Dataset Information

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

ABSTRACT: The local environment of the geographical origin of plants shaped their genetic variations through environmental adaptation. While the characteristics of the local environment correlate with the genotypes and other genomic features of the plants, they can also be indicative of genotype-phenotype associations providing additional information relevant to environmental dependence. In this study, we investigate how the geoclimatic features from the geographical origin of the Arabidopsis thaliana accessions can be integrated with genomic features for phenotype prediction and association analysis using advanced canonical correlation analysis (CCA). In particular, we propose a novel method called hierarchical canonical correlation analysis (HCCA) to combine mutations, gene expressions, and DNA methylations with geoclimatic features for informative coprojections of the features. HCCA uses a condition number of the cross-covariance between pairs of datasets to infer a hierarchical structure for applying CCA to combine the data. In the experiments on Arabidopsis thaliana data from 1001 Genomes and 1001 Epigenomes projects and climatic, atmospheric, and soil environmental variables combined by CLIMtools, HCCA provided a joint representation of the genomic data and geoclimate data for better prediction of the special flowering time at 10°C (FT10) of Arabidopsis thaliana. We also extended HCCA with information from a protein-protein interaction (PPI) network to guide the feature learning by imposing network modules onto the genomic features, which are shown to be useful for identifying genes with more coherent functions correlated with the geoclimatic features. The findings in this study suggest that environmental data comprise an important component in plant phenotype analysis. HCCA is a useful data integration technique for phenotype prediction, and a better understanding of the interactions between gene functions and environment as more useful functional information is introduced by coprojections of multiple genomic datasets.

SUBMITTER: Petegrosso R

PROVIDER: S-EPMC7706319 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

Petegrosso Raphael R Song Tianci T Kuang Rui R

Plant phenomics (Washington, D.C.) 20200331

The local environment of the geographical origin of plants shaped their genetic variations through environmental adaptation. While the characteristics of the local environment correlate with the genotypes and other genomic features of the plants, they can also be indicative of genotype-phenotype associations providing additional information relevant to environmental dependence. In this study, we investigate how the geoclimatic features from the geographical origin of the <i>Arabidopsis thaliana< ...[more]

PMID: 33313545

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Project description:INTRODUCTION: Clinical variability associated with the common 22q11.2 microdeletion is well known, and has led to a broad application of FISH diagnostics with probes for loci TUPLE1 or D22S75 (N25), although, rarely reported atypical deletions associated with the same phenotypic spectrum would not be discovered by these probes. As most types of 22q11.2 deletions occur between low copy repeats within the region (LCR22), we assumed that atypical deletions should be more common than has been reported. To address this question and the possibility of a deletion size related genotype-phenotype correlation, we systematically assessed the frequency of typical and atypical 22q11.2 deletions in a large cohort of patients. METHODS: We used a set of 10 fluorescent in situ hybridisation (FISH) DNA probes, capable of detecting all reported and hypothetical deletions between the LCR22, and analysed 350 patients. Deletion sizes in atypical deletions were established by use of further FISH probes. Frequency of certain atypical deletions was analysed in controls by FISH and quantitative PCR. RESULTS: Patients with conotruncal heart defects (ctCHD) and with typical VCFS phenotype showed the common 3 Mb or nested 1.5 Mb deletions (in 18.5% and 78.6%, respectively), but no atypical deletion, while 5% (3/63) of patients with a mildly suggestive, atypical phenotype showed atypical distal deletions, which were not detected in patients with mental retardation of unknown origin or in healthy controls. DISCUSSION: These statistically significant differences demonstrate that atypical distal 22q11.2 deletions are very uncommon in patients with ctCHDs, while atypical congenital heart defects and mild dysmorphism are recognisable feature of atypical distal deletions. Further phenotype-genotype analysis disclosed association of significant developmental delay with the distal part of the common deletion region, and choanal atresia and atypical CHDs with the adjacent distal deletion region.

Dataset Information

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

Publications

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

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