scholarly journals Genetic dissection of photosynthetic performances in maize under drought-stressed and well-watered environments

2020 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Yuan Zhong ◽  
Wenli Li ◽  
Dan Zhang
Keyword(s):  
Drought Stress ◽  
Candidate Genes ◽  
Composite Interval Mapping ◽  
Interval Mapping ◽  
Mixed Linear Model ◽  
Joint Analysis ◽  
Carboxylase Activity ◽  
Critical Function ◽  
Photosynthetic Performances ◽  
Two Populations

Abstract BackgroundMaintaining photosynthetic capacity is a critical function that allows maize (Zea mays L.) to adapt to drought stress. The elucidation of genetic controls of photosynthetic performances, and tightly linked molecular markers under water stress are thus of great importance in marker-assisted selection (MAS) breeding. Meanwhile, little is known regarding their genetic controls under drought stress. Two F4 populations were developed to identify quantitative trait loci (QTLs) and dissect the genetic variation underlying six photosynthetic-related traits, namely, net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO2 concentration (Ci), transpiration rate (Tr), ribulose 1,5-biphosphate carboxylase activity (RuBP), and water use efficiency (WUE) under drought-stressed and well-watered environments.ResultsFor two populations, we detected 54 QTLs under drought-stressed and well-watered environments by single-environment mapping with composite interval mapping (CIM), approximately 81.8~100 % QTLs displayed non-additive effects, and 43 of the 54 QTLs were identified under drought-stressed environment. We also dissected 54 QTLs via joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 24 QTLs involved in QTL × environment interactions (QEIs), approximately 87.5 % QEIs were identified under drought-stressed environments, as well as 14 pair epistasis exhibited dominance-by-additive/dominance (DA/DD) effects under constracting environments. We further identified 8 constitutive QTLs (cQTLs) across two populations by CIM/MCIM under multiple environments. Remarkably, bin 1.07_1.10 (cQTL2), bin 6.05 (cQTL5), bin 7.02_7.04 (cQTL6), bin 8.03 (cQTL7), and bin 10.03 (cQTL8) exhibited 5 pleiotropic cQTLs that were consistent with phenotypic correlations among all photosynthetic-related traits. Additionally, 17 candidate genes were validated in above cQTLs.ConclusionsPhotosynthetic performances in maize were predominantly controlled by non-additive and QEIs effects, where more QEIs effects occurred in drought stress. 8 cQTLs affecting six photosynthetic-related traits could be useful for genetic improvement of these traits via QTL pyramiding, corresponding 5 QTLs clusters indicated tight linkage or pleiotropy in the inheritance of these traits, and 17 candidate genes involved in leaf morphology and development, photosynthesis, and stress reponse coincided with above corresponding cQTLs.

scholarly journals Genetic dissection of photosynthetic performances in maize under drought-stressed and well-watered environments

2019 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Yantian Lu ◽  
Mingxing Bai ◽  
Wenli Li ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Drought Stress ◽  
Candidate Genes ◽  
Composite Interval Mapping ◽  
Interval Mapping ◽  
Mixed Linear Model ◽  
Joint Analysis ◽  
Carboxylase Activity ◽  
Critical Function ◽  
Photosynthetic Performances ◽  
Two Populations

Abstract Background: Maintaining photosynthetic capacities is a critical function that allows maize ( Zea mays L.) to adapt to drought stress. The elucidation of genetic controls of photosynthetic performances, and tightly linked molecular markers under water stress are thus of great importance in marker-assisted selection (MAS) breeding. Meanwhile, little is known regarding their genetic controls under drought stress. Two F 4 populations were developed to identify quantitative trait loci (QTLs) and dissect the genetic variation underlying six photosynthetic-related traits, namely, net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO 2 concentration (Ci), transpiration rate (Tr), ribulose 1,5-biphosphate carboxylase activity (RuBP), and water use efficiency (WUE) under drought-stressed and well-watered environments. Results: For two populations, we detected 54 QTLs under drought-stressed and well-watered environments by single-environment mapping with composite interval mapping (CIM), approximately 81.8~100 % QTLs displayed non-additive effects, and 43 of the 54 QTLs were identified under drought-stressed environment. We also dissected 54 QTLs via joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 24 QTLs involved in QTL × environment interactions (QEIs), approximately 87.5 % QEIs were identified under drought-stressed environments, as well as 14 pair epistasis exhibited dominance-by-additive/dominance (DA/DD) effects under constracting environments. We further identified 8 constitutive QTLs (cQTLs) across two populations by CIM/MCIM under multiple environments. Remarkably, bin 1.07_1.10 (cQTL2), bin 6.05 (cQTL5), bin 7.02_7.04 (cQTL6), bin 8.03 (cQTL7), and bin 10.03 (cQTL8) exhibited 5 pleiotropic cQTLs that were consistent with phenotypic correlations among all photosynthetic-related traits. Additionally, 17 candidate genes were validated in above cQTLs. Conclusions: Photosynthetic performances in maize were predominantly controlled by non-additive and QEIs effects, where more QEIs effects occurred in drought stress. 8 cQTLs affecting six photosynthetic-related traits could be useful for genetic improvement of these traits via QTL pyramiding, corresponding 5 QTLs clusters indicated tight linkage or pleiotropy in the inheritance of these traits, and 17 candidate genes involved in leaf morphology and development, photosynthesis, and stress reponse coincided with above corresponding cQTLs.

scholarly journals Comparative QTL analysis and candidate genes identification of seed size, shape and weight in soybean (Glycine max L.)

