Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L.

Bilgrami, Sayedehsaba; Ramandi, Hadi Darzi; Farokhzadeh, Sara; Rousseau‐Gueutin, Mathieu; Najafabadi, Ahmad Sobhani; Ghaderian, Mostafa; Huang, Pu; Liu, Liezhao

doi:10.1007/s00122-023-04401-2

Cited by 5 publications

(6 citation statements)

References 107 publications

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“…Given the polyploid nature of the rapeseed genome, the gene content of the candidate QTL regions was analyzed to determine possible homoeology with the numerous QTLs. Such homoeologous QTLs were reported particularly in relation to glucosinolate content (Howell et al, 2003), yield traits (Bouchet et al, 2016b; Bilgrami et al, 2023), or resistance to stem canker (Fopa Fomeju et al, 2014). Here, 47 homoeologous gene pairs were covered in one single QTL pair (Table S8, Figure 3), illustrating conservation between A and C subgenomes.…”

Section: Discussionmentioning

confidence: 98%

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Haelterman,

Louvieaux,

Chiodi

et al. 2024

Physiologia Plantarum

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Rapeseed (Brassica napus L.) is an oil‐containing crop of great economic value but with considerable nitrogen requirement. Breeding root systems that efficiently absorb nitrogen from the soil could be a driver to ensure genetic gains for more sustainable rapeseed production. The aim of this study is to identify genomic regions that regulate root morphology in response to nitrate availability. The natural variability offered by 300 inbred lines was screened at two experimental locations. Seedlings grew hydroponically with low or elevated nitrate levels. Fifteen traits related to biomass production and root morphology were measured. On average across the panel, a low nitrate level increased the root‐to‐shoot biomass ratio and the lateral root length. A large phenotypic variation was observed, along with important heritability values and genotypic effects, but low genotype‐by‐nitrogen interactions. Genome‐wide association study and bulk segregant analysis were used to identify loci regulating phenotypic traits. The first approach nominated 319 SNPs that were combined into 80 QTLs. Three QTLs identified on the A07 and C07 chromosomes were stable across nitrate levels and/or experimental locations. The second approach involved genotyping two groups of individuals from an experimental F2 population created by crossing two accessions with contrasting lateral root lengths. These individuals were found in the tails of the phenotypic distribution. Co‐localized QTLs found in both mapping approaches covered a chromosomal region on the A06 chromosome. The QTL regions contained some genes putatively involved in root organogenesis and represent selection targets for redesigning the root morphology of rapeseed.

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Section: Discussionmentioning

confidence: 98%

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Haelterman,

Louvieaux,

Chiodi

et al. 2024

Physiologia Plantarum

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“…Meta-analysis is a statistical method that combines consensus loci from various QTL studies for multiple traitsinto a single dataset to determine the most probable position and confidence interval (CI) of QTL regions (Loni et al 2023 ; Bilgrami et al 2023 ). This approach has been applied to identify genomic consensus regions over various QTL studies considering their effects and constancy across different genetic backgrounds and environments.…”

Section: Introductionmentioning

confidence: 99%

“…Another important advantage of meta-analysis of QTLs is its ability to decrease the CI of the MQTLs compared to QTLs. MQTL analysis determines the most constant QTLs irrespective of the population’s genetic background and field trial conditions, and it efficiently decreases the CI for identifying candidate genes and developing markers (Bilgrami et al 2023 ; Khahani et al 2021 ). Therefore, QTL-based meta-analysis provides more precise and stronger results.…”

Section: Introductionmentioning

confidence: 99%

“…Khahani et al ( 2021 ) conducted a meta-analysis of 536 QTLs related to yield and yield-associated traits such as yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) plus root-architecture related traits under drought stress conditions. They identified 61 stable MQTLs across different genetic backgrounds and environments (Bilgrami et al 2023 ; Khahani et al 2021 ). Abdirad et al ( 2022 ) combined root tip transcriptome sequencing and meta-analysis of QTLs to find the main genes engaged in drought stress response in rice (Abdirad et al 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, for complex quantitative traits, GWAS is widely employed to identify significant effects of genomic loci. It has been indicated that combining meta-analysis of QTLs and GWAS data can lead to dissecting important genomic regions and the genetic foundation of important quantitative traits (Bilgrami et al 2023 ; Bilgrami et al 2020 ; Daryani et al 2022 ). Furthermore, an integrated approach of meta-QTL analysis was used to identify the genomic regions and candidate genes related to drought tolerance and yield-related traits in foxtail millet (Loni et al 2023 ).…”

Section: Introductionmentioning

confidence: 99%

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Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach

Daryani,

Amirbakhtiar,

Soorni

et al. 2024

Rice

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The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain “Breeding MQTLs”. This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as “Breeding MQTLs”. These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.

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Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles

Khojasteh,

Darzi Ramandi,

Taghavi

et al. 2024

Plant Cell Rep

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Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L.

Cited by 5 publications

References 107 publications

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach

Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles

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