Inbreeding in Chinese fir: Insights into the adaptive growth traits of selfed progeny from mRNA, miRNA, and copy number variation.
Am J Bot
; : e16393, 2024 Aug 20.
Article
in En
| MEDLINE
| ID: mdl-39164836
ABSTRACT
PREMISE The impact of inbreeding on biological processes is well documented in individuals with severe inbreeding depression. However, the biological processes influencing the adaptive growth of normal selfed individuals are unknown. Here, we aimed to investigate how inbreeding affects gene expression for adaptive growth of normal selfed seedlings from a self-fertilizing parent in Chinese fir (Cunninghamia lanceolata). METHODS:
Using RNA-seq data from above- and underground tissues of abnormal and normal selfed seedlings, we analyzed GO biological processes network. We also sequenced small RNAs in the aboveground tissues and measured the copy number variations (CNV) of the hub genes.RESULTS:
Phenotypic fitness analysis revealed that the normal seedlings were better adapted than their abnormal counterparts. Upregulated differentially expressed genes (DEGs) were associated with development processes, and downregulated DEGs were mainly enriched in fundamental metabolism and stress response. Results of mRNA-miRNA parallel sequencing revealed that upregulated target genes were predominantly associated with development, highlighting their crucial role in phosphorylation in signal transduction networks. We also discovered a moderate correlation (0.1328 < R2 < 0.6257) between CNV and gene expression levels for three hub genes (TMKL1, GT2, and RHY1A).CONCLUSIONS:
We uncovered the key biological processes underpinning the growth of normal selfed seedlings and established the relationship between CNV and the expression levels of hub genes in selfed seedlings. Understanding the candidate genes involved in the growth of selfed seedlings will help us comprehend the genetic mechanisms behind inbreeding depression in the evolutionary biology of plants.
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Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Am J Bot
Year:
2024
Type:
Article