2021 ◽  
Author(s):  
Mahmoud A Elattar ◽  
Benjamin Karikari ◽  
Shuguang Li ◽  
Shiyu Song ◽  
Yongce Cao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Seed Size ◽  
Composite Interval Mapping ◽  
Mixed Model ◽  
Interval Mapping ◽  
Genetic Maps ◽  
Potential Candidate ◽  
Go Enrichment ◽  
Glycine Max L ◽  
Genomic Regions

Abstract Dissecting the genetic mechanism underlying seed size, shape and weight is essential to these traits for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line populations, LM6 and ZM6, evaluated in multiple environments to identify candidate genes behind seed-related traits major and stable QTLs. A total of 239 and 43 M-QTL were mapped by composite interval mapping and mixed-model based composite interval mapping approaches, respectively, from which 22 common QTLs including four major and novel QTLs. CIM and MCIM approaches identified 180 and 18 novel M-QTLs, respectively. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Seed flatness index QTLs (34 QTLs) were identified and reported for the first time. Seven QTL clusters underlying the inheritance of seed size, shape and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17 and 19 were identified. Gene annotations, gene ontology (GO) enrichment and RNA-seq analyses identified 47 candidate genes for seed-related traits within the genomic regions of those 7 QTL clusters. These genes are highly expressed in seed-related tissues and nodules, that might be deemed as potential candidate genes regulating the above traits in soybean. This study provides detailed information for the genetic bases of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning as well as for MAS targeted at improving these traits individually or concurrently.

scholarly journals Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations

2021 ◽  
Vol 12 ◽  
Author(s):  
Mahmoud A. Elattar ◽  
Benjamin Karikari ◽  
Shuguang Li ◽  
Shiyu Song ◽  
Yongce Cao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Seed Size ◽  
Composite Interval Mapping ◽  
Soybean Seed ◽  
Interval Mapping ◽  
Genetic Maps ◽  
Potential Candidate ◽  
Major Qtls ◽  
Multiple Environments ◽  
Genomic Regions

Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.

scholarly journals Mapping quantitative trait loci for yield-related traits and predicting candidate genes for grain weight in maize

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yanming Zhao ◽  
Chengfu Su
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Developmental Stages ◽  
Interval Mapping ◽  
Kernel Weight ◽  
Grain Weight ◽  
Trait Loci ◽  
Stable Qtls

Abstract Quantitative trait loci (QTLs) mapped in different genetic populations are of great significance for marker-assisted breeding. In this study, an F2:3 population were developed from the crossing of two maize inbred lines SG-5 and SG-7 and applied to QTL mapping for seven yield-related traits. The seven traits included 100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, ear weight, and grain weight per plant. Based on an ultra-high density linkage map, a total of thirty-three QTLs were detected for the seven studied traits with composite interval mapping (CIM) method, and fifty-four QTLs were indentified with genome-wide composite interval mapping (GCIM) methods. For these QTLs, Fourteen were both detected by CIM and GCIM methods. Besides, eight of the thirty QTLs detected by CIM were identical to those previously mapped using a F2 population (generating from the same cross as the mapping population in this study), and fifteen were identical to the reported QTLs in other recent studies. For the fifty-four QTLs detected by GCIM, five of them were consistent with the QTLs mapped in the F2 population of SG-5 × SG-7, and twenty one had been reported in other recent studies. The stable QTLs associated with grain weight were located on maize chromosomes 2, 5, 7, and 9. In addition, differentially expressed genes (DEGs) between SG-5 and SG-7 were obtained from the transcriptomic profiling of grain at different developmental stages and overlaid onto the stable QTLs intervals to predict candidate genes for grain weight in maize. In the physical intervals of confirmed QTLs qKW-7, qEW-9, qEW-10, qGWP-6, qGWP-8, qGWP-10, qGWP-11 and qGWP-12, there were 213 DEGs in total. Finally, eight genes were predicted as candidate genes for grain size/weight. In summary, the stable QTLs would be reliable and the candidate genes predicted would be benefit for maker assisted breeding or cloning.

scholarly journals Time-Related Mapping of Quantitative Trait Loci Underlying Tiller Number in Rice

