Biology subjects

Leple, J.-C.

Publications and source records attributed to Leple, J.-C..

3 recordsLinked to original sources

bioRxiv2026

Chromosome-scale assembly of the Cupressus sempervirens genome unravels new insights into the evolutionary history of conifers

Conifers, which comprise nearly two-thirds of extant gymnosperm species, are ecologically and economically important but remain genomically understudied because of their exceptionally large, repeat-rich genomes. Here, we report a chromosome-level assembly of the haploid genome of Cupressus sempervirens generated using PacBio HiFi reads and scaffolded with optical and genetic maps. The 10 Gb assembly shows exceptional contiguity for a conifer genome (contig N50 = 29.8 Mb) and was organized into 11 pseudomolecules. Iso-Seq-supported annotation identified 42,980 protein-coding genes. Repetitive elements account for over 80% of the genome, with LTR retrotransposons alone representing 52.5%. Transposable elements (TE) are pervasive in both intergenic and genic regions and have a major impact on gene architecture: TE insertions within introns generate ultra-long introns, often exceeding 100 kb, and drive gene size expansion. Analyses of LTR retrotransposon dynamics indicate that genome enlargement in C. sempervirens was driven not by recent transpositional bursts, but by the long-term accumulation and incomplete removal of ancient LTR retrotransposons. Consistent with this pattern, paleogenomic reconstruction across representative gymnosperms found no evidence of whole-genome duplication in the Cupressus lineage. This reference genome provides a valuable resource for studying conifer genome evolution, gene structure, and traits of agronomic and ecological interest, including cypress pollinosis.

genomics↗

bioRxiv2021

Genome-wide evolutionary response of European oakssince the Little Ice Age

The pace of tree microevolution during Anthropocene warming is largely unknown. We used a retrospective approach to monitor genomic changes in oak trees since the Little Ice Age (LIA). Allelic frequency changes were assessed from whole-genome pooled sequences for four age-structured cohorts of sessile oak (Quercus petraea) dating back to 1680, in each of three different oak forests in France. The genetic covariances of allelic frequency changes increased between successive time periods, highlighting genome-wide effects of linked selection. We found imprints of convergent linked selection in the three forests during the late LIA, and a shift of selection during more recent time periods. The changes in allelic covariances within and between forests mirrored the documented changes in the occurrence of extreme events (droughts and frosts) over the last three hundred years. The genomic regions with the highest covariances were enriched in genes involved in plant responses to pathogens and abiotic stresses (temperature and drought). These responses are consistent with the reported sequence of frost (or drought) and disease damage ultimately leading to the oak dieback after extreme events. Our results therefore provide evidence of selection operating on long-lived species during recent climatic changes.

evolutionary biology↗

bioRxiv2019

Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory

Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. We sequenced RNA in a Populus nigra collection and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes deemed important for trait prediction, they did not systematically predict better than peripherals or even random genes. Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

genomics↗