scholarly journals Remote-Sensing-Combined Haplotype Analysis Using Multi-Parental Advanced Generation Inter-Cross Lines Reveals Phenology QTLs for Canopy Height in Rice

2021 ◽  
Vol 12 ◽  
Author(s):  
Daisuke Ogawa ◽  
Toshihiro Sakamoto ◽  
Hiroshi Tsunematsu ◽  
Noriko Kanno ◽  
Yasunori Nonoue ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Grain Yield ◽  
Haplotype Analysis ◽  
Association Studies ◽  
Canopy Height ◽  
Surface Model ◽  
Genome Wide Association Studies ◽  
Multiple Alleles ◽  
Vegetation Fraction ◽  
Advanced Generation

High-throughput phenotyping systems with unmanned aerial vehicles (UAVs) enable observation of crop lines in the field. In this study, we show the ability of time-course monitoring of canopy height (CH) to identify quantitative trait loci (QTLs) and to characterise their pleiotropic effect on various traits. We generated a digital surface model from low-altitude UAV-captured colour digital images and investigated CH data of rice multi-parental advanced generation inter-cross (MAGIC) lines from tillering and heading to maturation. Genome-wide association studies (GWASs) using the CH data and haplotype information of the MAGIC lines revealed 11 QTLs for CH. Each QTL showed haplotype effects on different features of CH such as stage-specificity and constancy. Haplotype analysis revealed relationships at the QTL level between CH and, vegetation fraction and leaf colour [derived from UAV red–green–blue (RGB) data], and CH and yield-related traits. Noticeably, haplotypes with canopy lowering effects at qCH1-4, qCH2, and qCH10-2 increased the ratio of panicle weight to leaf and stem weight, suggesting biomass allocation to grain yield or others through growth regulation of CH. Allele mining using gene information with eight founders of the MAGIC lines revealed the possibility that qCH1-4 contains multiple alleles of semi-dwarf 1 (sd1), the IR-8 allele of which significantly contributed to the “green revolution” in rice. This use of remote-sensing-derived phenotyping data into genetics using the MAGIC lines gives insight into how rice plants grow, develop, and produce grains in phenology and provides information on effective haplotypes for breeding with ideal plant architecture and grain yield.

scholarly journals Unlocking the relationships among population structure, plant architecture, growing season, and environmental adaptation in Henan wheat cultivars

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jian Yang ◽  
Yanjie Zhou ◽  
Weiguo Hu ◽  
Yu’e Zhang ◽  
Yong Zhou ◽  
...  
Keyword(s):  
Grain Yield ◽  
Plant Architecture ◽  
Selective Sweep ◽  
Association Studies ◽  
Growing Season ◽  
Kernel Weight ◽  
High Yield ◽  
Population Divergence ◽  
Genome Wide Association Studies ◽  
Wheat Cultivars

Abstract Background Ecological environments shape plant architecture and alter the growing season, which provides the basis for wheat genetic improvement. Therefore, understanding the genetic basis of grain yield and yield-related traits in specific ecological environments is important. Results A structured panel of 96 elite wheat cultivars grown in the High-yield zone of Henan province in China was genotyped using an Illumina iSelect 90 K SNP assay. Selection pressure derived from ecological environments of mountain front and plain region provided the initial impetus for population divergence. This determined the dominant traits in two subpopulations (spike number and spike percentage were dominance in subpopulation 2:1; thousand-kernel weight, grain filling rate (GFR), maturity date (MD), and fertility period (FP) were dominance in subpopulation 2:2), which was also consistent with their inheritance from the donor parents. Genome wide association studies identified 107 significant SNPs for 12 yield-related traits and 10 regions were pleiotropic to multiple traits. Especially, GY was co-located with MD/FP, GFR and HD at QTL-ple5A, QTL-ple7A.1 and QTL-ple7B.1 region. Further selective sweep analysis revealled that regions under selection were around QTLs for these traits. Especially, grain yield (GY) is positively correlated with MD/FP and they were co-located at the VRN-1A locus. Besides, a selective sweep signal was detected at VRN-1B locus which was only significance to MD/FP. Conclusions The results indicated that extensive differential in allele frequency driven by ecological selection has shaped plant architecture and growing season during yield improvement. The QTLs for yield and yield components detected in this study probably be selectively applied in molecular breeding.

