Dataset Information

Tail Wags the Dog? Functional Gene Classes Driving Genome-Wide GC Content in Plasmodium spp.

ABSTRACT: Plasmodium parasites are valuable models to understand how nucleotide composition affects mutation, diversification, and adaptation. No other observed eukaryotes have undergone such large changes in genomic Guanine-Cytosine (GC) content as seen in the genus Plasmodium (∼30% within 35-40 Myr). Although mutational biases are known to influence GC content in the human-infective Plasmodium vivax and Plasmodium falciparum; no study has addressed how different gene functional classes contribute to genus-wide compositional changes, or if Plasmodium GC content variation is driven by natural selection. Here, we tested the hypothesis that certain gene processes and functions drive variation in global GC content between Plasmodium species. We performed a large-scale comparative genomic analysis using the genomes and predicted genes of 17 Plasmodium species encompassing a wide genomic GC content range. Genic GC content was sorted and divided into ten equally sized quantiles that were then assessed for functional enrichment classes. In agreement that selection on gene classes may drive genomic GC content, trans-membrane proteins were enriched within extreme GC content quantiles (Q1 and Q10). Specifically, variant surface antigens, which primarily interact with vertebrate immune systems, showed skewed GC content distributions compared with other trans-membrane proteins. Although a definitive causation linking GC content, expression, and positive selection within variant surface antigens from Plasmodium vivax, Plasmodium berghei, and Plasmodium falciparum could not be established, we found that regardless of genomic nucleotide composition, genic GC content and expression were positively correlated during trophozoite stages. Overall, these data suggest that, alongside mutational biases, functional protein classes drive Plasmodium GC content change.

SUBMITTER: Castillo AI

PROVIDER: S-EPMC6385630 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundUnderstanding mechanisms of sugar accumulation and composition is essential to determining fruit quality and maintaining a desirable balance of sugars in plant storage organs. The major sugars in mature Rosaceae fruits are sucrose, fructose, glucose, and sorbitol. Among these, sucrose and fructose have high sweetness, whereas glucose and sorbitol have low sweetness. Japanese pear has extensive variation in individual sugar contents in mature fruit. Increasing total sugar content and that of individual high-sweetness sugars is a major target of breeding programs. The objective of this study was to identify quantitative trait loci (QTLs) associated with fruit traits including individual sugar accumulation, to infer the candidate genes underlying the QTLs, and to assess the potential of genomic selection for breeding pear fruit traits.ResultsWe evaluated 10 fruit traits and conducted genome-wide association studies (GWAS) for 106 cultivars and 17 breeding populations (1112 F1 individuals) using 3484 tag single-nucleotide polymorphisms (SNPs). By implementing a mixed linear model and a Bayesian multiple-QTL model in GWAS, 56 SNPs associated with fruit traits were identified. In particular, a SNP located close to acid invertase gene PPAIV3 on chromosome 7 and a newly identified SNP on chromosome 11 had quite large effects on accumulation of sucrose and glucose, respectively. We used 'Golden Delicious' doubled haploid 13 (GDDH13), an apple reference genome, to infer the candidate genes for the identified SNPs. In the region flanking the SNP on chromosome 11, there is a tandem repeat of early responsive to dehydration (ERD6)-like sugar transporter genes that might play a role in the phenotypes observed.ConclusionsSNPs associated with individual sugar accumulation were newly identified at several loci, and candidate genes underlying QTLs were inferred using advanced apple genome information. The candidate genes for the QTLs are conserved across Pyrinae genomes, which will be useful for further fruit quality studies in Rosaceae. The accuracies of genomic selection for sucrose, fructose, and glucose with genomic best linear unbiased prediction (GBLUP) were relatively high (0.67-0.75), suggesting that it would be possible to select individuals having high-sweetness fruit with high sucrose and fructose contents and low glucose content.

Dataset Information

Tail Wags the Dog? Functional Gene Classes Driving Genome-Wide GC Content in Plasmodium spp.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets