Ekaterina Khrameeva

Assistant Professor
Center of Life Sciences

Dr. Ekaterina Khrameeva graduated from the Department of Bioengineering and Bioinformatics, Moscow State University, in 2009. Since 2007, she has been working with Prof. Mikhail Gelfand at the Institute for Information Transmission Problems, where she defended her PhD thesis on chromatin architecture and alternative splicing, in 2015. During her postgraduate studies, Ekaterina worked as a bioinformatician at the Justus Liebig University (Giessen), the Helmholtz Zentrum München (Munich), the Partner Institute for Computational Biology (Shanghai), and the Leiden University Medical Center (Netherlands). Starting from 2014, she has been working on the analysis of lipidome and transcriptome in the human brain with Prof. Philipp Khaitovich at Skoltech. In 2019, Ekaterina has been promoted to the position of an Assistant Professor at the Center of Life Sciences. Ekaterina won several competitions and research grants and published 29 papers.

The research area spans a wide range of biological problems, organisms, and types of biological data: from genome variation to the chromatin architecture, gene expression, and metabolic evolution, from unicellular organisms to humans, and from genome to the metabolome. The main focus is on the deep bioinformatics analysis of various types of ‘omics data generated by wet-lab collaborators, and on the integration of biological data sets that can lead to the discovery of important biological insights on mechanisms of cell and organ functioning.

Ongoing projects:

Chromatin organization changes between life stages of soil-living amoeba Dictyostelium discoideum. Recent advances enabled by the Hi-C technique had unraveled many principles of chromosomal folding that have been subsequently linked to disease and gene regulation. However, we still know remarkably little about chromatin architecture in organisms other than mammals and fruit flies. To explore the changes of chromosomal folding during the life cycle of soil-living amoeba Dictyostelium discoideum, we performed Hi-C in two biological replicates at 0, 2, 5, and 8 h, and constructed high-resolution interaction maps that revealed the presence of loops. Loops often form regular patterns and do not change their position in the genome between the life cycle stages. Interestingly, the orientation of genes near loops is not random: housekeeping genes clearly tend to have convergent orientation, while differentially expressed genes show a weaker tendency. Moreover, genes inside loops have higher expression than genes outside loops. Thus, gene orientation and expression is important for loop formation but the exact mechanism remains to be unraveled.

Histone acetylation level regulates formation of TADs. Hi-C technique revealed that chromosomes of mammals and fruit flies are organized into spatially compact Topologically Associating Domains (TADs). In fruit flies, the mechanism of TAD formation is not yet clear. In this project, we test the hypothesis that the mechanism of TAD self-assembly is based on the ability of nucleosomes from inactive chromatin to aggregate, and on the lack of this ability in acetylated nucleosomal arrays. We analyzed data of Hi-C and Chip-Seq (with antibodies against pan acetylated H3 histone) experiments in control D. melanogaster late embryonic (Schneider-2) cells, as well as in HDAC1-depleted cells and in cells treated with histone acetyltransferase inhibitor curcumin or histone deacetylase inhibitor trichostatin A. Acetylation level changes were studied, in association with TAD position and density differences. Inhibition of HDAC1 was found to lead to an increase of acetylation level in interTAD regions, and coordinated changes in TAD structure. Thus, histone acetylation plays a key role in the mechanism of TAD formation in Drosophila.

Chromatin structure changes during Drosophila spermatogenesis. Spermatogenesis is accompanied by dramatic changes of gene expression. The spatial organization of chromatin can impact gene expression but the extent of chromatin structure changes during the development of sperm cells remains unclear. To investigate links between chromatin architecture and gene expression changes during spermatogenesis, we analyzed RNA-seq data and high-resolution Hi-C interaction maps of Drosophila testis at two spermatogenesis stages, spermatocytes and spermatogonia. The study included chromatin interactions at different scales: from interactions of single genes to chromatin compartments. Preliminary results show a clear correlation (Spearman’s R=0.27) between chromatin compartmentalization and expression changes. Namely, transition from an inactive to an active compartment is associated with an increase of total expression level. Moreover, genes that are active in spermatocytes tend to have less compact chromatin around their TSSs (p<10-9), in line with current understanding of interplay between chromatin folding and transcription.

