scholarly journals Stable Qtl And Candidate Genes Involved Into The Genetic Network Affecting Grain Yield And Seed Size In Durum Wheat

2020 ◽  
Author(s):  
Giacomo Mangini ◽  
Antonio Blanco ◽  
Domenica Nigro ◽  
Massimo Antonio Signorile ◽  
Rosanna Simeone
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Candidate Genes ◽  
Yield Components ◽  
Snp Array ◽  
Genetic Network ◽  
Phenotypic Variance ◽  
Serine Carboxypeptidase ◽  
Qtl Cluster ◽  
Ril Population

Abstract Background: In wheat grain yield is expressed as the product of different components. Among these, thousand kernels weight (TKW) reflects the combination of several grain related traits including grain length (GL), grain width (GW) and area. Grain weight is also affected by phenological traits, such as heading time (HT) and plant height (PH). To detect stable QTL and candidate genes involved in phenotypic control of grain yield, a recombinant inbred line (RIL) population derived from two elite durum wheat cultivars (Liberdur and Anco Marzio) was evaluated for yield components and grain related traits for three growing seasons in southern Italy. The mapping population was genotyped with a 90K SNP array and a high-density genetic linkage map with 5134 markers were obtained.Results: A total of 30 QTL were detected on the durum RIL population including 9 stable QTL for TKW (2 QTL), GL, GW (2 QTL), AREA, HT and PH (2 QTL) distributed on 1B, 2A, 3A and 6B chromosomes. Interestingly, a QTL cluster mapped on 2A included a major QTL for HT explaining at least 70% of phenotypic variance and co-located with a QTL for YLD, TKW, GL and GW and AREA, respectively. In the physical position of this QTL cluster a photoperiod sensitivity gene (Ppd-A1) was found. Serine carboxypeptidase, Big Grain 1 and β-fructofuranosidase candidate genes were mapped in clusters containing stable QTL. Candidate genes involved in auxin metabolism were also found in QTL clusters in which a QTL for AREA was declared. Conclusions: This study showed that yield components and phenological traits had higher inheritances than grain yield, allowing an accurate stable QTL cluster detection. This was a powerful requisite to physically map QTL on the reference durum wheat genome and to identify candidate genes strongly affecting the genetic grain yield network.

scholarly journals Candidate Genes and Stable QTL for Grain Yield and Seed Size in Durum Wheat

2021 ◽  
Author(s):  
Giacomo Mangini ◽  
Antonio Blanco ◽  
Domenica Nigro ◽  
Massimo Antonio Signorile ◽  
Rosanna Simeone
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Candidate Genes ◽  
Yield Components ◽  
Snp Array ◽  
Phenotypic Variance ◽  
Serine Carboxypeptidase ◽  
Growing Seasons ◽  
Qtl Cluster ◽  
Ril Population

Abstract Background: In wheat grain yield is expressed as the product of different components. Among these, thousand kernels weight (TKW) reflects the combination of several grain related traits including grain length (GL), grain width (GW) and area. Grain weight is also affected by phenological traits, such as heading time (HT) and plant height (PH). To detect stable QTL and candidate genes involved in phenotypic control of grain yield, a recombinant inbred line (RIL) population derived from two elite durum wheat cultivars (Liberdur and Anco Marzio) was evaluated for yield components and grain related traits for three growing seasons in southern Italy. The mapping population was genotyped with a 90K SNP array and a high-density genetic linkage map with 5134 markers was obtained.Results: A total of 30 QTL were detected on the durum RIL population including 9 stable QTL for TKW (2 QTL), GL, GW (2 QTL), AREA, HT and PH (2 QTL) distributed on 1B, 2A, 3A and 6B chromosomes. Interestingly, a QTL cluster mapped on 2A included a major QTL for HT explaining at least 70% of phenotypic variance and co-located with a QTL for YLD, TKW, GL and GW and AREA, respectively. In the physical position of this QTL cluster a photoperiod sensitivity gene (Ppd-A1) was found. Serine carboxypeptidase, Big Grain 1 and β-fructofuranosidase candidate genes were mapped in clusters containing stable QTL. Candidate genes involved in auxin metabolism were also found in QTL clusters in which a QTL for AREA was declared. Conclusions: This study showed that yield components and phenological traits had higher inheritances than grain yield, allowing an accurate stable QTL cluster detection. This was a powerful requisite to physically map QTL on the reference durum wheat genome and to identify candidate genes strongly affecting the genetic grain yield network.

scholarly journals Candidate Genes and Stable QTL for Grain Yield and Seed Size in Durum Wheat

2020 ◽  
Author(s):  
Giacomo Mangini ◽  
Antonio Blanco ◽  
Domenica Nigro ◽  
Massimo Antonio Signorile ◽  
Rosanna Simeone
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Candidate Genes ◽  
Yield Components ◽  
Snp Array ◽  
Phenotypic Variance ◽  
Serine Carboxypeptidase ◽  
Growing Seasons ◽  
Qtl Cluster ◽  
Ril Population

Abstract Background: In wheat grain yield is expressed as the product of different components. Among these, thousand kernels weight (TKW) reflects the combination of several grain related traits including grain length (GL), grain width (GW) and area. Grain weight is also affected by phenological traits, such as heading time (HT) and plant height (PH). To detect stable QTL and candidate genes involved in phenotypic control of grain yield, a recombinant inbred line (RIL) population derived from two elite durum wheat cultivars (Liberdur and Anco Marzio) was evaluated for yield components and grain related traits for three growing seasons in southern Italy. The mapping population was genotyped with a 90K SNP array and a high-density genetic linkage map with 5134 markers was obtained.Results: A total of 30 QTL were detected on the durum RIL population including 9 stable QTL for TKW (2 QTL), GL, GW (2 QTL), AREA, HT and PH (2 QTL) distributed on 1B, 2A, 3A and 6B chromosomes. Interestingly, a QTL cluster mapped on 2A included a major QTL for HT explaining at least 70% of phenotypic variance and co-located with a QTL for YLD, TKW, GL and GW and AREA, respectively. In the physical position of this QTL cluster a photoperiod sensitivity gene (Ppd-A1) was found. Serine carboxypeptidase, Big Grain 1 and β-fructofuranosidase candidate genes were mapped in clusters containing stable QTL. Candidate genes involved in auxin metabolism were also found in QTL clusters in which a QTL for AREA was declared.Conclusions: This study showed that yield components and phenological traits had higher inheritances than grain yield, allowing an accurate stable QTL cluster detection. This was a powerful requisite to physically map QTL on the reference durum wheat genome and to identify candidate genes strongly affecting the genetic grain yield network.

scholarly journals Candidate Genes and Quantitative Trait Loci for Grain Yield and Seed Size in Durum Wheat

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 312
Author(s):  
Giacomo Mangini ◽  
Antonio Blanco ◽  
Domenica Nigro ◽  
Massimo Antonio Signorile ◽  
Rosanna Simeone
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Durum Wheat ◽  
Candidate Genes ◽  
Seed Size ◽  
Quantitative Trait ◽  
Yield Components ◽  
Snp Array ◽  
Qtl Cluster ◽  
Trait Loci

Grain yield (YLD) is affected by thousand kernel weight (TKW) which reflects the combination of grain length (GL), grain width (GW) and grain area (AREA). Grain weight is also influenced by heading time (HT) and plant height (PH). To detect candidate genes and quantitative trait loci (QTL) of yield components, a durum wheat recombinant inbred line (RIL) population was evaluated in three field trials. The RIL was genotyped with a 90K single nucleotide polymorphism (SNP) array and a high-density genetic linkage map with 5134 markers was obtained. A total of 30 QTL were detected including 23 QTL grouped in clusters on 1B, 2A, 3A, 4B and 6B chromosomes. A QTL cluster on 2A chromosome included a major QTL for HT co-located with QTL for YLD, TKW, GL, GW and AREA, respectively. The photoperiod sensitivity (Ppd-A1) gene was found in the physical position of this cluster. Serine carboxypeptidase, Big grain 1 and β-fructofuranosidase candidate genes were mapped in clusters containing QTL for seed size. This study showed that yield components and phenological traits had higher inheritances than grain yield, allowing an accurate QTL cluster detection. This was a requisite to physically map QTL on durum genome and to identify candidate genes affecting grain yield.

