scholarly journals Molecular Characterization of Global Finger Millet (Eleusine coracana, L. Gaertn) germplasm Reaction to Striga in Kenya

2018 ◽  
pp. 1-14
Author(s):  
Sirengo Peter Nyongesa ◽  
Wamalwa Dennis Simiyu ◽  
Oduor Chrispus ◽  
Odeny Damaris Achieng ◽  
Dangasuk Otto George
Keyword(s):  
Finger Millet ◽  
Association Studies ◽  
Block Design ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Eleusine Coracana ◽  
Striga Hermonthica ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Striga Resistance

Finger millet (Eleusine coracana, L. Gaertn) is an important food crop in Africa and Asia. The parasitic weed Striga hermonthica (Del.) Benth limits finger millet production through reduced yield in agro-ecologies where they exist. The damage of Striga to cereal crops is more severe under drought and low soil fertility. This study aims to determine genetic basis for reaction to Striga hermonthica among the selected germplasm of finger millets through genotyping by sequencing (GBS). One hundred finger millet genotypes were evaluated for reaction to Striga hermonthica infestation under field conditions at Alupe and Kibos in Western Kenya. The experiment was laid out in a randomized complete block design (RCBD) consisting of 10 x 10 square (triple lattice) under Striga (inoculated) and no Striga conditions and plant growth monitored to maturity after 110 days. All genotypes were genotyped by genotyping by sequencing (GBS) and data analyzed using the non-reference based Universal Network Enabled Analysis Kit (UNEAK) pipeline. Genome wide association studies (GWAS) were done to establish the association of detected Single Nucleotide Polymorphisms (SNPs) with Striga reaction based on field results. In molecular analysis 117,542 SNPs from raw GBS data used in GWAS revealed that markers TP 85424 and TP 88244 were associated with Striga resistance in the 95 genotypes. Principal Component Analysis revealed that the first and third component axes accounted for 2.5 and 8% of total variance respectively and the genotypes were distributed according to their reaction to Striga weed. Genetic diversity analysis grouped the 95 accessions into three major clusters containing; 32 (A), 56 (B), and 7 (C) genotypes.  All finger millet genotypes that showed high resistance to Striga in the field were from cluster B while the most susceptible genotypes were from clusters A and C. Results revealed genetic variation for Striga resistance in cultivated finger millet genotypes and hence the possibility of marker –assisted breeding for resistance to Striga.

scholarly journals Morphological Characterisation of Global Finger Millet (Eleusine coracana, L. Gaertn) Germplasm Reaction to Striga in Kenya

2018 ◽  
pp. 1-17
Author(s):  
Sirengo Peter Nyongesa ◽  
Oduor Chrispus ◽  
Dennis Simiyu Wamalwa ◽  
Odeny Damaris Achieng ◽  
Rajneesh Paliwal ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Finger Millet ◽  
Block Design ◽  
Genotyping By Sequencing ◽  
Eleusine Coracana ◽  
Striga Hermonthica ◽  
Phenotypic Data ◽  
Western Kenya ◽  
Statistical Analysis System ◽  
Analysis System

Finger millet (Eleusine coracana, L. Gaertn) is an important food crop in Africa and Asia. Its grain is richer in protein, fat and minerals than other major cereals. The parasitic weed Striga hermonthica (Del.) Benth seriously limits finger millet production through reduced yield in agro-ecologies where they co-exist. The damage of Striga to cereal crops is more severe under drought and low soil fertility. The main objective of this study was to determine genetic basis for reaction to S. hermonthica among the selected germplasm of finger millet through genotyping by sequencing (GBS). One hundred finger millet genotypes were evaluated for reaction to S. hermonthica (Del) Benth infestation under field conditions at Alupe and Kibos in Western Kenya. The experiment was laid out as a randomized complete block design (RCBD) consisting of 10 x 10 square (triple lattice). The genotypes were planted both under Striga (inoculated) and no Striga conditions and plant growth was monitored to maturity. Statistical analysis of phenotypic data using Statistical Analysis System (SAS) PROC ANOVA revealed highly significant differences among genotypes for morphological traits at P<0.05.

scholarly journals Powerful Tukey's One Degree-of-Freedom Test for Detecting Gene-Gene and Gene-Environment Interactions