Neural network applications for chromatin 3D structure analysis. Hi-C method allows one to analyze three-dimensional structure of chromosomes with high accuracy, however it has technical drawbacks. One of them is the presence of regions with missing values in resulting Hi-C maps that create difficulties for downstream analysis. We developed a procedure of missing values inference from the surrounding map segments using neural networks as the predictive model. Training and test sets were formed from the Drosophila embryo Hi-C data, excluding empty or low-quality map regions. We trained and tested three predictive models – shallow neural network with two features (upper and lower pixels), medium sized neural network with eight features (diagonal pixels) and deep neural network with twenty features (the surrounding square of pixels). We calculated RMSE and R^2 values and reconstructed Hi-C map regions using these three models. Deep neural network with twenty features demonstrated the best performance.

Close to completion:

Evolution of the human brain transcriptome at the single-cell resolution. While our understanding of the human brain evolution is advancing, our knowledge of expression differences unique to its particular areas and cell types is still incomplete. In this project, we present an analysis of gene expression differences between humans and age-matched chimpanzees, bonobos, and rhesus monkeys conducted in 33 brain regions using conventional RNA sequencing. For three of these regions, we further analyzed uniquely human expression differences at the single cell level, generating data from more than 100,000 cell nuclei. We show that gene expression evolves rapidly within cell types, with more than two-thirds of cell type-specific differences not detected using conventional RNA sequencing. Neurons tend to evolve faster in all hominids, but astrocytes show more differences on the human lineage, including alterations of spatial distribution across neocortical layers. Integration of human-specific differences across 33 brain regions further reveals co-evolving anatomically distributed regional modules coinciding with functional networks defined by functional brain imaging.

A comprehensive map of the human brain lipidome and its evolution. The lipid composition of brain anatomical structures remains poorly understood, particularly in humans and closely related non-human primates. We describe the generation and analysis of a lipidome atlas of the adult human brain, comprising a large-scale mass spectrometry-based lipidome profiling of 75 anatomically precise subdivisions in four individuals. To explore evolution of the human brain lipidome, we additionally produce lipidome atlases of adult chimpanzee, bonobo and macaque brains in three individuals per species, as well as transcriptome atlases for the same 597 samples of these primate species and human. Lipidome profiles show striking anatomical specificity in non-cortical brain regions, while in neocortex lipidome composition is strongly associated with functional networks of the brain structures. By contrast, at the level of transcriptome, anatomical specificity of gene expression levels prevails both in non-cortical and cortical structures. Prefrontal cortical regions, together with the white matter, show the highest human-specificity of lipid intensities, supported by observations at the gene expression level.

Khrameeva E*, Kurochkin I*, Han D*, Guijarro P, Kanton S, Santel M, Qian Z, Rong S, Mazin P, Sabirov M, Bulat M, Efimova O, Tkachev A, Guo S, Sherwood CC, Camp JG, Pääbo S, Treutlein B, Khaitovich P. Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains. Genome Res. 2020 May;30(5):776-789.

Yegodayev KM, Novoplansky O, Golden A, Prasad M, Levin L, Jagadeeshan S, Zorea J, Dimitstein O, Joshua BZ, Cohen L, Khrameeva E*, Elkabets M*. TGF-Beta-Activated Cancer-Associated Fibroblasts Limit Cetuximab Efficacy in Preclinical Models of Head and Neck Cancer. Cancers (Basel). 2020 Feb 3;12(2).

Tkachev A, Stepanova V, Zhang L, Khrameeva E, Zubkov D, Giavalisco P, Khaitovich P. Differences in lipidome and metabolome organization of prefrontal cortex among human populations. Sci Rep. 2019 Dec 4;9(1):18348.

Kurochkin I*, Khrameeva E*, Tkachev A, Stepanova V, Vanyushkina A, Stekolshchikova E, Li Q, Zubkov D, Shichkova P, Halene T, Willmitzer L, Giavalisco P, Akbarian S, Khaitovich P. Metabolome signature of autism in the human prefrontal cortex. Commun Biol. 2019 Jun 21;2:234.

Ulianov SV*, Doronin SA*, Khrameeva EE*, Kos PI*, Luzhin AV, Starikov SS, Galitsyna AA, Nenasheva VV, Ilyin AA, Flyamer IM, Mikhaleva EA, Logacheva MD, Gelfand MS, Chertovich AV, Gavrilov AA, Razin SV, Shevelyov YY. Nuclear lamina integrity is required for proper spatial organization of chromatin in Drosophila. Nat Commun. 2019; 10(1):1176.