scholarly journals Genome‐Wide Association Studies of Grain Yield Components in Diverse Sorghum Germplasm

2016 ◽  
Vol 9 (2) ◽  
Author(s):  
Richard E. Boyles ◽  
Elizabeth A. Cooper ◽  
Matthew T. Myers ◽  
Zachary Brenton ◽  
Bradley L. Rauh ◽  
...  
Keyword(s):  
Grain Yield ◽  
Yield Components ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Grain Yield Components ◽  
Sorghum Germplasm

scholarly journals Haplotype-based genome wide association study using a novel SNP-set method : RAINBOW

2019 ◽  
Author(s):  
Kosuke Hamazaki ◽  
Hiroyoshi Iwata
Keyword(s):  
Haplotype Block ◽  
Rare Variants ◽  
Association Studies ◽  
False Positives ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Alleles ◽  
Genome Wide ◽  
Causal Variants ◽  
Novel Snp

AbstractBackgroundDiffculty in detecting rare variants is one of the problems in conventional genome wide association studies (GWAS). The problem is closely related to the complex gene compositions comprising multiple alleles, such as haplotypes. Several single nucleotide polymorphism (SNP) set approaches have been proposed to solve this problem. These methods, however, have been rarely discussed in connection with haplotypes. In this study, we developed a novel SNP-set GWAS method named “RAINBOW” and applied the method to haplotype-based GWAS by regarding a haplotype block as a SNP-set. Combining haplotype block estimation and SNP-set GWAS, haplotype-based GWAS can be conducted without prior information of haplotypes.ResultsWe prepared 100 datasets of simulated phenotypic data and real marker genotype data of Oryza sativa subsp. indica, and performed GWAS of the datasets. We compared the power of our method, the conventional single-SNP GWAS, the conventional haplotype-based GWAS, and the conventional SNP-set GWAS. The results of the comparison indicated that the proposed method was able to better control false positives than the others. The proposed method was also excellent at detecting causal variants without relying on the linkage disequilibrium if causal variants were genotyped in the dataset. Moreover, the proposed method showed greater power than the other methods, i.e., it was able to detect causal variants that were not detected by the others, especially when the causal variants were located very close to each other and the directions of their effects were opposite.ConclusionThe proposed method, RAINBOW, is especially superior in controlling false positives, detecting causal variants, and detecting nearby causal variants with opposite effects. By using the SNP-set approach as the proposed method, we expect that detecting not only rare variants but also genes with complex mechanisms, such as genes with multiple causal variants, can be realized. RAINBOW was implemented as the R package and is available at https://github.com/KosukeHamazaki/RAINBOW.

scholarly journals SSR Marker Based Genetic Diversity Analysis and SNP Haplotyping of Genes Associating Abiotic and Biotic Stress Tolerance, Rice Growth and Development and Yield Across 93 Rice Landraces

2021 ◽  
Author(s):  
Smitha Kunhiraman Vasumathy ◽  
Manickavelu Alagu
Keyword(s):  
Genetic Diversity ◽  
Stress Tolerance ◽  
Growth And Development ◽  
Haplotype Analysis ◽  
Association Studies ◽  
Abiotic Stress Tolerance ◽  
Crop Improvement ◽  
World Population ◽  
Genome Wide Association Studies ◽  
Rice Landraces

