Biology subjects

Parkin, I.

Publications and source records attributed to Parkin, I..

6 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↗

bioRxiv2024

Unveiling unique metabolomic and transcriptomic profiles in three Brassicaceae crops

Brassica napus, Camelina sativa and field pennycress (Thlaspi arvense), represent one highly economically valuable crop and two emerging oilseed crops of the Brassicaceae family, respectively. As sessile organisms, these crops are continuously exposed to various stresses when grown in the field. Interestingly, the responses of these three crops to different environmental stimuli vary to a great extent, but there is very limited knowledge about the molecular basis of these differential responses. In this study, we employed untargeted metabolomics to compare the metabolic profile of these crops, and examined the potentially related genes through further integration with transcriptomic analysis. Our data revealed distinctive overall metabolic profiles among these three crops, where in particular, a variety of phenylpropanoids showed differential accumulation and the corresponding putative genes expression varied significantly. The results provide a valuable resource for those studying Brassicaceae species and will provide insight into the understanding of metabolic variation among these three important oilseed crops, and provide potential targets for the future breeding of stress tolerant crops.

plant biology↗

bioRxiv2024

Dissecting the molecular basis of variability for flowering time in Camelina sativa

Camelina sativa is an important polyploid oilseed crop with multiple favorable agronomic traits. Capturing the leaf transcriptome of 48 accessions of C. sativa suggests allelic variation for gene expression levels and notably sub-genome dominance, both of which could provide opportunities for crop improvement. Flowering time (FT) is a crucial factor affecting the overall yield of crops. However, our understanding of the molecular mechanisms underlying FT regulation in C. sativa are still limited, partly due to its complex allohexaploid genome. In this study, weighted gene co-expression network analysis (WGCNA), expression quantitative trait loci (eQTL) analysis and transcriptome-wide association study (TWAS) were employed to explore the FT diversity among 48 C. sativa accessions and dissect the underlying molecular basis. Our results revealed a FT-related co-expressed gene module highly enriched with SOC1s and SOC1-like genes, and identified 10 significant FT-associated single nucleotide polymorphisms (SNPs) defining three haplotype groups; thus providing a molecular basis for future genetic improvements in C. sativa breeding.

plant biology↗

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↗

bioRxiv2021

ePlant in 2021: New Species, Viewers, Data Sets, and Widgets

ePlant was introduced in 2017 for exploring large Arabidopsis thaliana data sets from the kilometre to nanometre scales. In the past four years we have used the ePlant framework to develop ePlants for 15 agronomically-important species: maize, poplar, tomato, Camelina sativa, soybean, potato, barley, Medicago truncatula, eucalyptus, rice, willow, sunflower, Cannabis sativa, wheat and sugarcane. We also updated the interface to improve performance and accessibility, and added two new views to the Arabidopsis ePlant - the Navigator and Pathways viewers. The former shows phylogenetic relationships between homologs in other species and their expression pattern similarities, with links to view data for those genes in the respective ePlants. The latter shows Plant Reactome metabolic reactions. We also describe new Arabidopsis data sets including single cell RNA-seq data from roots, and how to embed ePlant eFP expression pictographs into any web page.

bioinformatics↗