Dataset Information

Principal Component Analysis and Molecular Characterization of Reniform Nematode Populations in Alabama.

ABSTRACT: U.S. cotton production is suffering from the yield loss caused by the reniform nematode (RN), Rotylenchulus reniformis. Management of this devastating pest is of utmost importance because, no upland cotton cultivar exhibits adequate resistance to RN. Nine populations of RN from distinct regions in Alabama and one population from Mississippi were studied and thirteen morphometric features were measured on 20 male and 20 female nematodes from each population. Highly correlated variables (positive) in female and male RN morphometric parameters were observed for body length (L) and distance of vulva from the lip region (V) (r = 0.7) and tail length (TL) and c' (r = 0.8), respectively. The first and second principal components for the female and male populations showed distinct clustering into three groups. These results show pattern of sub-groups within the RN populations in Alabama. A one-way ANOVA on female and male RN populations showed significant differences (p ? 0.05) among the variables. Multiple sequence alignment (MSA) of 18S rRNA sequences (421) showed lengths of 653 bp. Sites within the aligned sequences were conserved (53%), parsimony-informative (17%), singletons (28%), and indels (2%), respectively. Neighbor-Joining analysis showed intra and inter-nematodal variations within the populations as clone sequences from different nematodes irrespective of the sex of nematode isolate clustered together. Morphologically, the three groups (I, II and III) could not be distinctly associated with the molecular data from the 18S rRNA sequences. The three groups may be identified as being non-geographically contiguous.

SUBMITTER: Nyaku ST

PROVIDER: S-EPMC4853102 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Principal Component Analysis and Molecular Characterization of Reniform Nematode Populations in Alabama.

Nyaku Seloame T ST Kantety Ramesh V RV Cebert Ernst E Lawrence Kathy S KS Honger Joseph O JO Sharma Govind C GC

The plant pathology journal 20160401 2

U.S. cotton production is suffering from the yield loss caused by the reniform nematode (RN), Rotylenchulus reniformis. Management of this devastating pest is of utmost importance because, no upland cotton cultivar exhibits adequate resistance to RN. Nine populations of RN from distinct regions in Alabama and one population from Mississippi were studied and thirteen morphometric features were measured on 20 male and 20 female nematodes from each population. Highly correlated variables (positive) ...[more]

PMID: 27147932

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Project description:BackgroundPrincipal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit.ResultsThe effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes.ConclusionsTogether, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.

Project description:BackgroundReniform nematode (Rotylenchulus reniformis) has emerged as one of the most destructive root pathogens of upland cotton (Gossypium hirsutum) in the United States. Management of R. reniformis has been hindered by the lack of resistant G. hirsutum cultivars; however, resistance has been frequently identified in germplasm accessions from the G. arboreum collection. To determine the genetic basis of reniform nematode resistance, a genome-wide association study (GWAS) was performed using 246 G. arboreum germplasm accessions that were genotyped with 7220 single nucleotide polymorphic (SNP) sequence markers generated from genotyping-by-sequencing.ResultsFifteen SNPs representing 12 genomic loci distributed over eight chromosomes showed association with reniform nematode resistance. For 14 SNPs, major alleles were shown to be associated with resistance. From the 15 significantly associated SNPs, 146 genes containing or physically close to these loci were identified as putative reniform nematode resistance candidate genes. These genes are involved in a broad range of biological pathways, including plant innate immunity, transcriptional regulation, and redox reaction that may have a role in the expression of resistance. Eighteen of these genes corresponded to differentially expressed genes identified from G. hirsutum in response to reniform nematode infection.ConclusionsThe identification of multiple genomic loci associated with reniform nematode resistance would indicate that the G. arboreum collection is a significant resource of novel resistance genes. The significantly associated markers identified from this GWAS can be used for the development of molecular tools for breeding improved reniform nematode resistant upland cotton with resistance introgressed from G. arboreum. Additionally, a greater understanding of the molecular mechanisms of reniform nematode resistance can be determined through genetic structure and functional analyses of candidate genes, which will aid in the pyramiding of multiple resistance genes.

Dataset Information

Principal Component Analysis and Molecular Characterization of Reniform Nematode Populations in Alabama.

Publications

Principal Component Analysis and Molecular Characterization of Reniform Nematode Populations in Alabama.

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