scholarly journals Genetic Mapping by Integration of 55K SNP Array and KASP Markers Reveals Candidate Genes for Important Agronomic Traits in Hexaploid Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Hongchun Xiong ◽  
Yuting Li ◽  
Huijun Guo ◽  
Yongdun Xie ◽  
Linshu Zhao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Phenotypic Variation ◽  
Agronomic Traits ◽  
Recombinant Inbred Lines ◽  
Wheat Yield ◽  
Snp Array ◽  
Heading Date ◽  
Sequencing Data ◽  
Gene Encoding ◽  
Kasp Markers

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0–48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2–22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.

scholarly journals QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 604
Author(s):  
Paolo Vitale ◽  
Fabio Fania ◽  
Salvatore Esposito ◽  
Ivano Pecorella ◽  
Nicola Pecchioni ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Recombinant Inbred Lines ◽  
Snp Array ◽  
Heading Date ◽  
Tiller Number ◽  
Genetic Maps ◽  
Yield Potential ◽  
Adaptation To Climate Change ◽  
Map Resolution ◽  
Mapping Populations

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F2 and F2-derived F3 families) and late (F6 and F7, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F2 and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F2 mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

scholarly journals Identification of Genetic Loci and Candidate Genes Related to Grain Zinc and Iron Concentration Using a Zinc-Enriched Wheat ‘Zinc-Shakti’

2021 ◽  
Vol 12 ◽  
Author(s):  
Nagenahalli Dharmegowda Rathan ◽  
Deepmala Sehgal ◽  
Karthikeyan Thiyagarajan ◽  
Ravi Singh ◽  
Anju-Mahendru Singh ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Agronomic Traits ◽  
Recombinant Inbred Lines ◽  
Iron Concentration ◽  
Small Peptides ◽  
Growing Seasons ◽  
Grain Zinc ◽  
Pleiotropic Qtl ◽  
Genomic Regions ◽  
Yield Trials

The development of nutritionally enhanced wheat (Triticum aestivum L.) with higher levels of grain iron (Fe) and zinc (Zn) offers a sustainable solution to micronutrient deficiency among resource-poor wheat consumers. One hundred and ninety recombinant inbred lines (RILs) from ‘Kachu’ × ‘Zinc-Shakti’ cross were phenotyped for grain Fe and Zn concentrations and phenological and agronomically important traits at Ciudad Obregon, Mexico in the 2017–2018, 2018–2019, and 2019–2020 growing seasons and Diversity Arrays Technology (DArT) molecular marker data were used to determine genomic regions controlling grain micronutrients and agronomic traits. We identified seven new pleiotropic quantitative trait loci (QTL) for grain Zn and Fe on chromosomes 1B, 1D, 2B, 6A, and 7D. The stable pleiotropic QTL identified have expanded the diversity of QTL that could be used in breeding for wheat biofortification. Nine RILs with the best combination of pleiotropic QTL for Zn and Fe have been identified to be used in future crossing programs and to be screened in elite yield trials before releasing as biofortified varieties. In silico analysis revealed several candidate genes underlying QTL, including those belonging to the families of the transporters and kinases known to transport small peptides and minerals (thus assisting mineral uptake) and catalyzing phosphorylation processes, respectively.

scholarly journals Genetic dissection of grain architecture-related traits in a winter wheat population

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Matías Schierenbeck ◽  
Ahmad M. Alqudah ◽  
Ulrike Lohwasser ◽  
Rasha A. Tarawneh ◽  
María Rosa Simón ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Allelic Variation ◽  
Wheat Yield ◽  
Snp Array ◽  
Significant Snps ◽  
Kernel Weight ◽  
Yield Potential ◽  
Oxidoreductase Activity ◽  
Global Food Security ◽  
Kernel Length

Abstract Background The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767–602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

scholarly journals The 55K SNP-Based Exploration of QTLs for Spikelet Number Per Spike in a Tetraploid Wheat (Triticum turgidum L.) Population: Chinese Landrace “Ailanmai” × Wild Emmer

