Allelic variation in the autotetraploid potato: genes involved in starch and steroidal glycoalkaloid metabolism as a case study.

BACKGROUND: Tuber starch and steroidal glycoalkaloid (SGA)-related traits have been consistently prioritized in potato breeding, while allelic variation pattern of genes that underlie these traits is less explored. RESULTS: Here, we focused on the genes involved in two important metabolic pathways in the potato: starch metabolism and SGA biosynthesis. We identified 119 genes consisting of 81 involved in starch metabolism and 38 in the biosynthesis of steroidal glycoalkaloids, and discovered 96,166 allelic variants among 2,169 gene haplotypes in six autotetraploid potato genomes. Comparative analyses revealed an uneven distribution of allelic variants among gene haplotypes and that the vast majority of deleterious mutations in these genes are retained in heterozygous state in the autotetraploid potato genomes. Leveraging full-length cDNA sequencing data, we find that approximately 70% of haplotypes of the 119 genes are transcribable. Population genetic analyses identify starch and SGA biosynthetic genes that are potentially conserved or diverged between potato varieties with varying starch or SGA content. CONCLUSIONS: These results deepen the understanding of haplotypic diversity within functionally important genes in autotetraploid genomes and may facilitate functional characterization of genes or haplotypes contributing to traits related to starch and SGA in potato.

Phased, chromosome-scale genome assemblies of tetraploid potato reveal a complex genome, transcriptome, and predicted proteome landscape underpinning genetic diversity.

Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome. Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity, including altered coding and transcript sequences, preferential allele expression, and structural variation that collectively result in a highly complex transcriptome and predicted proteome, which are distributed across the homologous chromosomes. Wild species contribute to the extensive allelic diversity in tetraploid cultivars, demonstrating ancestral introgressions predating modern breeding efforts. As a clonally propagated autotetraploid that undergoes limited meiosis, dysfunctional and deleterious alleles are not purged in tetraploid potato. Nearly a quarter of the loci bore mutations are predicted to have a high negative impact on protein function, complicating breeder's efforts to reduce genetic load. The StCDF1 locus controls maturity, and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent manner. Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous, diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.

De novo whole-genome assembly of Chrysanthemum makinoi, a key wild chrysanthemum.

Chrysanthemum is among the top 10 cut, potted, and perennial garden flowers in the world. Despite this, to date, only the genomes of two wild diploid chrysanthemums have been sequenced and assembled. Here, we present the most complete and contiguous chrysanthemum de novo assembly published so far, as well as a corresponding ab initio annotation. The cultivated hexaploid varieties are thought to originate from a hybrid of wild chrysanthemums, among which the diploid Chrysanthemum makinoi has been mentioned. Using a combination of Oxford Nanopore long reads, Pacific Biosciences long reads, Illumina short reads, Dovetail sequences, and a genetic map, we assembled 3.1 Gb of its sequence into nine pseudochromosomes, with an N50 of 330 Mb and a BUSCO complete score of 92.1%. Our ab initio annotation pipeline predicted 95,074 genes and marked 80.0% of the genome as repetitive. This genome assembly of C. makinoi provides an important step forward in understanding the chrysanthemum genome, evolution, and history.

Systematic analysis of bypass suppression of essential genes.

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

Solyntus, the New Highly Contiguous Reference Genome for Potato (Solanum tuberosum).

With the rapid expansion of the application of genomics and sequencing in plant breeding, there is a constant drive for better reference genomes. In potato (Solanum tuberosum), the third largest food crop in the world, the related species S. phureja, designated "DM", has been used as the most popular reference genome for the last 10 years. Here, we introduce the de novo sequenced genome of Solyntus as the next standard reference in potato genome studies. A true Solanum tuberosum made up of 116 contigs that is also highly homozygous, diploid, vigorous and self-compatible, Solyntus provides a more direct and contiguous reference then ever before available. It was constructed by sequencing with state-of-the-art long and short read technology and assembled with Canu. The 116 contigs were assembled into scaffolds to form each pseudochromosome, with three contigs to 17 contigs per chromosome. This assembly contains 93.7% of the single-copy gene orthologs from the Solanaceae set and has an N50 of 63.7 Mbp. The genome and related files can be found at https://www.plantbreeding.wur.nl/Solyntus/ With the release of this research line and its draft genome we anticipate many exciting developments in (diploid) potato research.

A framework for exhaustively mapping functional missense variants.

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.

Exploring genetic suppression interactions on a global scale.

Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

Assessment of Eclipse electron Monte Carlo output prediction for various topologies.

Monte Carlo simulation is deemed to be the leading algorithm for accurate dose calculation with electron beams. Patient anatomy (contours and tissue densities) as well as irradiation geometry is accounted for. The accuracy of the Monitor Unit (MU) determination is one essential aspect of a treatment planning system. Patient-specific quality assurance of a Monte Carlo plan usually involves verification of the MUs with an independent simpler calculation approach, in which flat geometry is to be assumed. The magnitude of the discrepancies between flat and varied surfaces for a few scenarios has been investigated in this study. The ability to predict MUs for various surface topologies by the commercial electron Monte Carlo implementation from Varian Eclipse system (Eclipse eMC) has been evaluated and compared to the Generalized Gaussian Pencil Beam (GGPB) algorithm. Ten phantoms with different topologies were constructed of water-equivalent material. Measurements with a parallel plate ionization chamber were performed using these phantoms to gauge their relative impact on outputs for 6, 9, 12, 16, and 20MeV electron beams from a Varian TrueBeam with cone sizes ranging from 6 × 6 cm2 to 25 × 25 cm2. The corresponding Monte Carlo simulations of the measured geometries were carried out using the CT scans of these phantoms. The results indicated that the Eclipse eMC algorithm can predict these output changes within 3% for most scenarios. However, at the lowest energy, the discrepancy was the greatest, up to 6%. In comparison, the Eclipse GGPB algorithm had much worse agreement, with discrepancies up to 17% at the lowest energies.