Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing

Biological Research, Год журнала: 2024, Номер 57(1)

Опубликована: Ноя. 7, 2024

Abstract Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype–phenotype analysis. This shift has led to precise and efficient development through genomics-based approaches, including molecular markers, genomic selection, genome editing. Molecular such as SNPs, are crucial identifying regions linked important traits, enhancing accuracy efficiency. Genomic resources viz. genetic reference genomes, sequence protein databases, transcriptomes, gene expression profiles, vital in plant aid identification of key understanding diversity, assist mapping, support marker-assisted selection speeding up programs. Advanced techniques like CRISPR/Cas9 allow modification, accelerating processes. Key Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), (GS) enable trait prediction outcomes, improving yield, disease resistance, stress tolerance. These handy complex traits influenced by multiple genes environmental factors. paper explores new technologies editing showcasing their impact on developing varieties.

Язык: Английский

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What Is Fusarium Head Blight (FHB) Resistance and What Are Its Food Safety Risks in Wheat? Problems and Solutions—A Review

Toxins, Год журнала: 2024, Номер 16(1), С. 31 - 31

Опубликована: Янв. 8, 2024

The term "Fusarium Head Blight" (FHB) resistance supposedly covers common resistances to different

Язык: Английский

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Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

Scientific Reports, Год журнала: 2022, Номер 12(1)

Опубликована: Авг. 11, 2022

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat (HS), salinity (SS), water-logging (WS), pre-harvest sprouting (PHS), and aluminium (AS) which predicted total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six out the 132 physically anchored were also verified genome-wide association studies. Around 43% had genetic physical confidence intervals less than 1 cM 5 Mb, respectively. Consequently, 539 genes in some selected providing 6 stresses. Comparative analysis underlying four RNA-seq based transcriptomic datasets unravelled 189 differentially expressed included 11 most promising candidate common among different datasets. The promoter showed promoters these include many responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, WUN-motif others. Further, overlapped 34 known genes. addition, numerous ortho-MQTLs maize, rice genomes discovered. These findings could help fine mapping gene cloning, well marker-assisted breeding for multiple tolerances wheat.

Язык: Английский

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Priority actions for Fusarium head blight resistance in durum wheat: Insights from the wheat initiative

The Plant Genome, Год журнала: 2025, Номер 18(1)

Опубликована: Янв. 6, 2025

Fusarium head blight (FHB), mainly caused by graminearum and culmorum, is a major wheat disease. Significant efforts have been made to improve resistance FHB in bread (Triticum aestivum), but more work needed for durum turgidum spp. durum). Bread has ample genetic variation breeding, which can be readily exploited, while characterized higher disease susceptibility fewer valuable sources. The Wheat Initiative - Expert Working Group on Durum Genomics Breeding promoted scientific discussion define the key actions that should prioritized achieving comparable found wheat. Here, detailed state of art novel tools are presented, together with perspective next steps forward. A meta-analysis grouping all quantitative trait loci (QTL) associated both conducted identify hotspot regions do not overlap Rht alleles, known negatively correlate resistance. list QTL related deoxynivalenol contamination lines carrying different sources provided as strategic resource. QTL, closely linked markers useful selected design an effective breeding program. Finally, we highlight priority implemented achieve satisfactory

Язык: Английский

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Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

Theoretical and Applied Genetics, Год журнала: 2023, Номер 136(4)

Опубликована: Апрель 1, 2023

Linkage disequilibrium (LD)-based haplotyping with subsequent SNP tagging improved the genomic prediction accuracy up to 0.07 and 0.092 for Fusarium head blight resistance spike width, respectively, across six different models. Genomic is a powerful tool enhance genetic gain in plant breeding. However, method accompanied by various complications leading low accuracy. One of major challenges arises from complex dimensionality marker data. To overcome this issue, we applied two pre-selection methods markers viz. LD-based haplotype-tagging GWAS-based trait-linked identification. Six models were tested preselected SNPs predict estimated breeding values (GEBVs) four traits measured 419 winter wheat genotypes. Ten sets haplotype-tagged selected adjusting level LD thresholds. In addition, identified scenarios training-test combined only training populations. The BRR RR-BLUP developed had higher FHB SPW 0.092, compared corresponding without pre-selection. highest was achieved tagged pruned at weak thresholds (r2 < 0.5), while stringent required length (SPL) flag leaf area (FLA). Trait-linked populations failed improve studied traits. Pre-selection via could play vital role optimizing selection reducing genotyping costs. Furthermore, pave way developing low-cost through customized platforms targeting key essential haplotype blocks.

Язык: Английский

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Multi‐trait genomic selection improves the prediction accuracy of end‐use quality traits in hard winter wheat

The Plant Genome, Год журнала: 2023, Номер 16(4)

Опубликована: Май 17, 2023

Improvement of end-use quality remains one the most important goals in hard winter wheat (HWW) breeding. Nevertheless, evaluation traits is confined to later development generations owing resource-intensive phenotyping. Genomic selection (GS) has shown promise facilitating for quality; however, lower prediction accuracy (PA) complex a challenge GS implementation. Multi-trait genomic (MTGP) models can improve PA by incorporating information on correlated secondary traits, but these remain be optimized HWW. A set advanced breeding lines from 2015 2021 were genotyped with 8725 single-nucleotide polymorphisms and was used evaluate MTGP predict various that are otherwise difficult phenotype earlier generations. The model outperformed ST up twofold increase PA. For instance, improved 0.38 0.75 bake absorption 0.32 0.52 loaf volume. Further, we compared including different combinations easy-to-score as covariates traits. Incorporation simple such flour protein (FLRPRO) sedimentation weight value (FLRSDS), substantially MT models. Thus, rapid low-cost measurement like FLRPRO FLRSDS facilitate use GP mixograph baking provide breeders an opportunity culling inferior genetic gains.

