Because C. hodginsii is an economically important conifer with high-quality wood and a large genome, genomic differentiation among its geographic provenances remains poorly characterized. The researchers reanalyzed existing RNA-seq data rather than conducting a new field or greenhouse experiment. Coverage-aware joint genotyping produced 53,041 quality-filtered transcriptome-derived SNPs. A stricter filter for missing data retained 19,469 SNPs for analyses of population structure and differentiation, while a separate set of 51,873 splice-junction-filtered SNPs was used for the broader functional-variant analysis.

Two analytical approaches grouped the sampled provenances consistently. Principal component analysis and SNP-based maximum-likelihood clustering placed L6, L11 and L12 in a group designated Pop1, while the remaining 10 provenances formed Pop2. The researchers quantified differentiation between these groups with mean and weighted Fst values of 0.0764 and 0.0918, respectively. These results establish measurable genetic separation under the study’s population-genetic analyses, but they do not by themselves demonstrate that particular variants cause differences in wood density, strength or other wood properties.

The team next used XP-CLR to identify genomic windows showing elevated differentiation between Pop1 and Pop2. The analysis returned 81 windows in the top 5% of candidate regions. Merging overlapping windows produced 10 non-overlapping genomic regions for further examination. Within these regions, strict SIFT4G filtering retained 12 predicted deleterious nonsynonymous variants across five preliminary candidate genes. These are computational predictions of possible effects on protein function; the supplied study did not report experimental confirmation of their biological effects.

In the analysis across all 51,873 splice-junction-filtered SNPs, Pop2 carried a higher normalized burden of SIFT4G-predicted deleterious alternative alleles than Pop1. Together, the clustering, Fst, XP-CLR and allele-burden results provide a transcriptome-derived resource for studying population structure in C. hodginsii. Their scope is limited to the sampled provenances, the RNA-seq dataset and the computational models used. Because the study relies on transcriptome-derived markers and predicted functional effects, the highlighted regions and genes require population-genetic and functional validation before they can be treated as causal loci for wood-property variation.

Subject of Research: Population-genomic differentiation among 13 Chamaecyparis hodginsii provenances

Article Title: Transcriptome-derived SNPs reveal genomic differentiation among Chamaecyparis hodginsii provenances with contrasting wood-property profiles

Article References: Zou, Y., Xiao, S., Xiao, J., Shen, Q., He, T., Chen, L., Chen, L., Rong, J., & Zheng, Y. (2026). Transcriptome-derived SNPs reveal genomic differentiation among Chamaecyparis hodginsii provenances with contrasting wood-property profiles. BMC Plant Biology. https://doi.org/10.1186/s12870-026-10230-4

Image Credits: AI Generated

DOI: 10.1186/s12870-026-10230-4

Keywords: Chamaecyparis hodginsii, RNA sequencing, single-nucleotide polymorphisms, population genomics, genetic differentiation, provenance variation, wood properties, Fst analysis, candidate genes, conifer genomics, Transcriptome-derived, SNPs