Abstract I. Background: As rice is the staple food for more than half of the world population, enhancing grain yield irrespective of the variable climatic conditions is indispensable. Many of the traditionally cultivated rice landraces are well adapted to severe environmental conditions and have high genetic diversity that could play an important role in crop improvement.II. Methods and Results: The present study disclosed high level of genetic diversity among the unexploited rice landraces cultivated by farmers of Kerala. Twelve polymorphic markers detected a total of seventy- seven alleles with an average of 6.416 alleles per locus. PIC value ranged from 0.459 to 0.809 and to differentiate the rice genotypes, RM 242 was found to be the most appropriate marker with the highest value of 0.809. The current study indicated that the rice landraces were highly diverse with higher values of the effective number of alleles, PIC, and Shannon information index and utilizing these informative SSR markers for future molecular characterization and population genetic studies in rice landraces are advisable. Haplotypes are sets of genomic regions within a chromosome that are inherited together and haplotype-based breeding is a promising strategy for designing next-generation rice varieties. Here, haplotype analysis explored 270 haplotype blocks and 775 haplotypes from all the chromosomes of landraces under study. The number of SNPs in each haplotype block ranged from two to 28. Haplotypes of genes related to biotic and abiotic stress tolerance, yield-enhancing, and growth and development in rice landraces were also elucidated in the current study.III. Conclusions: The present investigation revealed genetic diversity of rice landraces and the haplotype analysis will open the way for genome wide association studies, QTL identification, and marker assisted selection in the unexplored rice landraces collected from Kerala.

Genome-wide association studies for Fusarium head blight resistance and it’s trade-off with grain yield in soft red winter wheat

Plant Disease ◽  
2021 ◽  
Author(s):  
Rupesh Gaire ◽  
Gina Brown-Guedira ◽  
Yanhong Dong ◽  
Herbert Ohm ◽  
Mohsen Mohammadi
Keyword(s):  
Grain Yield ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Head Blight ◽  
Trade Off ◽  
Soft Red Winter Wheat ◽  
Genome Wide ◽  
Fhb Resistance ◽  
Red Winter Wheat

Identification of quantitative trait loci for Fusarium head blight (FHB) resistance from different sources and pyramiding them into cultivars could provide effective protection against FHB. The objective of this study was to characterize a soft red winter wheat (SRWW) breeding population that has been subjected to intense germplasm introduction and alien introgression for FHB resistance in the past. The population was evaluated under misted FHB nurseries inoculated with Fusarium graminearum infested corn spawn for two years. Phenotypic data included disease incidence (INC), disease severity (SEV), Fusarium damaged kernels (FDK), FHB index (FHBdx), and deoxynivalenol concentration (DON). Genome-wide association studies by using 13,784 SNP markers identified twenty-five genomic regions at -logP ≥ 4.0 that were associated with five FHB-related traits. Of these 25, the marker trait associations that explained more than 5% phenotypic variation were localized on chromosomes 1A, 2B, 3B, 5A, 7A, 7B, and 7D, and from diverse sources including adapted SRWW lines such as Truman and Bess, and unadapted common wheat lines such as Ning7840 and Fundulea 201R. Furthermore, individuals with favorable alleles at the four loci Fhb1, Qfhb.nc-2B.1 (Q2B.1), Q7D.1, and Q7D.2 showed better FDK and DON scores (but not INC, SEV, and FHBdx) compared to other allelic combinations. Our data also showed while pyramiding multiple loci provides protection against FHB disease, it has significant trade-off with grain yield.

scholarly journals Haplotype analysis of data from UAV imagery of rice MAGIC population for the trait dissection of biomass and plant architecture

2020 ◽  
Author(s):  
Daisuke Ogawa ◽  
Toshihiro Sakamoto ◽  
Hiroshi Tsunematsu ◽  
Noriko Kanno ◽  
Yasunori Nonoue ◽  
...  
Keyword(s):  
High Resolution ◽  
High Throughput ◽  
Early Stage ◽  
Association Studies ◽  
Image Data ◽  
Shoot Biomass ◽  
Genome Wide Association Studies ◽  
Vegetation Fraction ◽  
High Throughput Phenotyping ◽  
Uav Images

