Genetic strategies for improving crop yields

Nature, Journal Year: 2019, Volume and Issue: 575(7781), P. 109 - 118

Published: Nov. 6, 2019

Language: Английский

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Trends in Global Agricultural Land Use: Implications for Environmental Health and Food Security

Annual Review of Plant Biology, Journal Year: 2018, Volume and Issue: 69(1), P. 789 - 815

Published: Feb. 28, 2018

The eighteenth-century Malthusian prediction of population growth outstripping food production has not yet come to bear. Unprecedented agricultural land expansions since 1700, and technological innovations that began in the 1930s, have enabled more calorie per capita than was ever available before history. This remarkable success, however, at a great cost. Agriculture is major cause global environmental degradation. Malnutrition persists among large sections population, new epidemic obesity on rise. We review both successes failures system, addressing ongoing debates pathways health security. To deal with these challenges, coordinated research program blending modern breeding agro-ecological methods needed. call plant biologists lead this effort help steer humanity toward safe operating space for agriculture.

Language: Английский

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Multiple wheat genomes reveal global variation in modern breeding

Nature, Journal Year: 2020, Volume and Issue: 588(7837), P. 277 - 283

Published: Nov. 25, 2020

Abstract Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts wheat ( Triticum spp.) been more challenging. This is largely owing to size and complexity genome 1 , lack genome-assembly data for multiple lines 2,3 . Here we generated ten chromosome pseudomolecule five scaffold assemblies hexaploid explore genomic diversity among from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions wild relatives differences gene content resulting complex histories aimed at improving adaptation diverse environments, grain yield quality, resistance stresses 4,5 We provide examples outlining utility these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved disease characterization Sm1 6 associated with insect resistance. These will basis functional discovery deliver next generation modern cultivars.

Language: Английский

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Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

Molecular Plant, Journal Year: 2017, Volume and Issue: 10(8), P. 1047 - 1064

Published: June 29, 2017

Language: Английский

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Designing Future Crops: Genomics-Assisted Breeding Comes of Age

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

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Genomic diversifications of five Gossypium allopolyploid species and their impact on cotton improvement

Nature Genetics, Journal Year: 2020, Volume and Issue: 52(5), P. 525 - 533

Published: April 20, 2020

Abstract Polyploidy is an evolutionary innovation for many animals and all flowering plants, but its impact on selection domestication remains elusive. Here we analyze genome evolution diversification five allopolyploid cotton species, including economically important Upland Pima cottons. Although these polyploid genomes are conserved in gene content synteny, they have diversified by subgenomic transposon exchanges that equilibrate size, rate heterogeneities positive between homoeologs within among lineages. These differential trajectories accompanied gene-family homoeolog expression divergence Selection drive parallel similarities fibers of two cultivated cottons, involving coexpression networks N 6 -methyladenosine RNA modifications. Furthermore, polyploidy induces recombination suppression, which correlates with altered epigenetic landscapes can be overcome wild introgression. genomic insights will empower efforts to manipulate genetic modify target genes crop improvement.

Language: Английский

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Salt stress under the scalpel – dissecting the genetics of salt tolerance

The Plant Journal, Journal Year: 2018, Volume and Issue: 97(1), P. 148 - 163

Published: Dec. 13, 2018

Summary Salt stress limits the productivity of crops grown under saline conditions, leading to substantial losses yield in soils and brackish irrigation. tolerant could alleviate these while both increasing irrigation opportunities reducing agricultural demands on dwindling freshwater resources. However, despite significant efforts, progress towards this goal has been limited, largely because genetic complexity salt tolerance for agronomically important yield‐related traits. Consequently, focus is shifting study traits that contribute overall tolerance, thus breaking down into components are more genetically tractable. Greater consideration plasticity mechanisms throughout development across environmental conditions furthers dissection. The demand sophisticated comprehensive methodologies being met by parallel advances high‐throughput phenotyping sequencing technologies enabling multivariate characterisation vast germplasm Alongside steady improvements statistical genetics models, forward approaches elucidating gaining momentum. Subsequent quantitative trait locus gene validation also become accessible, most recently through advanced techniques molecular biology genomic analysis, facilitating translation findings field. Besides fuelling improvement established crop species, facilitates domestication naturally orphan crops. Taken together, herald a promising era discovery research plants.

Language: Английский

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Enhancing genetic gain in the era of molecular breeding

Journal of Experimental Botany, Journal Year: 2017, Volume and Issue: 68(11), P. 2641 - 2666

Published: April 7, 2017

As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as amount increase performance that is achieved annually through artificial selection. To develop pro ducts meet increasing demand mankind, especially for food feed, addition to various industrial uses, breeders are challenged enhance potential continuously, at ever higher rates, while they close gaps remain between yield breeders' demonstration trials actual farmers' fields. Factors affecting include variation available breeding materials, heritability traits interest, selection intensity, time required complete a cycle. Genetic improved enhancing closing gaps, which has been evolving complemented with modern techniques platforms, mainly driven by molecular genomic tools, combined agronomic practice. Several key strategies reviewed this article. Favorable unlocked created approaches including mutation, gene mapping discovery, transgene genome editing. Estimation refining field experiments well-controlled precisely assayed environmental factors or envirotyping, particularly understanding controlling spatial heterogeneity level. Selection intensity significantly heightened improvements scale precision genotyping phenotyping. The cycle shortened accelerating procedures integrated such marker-assisted doubled haploid development. All other widely used programs gain. More transdisciplinary approaches, team will address challenge maintaining plentiful safe supply future generations. New opportunities gain, high efficiency pipeline, broad-sense also discussed prospectively.

Language: Английский

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Super-Pangenome by Integrating the Wild Side of a Species for Accelerated Crop Improvement

Trends in Plant Science, Journal Year: 2019, Volume and Issue: 25(2), P. 148 - 158

Published: Nov. 29, 2019

The pangenome provides genomic variations in the cultivated gene pool for a given species. However, as crop's comprises many species, especially wild relatives with diverse genetic stock, here we suggest using accessions from all available species of genus development more comprehensive and complete pangenome, which refer to super-pangenome. super-pangenome variation repertoire offers unprecedented opportunities crop improvement. This opinion article focuses on recent developments pangenomics, need that should include its application

Language: Английский

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Fast-Forwarding Genetic Gain

Trends in Plant Science, Journal Year: 2018, Volume and Issue: 23(3), P. 184 - 186

Published: Feb. 7, 2018

'Speed breeding' enables scientists to exploit gene bank accessions and mutant collections for an unparalleled rapid discovery deployment. Combining speed breeding other leading-edge plant technologies with strategic global partnerships, has the potential achieve genetic gain targets required deliver our future crops.

Language: Английский

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