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Sielemann, K.

Publications and source records attributed to Sielemann, K..

5 recordsLinked to original sources

Repeat turnover meets stable chromosomes: repetitive DNA sequences mark speciation and gene pool boundaries in sugar beet and wild beets

BackgroundSugar beet (Beta vulgaris subsp. vulgaris) and its crop wild relatives share a base chromosome number of nine and similar chromosome morphologies. Yet, interspecific breeding is impeded by chromosome and sequence divergence that is still not fully understood. Since repetitive DNA sequences represent the fastest evolving parts of the genome, they likely impact genomic variability and contribute to the separation of beet gene pools. Hence, we investigated if innovations and losses in the repeatome can be linked to chromosomal differentiation and speciation. ResultsWe traced genome- and chromosome-wide evolution across sugar beet and twelve wild beets comprising all sections of the beet genera Beta and Patellifolia. For this, we combined data from short and long read sequencing, flow cytometry, and cytogenetics to build a comprehensive data framework for our beet panel that spans the complete scale from DNA sequence to chromosome up to the genome. Genome sizes and repeat profiles reflect the separation of the beet species into three gene pools. These gene pools harbor repeats with contrasting evolutionary patterns: We identified section- and species-specific repeat emergences and losses, e.g. of the retrotransposons causal for genome expansions in the section Corollinae/Nanae. Since most genomic variability was found in the satellite DNAs, we focused on tracing the 19 beetSat families across the three beet sections/genera. These taxa harbor evidence for contrasting strategies in repeat evolution, leading to contrasting satellite DNA profiles and fundamentally different centromere architectures, ranging from chromosomal uniformity in Beta and Patellifolia species to the formation of patchwork chromosomes in Corollinae/Nanae species. ConclusionsWe show that repetitive DNA sequences are causal for genome size expansion and contraction across the beet genera, providing insights into the genomic underpinnings of beet speciation. Satellite DNAs in particular vary considerably among beet taxa, leading to the evolution of distinct chromosomal setups. These differences likely contribute to the barriers in beet breeding between the three gene pools. Thus, with their isokaryotypic chromosome sets, beet genomes present an ideal system for studying the link between repeats, genome variability, and chromosomal differentiation/evolution and provide a theoretical basis for understanding barriers in crop breeding.

genomics↗

Pangenome of cultivated beet and crop wild relatives reveals parental relationships of a tetraploid wild beet

Most crop plants, including sugar beet (Beta vulgaris subsp. vulgaris), suffer from domestication bottlenecks and low genetic diversity caused by extensive selection for few traits. However, crop wild relatives (CWRs) harbour useful traits relevant for crop improvement, including enhanced adaptation to biotic and abiotic stresses. Especially polyploids are interesting from an evolutionary perspective as genes undergo reorganisation after the polyploidisation event. Through neo-and subfunctionalisation, novel functions emerge, which enable plants to cope with changing environments and extreme/harsh conditions. Particularly in the face of climate change, specific stress and pathogen resistances or tolerances gain importance. To introduce such traits into breeding material, CWRs have already been identified as an important source for sustainable breeding. The identification of genes underlying traits of interest is crucial for crop improvement. For beets, the section Corollinae contains the tetraploid species Beta corolliflora (2n=4x=36) that harbours salt and frost tolerances as well as a wealth of pathogen resistances. The number of beneficial traits of B. corolliflora is increased compared to those of the known diploids in this section (all 2n=2x=18). Nevertheless, neither the parental relationships of B. corolliflora have been resolved, nor are genomic resources available to steer sustainable, genomics-informed breeding. To benefit from the resources offered by polyploid beet wild relatives, we generated a comprehensive pangenome dataset including B. corolliflora, Beta lomatogona, and Beta macrorhiza, as well as a more distant wild beet Patellifolia procumbens (2n=2x=18). Joined analyses with publicly available genome sequences of two additional wild beets allowed the identification of genomic regions absent from cultivated beet, providing a sequence database harbouring traits relevant for future breeding endeavours. In addition, we present strong evidence for the parental relationship of the B. corolliflora wild beet as an autotetraploid emerging from B. macrorhiza.