Detection of molecular markers associated with yield and yield components in durum wheat (Triticum turgidum L. var. durum) under saline conditions

2013 ◽  
Vol 64 (10) ◽  
pp. 957 ◽  
Author(s):  
S. Dura ◽  
M. Duwayri ◽  
M. Nachit ◽  
F. Al Sheyab
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Yield Components ◽  
Agronomic Traits ◽  
Triticum Turgidum ◽  
Recombinant Inbred Lines ◽  
Wheat Breeding ◽  
Phenotypic Data ◽  
Yield And Yield Components ◽  
Ssr Loci

Durum wheat is one of the most important staple food crops, grown mainly in the Mediterranean region where its productivity is drastically affected by salinity. The objective of this study was to identify markers associated with grain yield and its related traits under saline conditions. A population of 114 F8 recombinant inbred lines (RILs) was derived by single-seed descent from a cross between Belikh2 (salinity-tolerant variety) and Omrabi5 (less salinity tolerant) was grown under non-saline and saline conditions in a glasshouse. Phenotypic data of the RILs and parental lines were measured for 15 agronomic traits. Association of 96 simple sequence repeat (SSR) loci covering all 14 chromosomes with 15 agronomic traits was analysed with a mixed linear model. In total, 49 SSR loci were significantly associated with these traits. Under saline conditions, 12 markers were associated with phenological traits and 19 markers were associated with yield and yield components. Marker alleles from Belikh2 were associated with a positive effect for the majority of markers associated with yield and yield components. Under saline condition, five markers (Xwmc182, Xwmc388, Xwmc398, Xbarc61, and Xwmc177) were closely linked with grain yield, located on chromosomes 2A, 3A, 3B, 4B, 5A, 6B, and 7A. These markers could be used for marker-assisted selection in durum wheat breeding under saline conditions.

scholarly journals Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Ning Gao ◽  
Yilong Chen ◽  
Xiaohong Liu ◽  
Yunxiang Zhao ◽  
Lin Zhu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Sperm Motility ◽  
Male Fertility ◽  
Snp Array ◽  
Single Step ◽  
Sperm Cells ◽  
Phenotypic Variance ◽  
Morphological Abnormalities ◽  
Genetic Variances ◽  
Progressive Motility

Abstract Background In the pig production industry, artificial insemination (AI) plays an important role in enlarging the beneficial impact of elite boars. Understanding the genetic architecture and detecting genetic markers associated with semen traits can help in improving genetic selection for such traits and accelerate genetic progress. In this study, we utilized a weighted single-step genome-wide association study (wssGWAS) procedure to detect genetic regions and further candidate genes associated with semen traits in a Duroc boar population. Overall, the full pedigree consists of 5284 pigs (12 generations), of which 2693 boars have semen data (143,113 ejaculations) and 1733 pigs were genotyped with 50 K single nucleotide polymorphism (SNP) array. Results Results show that the most significant genetic regions (0.4 Mb windows) explained approximately 2%~ 6% of the total genetic variances for the studied traits. Totally, the identified significant windows (windows explaining more than 1% of total genetic variances) explained 28.29, 35.31, 41.98, and 20.60% of genetic variances (not phenotypic variance) for number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, respectively. Several genes that have been previously reported to be associated with mammal spermiogenesis, testes functioning, and male fertility were detected and treated as candidate genes for the traits of interest: Number of sperm cells, TDRD5, QSOX1, BLK, TIMP3, THRA, CSF3, and ZPBP1; Sperm motility, PPP2R2B, NEK2, NDRG, ADAM7, SKP2, and RNASET2; Sperm progressive motility, SH2B1, BLK, LAMB1, VPS4A, SPAG9, LCN2, and DNM1; Total morphological abnormalities, GHR, SELENOP, SLC16A5, SLC9A3R1, and DNAI2. Conclusions In conclusion, candidate genes associated with Duroc boars’ semen traits, including the number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, were identified using wssGWAS. KEGG and GO enrichment analysis indicate that the identified candidate genes were enriched in biological processes and functional terms may be involved into spermiogenesis, testes functioning, and male fertility.

Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

1983 ◽  
Vol 101 (2) ◽  
pp. 383-387 ◽  
Author(s):  
A. Hadjichristodoulou
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Edge Effect ◽  
Edge Effects ◽  
Yield Components ◽  
Straw Yield ◽  
Varietal Differences ◽  
Arid Conditions ◽  
1000 Grain Weight ◽  
Semi Arid

SUMMARYA series of trials were conducted during 1979–82 under semi-arid conditions in a Mediterranean-type environment to study the edge effects in mechanized durum wheat and barley variety trials when uncropped pathways are left between plots. Varietal differences in edge effects on grain yield were in most trials not significant. Thus, edge effects do not distort significantly the relative ranking of varieties.Edge effects were significant for all traits studied and higher in grain and straw yields. These effects were also higher in drier seasons. The overestimation of grain yield from whole plots was 13–18% in relatively high rainfall seasons and 29% in a dry season. In two seasons the scores on the two outer rows were higher than on the two central rows by 89 and 117 % for grain yield, by 72 and 73% for straw yield, by 44 and 48% for numbers of tillers, by 6% for 1000-grain weight and by 14 and 40% for number of grains per tiller. The edge effect was not confined to the outer rows, but it extended to the inner rows of the plot; the magnitude of this effect varied with season and trait.Rows adjacent to the pathway and unprotected from wind had a lower value for all traits than the opposite rows of the pathway, which were protected by the inner rows.

scholarly journals Identification and Validation of a Novel Locus Controlling Spikelet Number in Bread Wheat (Triticum aestivum L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Li ◽  
Guangbing Deng ◽  
Yanyan Tang ◽  
Yan Su ◽  
Jinhui Wang ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genetic Map ◽  
Molecular Mechanisms ◽  
Limit Of Detection ◽  
Expression Patterns ◽  
Snp Array ◽  
Phenotypic Variance ◽  
Spikelet Number ◽  
Grain Number Per Spike ◽  
Spikelet Number Per Spike

Spikelet number is an important target trait for wheat yield improvement. Thus, the identification and verification of novel quantitative trait locus (QTL)/genes controlling spikelet number are essential for dissecting the underlying molecular mechanisms and hence for improving grain yield. In the present study, we constructed a high-density genetic map for the Kechengmai1/Chuanmai42 doubled haploid (DH) population using 13,068 single-nucleotide polymorphism (SNP) markers from the Wheat 55K SNP array. A comparison between the genetic and physical maps indicated high consistence of the marker orders. Based on this genetic map, a total of 27 QTLs associated with total spikelet number per spike (TSN) and fertile spikelet number per spike (FSN) were detected on chromosomes 1B, 1D, 2B, 2D, 3D, 4A, 4D, 5A, 5B, 5D, 6A, 6B, and 7D in five environments. Among them, five QTLs on chromosome 2D, 3D, 5A, and 7D were detected in multiple environments and combined QTL analysis, explaining the phenotypic variance ranging from 3.64% to 23.28%. Particularly, QTsn/Fsn.cib-3D for TSN and FSN [phenotypic variation explained (PVE) = 5.97–23.28%, limit of detection (LOD) = 3.73–18.51] is probably a novel locus and located in a 4.5-cM interval on chromosome arm 3DL flanking by the markers AX-110914105 and AX-109429351. This QTL was further validated in other two populations with different genetic backgrounds using the closely linked Kompetitive Allele-Specific PCR (KASP) marker KASP_AX-110914105. The results indicated that QTsn/Fsn.cib-3D significantly increased the TSN (5.56–7.96%) and FSN (5.13–9.35%), which were significantly correlated with grain number per spike (GNS). We also preliminary analyzed the candidate genes within this locus by sequence similarity, spatial expression patterns, and collinearity analysis. These results provide solid foundation for future fine mapping and cloning of QTsn/Fsn.cib-3D. The developed and validated KASP markers could be utilized in molecular breeding aiming to increase the grain yield in wheat.