Luzhin AV, Flyamer IM, Khrameeva EE, Ulianov SV, Razin SV, Gavrilov AA. Quantitative differences in TAD border strength underly the TAD hierarchy in Drosophila chromosomes. J Cell Biochem. 2019; 120(3):4494-4503.

Khrameeva E*, Kurochkin I*, Bozek K, Giavalisco P, Khaitovich P. Lipidome evolution in mammalian tissues. Mol Biol Evol. 2018; 35(8):1947-1957.

Akkuratov EE, Gelfand MS, Khrameeva EE. Neanderthal and Denisovan ancestry in Papuans: A functional study. J Bioinform Comput Biol. 2018; 16(2):1840011.

Triska P, Chekanov N, Stepanov V, Khusnutdinova EK, Kumar GPA, Akhmetova V, Babalyan K, Boulygina E, Kharkov V, Gubina M, Khidiyatova I, Khitrinskaya I, Khrameeva EE, Khusainova R, Konovalova N, Litvinov S, Marusin A, Mazur AM, Puzyrev V, Ivanoshchuk D, Spiridonova M, Teslyuk A, Tsygankova S, Triska M, Trofimova N, Vajda E, Balanovsky O, Baranova A, Skryabin K, Tatarinova TV, Prokhortchouk E. Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe. BMC Genet. 2017;18(Suppl 1):110.

Ulianov SV, Galitsyna AA, Flyamer IM, Golov AK, Khrameeva EE, Imakaev MV, Abdennur NA, Gelfand MS, Gavrilov AA, Razin SV. Activation of the alpha-globin gene expression correlates with dramatic upregulation of nearby non-globin genes and changes in local and large-scale chromatin spatial structure. Epigenetics&Chromatin. 2017; 10(1):35.

Bozek K, Khrameeva EE, Reznick J, Omerbašić D, Bennett NC, Lewin GR, Azpurua J, Gorbunova V, Seluanov A, Regnard P, Wanert F, Marchal J, Pifferi F, Aujard F, Liu Z, Shi P, Pääbo S, Schroeder F, Willmitzer L, Giavalisco P, Khaitovich P. Lipidome determinants of maximal lifespan in mammals. Sci Rep. 2017; 7(1):5.

Gavrilov AA, Shevelyov YY, Ulianov SV, Khrameeva EE, Kos P, Chertovich A, Razin SV. Unraveling the mechanisms of chromatin fibril packaging. Nucleus. 2016; 7(3):319-24.

Khrameeva EE, Fudenberg G, Gelfand MS, Mirny LA. History of chromosome rearrangements reflects the spatial organization of yeast chromosomes. J Bioinform Comput Biol. 2016; 1641002.

Zhang B, Han D, Korostelev Y, Yan Z, Shao N, Khrameeva E, Velichkovsky BM, Chen YP, Gelfand MS, Khaitovich P. Changes in snoRNA and snRNA abundance in the human, chimpanzee, macaque and mouse brain. Genome Biol Evol. 2016; evw038.

Flegontov P, Changmai P, Zidkova A, Logacheva MD, Altınışık NE, Flegontova O, Gelfand MS, Gerasimov ES, Khrameeva EE, Konovalova OP, Neretina T, Nikolsky YV, Starostin G, Stepanova VV, Travinsky IV, Tříska M, Tříska P, Tatarinova TV. Genomic study of the Ket: a Paleo-Eskimo-related ethnic group with significant ancient North Eurasian ancestry. Sci Rep. 2016; 6:20768.

Ulianov SV*, Khrameeva EE*, Gavrilov AA, Flyamer IM, Kos P, Mikhaleva EA, Penin AA, Logacheva MD, Imakaev MV, Chertovich A, Gelfand MS, Shevelyov YY, Razin SV. Active chromatin and transcription play a key role in chromosome partitioning into topologically associating domains. Genome Res. 2016; 26(1):70-84.

Torkova A, Koroleva O, Khrameeva E, Fedorova T, Tsentalovich M. Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction. Int J Mol Sci. 2015; 16(10):25353-76.

Kaufmann S, Fuchs C, Gonik M, Khrameeva EE, Mironov AA, Frishman D. Inter-chromosomal contact networks provide insights into Mammalian chromatin organization. PLoS One. 2015; 10(5):e0126125.

