scholarly journals Population genetic structure and association mapping for iron toxicity tolerance in rice

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246232
Author(s):  
S. Pawar ◽  
E. Pandit ◽  
I. C. Mohanty ◽  
D. Saha ◽  
S. K. Pradhan
Keyword(s):  
Genetic Variation ◽  
Genetic Structure ◽  
Association Mapping ◽  
Stress Tolerance ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Mixed Linear Model ◽  
Iron Toxicity ◽  
Rice Grain ◽  
Fe Toxicity

Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.

Association mapping of genomic loci linked with Fusarium wilt resistance (Foc2) in chickpea

2021 ◽  
pp. 1-8
Author(s):  
Uday Chand Jha ◽  
Rintu Jha ◽  
Abhishek Bohra ◽  
Lakshmaiah Manjunatha ◽  
Parasappa Rajappa Saabale ◽  
...  
Keyword(s):  
Association Mapping ◽  
Linear Model ◽  
Fusarium Wilt ◽  
Generalized Linear Model ◽  
Mixed Linear Model ◽  
Diversity Analysis ◽  
Breeding Lines ◽  
Genetic Diversity Analysis ◽  
Simple Sequence ◽  
Model Approach

Abstract Improving plant resistance against Fusarium wilt (FW) is key to sustaining chickpea production worldwide. Given this, the current study tested a set of 75 FW-responsive chickpea breeding lines including checks in a wilt-sick plot for two consecutive years (2016 and 2017). Genetic diversity analysis using 75 simple sequence repeats (SSRs) revealed a total of 267 alleles with an average of 3.56 alleles per marker. The entire set was divided into two major classes based on clustering method and factorial analysis. Similarly, STRUCTURE analysis placed the 75 genotypes into three distinct sub-groups (K = 3). Marker-trait association (MTA) analysis using the generalized linear model approach revealed nine and eight significant MTAs for FW resistance in the years 2016 and 2017, respectively. Three significant MTAs were obtained for FW resistance following the mixed linear model approach for both years. The SSR markers CESSR433, NCPGR21 and ICCM0284 could be potentially employed for targeted and accelerated improvement of FW resistance in chickpea. To the best of our knowledge, this is the first report on association mapping of the genomic loci controlling FW (Foc2) resistance in chickpea.

scholarly journals Linkage disequilibrium and association mapping of fibre quality traits in elite Asiatic cotton (Gossypium arboreum) germplasm populations

2017 ◽  
Vol 53 (No. 4) ◽  
pp. 159-167 ◽  
Author(s):  
K. Sethi ◽  
P. Siwach ◽  
S.K. Verma
Keyword(s):  
Linkage Disequilibrium ◽  
Association Mapping ◽  
Linear Model ◽  
Ssr Markers ◽  
Mixed Linear Model ◽  
Quality Traits ◽  
Fibre Quality ◽  
Gossypium Arboreum ◽  
Mixed Ancestry ◽  
Ssr Loci

Cotton productivity has been hindered by the narrow genetic base of cultivated cotton. Linkage disequilibrium-based association mapping has become a powerful molecular tool to dissect and exploit genetic diversity. In the present study, population structure and marker-trait associations for fibre quality traits in genotypes belonging to six races of Gossypium arboreum were assessed. Out of 300 simple sequence repeat (SSR) markers, 100 were found polymorphic, yielding a total of 240 alleles (all polymorphic). Structure analysis revealed allelic admixtures between genotypes. A Q-matrix exhibited mixed ancestry for the majority of genotypes, the race indicum forming a significant percent ancestry for almost all genotypes. At significant threshold values of r<sup>2</sup> ≥ 0.05, 7.37% of SSR loci showed significant linkage disequilibrium (LD), while at highly significant threshold of r<sup>2</sup> ≥ 0.1, the value was reduced to 5.31%. LD clearly decayed within the genetic distance of 9–10 cM, with r<sup>2</sup> ≥ 0.1. Twenty-eight SSR markers were found associated with six fibre quality traits using general linear model and mixed linear model.

scholarly journals Mixed Linear Model Approaches of Association Mapping for Complex Traits Based on Omics Variants

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Fu-Tao Zhang ◽  
Zhi-Hong Zhu ◽  
Xiao-Ran Tong ◽  
Zhi-Xiang Zhu ◽  
Ting Qi ◽  
...  
Keyword(s):  
Association Mapping ◽  
Linear Model ◽  
Complex Traits ◽  
Mixed Linear Model

scholarly journals Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jindong Liu ◽  
Junhui Zhan ◽  
Jingguang Chen ◽  
Xiang Lu ◽  
Shuai Zhi ◽  
...  
Keyword(s):  
Linear Model ◽  
Association Analysis ◽  
Zinc Content ◽  
Mixed Linear Model ◽  
Rice Grain ◽  
Phenotypic Variance ◽  
Breeding Lines ◽  
Breeding Populations ◽  
Grain Zinc ◽  
Zn Homeostasis

Several key genes governing Zn homeostasis and grain zinc content (GZC) have been functionally characterized. However, the effects of these genes in diverse breeding populations have not been evaluated; thus, their availability in breeding is unclear. In this study, the effects of 65 genes related to rice zinc responses on GZC were evaluated using two panels of breeding lines, and the superior haplotypes were identified. One panel consisted of mega varieties from the International Rice Research Institute (IRRI), South Asia, and Southeast Asia (SEA), and the other panel is breeding lines/varieties from South China (SC). In addition, a multiparent advanced generation intercross (MAGIC) population, named as DC1, was also employed. Three analytical methods, single-locus mixed linear model (SL-MLM), multilocus random-SNP-effect mixed linear model (mrMLM), and haplotype-based association analysis (Hap-AA), were applied. OsIDEF1 (which explained 12.3% of the phenotypic variance) and OsZIFL7 (8.3–9.1%), OsZIP7 (18.9%), and OsIRT1 (17.9%) were identified by SL-MLM in SEA and SC, respectively, whereas no gene was significantly associated with GZC in DC1. In total, five (OsNRAMP6, OsYSL15, OsIRT1, OsIDEF1, and OsZIFL7, 7.70–15.39%), three (OsFRDL1, OsIRT1, and OsZIP7, 11.87–17.99%), and two (OsYSL7 and OsZIP7, 9.85–10.57%) genes were detected to be significantly associated with GZC in SEA, SC, and DC1 by mrMLM, respectively. Hap-AA indicated that Hap1-OsNRAMP5, Hap5-OsZIP4, Hap1-OsIRT1, Hap3-OsNRAMP6, Hap6-OsMTP1, and Hap6-OsYSL15 had the largest effects for GZC in SEA, whereas Hap3-OsOPT7, Hap4-OsIRT2, Hap4-OsZIP7, Hap5-OsIRT1, and Hap5-OsSAMS1 were the most significant in the SC population. Besides, superior alleles were also identified for the significant genes. The genes significantly associated with GZC and their superior haplotypes identified in different panels could be used in enhancing GZC through molecular breeding, which could further address the problem of Zn malnutrition among rice consumers.

scholarly journals Association Mapping for Drought Tolerance and Yield-Related Traits in Cowpea Accessions

2020 ◽  
Author(s):  
Gabriel Vusanimuzi Nkomo ◽  
Moosa Sedibe ◽  
Maletsema Alina Mofokeng ◽  
Rian Pierneef
Keyword(s):  
Drought Tolerance ◽  
Association Mapping ◽  
Linear Model ◽  
Genotyping By Sequencing ◽  
Mixed Linear Model ◽  
Snp Markers ◽  
P Value ◽  
Nucleotide Polymorphisms ◽  
Single Marker ◽  
Peak Of Delta

The objective of this study were to conduct association mapping for drought tolerance at the seedling stage and yield-related traits. 60 cowpea accessions were used in the study. Single-nucleotide polymorphisms (SNPs) discovered through genotyping by sequencing (GBS) were used for genotyping. Association mapping was conducted using single-marker regression (SMR) in Q Gene, and general linear model (GLM) and mixed linear model (MLM) built in TASSEL. The population of the cowpea accessions were analysed using STRUCTURE 2.3.4 and the peak of delta K in the greenhouse showed seven population types, whereas the peak of delta K in the glasshouse indicated the presence of six population types. One SNP marker, 14083649|F|0-9 was associated with NP with a p value &lt;0.001. Fifty SNP markers were associated with PWT at p &lt;0.001. Four SNP markers, 14074781|F|0-16, 100047392|F|0-36, 14083801|F|0-28 and 100051488|F|0-49 were associated with AVSPD at p &lt;0.001. SNP markers, 14074781|F|0-16, 14083801|F|0-28 and 100051488|F|0-49 were associated with PL at P &lt;0.001. Five SNP markers, 100047392|F|0-36, 14083801|F|0-28, 100072738|F|0-34, 14076881|F|0-49 and 14076881|F|0-49 were associated with PWDTH at p &lt;0.001. The 65 SNP markers identified can be used in cowpea molecular breeding to select for AVSPD, NP, PL, PWDTH, PWT, and RR through marker assisted selection (MAS).

scholarly journals Genomic variation in the American pika: signatures of geographic isolation and implications for conservation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kelly B. Klingler ◽  
Joshua P. Jahner ◽  
Thomas L. Parchman ◽  
Chris Ray ◽  
Mary M. Peacock
Keyword(s):  
Genetic Variation ◽  
Genetic Structure ◽  
Sierra Nevada ◽  
Spatial Genetic Structure ◽  
Spatial Scales ◽  
Thermal Sensitivity ◽  
Genomic Variation ◽  
Genome Wide ◽  
A Genome ◽  
American Pika

Abstract Background Distributional responses by alpine taxa to repeated, glacial-interglacial cycles throughout the last two million years have significantly influenced the spatial genetic structure of populations. These effects have been exacerbated for the American pika (Ochotona princeps), a small alpine lagomorph constrained by thermal sensitivity and a limited dispersal capacity. As a species of conservation concern, long-term lack of gene flow has important consequences for landscape genetic structure and levels of diversity within populations. Here, we use reduced representation sequencing (ddRADseq) to provide a genome-wide perspective on patterns of genetic variation across pika populations representing distinct subspecies. To investigate how landscape and environmental features shape genetic variation, we collected genetic samples from distinct geographic regions as well as across finer spatial scales in two geographically proximate mountain ranges of eastern Nevada. Results Our genome-wide analyses corroborate range-wide, mitochondrial subspecific designations and reveal pronounced fine-scale population structure between the Ruby Mountains and East Humboldt Range of eastern Nevada. Populations in Nevada were characterized by low genetic diversity (π = 0.0006–0.0009; θW = 0.0005–0.0007) relative to populations in California (π = 0.0014–0.0019; θW = 0.0011–0.0017) and the Rocky Mountains (π = 0.0025–0.0027; θW = 0.0021–0.0024), indicating substantial genetic drift in these isolated populations. Tajima’s D was positive for all sites (D = 0.240–0.811), consistent with recent contraction in population sizes range-wide. Conclusions Substantial influences of geography, elevation and climate variables on genetic differentiation were also detected and may interact with the regional effects of anthropogenic climate change to force the loss of unique genetic lineages through continued population extirpations in the Great Basin and Sierra Nevada.

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