genomics↗

Genomic characterization of a nematode tolerance locus in sugar beet

BackgroundInfection by beet cyst nematodes (BCN, Heterodera schachtii) causes a serious disease of sugar beet, and climatic change is expected to improve the conditions for BCN infection. Yield and yield stability under adverse conditions are among the main breeding objectives. Breeding of BCN tolerant sugar beet cultivars offering high yield in the presence of the pathogen is therefore of high relevance. ResultsTo identify causal genes providing tolerance against BCN infection, we combined several experimental and bioinformatic approaches. Relevant genomic regions were detected through mapping-by-sequencing using a segregating F2 population. DNA sequencing of contrasting F2 pools and analyses of allele frequencies for variant positions identified a single genomic region which confers nematode tolerance. The genomic interval was confirmed and narrowed down by genotyping with newly developed molecular markers. To pinpoint the causal genes within the potential nematode tolerance locus, we generated long read-based genome sequence assemblies of the tolerant parental breeding line Strube U2Bv and the susceptible reference line 2320Bv. We analyzed continuous sequences of the potential locus with regard to functional gene annotation and differential gene expression upon BCN infection. A cluster of genes with similarity to the Arabidopsis thaliana gene encoding nodule inception protein-like protein 7 (NLP7) was identified. Gene expression analyses confirmed transcriptional activity and revealed clear differences between susceptible and tolerant genotypes. ConclusionsOur findings provide new insights into the genomic basis of plant-nematode interactions that can be used to design and accelerate novel management strategies against BCN.

plant biology↗

plASgraph - using graph neural networks to detect plasmid contigs from an assembly graph

Identification of plasmids from sequencing data is an important and challenging problem related to antimicrobial resistance spread and other One-Health issues. In our work, we provide a new architecture for identifying plasmid contigs in fragmented genome assemblies built from short-read data. Unlike previous machine-learning approaches for this problem, which classify individual contigs separately, we employ graph neural networks (GNNs) to include information from the assembly graph. Propagation of information from nearby nodes in the graph allows accurate classification of even short contigs that are difficult to classify based on sequence features or database searches alone. Our new species-agnostic software tool plASgraph outperforms recently developed PlasForest, which uses database searches to supplement sequence-based features. Since our tool does not rely on existing plasmid databases, it is more suitable for classification of contigs in novel species and discovery of previously unknown plasmid sequences. Our tool can also be trained on a specific species, and in that scenario it outperforms mlplasmids trained on the same species. On one hand, our work provides a new, accurate, and easy to use tool for plasmid classification; on the other hand, it serves as a motivation for more widespread use of GNNs in bioinformatics, such as in pangenome sequence analysis, where sequence graphs serve as a fundamental data structure. Availabilityhttps://github.com/cchauve/plASgraph

bioinformatics↗

Complete pan-plastome sequences enable high resolution phylogenetic classification of sugar beet and closely related crop wild relatives

BackgroundAs the major source of sugar in moderate climates, sugar-producing beets (Beta vulgaris subsp. vulgaris) have a high economic value. However, the low genetic diversity within cultivated beets requires introduction of new traits, for example to increase their tolerance and resistance attributes - traits that often reside in the crop wild relatives. For this, genetic information of wild beet relatives and their phylogenetic placements to each other are crucial. To answer this need, we sequenced and assembled the complete plastome sequences from a broad species spectrum across the beet genera Beta and Patellifolia, both embedded in the Betoideae (order Caryophyllales). This pan-plastome dataset was then used to determine the wild beet phylogeny in high-resolution. ResultsWe sequenced the plastomes of 18 closely related accessions representing 11 species of the Betoideae subfamily and provided high-quality plastome assemblies which represent an important resource for further studies of beet wild relatives and the diverse plant order Caryophyllales. Their assembly sizes range from 149,723 bp (Beta vulgaris subsp. vulgaris) to 152,816 bp (Beta nana), with most variability in the intergenic sequences. Combining plastome-derived phylogenies with read-based treatments based on mitochondrial information, we were able to suggest a unified and highly confident phylogenetic placement of the investigated Betoideae species. Our results show that the genus Beta can be divided into the two clearly separated sections Beta and Corollinae. Our analysis confirms the affiliation of B. nana with the other Corollinae species, and we argue against a separate placement in the Nanae section. Within the Patellifolia genus, the two diploid species Patellifolia procumbens and Patellifolia webbiana are, regarding the plastome sequences, genetically more similar to each other than to the tetraploid Patellifolia patellaris. Nevertheless, all three Patellifolia species are clearly separated. ConclusionIn conclusion, our wild beet plastome assemblies represent a new resource to understand the molecular base of the beet germplasm. Despite large differences on the phenotypic level, our pan-plastome dataset is highly conserved. For the first time in beets, our whole plastome sequences overcome the low sequence variation in individual genes and provide the molecular backbone for highly resolved beet phylogenomics. Hence, our plastome sequencing strategy can also guide genomic approaches to unravel other closely related taxa.

genomics↗