Estimates of heterosis and association of genetic distance with heterosis in durum wheat under different moisture regimes

2007 ◽  
Vol 145 (3) ◽  
pp. 239-248 ◽  
Author(s):  
K. F. SOLOMON ◽  
M. T. LABUSCHAGNE ◽  
C. D. VILJOEN
Keyword(s):  
Cluster Analysis ◽  
Grain Yield ◽  
Durum Wheat ◽  
Yield Components ◽  
Agronomic Traits ◽  
Moisture Stress ◽  
Genetic Distances ◽  
Stress Conditions ◽  
Treatment Conditions ◽  
Yield And Yield Components

The objectives of the present study were to evaluate heterosis for grain yield and yield components in durum wheat, and to assess the prediction potential of amplified fragment length polymorphism (AFLP) based and agronomic trait based genetic distances (GD and MD, respectively) to F1 performance, mid parent heterosis (MPH), and specific combining ability effects (SCA) under well-watered and moisture stress conditions. Six parental genotypes with different responses to moisture stress and their 15 F1 crosses were evaluated for their responses to moisture stress conditions in a glasshouse. Some cross combinations showed significant MPH for grain yield and yield components. The expression of heterosis for grain yield was greater under moisture stress conditions than under well-watered conditions. Cluster analysis of the parental lines based on agronomic performance under stress conditions was similar to cluster analysis result based on AFLP marker profiles. F1 performance was strongly correlated to both SCA effects and MPH under both stress and well water conditions. The correlation between SCA and MPH was very high under both treatment conditions for all traits. Correlation between GD and MD was significant only under stress conditions. Positive correlation was found only for the association between GD v. F1 performance and GD v. SCA effects for harvest index (HI) under well-watered conditions. None of the correlations between MD and SCA effects were significant. The absence of association between GD and heterosis for yield and most agronomic traits implied that heterozygosity per se diversity is not a good predictor of heterosis or F1 performance under both well-watered and stressed conditions.

Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions

2021 ◽  
Vol 3 (2) ◽  
pp. 54
Author(s):  
Yheni Dwiningsih ◽  
Anuj Kumar ◽  
Julie Thomas ◽  
Charlez Ruiz ◽  
Jawaher Alkahtani ◽  
...  
Keyword(s):  
Drought Stress ◽  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Candidate Genes ◽  
Chlorophyll Content ◽  
Quantitative Trait ◽  
Flag Leaf ◽  
Drought Condition ◽  
Ril Population ◽  
Trait Loci

Rice (Oryza sativa) is the staple food for more than half of the world population. Rice needs 2-3 times more water compared to other crops. Drought condition is one of the limited factor in rice production. Recombinant inbred line population derived from a cross between rice genotype tropical japonica Kaybonnet and indica ZHE733 named K/Z RIL population was used to identify candidate genes for chlorophyll content related to grain yield under drought condition. Chlorophyll content in the flag leaf of the rice plant is related to the grain yield since chlorophyll plays an important role in the photosynthesis. The K/Z RIL population was screened in the field at Fayetteville, Arkansas, USA by controlled drought stress treatment at the reproductive stage (R3), and the effect of drought stress was quantify by measuring chlorophyll content, flag leaf characteristics, and grain yield. Quantitative trait loci (QTL) analysis was performed with a set of 4133 single nucleotide polymorphism (SNP) markers by using QTL IciMapping software version 4.2.53. Candidate genes within the QTL regions were identified by using the MSU Rice Genome Annotation Project database release 7.0 as the reference. A total of eleven QTLs and forty-three candidate genes were identified for chlorophyll content related to the grain yield under drought condition. Most of the candidate genes involve in biological processes, molecular functions, and cell components. By understanding the genetic complexity of the chlorophyll content, this research provides information to develop drought-resistant rice varieties with greater productivity under drought stress condition.

Sign in / Sign up

Export Citation Format

Share Document