Genetics ◽  
1999 ◽  
Vol 151 (1) ◽  
pp. 297-303 ◽  
Author(s):  
Wei-Ren Wu ◽  
Wei-Ming Li ◽  
Ding-Zhong Tang ◽  
Hao-Ran Lu ◽  
A J Worland
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Interval Mapping ◽  
Tiller Number ◽  
Multiple Trait ◽  
Phenotypic Data ◽  
Recombinant Inbred Population ◽  
Trait Loci ◽  
Final Observation

Abstract Using time-related phenotypic data, methods of composite interval mapping and multiple-trait composite interval mapping based on least squares were applied to map quantitative trait loci (QTL) underlying the development of tiller number in rice. A recombinant inbred population and a corresponding saturated molecular marker linkage map were constructed for the study. Tiller number was recorded every 4 or 5 days for a total of seven times starting at 20 days after sowing. Five QTL were detected on chromosomes 1, 3, and 5. These QTL explained more than half of the genetic variance at the final observation. All the QTL displayed an S-shaped expression curve. Three QTL reached their highest expression rates during active tillering stage, while the other two QTL achieved this either before or after the active tillering stage.

scholarly journals Comprehensive analysis and identification of drought-responsive candidate NAC genes in three semi-arid tropics (SAT) legume crops

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sadhana Singh ◽  
Himabindu Kudapa ◽  
Vanika Garg ◽  
Rajeev K. Varshney
Keyword(s):  
Drought Stress ◽  
Candidate Genes ◽  
Developmental Stages ◽  
Biological Activities ◽  
Expression Patterns ◽  
Genome Wide ◽  
Legume Crops ◽  
Root Tissues ◽  
Semi Arid ◽  
Comprehensive Study

Abstract Background Chickpea, pigeonpea, and groundnut are the primary legume crops of semi-arid tropics (SAT) and their global productivity is severely affected by drought stress. The plant-specific NAC (NAM - no apical meristem, ATAF - Arabidopsis transcription activation factor, and CUC - cup-shaped cotyledon) transcription factor family is known to be involved in majority of abiotic stresses, especially in the drought stress tolerance mechanism. Despite the knowledge available regarding NAC function, not much information is available on NAC genes in SAT legume crops. Results In this study, genome-wide NAC proteins – 72, 96, and 166 have been identified from the genomes of chickpea, pigeonpea, and groundnut, respectively, and later grouped into 10 clusters in chickpea and pigeonpea, while 12 clusters in groundnut. Phylogeny with well-known stress-responsive NACs in Arabidopsis thaliana, Oryza sativa (rice), Medicago truncatula, and Glycine max (soybean) enabled prediction of putative stress-responsive NACs in chickpea (22), pigeonpea (31), and groundnut (33). Transcriptome data revealed putative stress-responsive NACs at various developmental stages that showed differential expression patterns in the different tissues studied. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression patterns of selected stress-responsive, Ca_NAC (Cicer arietinum - 14), Cc_NAC (Cajanus cajan - 15), and Ah_NAC (Arachis hypogaea - 14) genes using drought-stressed and well-watered root tissues from two contrasting drought-responsive genotypes of each of the three legumes. Based on expression analysis, Ca_06899, Ca_18090, Ca_22941, Ca_04337, Ca_04069, Ca_04233, Ca_12660, Ca_16379, Ca_16946, and Ca_21186; Cc_26125, Cc_43030, Cc_43785, Cc_43786, Cc_22429, and Cc_22430; Ah_ann1.G1V3KR.2, Ah_ann1.MI72XM.2, Ah_ann1.V0X4SV.1, Ah_ann1.FU1JML.2, and Ah_ann1.8AKD3R.1 were identified as potential drought stress-responsive candidate genes. Conclusion As NAC genes are known to play role in several physiological and biological activities, a more comprehensive study on genome-wide identification and expression analyses of the NAC proteins have been carried out in chickpea, pigeonpea and groundnut. We have identified a total of 21 potential drought-responsive NAC genes in these legumes. These genes displayed correlation between gene expression, transcriptional regulation, and better tolerance against drought. The identified candidate genes, after validation, may serve as a useful resource for molecular breeding for drought tolerance in the SAT legume crops.

