crucial in sustaining global response trigger stress-related genes, proteins, accumulation metabolites cope with adverse consequence Therefore, this review presents an overview plants. We highlight advances modern biotechnological tools, such as omics (genomics, transcriptomics, proteomics, metabolomics) approaches different genome editing tools (ZFN, TALEN, CRISPR/Cas system) for accomplish goal "zero hunger," a sustainable development proposed FAO.

Language: Английский

Citations

166

Drought Stress in Grain Legumes: Effects, Tolerance Mechanisms and Management DOI Creative Commons
Marium Khatun, Sumi Sarkar,

Farzana Mustafa Era

et al.

Agronomy, Journal Year: 2021, Volume and Issue: 11(12), P. 2374 - 2374

Published: Nov. 23, 2021

Grain legumes are important sources of proteins, essential micronutrients and vitamins for human nutrition. Climate change, including drought, is a severe threat to grain legume production throughout the world. In this review, morpho-physiological, physio-biochemical molecular levels drought stress in described. Moreover, different tolerance mechanisms, such as morphological, mechanisms legumes, also reviewed. various management approaches mitigating effects assessed. Reduced leaf area, shoot root growth, chlorophyll content, stomatal conductance, CO2 influx, nutrient uptake translocation, water-use efficiency (WUE) ultimately affect yields. The yield loss varies from species species, even variety within depending upon severity several other factors, phenology, soil textures agro-climatic conditions. Closure stomata leads an increase temperature by reducing transpiration rate, and, so, plant faces another under stress. biosynthesis reactive oxygen (ROS) most detrimental effect Legumes can adapt changing their morphology, physiology mechanism. Improved system architecture (RSA), reduced number size leaves, stress-induced phytohormone, closure, antioxidant defense system, solute accumulation (e.g., proline) altered gene expression play crucial role tolerance. Several agronomic, breeding both conventional molecular, biotechnological used practices developing drought-tolerant without affecting crop yield. Exogenous application plant-growth regulators (PGRs), osmoprotectants inoculation Rhizobacteria arbuscular mycorrhizal fungi promotes legumes. Genome-wide association studies (GWASs), genomic selection (GS), marker-assisted (MAS), OMICS-based technology CRISPR/Cas9 make work easy save time developmental cycle get resistant drought-resistant chickpea, faba bean, common bean pigeon pea, were developed institutions. Drought-tolerant transgenic example, chickpeas, introgressing desired genes through approaches. quantitative trait loci (QTLs), candidate occupying traits, identified but not all proper implementation. Hence, more research should be conducted improve traits avoiding losses during drought.

Language: Английский

Citations

142

Modern plant biotechnology as a strategy in addressing climate change and attaining food security DOI Creative Commons
T. I. K. Munaweera, Nadeeka U. Jayawardana,

Rathiverni Rajaratnam

et al.

Agriculture & Food Security, Journal Year: 2022, Volume and Issue: 11(1)

Published: April 3, 2022

Abstract Global warming causes a range of negative impacts on plants especially due to rapid changes in temperatures, alterations rainfall patterns, floods or drought conditions, and outbreaks pests diseases. These, turn, affect crop production reducing the quality quantity agricultural produce. Climatic extremes high population growth significantly increase world’s food demand. Therefore, fulfilling goal attaining security for present future generations is prime importance. Biotechnology enables creating dramatic crops withstand stress which difficult attain using conventional breeding approaches. It viable tool used improve production. The development biotechnological approaches such as genetic engineering, genome editing, RNA-mediated gene silencing armored with next-generation sequencing, mapping have paved way precise faster modifications plants. Such intensive efforts are currently underway desirable cultivars meet demand support sustainable productivity climate change adaptation.

Language: Английский

Citations

113

Role of phytohormones in regulating cold stress tolerance: Physiological and molecular approaches for developing cold-smart crop plants DOI Creative Commons
Ali Raza, Sidra Charagh, Shiva Najafi-Kakavand

et al.

Plant Stress, Journal Year: 2023, Volume and Issue: 8, P. 100152 - 100152

Published: March 23, 2023

Global climate variations induce extreme temperatures and significantly decrease crop production, leading to food insecurity worldwide. Temperature extremes (mainly cold stress (CS): chilling 0–15 °C freezing <0 temperatures) limit plant growth development severely affect physiology biochemical molecular processes. Subsequently, plants execute numerous endogenous mechanisms, including phytohormone biosynthesis (i.e., abscisic acid, cytokinins, jasmonic salicylic gibberellic brassinosteroids, indole-3-acetic ethylene, strigolactones) tolerate stressful environments. Phytohormones are vital for managing diverse events associated with under CS as important signaling substances that dynamically arbitrate many physiological, biochemical, responses through a stress-responsive regulatory cascade. This review briefly appraises adaptation mechanisms then comprehensively reports on the crucial role of several phytohormones in adjusting response acclimation. We also discuss phytohormone-regulated genes controlling tolerance their genetic engineering combat species develop future CS-smart plants. The potential state-of-the-art omics approaches help identify phytohormone-induced novel genes, metabolites, metabolic pathways is discussed. In short, we conclude exogenous application phytohormones-regulated promising techniques developing cold-smart

Language: Английский

Citations

108

Features and applications of haplotypes in crop breeding DOI Creative Commons
Javaid Akhter Bhat, Deyue Yu, Abhishek Bohra

et al.