2015 ◽  
Vol 14s2 ◽  
pp. CIN.S17305 ◽  
Author(s):  
Yaping Wang ◽  
Donghui Li ◽  
Peng Wei
Keyword(s):  
Statistical Power ◽  
Association Studies ◽  
Score Test ◽  
Principal Component ◽  
Case Control ◽  
Degree Of Freedom ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Missing Heritability ◽  
Gene Environment

Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) robustly associated with hundreds of complex human diseases including cancers. However, the large number of G WAS-identified genetic loci only explains a small proportion of the disease heritability. This “missing heritability” problem has been partly attributed to the yet-to-be-identified gene-gene (G × G) and gene-environment (G × E) interactions. In spite of the important roles of G × G and G × E interactions in understanding disease mechanisms and filling in the missing heritability, straightforward GWAS scanning for such interactions has very limited statistical power, leading to few successes. Here we propose a two-step statistical approach to test G × G/G × E interactions: the first step is to perform principal component analysis (PCA) on the multiple SNPs within a gene region, and the second step is to perform Tukey's one degree-of-freedom (1-df) test on the leading PCs. We derive a score test that is computationally fast and numerically stable for the proposed Tukey's 1-df interaction test. Using extensive simulations we show that the proposed approach, which combines the two parsimonious models, namely, the PCA and Tukey's 1-df form of interaction, outperforms other state-of-the-art methods. We also demonstrate the utility and efficiency gains of the proposed method with applications to testing G × G interactions for Crohn's disease using the Wellcome Trust Case Control Consortium (WTCCC) GWAS data and testing G × E interaction using data from a case-control study of pancreatic cancer.

scholarly journals PCA-Based Multiple-Trait GWAS Analysis: A Powerful Model for Exploring Pleiotropy

Animals ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 239 ◽  
Author(s):  
Wengang Zhang ◽  
Xue Gao ◽  
Xinping Shi ◽  
Bo Zhu ◽  
Zezhao Wang ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Statistical Power ◽  
Muscle Development ◽  
Association Studies ◽  
Simulated Data ◽  
Principal Component ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Multiple Trait ◽  
Gwas Analysis

Principal component analysis (PCA) is a potential approach that can be applied in multiple-trait genome-wide association studies (GWAS) to explore pleiotropy, as well as increase the power of quantitative trait loci (QTL) detection. In this study, the relationship of test single nucleotide polymorphisms (SNPs) was determined between single-trait GWAS and PCA-based GWAS. We found that the estimated pleiotropic quantitative trait nucleotides (QTNs) β * ^ were in most cases larger than the single-trait model estimations ( β 1 ^ and β 2 ^ ). Analysis using the simulated data showed that PCA-based multiple-trait GWAS has improved statistical power for detecting QTL compared to single-trait GWAS. For the minor allele frequency (MAF), when the MAF of QTNs was greater than 0.2, the PCA-based model had a significant advantage in detecting the pleiotropic QTNs, but when its MAF was reduced from 0.2 to 0, the advantage began to disappear. In addition, as the linkage disequilibrium (LD) of the pleiotropic QTNs decreased, its detection ability declined in the co-localization effect model. Furthermore, on the real data of 1141 Simmental cattle, we applied the PCA model to the multiple-trait GWAS analysis and identified a QTL that was consistent with a candidate gene, MCHR2, which was associated with presoma muscle development in cattle. In summary, PCA-based multiple-trait GWAS is an efficient model for exploring pleiotropic QTNs in quantitative traits.

scholarly journals Genotyping-by-Sequencing-Based Genome-Wide Association Studies of Fusarium Wilt Resistance in Radishes (Raphanus sativus L.)

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 858
Author(s):  
O New Lee ◽  
Hyunjin Koo ◽  
Jae Woong Yu ◽  
Han Yong Park
Keyword(s):  
Fusarium Wilt ◽  
Association Studies ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Gwas Study ◽  
F2 Population ◽  
Genome Wide ◽  
Resistant Varieties