2021 ◽  
Vol 12 ◽  
Author(s):  
Ziqiang Mo ◽  
Jing Zhu ◽  
Jiatai Wei ◽  
Jieguang Zhou ◽  
Qiang Xu ◽  
...  
Keyword(s):  
Common Wheat ◽  
Agronomic Traits ◽  
Wheat Yield ◽  
Snp Array ◽  
Tetraploid Wheat ◽  
Wild Emmer ◽  
Potential Candidate ◽  
Spikelet Number ◽  
Improvement Programs ◽  
Spikelet Number Per Spike

Spikelet number per spike (SNS) is the primary factor that determines wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace “Ailanmai” × wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using a wheat 55K single- nucleotide polymorphism (SNP) array. The linkage map containing 1,150 bin markers with a total genetic distance of 2,411.8 cm was obtained. Based on the phenotypic data from the eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTLs) for SNS were identified, explaining 6.71–29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.2 and QSns.sau-AM-3B.2, were detected as a major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked kompetitive allele-specific PCR (KASP) markers. Potential candidate genes within the physical intervals of the corresponding QTLs were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of the wheat 55K SNP array developed for common wheat in the genetic mapping of tetraploid population and shows the potential application of wheat-related species in wheat improvement programs.

scholarly journals Linkage Mapping and Genome-Wide Association Study Reveals Conservative QTLs and Candidate Genes for Fusarium Rot Resistance in Maize

2020 ◽  
Author(s):  
Yabin Wu ◽  
Zijian Zhou ◽  
Chaopei Dong ◽  
Jiafa Chen ◽  
Junqiang Ding ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Phenotypic Variation ◽  
Linkage Mapping ◽  
Genome Wide Association Study ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Genome Wide Association ◽  
Ear Rot ◽  
Genome Wide

Abstract Background: Fusarium ear rot (FER) caused by Fusarium verticillioides is a major disease of maize that reduces grain yield and quality globally. However, there have been few reports of major loci for FER were verified and cloned. Result: To gain a comprehensive understanding of the genetic basis of natural variation in FER resistance, a recombinant inbred lines (RIL) population and one panel of inbred lines were used to map quantitative trait loci (QTL) for resistance. As a result, a total of 10 QTL were identified by linkage mapping under four environments, which were located on six chromosomes and explained 1.0%-7.1% of the phenotypic variation. Epistatic mapping detected four pairs of QTL that showed significant epistasis effects, explaining 2.1%-3.0% of the phenotypic variation. Additionally, 18 single nucleotide polymorphisms (SNPs) were identified across the whole genome by genome-wide association study (GWAS) under five environments. Compared linkage and association mapping revealed five common intervals located on chromosomes 3, 4, and 5 associated with FER resistance, four of which were verified in different near-isogenic lines (NILs) populations. GWAS identified three candidate genes in these consistent intervals, which belonged to the Glutaredoxin protein family , actin-depolymerizing factors (ADFs), and AMP-binding proteins. In addition, two verified FER QTL regions were found consistent with Fusarium cob rot (FCR) and Fusarium seed rot (FSR). Conclusions: These results revealed that multi pathways were involved in FER resistance, which was a complex trait that was controlled by multiple genes with minor effects, and provided important QTL and genes, which could be used in molecular breeding for resistance.

scholarly journals Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 713
Author(s):  
Shunda Li ◽  
Liang Wang ◽  
Yaning Meng ◽  
Yuanfeng Hao ◽  
Hongxin Xu ◽  
...  
Keyword(s):  
Recombinant Inbred Lines ◽  
Wheat Yield ◽  
Snp Array ◽  
Kernel Weight ◽  
Yield Potential ◽  
Phenotypic Variance ◽  
Genetic Dissection ◽  
Single Nucleotide ◽  
Grain Width ◽  
Potential Improvement

Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F6 recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4–24.8%, 4.1–8.8% and 15.7–24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7–17.8% and 13.6–19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6–19.8% and 9.8–10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

scholarly journals Linkage Mapping and Genome-Wide Association Study Reveals Conservative QTLs and Candidate Genes for Fusarium Rot Resistance in  Maize