Язык: Английский

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Emerging Trends in Wheat (Triticum spp.) Breeding: Implications for the Future

Frontiers in Bioscience-Elite, Год журнала: 2024, Номер 16(1), С. 2 - 2

Опубликована: Янв. 31, 2024

Wheat (Triticum spp and, particularly, T. aestivum L.) is an essential cereal with increased human and animal nutritional demand. Therefore, there a need to enhance wheat yield genetic gain using modern breeding technologies alongside proven methods achieve the necessary increases in productivity. These will allow breeders develop improved cultivars more quickly efficiently. This review aims highlight emerging technological trends used worldwide breeding, focus on enhancing yield. The key for introducing variation (hybridization among species, synthetic wheat, hybridization; genetically modified wheat; transgenic gene-edited), inbreeding (double haploid (DH) speed (SB)), selection evaluation (marker-assisted (MAS), genomic (GS), machine learning (ML)) hybrid are discussed current opportunities development of future cultivars.

Язык: Английский

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Optimizing genomic selection of agricultural traits using K-wheat core collection

Frontiers in Plant Science, Год журнала: 2023, Номер 14

Опубликована: Июнь 14, 2023

The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This and combination of complicates the process selection breeding. study examined potential genome-wide association studies (GWAS) genomewide (GS) for ten by using SNPs. As a first step, trait-associated candidate marker was identified GWAS genetically diverse 567 Korean (K)-wheat core collection. accessions were genotyped an Axiom® 35K wheat DNA chip, determined (awn color, awn length, culm ear days to heading, maturity, leaf width). It is essential sustain global production utilizing Among associated with color showed high positive correlation, SNP located on chr1B significantly both traits. Next, GS evaluated prediction accuracy six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), random forest) various training populations (TPs). With exception SVM, all statistical demonstrated 0.4 better. For optimization TP, number TPs randomly selected (10%, 30%, 50% 70%) divided into three subgroups (CC-sub 1, CC-sub 2 3) based subpopulation structure. Based subgroup-based TPs, better found width. A variety cultivars used validation evaluate ability populations. Seven out phenotype-consistent results genomics-evaluated values (GEBVs) calculated space (RKHS) model. Our research provides basis improving programs through genomics assisted our can be as genomics-assisted

Язык: Английский

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Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight–related traits in winter wheat

The Plant Genome, Год журнала: 2024, Номер unknown

Опубликована: Июнь 9, 2024

Fusarium head blight (FHB) remains one of the most destructive diseases wheat (Triticum aestivum L.), causing considerable losses in yield and end-use quality. Phenotyping FHB resistance traits, Fusarium-damaged kernels (FDK), deoxynivalenol (DON), is either prone to human biases or resource expensive, hindering progress breeding for FHB-resistant cultivars. Though genomic selection (GS) can be an effective way select these inaccurate phenotyping a hurdle exploiting this approach. Here, we used artificial intelligence (AI)-based precise FDK estimation that exhibits high heritability correlation with DON. Further, GS using AI-based (FDK_QVIS/FDK_QNIR) showed two-fold increase predictive ability (PA) compared traditionally estimated (FDK_V). Next, was evaluated along other traits multi-trait (MT) models predict The inclusion FDK_QNIR FDK_QVIS days heading as covariates improved PA DON by 58% over baseline single-trait model. We next hyperspectral imaging FHB-infected novel avenue improve MT selected wavebands derived from surpassed model around 40%. Finally, phenomic prediction integrating deep learning directly observed accuracy (R

Язык: Английский

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Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat

Frontiers in Plant Science, Год журнала: 2022, Номер 13

Опубликована: Июль 25, 2022

Fusarium head blight (FHB), caused by the fungus graminearum Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding genetic basis native FHB in hard winter (HWW) combining it major quantitative trait loci (QTLs) can facilitate development FHB-resistant cultivars. In this study, we evaluated set 257 breeding lines South Dakota State University (SDSU) program to uncover US wheat. We conducted multi-locus genome-wide association study (ML-GWAS) 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total six distinct marker-trait associations (MTAs) were identified for index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, 7A. Further, eight MTAs Fusarium-damaged kernels (FDK) 5A, 6B, 6D, 7A, 7B. Out 14 significant MTAs, 10 found proximity previously reported regions classes validated HWW, while four represent likely novel resistance. Accumulation favorable alleles resulted significantly lower mean DIS FDK score, demonstrating additive effect alleles. Candidate gene analysis two several genes putative proteins interest; however, further investigation these needed identify conferring The current sheds light HWW germplasm resistant will be useful resources via marker-assisted selection.

Язык: Английский

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