Abstract Unmanned aerial vehicles (UAVs) are popular tools for high-throughput phenotyping of crops in the field. However, their use for evaluation of individual lines is limited in crop breeding because research on what the UAV image data represent is still developing. Here, we investigated the connection between shoot biomass of rice plants and the vegetation fraction (VF) estimated from high-resolution orthomosaic images taken by a UAV 10 m above a field during the vegetative stage. Haplotype-based genome-wide association studies of multi-parental advanced generation inter-cross (MAGIC) lines revealed four QTL for VF. VF was correlated with shoot biomass, but the haplotype effect on VF was better correlated with that on shoot biomass at these QTL. Further genetic characterization revealed the relationships between these QTL and plant spreading habit, final shoot biomass and panicle weight. Thus, genetic analysis using high-throughput phenotyping data derived from low-altitude, high-resolution UAV images during early stage of rice in the field provides insight into plant growth, architecture, final biomass and yield.

scholarly journals Multiple alleles at a single locus control seed dormancy in Swedish Arabidopsis

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Envel Kerdaffrec ◽  
Danièle L Filiault ◽  
Arthur Korte ◽  
Eriko Sasaki ◽  
Viktoria Nizhynska ◽  
...  
Keyword(s):  
Seed Dormancy ◽  
Field Experiments ◽  
Association Studies ◽  
Life History Trait ◽  
Genome Wide Association Studies ◽  
Multiple Alleles ◽  
Control Seed ◽  
Genome Wide ◽  
Complex Life History ◽  
Experimental Approaches

Seed dormancy is a complex life history trait that determines the timing of germination and is crucial for local adaptation. Genetic studies of dormancy are challenging, because the trait is highly plastic and strongly influenced by the maternal environment. Using a combination of statistical and experimental approaches, we show that multiple alleles at the previously identified dormancy locus DELAY OF GERMINATION1 jointly explain as much as 57% of the variation observed in Swedish Arabidopsis thaliana, but give rise to spurious associations that seriously mislead genome-wide association studies unless modeled correctly. Field experiments confirm that the major alleles affect germination as well as survival under natural conditions, and demonstrate that locally adaptive traits can sometimes be dissected genetically.

scholarly journals Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia

2018 ◽  
Author(s):  
Brian P. Ward ◽  
Gina Brown-Guedira ◽  
Frederic L. Kolb ◽  
David A. Van Sanford ◽  
Priyanka Tyagi ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Reference Genome ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Soft Red Winter Wheat ◽  
Locus Model ◽  
Genome Wide ◽  
Red Winter Wheat

AbstractGrain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 324 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate promising avenues for increasing grain yield by exploiting variation in traits relating to the number of grains per unit area, as well as phenological traits influencing grain-filling duration of genotypes.

scholarly journals Pyramiding of scald resistance genes in four spring barley MAGIC populations

2021 ◽  
Author(s):  
Juho Hautsalo ◽  
Fluturë Novakazi ◽  
Marja Jalli ◽  
Magnus Göransson ◽  
Outi Manninen ◽  
...  
Keyword(s):  
Association Studies ◽  
Spring Barley ◽  
Field Trials ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Yield Losses ◽  
Barley Cultivars ◽  
Genome Wide ◽  
Barley Leaf ◽  
Advanced Generation

AbstractGenome-Wide Association Studies (GWAS) of four Multi-parent Advanced Generation Inter-Cross (MAGIC) populations identified nine regions on chromosomes 1H, 3H, 4H, 5H, 6H and 7H associated with resistance against barley scald disease. Three of these regions are putatively novel resistance Quantitative Trait Loci (QTL). Barley scald is caused by Rhynchosporium commune, one of the most important barley leaf diseases that are prevalent in most barley-growing regions. Up to 40% yield losses can occur in susceptible barley cultivars. Four MAGIC populations were generated in a Nordic Public–Private Pre-breeding of spring barley project (PPP Barley) to introduce resistance to several important diseases. Here, these MAGIC populations consisting of six to eight founders each were tested for scald resistance in field trials in Finland and Iceland. Eight different model covariate combinations were compared for GWAS studies, and the models that deviated the least from the expected p-values were selected. For all QTL, candidate genes were identified that are predicted to be involved in pathogen defence. The MAGIC progenies contained new haplotypes of significant SNP-markers with high resistance levels. The lines with successfully pyramided resistance against scald and mildew and the significant markers are now distributed among Nordic plant breeders and will benefit development of disease-resistant cultivars.

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