Action of multiple intra-QTL genes concerted around a co-localized transcription factor underpins a large effect QTL

Dixit, Shalabh; Biswal, Akshaya Kumar; Min, Aung Myat; Henry, Amelia; Oane, R.; Raorane, Manish L.; Longkumer, Toshisangba; Pabuayon, Isaiah Catalino M.; Mutte, Sumanth K.; Vardarajan, Adithi R.; Miró, Berta; Govindan, Ganesan; Albano-Enriquez, Blesilda; Pueffeld, Mandy; Sreenivasulu, Nese; Slamet‐Loedin, Inez H.; Sundarvelpandian, Kalaipandian; Tsai, Yun-Long; Raghuvanshi, Saurabh; Hsing, Yue‐Ie C.; Kumar, Arvind; Kohli, Ajay

doi:10.1038/srep15183

Cited by 64 publications

(70 citation statements)

References 75 publications

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“…Alternatively, identification of large-effect QTLs which are more stable across environments and genetic backgrounds seems to be the most promising way of ensuring impact from genomics-assisted breeding methods. Dixit et al (2015) confirmed the multi-genic and multi-environment effectiveness of qDTY 12.1 , a large-effect QTL identified on chromosome 12 of the rice genome. They confirmed the central role of the no apical meristem (OsNAM 12.1 ) transcription factor in the activity of qDTY 12.1 together with promoters of six intra-QTL genes with NAM binding sites as well as three co-localized and/or partially co-expressed genes of OsNAM 12.1 .…”

Section: Manipulating Root System Architecture For Abiotic Stress Tolsupporting

confidence: 57%

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

2016

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The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture (RSA), made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops (RTCs) such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive ‘green revolution.’ In the current review, we discuss RSA with special reference to RTCs, and how knowledge on genetics of RSA can be manipulated to improve their tolerance to abiotic stresses.

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Section: Manipulating Root System Architecture For Abiotic Stress Tolsupporting

confidence: 57%

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

2016

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“…Initially, quantitative trait loci (QTLs) in model organisms were generally assumed to harbor one causal and multiple passenger alleles that affect a single causal gene; however, dissection of QTLs in inbred organisms has identified evidence of more than one gene in the same region. [6][7][8] In addition to identifying multiple genes at QTLs, fine-mapping efforts in model organisms have suggested multiple causal variants at a single locus. 8,9 Thus, genetic studies in model organisms suggest complex mechanisms that can involve multiple genes and variants at a single locus.…”

Section: Introductionmentioning

confidence: 99%

Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci

Cannon

Mohlke

2018

The American Journal of Human Genetics

104

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Genome-wide association studies (GWASs) have identified thousands of loci associated with hundreds of complex diseases and traits, and progress is being made toward elucidating the causal variants and genes underlying these associations. Functional characterization of mechanisms at GWAS loci is a multi-faceted challenge. Challenges include linkage disequilibrium and allelic heterogeneity at each locus, the noncoding nature of most loci, and the time and cost needed for experimentally evaluating the potential mechanistic contributions of genes and variants. As GWAS sample sizes increase, more loci are identified, and the complexities of individual loci emerge. Loci can consist of multiple association signals, each of which can reflect the influence of multiple variants, inseparable by association analyses. Each signal within a locus can influence the same or different target genes. Experimental studies of genes and variants can differ on the basis of cell type, cellular environment, or other context-specific variables. In this review, we describe the complexity of mechanisms at GWAS loci-including multiple signals, multiple variants, and/or multiple genes-and the implications these complexities hold for experimental study design and interpretation of GWAS mechanisms.

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“…S9). A multiple intraQTL in the qDTY 12.1 region centered on the NAM gene (OsNAM 12.1 ) was suggested to provide a concerted drought response (Dixit et al 2015). In our study, all genes in the qDTY 12.1 region but one (LOC_Os12g29220, nodulin Mt3, OsMtN3 12.1 ) co-localizing with the NAM gene were not expressed (Table S1).…”

Section: Test Of Ase In the Hybridmentioning

confidence: 61%

cis dominantly explains regulatory divergence between two indica rice genotypes; drought further enhances regulatory differences

Ereful

Liu

Kao

et al. 2019

Preprint

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Background. cis and/or trans regulatory divergence within or between related taxa on a genome-wide scale has been largely unexamined in crops, more so, the effect of stress on cis/trans architecture. In this study, the indica genotypes IR64, an elite drought-susceptible lowland variety, and Apo (IR55423-01 or NSIC RC9), a moderate drought-tolerant upland genotype together with their hybrid (IR64 × Apo) were exposed to non-and water-stress conditions. Evidence of cis and/or trans regulatory differences was tested between these two indica rice genotypes.Results. By sequencing (RNA-seq) the parents and their hybrid, we are able to map genes diverging in cis and/or trans factors between the two genotypes. Under non-stress conditions, cis dominantly explains (11.2%) regulatory differences, followed by trans (8.9%). Further analysis showed that water-limiting conditions largely affect trans and cis + trans factors.Between the two inbred lines, Apo appears to exhibit higher expression fold change of genes enriched in "response to stress" and "photosynthesis" under non-and water-stress conditions.On the molecular level, cis and/or trans regulatory divergence explains their genotypic differences and differential drought response.Conclusions. Parent-hybrid RNA-seq has the potential to identify genes diverging in cis and/or trans factors even between intra-sub-specifically related genotypes. By comparing cis/trans landscape under stressed and unstressed conditions, this approach has the ability to assess the impact of drought on gene expression. Computational analysis and association of several drought-yield QTL markers with cis-and/or trans-diverging genes provide converging evidences suggestive of a potential approach to identify trait-associated candidate genes using hybrids and their parents alone.3

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Action of multiple intra-QTL genes concerted around a co-localized transcription factor underpins a large effect QTL

Cited by 64 publications

References 75 publications

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci

cis dominantly explains regulatory divergence between two indica rice genotypes; drought further enhances regulatory differences

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