Communications Biology, Journal Year: 2021, Volume and Issue: 4(1)

Published: Nov. 4, 2021

Abstract Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop efficiency delivering better varieties. Fast-growing capacity affordability of DNA sequencing has motivated large-scale germplasm projects, thus opening exciting avenues for mining haplotypes applications. This review article highlights ways mine apply them complex trait dissection in GAB including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior hasten progress will be key safeguarding global food security.

Language: Английский

Citations

106

Prospects of microgreens as budding living functional food: Breeding and biofortification through OMICS and other approaches for nutritional security DOI Creative Commons
Astha Gupta, Tripti Sharma, Surendra Pratap Singh

et al.

Frontiers in Genetics, Journal Year: 2023, Volume and Issue: 14

Published: Jan. 25, 2023

Nutrient deficiency has resulted in impaired growth and development of the population globally. Microgreens are considered immature greens (required light for photosynthesis growing medium) developed from seeds vegetables, legumes, herbs, cereals. These “living superfood/functional food” due to presence chlorophyll, beta carotene, lutein, minerals like magnesium (Mg), Potassium (K), Phosphorus (P), Calcium (Ca). rich at nutritional level contain several phytoactive compounds (carotenoids, phenols, glucosinolates, polysterols) that helpful human health on Earth space their anti-microbial, anti-inflammatory, antioxidant, anti-carcinogenic properties. can be used as plant-based nutritive vegetarian foods will fruitful a nourishing constituent food industryfor garnish purposes, complement flavor, texture, color salads, soups, flat-breads, pizzas, sandwiches (substitute lettuce tacos, sandwich, burger). Good handling practices may enhance microgreens’stability, storage, shelf-life under appropriate conditions, including light, temperature, nutrients, humidity, substrate. Moreover, substrate liquid solution (hydroponic system) or solid medium (coco peat, coconut fiber, coir dust husks, sand, vermicompost, sugarcane filter cake, etc. ) based variety microgreens. However integrated multiomics approaches alongwith nutriomics foodomics explored utilized identify breed most potential microgreen genotypes, biofortify increasing content (macro-elements:K, Ca Mg; oligo-elements: Fe Zn antioxidant activity) microgreens related other traits viz., fast growth, good values, high germination percentage, through implementation includes genomics, transcriptomics, sequencing-based approaches, molecular breeding, machine learning, nanoparticles, seed priming strategiesetc.

Language: Английский

Citations

49

Developing future heat-resilient vegetable crops DOI Creative Commons
Faisal Saeed, Usman Khalid Chaudhry, Ali Raza

et al.

Functional & Integrative Genomics, Journal Year: 2023, Volume and Issue: 23(1)

Published: Jan. 24, 2023

Climate change seriously impacts global agriculture, with rising temperatures directly affecting the yield. Vegetables are an essential part of daily human consumption and thus have importance among all agricultural crops. The population is increasing daily, so there a need for alternative ways which can be helpful in maximizing harvestable yield vegetables. increase temperature affects plants' biochemical molecular processes; having significant impact on quality Breeding climate-resilient crops good yields takes long time lots breeding efforts. However, advent new omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, efficiency efficacy unearthing information pathways associated high-temperature stress resilience has improved many vegetable Besides omics, use genomics-assisted approaches gene editing speed allow creation modern cultivars that more resilient to high temperatures. Collectively, these will shorten create release novel varieties meet growing demands productivity quality. This review discusses effects heat vegetables highlights recent research focus how genome produce temperature-resilient efficiently faster.

Language: Английский

Citations

45

Fine mapping and gene cloning in the post-NGS era: advances and prospects DOI Creative Commons

Deepa Jaganathan,

Abhishek Bohra, Mahendar Thudi

et al.

Theoretical and Applied Genetics, Journal Year: 2020, Volume and Issue: 133(5), P. 1791 - 1810

Published: Feb. 10, 2020

Abstract Improvement in traits of agronomic importance is the top breeding priority crop improvement programs. Majority these show complex quantitative inheritance. Identification trait loci (QTLs) followed by fine mapping QTLs and cloning candidate genes/QTLs central to analysis. Advances genomic technologies revolutionized our understanding genetics traits, regions associated with were employed marker-assisted or QTLs/genes. Next-generation sequencing (NGS) have enabled genome-wide methodologies for development ultra-high-density genetic linkage maps different crops, thus allowing placement within few kbs genomes. In this review, we compare marker systems used QTL pre- post-NGS era. We then discuss how NGS platforms combination advanced experimental designs improved analysis mapping. opine that efficient genotyping/sequencing assays may circumvent need cumbersome procedures earlier A deeper architectures agricultural significance will be crucial accelerate improvement.

Language: Английский

Citations

124