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

Sugar beet and its 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 DNAs are among the fastest evolving parts of the genome, we investigated, if repeatome innovations and losses are linked to chromosomal differentiation and speciation. We traced genome and chromosome-wide evolution across 13 beet species comprising all sections of the genera Beta and Patellifolia. For this, we combined short and long read sequencing, flow cytometry, and cytogenetics to build a comprehensive framework that spans the complete scale from DNA to chromosome to genome. Genome sizes and repeat profiles reflect the separation into three gene pools with contrasting evolutionary patterns. Among all repeats, satellite DNAs harbor most genomic variability, leading to fundamentally different centromere architectures, ranging from chromosomal uniformity in Beta and Patellifolia to the formation of patchwork chromosomes in Corollinae/Nanae. We show that repetitive DNAs are causal for the genome expansions and contractions across the beet genera, providing insights into the genomic underpinnings of beet speciation. Satellite DNAs in particular vary considerably between beet genomes, leading to the evolution of distinct chromosomal setups in the three gene pools, likely contributing to the barriers in beet breeding. Thus, with their isokaryotypic chromosome sets, beet genomes present an ideal system for studying the link between repeats, genomic variability, and chromosomal differentiation and provide a theoretical fundament for understanding barriers in any crop breeding effort.

Genomic characterization of a nematode tolerance locus in sugar beet.

BACKGROUND: Infection 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. RESULTS: To 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. CONCLUSIONS: Our 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.

plASgraph2: 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. We provide a new architecture for identifying plasmid contigs in fragmented genome assemblies built from short-read data. We employ graph neural networks (GNNs) and the assembly graph to propagate the information from nearby nodes, which leads to more accurate classification, especially for short contigs that are difficult to classify based on sequence features or database searches alone. We trained plASgraph2 on a data set of samples from the ESKAPEE group of pathogens. plASgraph2 either outperforms or performs on par with a wide range of state-of-the-art methods on testing sets of independent ESKAPEE samples and samples from related pathogens. On one hand, our study provides a new accurate and easy to use tool for contig classification in bacterial isolates; on the other hand, it serves as a proof-of-concept for the use of GNNs in genomics. Our software is available at https://github.com/cchauve/plasgraph2 and the training and testing data sets are available at https://github.com/fmfi-compbio/plasgraph2-datasets.

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

BACKGROUND: As 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. RESULTS: We 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. CONCLUSION: In 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.

Truncated titin proteins and titin haploinsufficiency are targets for functional recovery in human cardiomyopathy due to TTN mutations.

Heterozygous truncating variants in TTN (TTNtv), the gene coding for titin, cause dilated cardiomyopathy (DCM), but the underlying pathomechanisms are unclear and disease management remains uncertain. Truncated titin proteins have not yet been considered as a contributor to disease development. Here, we studied myocardial tissues from nonfailing donor hearts and 113 patients with end-stage DCM for titin expression and identified a TTNtv in 22 patients with DCM (19.5%). We directly demonstrate titin haploinsufficiency in TTNtv-DCM hearts and the absence of compensatory changes in the alternative titin isoform Cronos. Twenty-one TTNtv-DCM hearts in our cohort showed stable expression of truncated titin proteins. Expression was variable, up to half of the total titin protein pool, and negatively correlated with patient age at heart transplantation. Truncated titin proteins were not detected in sarcomeres but were present in intracellular aggregates, with deregulated ubiquitin-dependent protein quality control. We produced human induced pluripotent stem cell­derived cardiomyocytes (hiPSC-CMs), comparing wild-type controls to cells with a patient-derived, prototypical A-band-TTNtv or a CRISPR-Cas9­generated M-band-TTNtv. TTNtv-hiPSC-CMs showed reduced wild-type titin expression and contained truncated titin proteins whose proportion increased upon inhibition of proteasomal activity. In engineered heart muscle generated from hiPSC-CMs, depressed contractility caused by TTNtv could be reversed by correction of the mutation using CRISPR-Cas9, eliminating truncated titin proteins and raising wild-type titin content. Functional improvement also occurred when wild-type titin protein content was increased by proteasome inhibition. Our findings reveal the major pathomechanisms of TTNtv-DCM and can be exploited for new therapies to treat TTNtv-related cardiomyopathies.

The Combined Human Genotype of Truncating TTN and RBM20 Mutations Is Associated with Severe and Early Onset of Dilated Cardiomyopathy.