Bayesian Mapping of Multiple Quantitative Trait Loci From Incomplete Inbred Line Cross Data

Genetics ◽  
1998 ◽  
Vol 148 (3) ◽  
pp. 1373-1388
Author(s):  
Mikko J Sillanpää ◽  
Elja Arjas
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Backcross Progeny ◽  
Random Variable ◽  
Interval Mapping ◽  
Mapping Method ◽  
Structure Mapping ◽  
Standard Interval ◽  
Trait Loci

Abstract A novel fine structure mapping method for quantitative traits is presented. It is based on Bayesian modeling and inference, treating the number of quantitative trait loci (QTLs) as an unobserved random variable and using ideas similar to composite interval mapping to account for the effects of QTLs in other chromosomes. The method is introduced for inbred lines and it can be applied also in situations involving frequent missing genotypes. We propose that two new probabilistic measures be used to summarize the results from the statistical analysis: (1) the (posterior) QTL-intensity, for estimating the number of QTLs in a chromosome and for localizing them into some particular chromosomal regions, and (2) the location wise (posterior) distributions of the phenotypic effects of the QTLs. Both these measures will be viewed as functions of the putative QTL locus, over the marker range in the linkage group. The method is tested and compared with standard interval and composite interval mapping techniques by using simulated backcross progeny data. It is implemented as a software package. Its initial version is freely available for research purposes under the name Multimapper at URL http://www.rni.helsinki.fi/~mjs.

scholarly journals Candidate genes and SNPs associated with stomatal conductance under drought stress in Vitis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Massimiliano Trenti ◽  
Silvia Lorenzi ◽  
Pier Luigi Bianchedi ◽  
Daniele Grossi ◽  
Osvaldo Failla ◽  
...  
Keyword(s):  
Drought Stress ◽  
Stomatal Conductance ◽  
Candidate Genes ◽  
Water Deficit ◽  
Genetic Basis ◽  
Phenotypic Diversity ◽  
Snp Array ◽  
A Genome ◽  
Raffinose Synthase ◽  
Response To Water

Abstract Background Understanding the complexity of the vine plant’s response to water deficit represents a major challenge for sustainable winegrowing. Regulation of water use requires a coordinated action between scions and rootstocks on which cultivars are generally grafted to cope with phylloxera infestations. In this regard, a genome-wide association study (GWAS) approach was applied on an ‘ad hoc’ association mapping panel including different Vitis species, in order to dissect the genetic basis of transpiration-related traits and to identify genomic regions of grape rootstocks associated with drought tolerance mechanisms. The panel was genotyped with the GrapeReSeq Illumina 20 K SNP array and SSR markers, and infrared thermography was applied to estimate stomatal conductance values during progressive water deficit. Results In the association panel the level of genetic diversity was substantially lower for SNPs loci (0.32) than for SSR (0.87). GWAS detected 24 significant marker-trait associations along the various stages of drought-stress experiment and 13 candidate genes with a feasible role in drought response were identified. Gene expression analysis proved that three of these genes (VIT_13s0019g03040, VIT_17s0000g08960, VIT_18s0001g15390) were actually induced by drought stress. Genetic variation of VIT_17s0000g08960 coding for a raffinose synthase was further investigated by resequencing the gene of 85 individuals since a SNP located in the region (chr17_10,497,222_C_T) was significantly associated with stomatal conductance. Conclusions Our results represent a step forward towards the dissection of genetic basis that modulate the response to water deprivation in grape rootstocks. The knowledge derived from this study may be useful to exploit genotypic and phenotypic diversity in practical applications and to assist further investigations.

Mapping QTLs for yield components and chlorophyll a fluorescence parameters in wheat under three levels of water availability

2011 ◽  
Vol 9 (2) ◽  
pp. 291-295 ◽  
Author(s):  
Ilona Czyczyło-Mysza ◽  
Izabela Marcińska ◽  
Edyta Skrzypek ◽  
Małgorzata Chrupek ◽  
Stanisław Grzesiak ◽  
...  
Keyword(s):  
Drought Stress ◽  
Chlorophyll A ◽  
Chlorophyll A Fluorescence ◽  
Wheat Yield ◽  
Dry Weight ◽  
Interval Mapping ◽  
Main Stem ◽  
Severe Drought ◽  
Single Marker Analysis ◽  
Fluorescence Parameters

Drought is one of the major factors limiting wheat yield in many developing countries worldwide. Parameters of chlorophyll a fluorescence kinetics under drought stress conditions have been used to characterize dehydration tolerance in wheat. In the present study, a set of 94 doubled haploid lines obtained from Chinese Spring × SQ1 (CSDH), mapped with 450 markers, was evaluated for yield (grain dry weight/main stem ear), number of grains/main stem ear (NG) and chlorophyll a fluorescence parameters (FC) under moderate and severe drought stress, and compared with results for well-watered plants. quantitative trait loci (QTLs) were identified using Windows QTLCartographer version 2.5 software and the results were analysed using single-marker analysis (SMA) and composite interval mapping (CIM). Analysis using SMA and CIM showed mostly similar QTLs for all traits, though more QTLs were identified by SMA than by CIM. The genetic control of yield, NG and FC varied considerably between drought-stressed and non-stressed plants. Although no major QTL co-locations were found for yield and FC using CIM, the co-location of QTLs for NG, yield and Fv/Fm in drought-stressed plants was observed on chromosome 5A using SMA.

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