Eynck, C. | Search bioRxiv

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↗