Fusarium wilt (FW) is a fungal disease that causes severe yield losses in radish production. The most effective method to control the FW is the development and use of resistant varieties in cultivation. The identification of marker loci linked to FW resistance are expected to facilitate the breeding of disease-resistant radishes. In the present study, we applied an integrated framework of genome-wide association studies (GWAS) using genotyping-by-sequencing (GBS) to identify FW resistance loci among a panel of 225 radish accessions, including 58 elite breeding lines. Phenotyping was conducted by manual inoculation of seedlings with the FW pathogen, and scoring for the disease index was conducted three weeks after inoculation during two constitutive years. The GWAS analysis identified 44 single nucleotide polymorphisms (SNPs) and twenty putative candidate genes that were significantly associated with FW resistance. In addition, a total of four QTLs were identified from F2 population derived from a FW resistant line and a susceptible line, one of which was co-located with the SNPs on chromosome 7, detected in GWAS study. These markers will be valuable for molecular breeding programs and marker-assisted selection to develop FW resistant varieties of R. sativus.

scholarly journals Adapting genotyping-by-sequencing and variant calling for heterogeneous stock rats

2019 ◽  
Author(s):  
Alexander F. Gileta ◽  
Jianjun Gao ◽  
Apurva S. Chitre ◽  
Hannah V. Bimschleger ◽  
Celine L. St. Pierre ◽  
...  
Keyword(s):  
Association Studies ◽  
Variant Calling ◽  
Genotyping By Sequencing ◽  
Genetic Maps ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Heterogeneous Stock ◽  
Genotype Information ◽  
Genotype By Sequencing ◽  
Inbred Rat

ABSTRACTThe heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We also evaluate multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.

scholarly journals Genomic regions associated with herbicide tolerance in a worldwide faba bean (Vicia faba L.) collection

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Lynn Abou-Khater ◽  
Fouad Maalouf ◽  
Abdulqader Jighly ◽  
Alsamman M. Alsamman ◽  
Diego Rubiales ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Faba Bean ◽  
Field Experiments ◽  
Core Protein ◽  
Association Studies ◽  
Herbicide Tolerance ◽  
Genotyping By Sequencing ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Herbicide Treatments

AbstractWeeds represent one of the major constraints for faba bean crop. The identification of molecular markers associated with key genes imparting tolerance to herbicides can facilitate and fasten the efficient and effective development of herbicide tolerant cultivars. We phenotyped 140 faba bean genotypes in three open field experiments at two locations in Lebanon and Morocco against three herbicide treatments (T1 metribuzin 250 g ai/ha; T2 imazethapyr 75 g ai/ha; T3 untreated) and one in greenhouse where T1 and T3 were applied. The same set was genotyped using genotyping by sequencing (GBS) which yield 10,794 high quality single nucleotide polymorphisms (SNPs). ADMIXTURE software was used to infer the population structure which revealed two ancestral subpopulations. To identify SNPs associated with phenological and yield related traits under herbicide treatments, Single-trait (ST) and Multi-trait (MT) Genome Wide Association Studies (GWAS) were fitted using GEMMA software, showing 10 and 14 highly significant associations, respectively. Genomic sequences containing herbicide tolerance associated SNPs were aligned against the NCBI database using BLASTX tool using default parameters to annotate candidate genes underlying the causal variants. SNPs from acidic endochitinase, LRR receptor-like serine/threonine-protein kinase RCH1, probable serine/threonine-protein kinase NAK, malate dehydrogenase, photosystem I core protein PsaA and MYB-related protein P-like were significantly associated with herbicide tolerance traits.

scholarly journals Genetic Diversity, Population Structure, and Linkage Disequilibrium in a Spanish Common Bean Diversity Panel Revealed through Genotyping-by-Sequencing

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 518 ◽  
Author(s):  
Ana Campa ◽  
Ester Murube ◽  
Juan José Ferreira
Keyword(s):  
Genetic Diversity ◽  
Common Bean ◽  
Association Studies ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Gene Pools ◽  
Genome Wide Association Studies ◽  
Snap Bean ◽  
Diversity Panel ◽  
Main Gene

A common bean (Phaseolus vulgaris) diversity panel of 308 lines was established from local Spanish germplasm, as well as old and elite cultivars mainly used for snap consumption. Most of the landraces included derived from the Spanish common bean core collection, so this panel can be considered to be representative of the Spanish diversity for this species. The panel was characterized by 3099 single-nucleotide polymorphism markers obtained through genotyping-by-sequencing, which revealed a wide genetic diversity and a low level of redundant material within the panel. Structure, cluster, and principal component analyses revealed the presence of two main subpopulations corresponding to the two main gene pools identified in common bean, the Andean and Mesoamerican pools, although most lines (70%) were associated with the Andean gene pool. Lines showing recombination between the two gene pools were also observed, most of them showing useful for snap bean consumption, which suggests that both gene pools were probably used in the breeding of snap bean cultivars. The usefulness of this panel for genome-wide association studies was tested by conducting association mapping for determinacy. Significant marker–trait associations were found on chromosome Pv01, involving the gene Phvul.001G189200, which was identified as a candidate gene for determinacy in the common bean.

