Biology subjects

Eynck, C.

Publications and source records attributed to Eynck, C..

3 recordsLinked to original sources

bioRxiv2025

A new subgenome of the Camelina genus reveals genome dominance is controlled by chromosomal proximity

Camelina sativa is an oilseed of the Brassicaceae, whose close relatives vary in ploidy number, providing a novel platform for studying plant genome evolution. The availability of diploid, tetraploid and hexaploid species of Camelina allow the evolutionary trajectory and fate of duplicated genes in the neopolyploid Camelina species to be elucidated. Here we report an improved assembly of the widely used C. sativa reference DH55 and three new genome assemblies of Camelina microcarpa; one tetraploid CN119243 (2n = 26), and two hexaploids with divergent chromosome numbers, Type 1 - CN119205 (2n=40) and Type 2 - CN120025 (2n=38). The tetraploid represents the first step in the evolutionary path to form C. sativa, while the hexaploids suggest three divergent lineages in the formation of higher ploidy Camelina species. The previously uncharacterized fourth subgenome found in C. microcarpa Type 2, although showing some homology to the C. sativa diploid progenitor genome, C. neglecta, showed numerous unique chromosomal rearrangements differentiating it from other subgenomes present in known Camelina species. Although this species was recently formed, the second subgenome showed gene expression dominance, which was in contrast to both 2n=40 Camelina species where the third subgenome was dominant. The expression dominance in Type 2 C. microcarpa contradicted the accepted two-step evolutionary process which led to the generation of related Brassicaceae species. However, the observed genome dominance in all Camelina species was negatively correlated with inter-subgenome chromatin interaction frequencies, suggesting that chromosome confirmation and proximity in the nucleus contributes to this mechanism of genome evolution. Despite the differences in genome structure, successful inter-specific hybridization provided evidence of chromosomal exchange between the divergent third sub-genomes of C. sativa and C. microcarpa Type 2, opening up a novel avenue to new diversity in the established oilseed. Key pointsO_LIAn improved genomic understanding of Camelina species and identification of distinct subgenome structures and relationships, which will facilitate strategies to increase the genetic diversity in C. sativa. C_LIO_LISubgenome evolution and subgenome dominance in polyploids is associated with chromosomal architecture and proximity in the nucleus. C_LIO_LIGenome assemblies representing all ploidy levels in the Camelina genus provide a unique and valuable platform for polyploid research. C_LI

genomics↗

bioRxiv2023

Mapping QTL for vernalization requirement identified adaptive divergence of the candidate gene Flowering Locus C in polyploid Camelina sativa

Vernalization requirement is an integral component of flowering in winter-type plants. The availability of winter ecotypes among Camelina species facilitated the mapping of QTL for vernalization requirement in C. sativa. An inter- and intraspecific crossing scheme between related Camelina species, where two different sources of the winter-type habit were used, resulted in the development of two segregating populations. Linkage maps generated with sequence-based markers identified three QTL associated with vernalization requirement in C. sativa; two from the inter-specific (chromosomes 13 and 20) and one from the intra-specific cross (chromosome 8). Notably, the three loci were mapped to different homologous regions of the hexaploid C. sativa genome. All three QTL were found in proximity to FLOWERING LOCUS C (FLC), variants of which have been reported to affect the vernalization requirement in plants. Temporal transcriptome analysis for winter-type Camelina alyssum demonstrated reduction in expression of FLC on chromosomes 13 and 20 during cold treatment, which would trigger flowering, since FLC would be expected to suppress floral initiation. FLC on chromosome 8 also showed reduced expression in the C. sativa ssp. pilosa winter parent upon cold treatment, but was expressed at very high levels across all time points in the spring-type C. sativa. The chromosome 8 copy carried a deletion in the spring-type line, which could impact its functionality. Contrary to previous reports, all three FLC loci can contribute to controlling the vernalization response in C. sativa and provide opportunities for manipulating this requirement in the crop. Significance StatementDeveloping winter C. sativa germplasm is an important breeding goal for this alternative oilseed, with application in the food, fuel and bioproduct industries. Studying the genetic architecture of the vernalization response has shown that contrary to previous reports all three FLC loci in Camelina species could be exploited to manipulate this important trait.

plant biology↗

bioRxiv2021

Deep Neural Networks for Genomic Prediction Do Not Estimate Marker Effects

Genomic prediction is a promising technology for advancing both plant and animal breeding, with many different prediction models evaluated in the literature. It has been suggested that the ability of powerful nonlinear models such as deep neural networks to capture complex epistatic effects between markers offers advantages for genomic prediction. However, these methods tend not to outperform classical linear methods, leaving it an open question why this capacity to model nonlinear effects does not seem to result in better predictive capability. In this work, we propose the theory that, due to a principle called shortcut learning, deep neural networks tend to base their predictions on overall genetic relatedness, rather than on the effects of particular markers, such as epistatic effects. Using several datasets of crop plants (lentil, wheat, and Brassica carinata), we demonstrate the networks indifference to the values of the markers by showing that the same network, provided with only the locations of matches between markers for two individuals, is able to perform prediction to the same level of accuracy.

bioinformatics↗