Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Karnatam KS

PROVIDER: S-EPMC10093813 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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

Karnatam Krishna Sai KS Chhabra Gautam G Saini Dinesh Kumar DK Singh Rajveer R Kaur Gurwinder G Praba Umesh Preethi UP Kumar Pankaj P Goyal Simran S Sharma Priti P Ranjan Rumesh R Sandhu Surinder K SK Kumar Ramesh R Vikal Yogesh Y

International journal of molecular sciences 20230324 7

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 ...[more]

PMID: 37047112

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Project description:IntroductionValidations of previously detected quantitative trait loci (QTLs) to assess their reliability are crucial before implementing breeding programs. The objective of this study was to determine the reliability and practical usefulness of previously reported QTLs for resistance to stem tunneling by the Mediterranean stem borer (MSB) and yield. These authors used approximately 600 recombinant inbred lines (RILs) from a multiparent advanced generation intercross (MAGIC) population to map QTL using a genome-wide association study (GWAS) approach.MethodsWe identified RILs situated at the extremes of resistance and yield distributions within the whole MAGIC, and those QTLs were evaluated per se and crossed to a tester (A638) using lattice designs. In each set, a significant single-nucleotide polymorphism (SNP) was considered validated if (1) the same SNP was associated with the trait with a p-value < 0.02, or (2) within a ±2-Mbp interval, an SNP associated with the trait exhibited a p-value < 0.02 and demonstrated linkage disequilibrium (r2 > 0.2) with the SNPs previously reported.Results and discussionThe novel QTL validation approach was implemented using improved experimental designs that led to higher heritability estimates for both traits compared to those estimated with the whole MAGIC population. The procedure used allowed us to jointly validate several QTL and to ascertain their possible contribution to hybrid improvement. Specifically, nearly three-quarters of the QTLs for tunnel length were confirmed. Notably, QTLs located in the genomic region 6.05-6.07 were consistently validated across different sets and have been previously linked to resistance against stalk tunneling in various mapping populations. For grain yield, approximately 10 out of 16 QTLs were validated. The validation rate for yield was lower than for tunnel length, likely due to the influence of dominance and/or epistatic effects. Overall, 9 out of 21 QTLs for tunnel length and 6 out of 17 QTLs for grain yield identified in our previous research were validated across both validation sets, indicating a moderate genetic correlation between per se and testcross performance of inbred lines. These findings offer insights into the reliability of QTL and genomic predictions, both derived from assessments conducted on the entire MAGIC population. Genomic predictions for tunnel length based on inbred line evaluations could be useful to develop more resistant hybrids; meanwhile, genomic prediction for yield could only be valid in a homozygous background.

Project description:Root system architecture (RSA) plays an important role in the acquisition of both nitrogen (N) and phosphorus (P) from the environment. Currently RSA is rarely considered as criteria for selection to improve nutrient uptake efficiency in crop breeding. Under field conditions roots can be greatly influenced by uncontrolled environment factors. Therefore, it is necessary to develop fast selection methods for evaluating root traits of young seedlings in the lab which can then be related to high nutrient efficiency of adult plants in the field. Here, a maize recombination inbred line (RILs) population was used to compare the genetic relationship between RSA and nitrogen and phosphorous efficiency traits. The phenotypes of eight RSA-related traits were evaluated in young seedlings using three different growth systems (i.e., paper roll, hydroponics and vermiculite), and then subjected to correlation analysis with N efficiency and P efficiency related traits measured under field conditions. Quantitative trait loci (QTL) of RSA were determined and QTL co-localizations across different growth systems were further analyzed. Phenotypic associations were observed for most of RSA traits among all three culture systems. RSA-related traits in hydroponics and vermiculite weakly correlated with Nitrogen (NupE) uptake efficiency (r = 0.17-0.31) and Phosphorus (PupE) uptake efficiency (r = 0.22-0.34). This correlation was not found in the paper roll growth system. A total of 14 QTLs for RSA were identified in paper rolls, 18 in hydroponics, and 14 in vermiculite. Co-localization of QTLs for RSA traits were identified in six chromosome regions of bin 1.04/1.05, 1.06, 2.04/2.05, 3.04, 4.05, and 5.04/5.05. The results suggest the problem of using the phenotype from one growth system to predict those in another growth system. Assessing RSA traits at the seedling stage using either hydroponics or a vermiculite system appears better suited than the paper roll system as an important index to accelerate the selection of high N and P efficient genotypes for maize breeding programs.

Project description:BackgroundBreeding for new maize varieties with propitious root systems has tremendous potential in improving water and nutrients use efficiency and plant adaptation under suboptimal conditions. To date, most of the previously detected root-related trait genes in maize were new without functional verification. In this study, seven seedling root architectural traits were examined at three developmental stages in a recombinant inbred line population (RIL) of 179 RILs and a genome-wide association study (GWAS) panel of 80 elite inbred maize lines through quantitative trait loci (QTL) mapping and genome-wide association study.ResultsUsing inclusive composite interval mapping, 8 QTLs accounting for 6.44-8.83 % of the phenotypic variation in root traits, were detected on chromosomes 1 (qRDWv3-1-1 and qRDW/SDWv3-1-1), 2 (qRBNv1-2-1), 4 (qSUAv1-4-1, qSUAv2-4-1, and qROVv2-4-1), and 10 (qTRLv1-10-1, qRBNv1-10-1). GWAS analysis involved three models (EMMAX, FarmCPU, and MLM) for a set of 1,490,007 high-quality single nucleotide polymorphisms (SNPs) obtained via whole genome next-generation sequencing (NGS). Overall, 53 significant SNPs with a phenotypic contribution rate ranging from 5.10 to 30.2 % and spread all over the ten maize chromosomes exhibited associations with the seven root traits. 17 SNPs were repeatedly detected from at least two growth stages, with several SNPs associated with multiple traits stably identified at all evaluated stages. Within the average linkage disequilibrium (LD) distance of 5.2 kb for the significant SNPs, 46 candidate genes harboring substantial SNPs were identified. Five potential genes viz. Zm00001d038676, Zm00001d015379, Zm00001d018496, Zm00001d050783, and Zm00001d017751 were verified for expression levels using maize accessions with extreme root branching differences from the GWAS panel and the RIL population. The results showed significantly (P < 0.001) different expression levels between the outer materials in both panels and at all considered growth stages.ConclusionsThis study provides a key reference for uncovering the complex genetic mechanism of root development and genetic enhancement of maize root system architecture, thus supporting the breeding of high-yielding maize varieties with propitious root systems.

Dataset Information

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

Publications

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

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