ATAna Tzvetkova

Ana Tzvetkova

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Ana Tzvetkova has a total of 38 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Integrated Multi-Omics Analysis Uncovers Molecular Dysregulation in Glucosylceramide Synthase-Deficient Human Induced Pluripotent Stem Cells

    by Julia Beimdiek, Karsten Cirksena, Charlotte Rossdam, Smilla Brand-Merseburger, Astrid Oberbeck, Philippe V. Barbosa, Ana Tzvetkova, Malte Juchem, Christian Bär, Thomas Thum, et al.

  • Open Access

    Genome-Wide Analysis of Copy Number Variation in Vietnamese Local Chickens

    by Thuy Thi-Dieu Nguyen, Ana Tzvetkova, Mai Thi-Dieu Bui, Vo-Anh-Khoa Do, Thuy Thi-Ngoc Dinh, Phuong Thanh Nguyen, Andreas Walter Kuss, Mauro Penasa, Filippo Cendron

    Copy number variants (CNVs) are large-scale genomic alterations that contribute substantially to genetic diversity and may influence phenotypic variation in livestock. This study investigated the genome-wide CNV landscape of three Vietnamese indigenous chicken breeds. Whole-genome sequencing on the Illumina platform (3–5× coverage) was performed on 24 individuals from Dong Tao (DT), Cay Cum (CC), and Ri (RI) breeds. A total of 1743 CNVs were detected, clustering into 315 copy number variation regions (CNVRs). Most CNVRs were rare, with 31.7% present in only one animal among breeds. Across the genome, 122 unique CNVRs were distributed over 28 chromosomes, predominantly the first five. Losses were the most frequent type (45.9%), followed by gains (39.3%), and mixed events (14.8%). Within these CNVRs, 3633 genes were identified. In DT and RI, CNVR-embedded genes included several candidates, potentially related to adaptability, development, and phenotypic diversification. Notably, DT harbored genes such as EGLN1, OASL, GPX1, DUOX1/DUOXA2 (adaptation, stress/immune response) and LRP4, ZIC1, ZIC4, JARID2, KMT2C, OGN, OMD, and PLOD2 (developmental and skeletal traits), whereas in RI they included genes such as CACNA1S, CALCR, CAPN3, and MAPK13/MAPK14, which may contribute to muscle, bone, and physiological regulation. Functional enrichment analysis revealed numerous genes and Quantitative Trait Loci (QTLs) associated with metabolic, developmental, and immune-related pathways. This study provides the first comprehensive genome-wide CNV profile of Vietnamese indigenous chickens and offers a valuable genomic resource for investigating the genetic basis of breed-specific and adaptive phenotypes.


  • Open Access

    Neighbourhood watch: genomic epidemiology of SARS-CoV-2 variants circulating in a German federal state, Mecklenburg-Western Pomerania, in 2020–2022

    by Christian Kohler, Jacqueline King, Lina Stacker, Katja V. Goller, Juliane Moritz, Anne Pohlmann, Neetika Nath, Ana Tzvetkova, Maximilian Rieck, Sofia Paraskevopoulou, et al.

    Global and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.