Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach

Daryani, Parisa; Ramandi, Hadi Darzi; Dezhsetan, Sara; Mansuri, Raheleh Mirdar; Salekdeh, Ghasem Hosseini; Shobbar, Zahra‐Sadat

doi:10.1007/s00122-021-03953-5

Cited by 23 publications

(18 citation statements)

References 151 publications

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“…A meta-analysis study of root traits, based on 128 published studies under field conditions, has shown that drought significantly decreased root length and root length density, while it increased root diameter and root-to-shoot biomass ratio (Zhou et al, 2018). A wholegenome meta-analysis was performed to find out candidate genes and genomic regions involved in controlling RSA traits under well-watered and drought stress conditions in rice (Daryani et al, 2022) and other major cereal crops including maize (Guo et al, 2018), bread wheat (Darzi-Ramandi et al, 2017;Soriano and Alvaro, 2019;Bilgrami et al, 2020), and durum wheat (Iannucci et al, 2017). Specifically, plant hormones are known to play critical roles in the molecular regulation of RSA traits under drought and the progress has been reviewed by Ranjan et al (2022).…”

Section: Introductionmentioning

confidence: 99%

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

2022

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Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.

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Section: Introductionmentioning

confidence: 99%

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

2022

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“…Meta-QTL (MQTL) analysis is a good integrated method. It had been used to estimate the CI of many traits of QTL in many crops [ 17 – 20 ]. In 2012, Sala et al summarized 184 QTLs related GWC and performed MQTL analysis on GWC of maize, 34 MQTLs related to GWC were obtained [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize

et al. 2022

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Background Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits. Results In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism. Conclusions Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.

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“…In the present study, 20 ortho-MQTLs were conserved between maize and rice genomes. Among the 20 ortho-MQTLs, 7 MQTLs (viz., MQTL 2.2, 2.5, 4.5, 4.7, 7.2, and 7.7) were verified by the rice root meta-QTL studies [ 35 , 36 ]. Such conserved ortho-MQTLs suggest the presence of some common regulatory elements that govern the functions of many root-related genes [ 35 , 42 ].…”

Section: Discussionmentioning

confidence: 88%

“…In the present study, 52.9% of MQTLs (36 out of 68) were validated using GWAS-MTAs obtained from ten maize root GWA studies. Such a comparison of the MQTLs with GWAS-based MTAs has been performed in a few earlier studies in maize [ 28 , 32 , 35 , 36 ]. These 36 MQTLs co-localized with MTAs associated with different traits, including root angle, diameter, length, number, area, and root weight.…”

Section: Discussionmentioning

confidence: 99%

“…In maize, MQTL analysis has been conducted for different traits, including multiple abiotic stress tolerance [ 31 ], disease resistance [ 32 ], root-related traits [ 33 ], and popping traits [ 34 ]. Besides maize, MQTL studies have been reported in other crops for root traits, including rice [ 35 , 36 ] and wheat [ 26 , 37 ]. Earlier MQTL analysis for root traits involved QTLs reported from only 20 published interval mapping studies using 512 QTLs [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

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Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

Karnatam

Chhabra

Saini

et al. 2023

IJMS

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Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

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Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach

Abstract: Applying an integrated meta-analysis approach lead to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits.

Cited by 23 publications

References 151 publications

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize

Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

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