Search

—Chloroplast capture, a phenomenon that can occur through interspecific hybridization and introgression, is frequently invoked to explain cytonuclear discordance in plants. However, relatively few studies have documented the mechanisms of cytonuclear coevolution and its potential for driving species differentiation and possible functional differences in the context of chloroplast capture. To address this crucial question, we chose the Aquilegia genus, which is known for having minimal sterility among species, and inferred that A. amurensis captured the plastome of A. parviflora based on cytonuclear discordance and gene flow between the 2 species. We focused on the introgression region and its differentiation from corresponding regions in closely related species, especially its composition in a chloroplast capture scenario. We found that nuclear genes encoding cytonuclear enzyme complexes (CECs; i.e. organelle-targeted genes) of chloroplast donor species were selectively retained and displaced the original CEC genes in chloroplast-receiving species due to cytonuclear interactions during introgression. Notably, the intrinsic correlation of CEC introgression was a greater degree of evolutionary distance for these CECs between A. amurensis and A. parviflora. Terpene synthase activity genes (GO: 0010333) were overrepresented among the introgressed genes, and more than 30% of these genes were CEC genes. These findings support our observations that floral terpene release pattern is similar between A. amurensis and A. parviflora compared with A. japoni ca. Our study clarifies the mechanisms of cytonuclear coevolution, species differentiation, and functional differences in the context of chloroplast capture and highlights the potential role of chloroplast capture in adaptation. [ABSTRACT FROM AUTHOR]

Motivation It is well known that batch effects exist in RNA-seq data and other profiling data. Although some methods do a good job adjusting for batch effects by modifying the data matrices, it is still difficult to remove the batch effects entirely. The remaining batch effect can cause artifacts in the detection of patterns in the data. Results In this study, we consider the batch effect issue in the pattern detection among the samples, such as clustering, dimension reduction and construction of networks between subjects. Instead of adjusting the original data matrices, we design an adaptive method to directly adjust the dissimilarity matrix between samples. In simulation studies, the method achieved better results recovering true underlying clusters, compared to the leading batch effect adjustment method ComBat. In real data analysis, the method effectively corrected distance matrices and improved the performance of clustering algorithms. Availability and implementation The R package is available at: https://github.com/tengfei-emory/QuantNorm. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]