scholarly journals Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats

2020 ◽  
Vol 10 (7) ◽  
pp. 2195-2205 ◽  
Author(s):  
Alexander F. Gileta ◽  
Jianjun Gao ◽  
Apurva S. Chitre ◽  
Hannah V. Bimschleger ◽  
Celine L. St. Pierre ◽  
...  
Keyword(s):  
Association Studies ◽  
Variant Calling ◽  
Genotyping By Sequencing ◽  
Genetic Maps ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Heterogeneous Stock ◽  
Genotype Information ◽  
Genotype By Sequencing ◽  
Inbred Rat

The heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We evaluated multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We have also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.

scholarly journals Non-Mendelian inheritance of SNP markers reveals extensive chromosomal translocations in dioecious hops (Humulus lupulus L.)

2016 ◽  
Author(s):  
Dong Zhang ◽  
Nicholi J. Pitra ◽  
Mark C. Coles ◽  
Edward S. Buckler ◽  
Paul D. Matthews
Keyword(s):  
Candidate Genes ◽  
Association Studies ◽  
Genotyping By Sequencing ◽  
Mendelian Inheritance ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Population Structures ◽  
Wild Accessions

AbstractGenome-wide meiotic recombination structures, sex chromosomes, and candidate genes for sex determination were discovered among Humulus spp. by application of a novel, high-density molecular marker system: ~1.2M single nucleotide polymorphisms (SNPs) were profiled with genotyping-by-sequencing (GBS) among 4512 worldwide accessions, including 4396 cultivars and landraces and 116 wild accessions of hops. Pre-qualified GBS markers were validated by inferences on families, population structures and phylogeny. Candidate genes discovered for several traits, including sex and drought stress-resistance, demonstrate the quality and utility of GBS SNPs for genome-wide association studies (GWAS) and Fst analysis in hops. Most importantly, pseudo-testcross mappings in F1 families delineated non-random linkage of Mendelian and non-Mendelian markers: structures that are indicative of unusual meiotic events which may have driven the evolution and cultivation of hops.

scholarly journals Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.)

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11593
Author(s):  
Vipin Tomar ◽  
Guriqbal Singh Dhillon ◽  
Daljit Singh ◽  
Ravi Prakash Singh ◽  
Jesse Poland ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Association Studies ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Genome Wide Association Studies ◽  
Breeding Lines ◽  
Structure Information

Genetic diversity and population structure information are crucial for enhancing traits of interest and the development of superlative varieties for commercialization. The present study elucidated the population structure and genetic diversity of 141 advanced wheat breeding lines using single nucleotide polymorphism markers. A total of 14,563 high-quality identified genotyping-by-sequencing (GBS) markers were distributed covering 13.9 GB wheat genome, with a minimum of 1,026 SNPs on the homoeologous group four and a maximum of 2,838 SNPs on group seven. The average minor allele frequency was found 0.233, although the average polymorphism information content (PIC) and heterozygosity were 0.201 and 0.015, respectively. Principal component analyses (PCA) and population structure identified two major groups (sub-populations) based on SNPs information. The results indicated a substantial gene flow/exchange with many migrants (Nm = 86.428) and a considerable genetic diversity (number of different alleles, Na = 1.977; the number of effective alleles, Ne = 1.519; and Shannon’s information index, I = 0.477) within the population, illustrating a good source for wheat improvement. The average PIC of 0.201 demonstrates moderate genetic diversity of the present evaluated advanced breeding panel. Analysis of molecular variance (AMOVA) detected 1% and 99% variance between and within subgroups. It is indicative of excessive gene traffic (less genetic differentiation) among the populations. These conclusions deliver important information with the potential to contribute new beneficial alleles using genome-wide association studies (GWAS) and marker-assisted selection to enhance genetic gain in South Asian wheat breeding programs.

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