2019 ◽  
Author(s):  
Yabin Wu ◽  
Zijian Zhou ◽  
Chaopei Dong ◽  
Jiafa Chen ◽  
Junqiang Ding ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Phenotypic Variation ◽  
Linkage Mapping ◽  
Genome Wide Association Study ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Genome Wide Association ◽  
Ear Rot ◽  
Genome Wide

Abstract Fusarium ear rot (FER) caused by Fusarium verticillioides is a major disease of maize that reduces grain yield and quality globally. To gain a comprehensive understanding of the genetic basis of natural variation in FER resistance, a recombinant inbred lines (RIL) population and one panel of inbred lines were used to map quantitative trait loci (QTL) for resistance. As a result, a total of 10 QTL were identified by linkage mapping under four environments, which were located on six chromosomes and explained 1.0%-7.1% of the phenotypic variation. Epistatic mapping detected four pairs of QTL that showed significant epistasis effects, explaining 2.1%-3.0% of the phenotypic variation. Additionally, 18 single nucleotide polymorphisms (SNPs) were identified across the whole genome by genome-wide association study (GWAS) under five environments. Compared linkage and association mapping revealed five common intervals located on chromosomes 3, 4, and 5 associated with FER resistance, four of which were verified in different near-isogenic lines (NILs) populations. GWAS identified three candidate genes in these consistent intervals, which belonged to the Glutaredoxin protein family, actin-depolymerizing factors (ADFs), and AMP-binding proteins. In addition, two verified FER QTL regions were found consistent with Fusarium cob rot (FCR) and Fusarium seed rot (FSR). These results revealed that multi pathways were involved in FER resistance, which was a complex trait that was controlled by multiple genes with minor effects, and provided important QTL and genes, which could be used in molecular breeding for resistance.

scholarly journals Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

2021 ◽  
Author(s):  
Katherine Jordan ◽  
Peter Bradbury ◽  
Zachary R Miller ◽  
Moses Nyine ◽  
Fei He ◽  
...  
Keyword(s):  
Data Storage ◽  
Recombinant Inbred Lines ◽  
Imputation Accuracy ◽  
Heading Date ◽  
Genotype Imputation ◽  
Exome Capture ◽  
P Value ◽  
Sequencing Data ◽  
Sequence Coverage ◽  
D Genome

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

scholarly journals Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) Associated with Variation in Physiological and Agronomical Traits under Contrasting Water Regimes

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1023
Author(s):  
Tatyana A. Pshenichnikova ◽  
Svetlana V. Osipova ◽  
Olga G. Smirnova ◽  
Irina N. Leonova ◽  
Marina D. Permyakova ◽  
...  
Keyword(s):  
Water Supply ◽  
Candidate Genes ◽  
Gene Networks ◽  
Agronomic Traits ◽  
Negative Impact ◽  
Critical Role ◽  
Wheat Yield ◽  
Snp Markers ◽  
Single Chromosome ◽  
Agronomical Traits

Understanding the genetic architecture of drought tolerance is of great importance for overcoming the negative impact of drought on wheat yield. Earlier, we discovered the critical role of chromosome 2A for the drought-tolerant status of wheat spring cultivar Saratovskaya 29. A set of 92 single-chromosome recombinant double haploid (SCRDH) lines were obtained in the genetic background of Saratovskaya 29. The lines carry fragments of chromosome 2A from the drought-sensitive cultivar Yanetzkis Probat. The SCRDH lines were used to identify regions on chromosome 2A associated with the manifestation of physiological and agronomical traits under distinct water supply, and to identify candidate genes that may be associated with adaptive gene networks in wheat. Genotyping was done with Illumina Infinium 15k wheat array using 590 SNP markers with 146 markers being polymorphic. In four identified regions of chromosome 2A, 53 out of 58 QTLs associated with physiological and agronomic traits under contrasting water supply were mapped. Thirty-nine candidate genes were identified, of which 18 were transcription factors. The region 73.8–78.1 cM included the largest number of QTLs and candidate genes. The variation in SNPs associated with agronomical and physiological traits revealed among the SCRDH lines may provide useful information for drought related marker-assisted breeding.

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