Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured B. napus Breeding Population.

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, Brassica napus, an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse B. napus breeding population, SKBnNAM, introduced here for the first time. The experiment comprised 50 spring-type B. napus lines, grown and phenotyped in six replicates under two treatment conditions (control and drought) over 38 days in a LemnaTec Scanalyzer 3D facility. Growth traits including plant height, width, projected leaf area, and estimated biovolume were extracted and derived through processing of RGB and NIR images. Anthesis was automatically and accurately scored (97% accuracy) and the number of flowers per plant and day was approximated alongside relevant canopy traits (width, angle). Further, supervised machine learning was used to predict the total number of raceme branches from flower attributes with 91% accuracy (linear regression and Huber regression algorithms) and to identify mild drought stress, a complex trait which typically has to be empirically scored (0.85 area under the receiver operating characteristic curve, random forest classifier algorithm). The study demonstrates the potential of HTP, image processing and computer vision for effective characterization of agronomic trait diversity in B. napus, although limitations of the platform did create significant variation that limited the utility of the data. However, the results underscore the value of machine learning for phenotyping studies, particularly for complex traits such as drought stress resistance.

A high-contiguity Brassica nigra genome localizes active centromeres and defines the ancestral Brassica genome.

It is only recently, with the advent of long-read sequencing technologies, that we are beginning to uncover previously uncharted regions of complex and inherently recursive plant genomes. To comprehensively study and exploit the genome of the neglected oilseed Brassica nigra, we generated two high-quality nanopore de novo genome assemblies. The N50 contig lengths for the two assemblies were 17.1 Mb (12 contigs), one of the best among 324 sequenced plant genomes, and 0.29 Mb (424 contigs), respectively, reflecting recent improvements in the technology. Comparison with a de novo short-read assembly corroborated genome integrity and quantified sequence-related error rates (0.2%). The contiguity and coverage allowed unprecedented access to low-complexity regions of the genome. Pericentromeric regions and coincidence of hypomethylation enabled localization of active centromeres and identified centromere-associated ALE family retro-elements that appear to have proliferated through relatively recent nested transposition events (<1 Ma). Genomic distances calculated based on synteny relationships were used to define a post-triplication Brassica-specific ancestral genome, and to calculate the extensive rearrangements that define the evolutionary distance separating B. nigra from its diploid relatives.

Quantitative trait variation is revealed in a novel hypomethylated population of woodland strawberry (Fragaria vesca).

BACKGROUND: Phenotypic variation is determined by a combination of genotype, environment and their interactions. The realization that allelic diversity can be both genetic and epigenetic allows the environmental component to be further separated. Partitioning phenotypic variation observed among inbred lines with an altered epigenome can allow the epigenetic component controlling quantitative traits to be estimated. To assess the contribution of epialleles on phenotypic variation and determine the fidelity with which epialleles are inherited, we have developed a novel hypomethylated population of strawberry (2n = 2x = 14) using 5-azacytidine from which individuals with altered phenotypes can be identified, selected and characterized. RESULTS: The hypomethylated population was generated using an inbred strawberry population in the F. vesca ssp. vesca accession Hawaii 4. Analysis of whole genome sequence data from control and hypomethylated lines indicate that 5-azacytidine exposure does not increase SNP above background levels. The populations contained only Hawaii 4 alleles, removing introgression of alternate F. vesca alleles as a potential source of variation. Although genome sequencing and genetic marker data are unable to rule out 5-azacytidine induced chromosomal rearrangements as a potential source of the trait variation observed, none were detected in our survey. Quantitative trait variation focusing on flowering time and rosette diameter was scored in control and treated populations where expanded levels of variation were observed among the hypomethylated lines. Methylation sensitive molecular markers indicated that 5-azacytidine induced alterations in DNA methylation patterns and inheritance of methylation patterns were confirmed by bisulfite sequencing of targeted regions. It is possible that methylation polymorphisms might underlie or have induced genetic changes underlying the observable differences in quantitative phenotypes. CONCLUSIONS: This population developed in a uniform genetic background provides a resource for the discovery of new variation controlling quantitative traits. Genome sequence analysis indicates that 5-azacytidine did not induce point mutations and the induced variation is largely restricted to DNA methylation. Using this resource, we have identified new variation and demonstrated the inheritance of both variant trait and methylation patterns. Although direct associations remain to be determined, these data suggest epigenetic variation might be subject to selection.

Microsatellite markers used for genome-wide association mapping of partial resistance to Sclerotinia sclerotiorum in a world collection of Brassica napus.

The fungal pathogen Sclerotinia sclerotiorum causes stem rot of oilseed rape (Brassica napus) worldwide. In preparation for genome-wide association mapping (GWAM) of sclerotinia resistance in B. napus, 152 accessions from diverse geographical regions were screened with a single Canadian isolate, #321. Plants were inoculated by attaching mycelium plugs to the main stem at full flower. Lesion lengths measured 7, 14 and 21 days after inoculation were used to calculate the area under the disease progress curve (AUDPC). Depth of penetration was noted and used to calculate percent soft and collapsed lesions (% s + c). The two disease traits were highly correlated (r = 0.93). Partially resistant accessions (AUDPC <7 and % s + c <2) were identified primarily from South Korea and Japan with a few from Pakistan, China and Europe. Genotyping of accessions with 84 simple sequence repeat markers provided 690 polymorphic loci for GWAM. The general linear model in TASSEL best fitted the data when adjusted for population structure (STRUCTURE), GLM + Q. After correction for positive false discovery rate, 34 loci were significantly associated with both disease traits of which 21 alleles contributed to resistance, while the remaining enhanced susceptibility. The phenotypic variation explained by the loci ranged from 6 to 25 %. Five loci mapped to published quantitative trait loci conferring sclerotinia resistance in Chinese lines.

Different cellular localization, translocation, and insulin-induced phosphorylation of PKBalpha in HepG2 cells and hepatocytes.

Protein kinase B (PKB), a serine/threonine protein kinase, prevents apoptosis and promotes cellular transformation. PKB activity is stimulated by insulin. In this report, we examined the relative amounts of expression, location, and translocation upon insulin stimulation of PKBalpha in normal primary hepatocytes and carcinoma cells, HepG2 cells. Non-phosphorylated PKBalpha was present in both types of unstimulated cells. The phosphorylated form of the enzyme was present in the nucleus of unstimulated HepG2 cells but not in normal hepatocytes. In the cytoplasm, PKBalpha was found in greater abundance in the hepatocytes as compared in HepG2 cells. Insulin induced the translocation of phosphorylated PKBalpha from the nucleus to the nuclear membrane in HepG2 cells. In contrast, insulin caused translocation and phosphorylation of PKBalpha from the cytosol to the plasma membrane in normal hepatocytes. In addition, there is a higher expression of PKBalpha in the HepG2 cells as compared to normal primary hepatocytes. These findings provide an important distinction between hepatocellular HepG2 cells and normal liver cells and suggest that the presence of constitutively active nuclear PKB in the transformed cells might be an important contributor in cell transformation and immortality of hepatoma cells.