A major cause of heart failure is cardiomyopathies, with dilated cardiomyopathy (DCM) as the most common form. Over 40 genes are linked to DCM, among them TTN and RBM20. Next Generation Sequencing in clinical DCM cohorts revealed truncating variants in TTN (TTNtv), accounting for up to 25% of familial DCM cases. Mutations in the cardiac splicing factor RNA binding motif protein 20 (RBM20) are also known to be associated with severe cardiomyopathies. TTN is one of the major RBM20 splicing targets. Most of the pathogenic RBM20 mutations are localized in the highly conserved arginine serine rich domain (RS), leading to a cytoplasmic mislocalization of mutant RBM20. Here, we present a patient with an early onset DCM carrying a combination of (likely) pathogenic TTN and RBM20 mutations. We show that the splicing of RBM20 target genes is affected in the mutation carrier. Furthermore, we reveal RBM20 haploinsufficiency presumably caused by the frameshift mutation in RBM20.

Reference-based QUantification Of gene Dispensability (QUOD).

BACKGROUND: Dispensability of genes in a phylogenetic lineage, e.g. a species, genus, or higher-level clade, is gaining relevance as most genome sequencing projects move to a pangenome level. Most analyses classify genes as core genes, which are present in all investigated individual genomes, and dispensable genes, which only occur in a single or a few investigated genomes. The binary classification as 'core' or 'dispensable' is often based on arbitrary cutoffs of presence/absence in the analysed genomes. Even when extended to 'conditionally dispensable', this concept still requires the assignment of genes to distinct groups. RESULTS: Here, we present a new method which overcomes this distinct classification by quantifying gene dispensability and present a dedicated tool for reference-based QUantification Of gene Dispensability (QUOD). As a proof of concept, sequence data of 966 Arabidopsis thaliana accessions (Ath-966) were processed to calculate a gene-specific dispensability score for each gene based on normalised coverage in read mappings. We validated this score by comparison of highly conserved Benchmarking Universal Single Copy Orthologs (BUSCOs) to all other genes. The average scores of BUSCOs were significantly lower than the scores of non-BUSCOs. Analysis of variation demonstrated lower variation values between replicates of a single accession than between iteratively, randomly selected accessions from the whole dataset Ath-966. Functional investigations revealed defense and antimicrobial response genes among the genes with high-dispensability scores. CONCLUSIONS: Instead of classifying a gene as core or dispensable, QUOD assigns a dispensability score to each gene. Hence, QUOD facilitates the identification of candidate dispensable genes, associated with high dispensability scores, which often underlie lineage-specific adaptation to varying environmental conditions.

Distinct Myocardial Transcriptomic Profiles of Cardiomyopathies Stratified by the Mutant Genes.

Cardiovascular diseases are the number one cause of morbidity and mortality worldwide, but the underlying molecular mechanisms remain not well understood. Cardiomyopathies are primary diseases of the heart muscle and contribute to high rates of heart failure and sudden cardiac deaths. Here, we distinguished four different genetic cardiomyopathies based on gene expression signatures. In this study, RNA-Sequencing was used to identify gene expression signatures in myocardial tissue of cardiomyopathy patients in comparison to non-failing human hearts. Therefore, expression differences between patients with specific affected genes, namely LMNA (lamin A/C), RBM20 (RNA binding motif protein 20), TTN (titin) and PKP2 (plakophilin 2) were investigated. We identified genotype-specific differences in regulated pathways, Gene Ontology (GO) terms as well as gene groups like secreted or regulatory proteins and potential candidate drug targets revealing specific molecular pathomechanisms for the four subtypes of genetic cardiomyopathies. Some regulated pathways are common between patients with mutations in RBM20 and TTN as the splice factor RBM20 targets amongst other genes TTN, leading to a similar response on pathway level, even though many differentially expressed genes (DEGs) still differ between both sample types. The myocardium of patients with mutations in LMNA is widely associated with upregulated genes/pathways involved in immune response, whereas mutations in PKP2 lead to a downregulation of genes of the extracellular matrix. Our results contribute to further understanding of the underlying molecular pathomechanisms aiming for novel and better treatment of genetic cardiomyopathies.

Transcriptome Analysis Reveals High Similarities between Adult Human Cardiac Stem Cells and Neural Crest-Derived Stem Cells.

For the identification of a stem cell population, the comparison of transcriptome data enables the simultaneous analysis of tens of thousands of molecular markers and thus enables the precise distinction of even closely related populations. Here, we utilized global gene expression profiling to compare two adult human stem cell populations, namely neural crest-derived inferior turbinate stem cells (ITSCs) of the nasal cavity and human cardiac stem cells (hCSCs) from the heart auricle. We detected high similarities between the transcriptomes of both stem cell populations, particularly including a range of neural crest-associated genes. However, global gene expression likewise reflected differences between the stem cell populations with regard to their niches of origin. In a broader analysis, we further identified clear similarities between ITSCs, hCSCs and other adherent stem cell populations compared to non-adherent hematopoietic progenitor cells. In summary, our observations reveal high similarities between adult human cardiac stem cells and neural crest-derived stem cells from the nasal cavity, which include a shared relation to the neural crest. The analyses provided here may help to understand underlying molecular regulators determining differences between adult human stem cell populations.

The reuse of public datasets in the life sciences: potential risks and rewards.

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.