scholarly journals Precision Mapping of a Maize MAGIC Population Identified a Candidate Gene for the Senescence-Associated Physiological Traits

2021 ◽  
Vol 12 ◽  
Author(s):  
Marlon Caicedo ◽  
Eduardo D. Munaiz ◽  
Rosa A. Malvar ◽  
José C. Jiménez ◽  
Bernardo Ordas

Senescence is an important trait in maize (Zea mais L.), a key crop that provides nutrition values and a renewable source of bioenergy worldwide. Genome-wide association studies (GWAS) can be used to identify causative genetic variants that influence the major physiological measures of senescence, which is used by plants as a defense mechanism against abiotic and biotic stresses affecting its performance. We measured four physiological and two agronomic traits that affect senescence. Six hundred seventy-two recombinant inbred lines (RILs) were evaluated in two consecutive years. Thirty-six candidate genes were identified by genome-wide association study (GWAS), and 11 of them were supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport, and sink activity. We identified a candidate gene, Zm00001d043586, significantly associated with chlorophyll, and independently studied its transcription expression in an independent panel. Our results showed that Zm00001d043586 affects chlorophyl rate degradation, a key determinant of senescence, at late plant development stages. These results contribute to better understand the genetic relationship of the important trait senescence with physiology related parameters in maize and provide new putative molecular markers that can be used in marker assisted selection for line development.

2010 ◽  
Vol 42 (11) ◽  
pp. 961-967 ◽  
Author(s):  
Xuehui Huang ◽  
Xinghua Wei ◽  
Tao Sang ◽  
Qiang Zhao ◽  
Qi Feng ◽  
...  

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yousef Rahimi ◽  
Mohammad Reza Bihamta ◽  
Alireza Taleei ◽  
Hadi Alipour ◽  
Pär K. Ingvarsson

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1446-1446
Author(s):  
Paola Sebastiani ◽  
Nadia Timofeev ◽  
Steven H. Hartley ◽  
Daniel Dworkis ◽  
Lindsay Farrer ◽  
...  

Abstract Genome-wide association studies (GWAS) allow an assessment of associations between single nucleotide polymorphisms (SNPs) and phenotypes or traits of interest in a non-hypothesis driven manner. Previously, based on limited candidate gene association analysis, we showed that survival in sickle cell anemia and exceptional longevity (EL) in the general population share common genetic modifiers (Blood, 52a, 2007). This preliminary result suggested that aging mechanisms and associated genes might play a role in the variability of sickle cell anemia. Using GWAS, we now report strong evidence supporting this conjecture. We conducted a GWAS using an Illumina platform that permits genotyping up to 1 million haplotype-tagging SNPs spread across the genome, as well as other types of genetic variation, in large populations. We used the Illumina 610K SNP array to discover SNPs that are associated with different degrees of severity of sickle cell anemia in 684 patients. Patients were assigned to either a severe or mild disease category based on an integrated measure of sickle cell anemia severity that was determined by a network model that assigns a score predicting the risk of death (Blood110: 272, 2007). In parallel, we used the Illumina 370K SNP and the Illumina 1M SNP arrays to discover SNPs associated with EL in 877 centenarians enrolled in the New England Centenarian Study and 1,850 younger controls. In both studies, each SNP was tested for association with the traits of severe or less severe sickle cell anemia and EL using Bayesian tests of general, dominant and recessive associations (BMC Genet.9, 2008). We then identified those SNPs satisfying these 3 criteria: at least one model of association was 10 times more likely than no association in the GWAS of EL; the same model of association was at least 3 times more likely (because of the smaller sample size) than no association in the GWAS of sickle cell anemia severity, the same allele was more frequent in centenarians and in sickle cell anemia patients with milder disease. This analysis identified 140 SNPs in more than 50 genes and some intergenic regions that showed robust and consistent associations. This number is more than twice the number that would be expected by chance. Among the most ‘significant’ genes with associated SNPs were ARFGEF2, ADAMTS12, DOK5, DPP10, FGF21, KCNQ1, IRF4, MYO3B NAIF1, TNNI3K; more than one SNP was found in ARFGEF2, NAIF1, DPP10, SORCS3, TNNI3K. KCNQ1 has a putative role in blood circulation and regulation of heart contraction. The frequency of the common genotype for SNP rs108961 increases by almost 60% in sickle cell anemia patients with severe disease (27% versus 43%). The same common genotype in random Caucasian controls has frequency 34% that decreases to 29% in centenarians. Mutations in this gene are associated with long and short QT syndrome, with familial atrial fibrillation, heart disease and sudden death. SNPs in 2 of the genes (HAO2, a peroxisome protein involved in fatty acid oxidation, and MAP2K1, a MAP kinase involved in multiple biochemical signals) that were significantly associated with both sickle cell disease severity and EL in our earlier candidate gene studies, were also associated in the GWAS. GWAS also revealed significant association with CDKN2A, a cyclin-dependent kinase that has been associated with Type 2 diabetes, risk of myocardial infarction and triglyceride levels in several GWAS, and with FGF21, the fibroblast growth factor 21 precursor that has been shown to regulate glucose metabolism. CDKN2A has been associated with disease free survival in other studies. Common metabolic pathways are likely to influence the chance of developing complications of Mendelian and multigenic diseases and the likelihood of achieving EL. This might explain the commonality of genes whose SNPs are associated with the vascular complications of sickle cell anemia, arteriosclerosis and diabetes. A new paradigm suggests that hitherto unexpected genetic differences modulate a limited number of pathways that form a common route toward determining good health and disease.


Genomics ◽  
2009 ◽  
Vol 93 (5) ◽  
pp. 415-419 ◽  
Author(s):  
Stefan Wilkening ◽  
Bowang Chen ◽  
Justo Lorenzo Bermejo ◽  
Federico Canzian

2021 ◽  
Author(s):  
Suong T. Cu ◽  
Nicholas Warnock ◽  
Julie Pasuquin ◽  
Michael Dingkuhn ◽  
James Stangoulis

Abstract This study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight (TGW). GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 controlling the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on TGW and multiple grain elements were elucidated through the involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suong T. Cu ◽  
Nicholas I. Warnock ◽  
Julie Pasuquin ◽  
Michael Dingkuhn ◽  
James Stangoulis

AbstractThis study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.


2021 ◽  
Author(s):  
Huanhuan Zhao ◽  
Keith W. Savin ◽  
Yongjun Li ◽  
Edmond J Breen ◽  
Pankaj Maharjan ◽  
...  

Abstract Background: Safflower (Carthamus tinctorius L.) has been cultivated worldwide for centuries, originally as a source of textile dyes. Modern safflower breeding has focused on high grain and oil yield and broad adaptability. Here, a genome-wide association study was conducted using a globally diverse Genebank collection of 406 accessions, which included landraces, breeding lines and elite cultivars. We explored the genetic architecture and genotype-by-environment interaction (G × E) patterns of grain yield (YP), days to flowering (DF ), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Results: Phenotypic variation within the global collection was observed for all traits under differed water stress environments. Two mixed linear models were adopted, and YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. Ninety-two marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites was identified for all traits. Five MTAs were associated with multiple traits, 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR and marker effects were consistent with phenotypic observations in different environments. The thresholds of different GWAS methods used in the study affected the number of MTAs identified for complex traits. Conclusions: This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments. This knowledge is essential to breed for high grain and oil yield and local adaption in safflower.


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