Zhenilo S, Khrameeva E, Tsygankova S, Zhigalova N, Mazur A, Prokhortchouk E. Individual genome sequencing identified a novel enhancer element in exon 7 of the CSFR1 gene by shift of expressed allele ratios. Gene. 2015; 566(2):223-8.

Yang J, Hung LH, Licht T, Kostin S, Looso M, Khrameeva E, Bindereif A, Schneider A, Braun T. RBM24 is a major regulator of muscle-specific alternative splicing. Dev Cell. 2014; 31(1):87-99.

Koroleva O, Torkova A, Nikolaev I, Khrameeva E, Fedorova T, Tsentalovich M, Amarowicz R. Evaluation of the antiradical properties of phenolic acids. Int J Mol Sci. 2014; 15(9):16351-80.

Khrameeva EE, Bozek K, He L, Yan Z, Jiang X, Wei Y, Tang K, Gelfand MS, Prufer K, Kelso J, Paabo S, Giavalisco P, Lachmann M, Khaitovich P. Neanderthal ancestry drives evolution of lipid catabolism in contemporary Europeans. Nat Commun. 2014; 5:3584.

Rossbach O, Hung LH, Khrameeva E, Schreiner S, König J, Curk T, Zupan B, Ule J, Gelfand MS, Bindereif A. Crosslinking-immunoprecipitation (iCLIP) analysis reveals global regulatory roles of hnRNP L. RNA Biol. 2014; 11(2):146-55.

Rösel-Hillgärtner TD, Hung LH, Khrameeva E, Le Querrec P, Gelfand MS, Bindereif A. A novel intra-U1 snRNP cross-regulation mechanism: alternative splicing switch links U1C and U1-70K expression. PLoS Genet. 2013; 9(10):e1003856.

Khrameeva EE, Gelfand MS. Biases in read coverage demonstrated by interlaboratory and interplatform comparison of 117 mRNA and genome sequencing experiments. BMC Bioinformatics. 2012; 13 Suppl 6:S4.

Khrameeva EE, Mironov AA, Fedonin GG, Khaitovich P, Gelfand MS. Spatial proximity and similarity of the epigenetic state of genome domains. PLoS One. 2012; 7(4):e33947.

Pervouchine DD, Khrameeva EE, Pichugina MY, Nikolaienko OV, Gelfand MS, Rubtsov PM, Mironov AA. Evidence for widespread association of mammalian splicing and conserved long-range RNA structures. RNA. 2012; 18(1):1-15.

Khrameeva EE, Drutsa VL, Vrzheshch EP, Dmitrienko DV, Vrzheshch PV. Mutants of monomeric red fluorescent protein mRFP1 at residue 66: structure modeling by molecular dynamics and search for correlations with spectral properties. Biochemistry (Mosc). 2008; 73(10):1085-95.

Feb. 2015: Institute for Information Transmission Problems

Candidate of biological sciences degree

2009 – 2012: Moscow State University

Faculty of Bioengineering and Bioinformatics

PhD student

Thesis “Distant interactions in eukaryotic genomes and regulation of splicing”

Supervisors Prof. Andrey Mironov, Prof. Mikhail Gelfand

2004 – 2009:  Moscow State University

Faculty of Bioengineering and Bioinformatics

Specialist degree, graduated cumlaudae

Thesis “Search for RNA secondary structures participating in regulation of splicing”

Supervisors Dr. Dmitry Pervouchine, Prof. Mikhail Gelfand

  • Chromatin 3D structure
  • Evolution and molecular biology
  • Neanderthal ancestry in modern humans
  • Regulation of alternative splicing
  • RNA secondary structure

Systems Biology Fellowship Program, 2016-2019.

Winner, for the project ‘Molecular signatures of normal and aberrant development, aging and longevity in human brain’.

Academia Europaea, 2014.

Prize for Young Russian Scientists.

Russian Foundation for Basic Research, 2012-2013.

Grant for young scientists.

Natural Science Foundation of China, 2012-2013.

The Research Fellowship for International Young Scientists.

Chinese Academy of Sciences, 2011-2012.

Fellowship for young international scientists.

Dynasty Foundation, 2010-2011 (Dmitry Zimin’s Russian Charitable Foundation).

Young scientist fellowship (molecular and cellular biology).

International Competition of Scientific Papers in Nanotechnology for Young Researchers «Rusnanotech ’08».

Winner, the second prize.

Severin Prize, 2008.

Winner, the first prize.

XV International Conference “Lomonosov-2008”.

Prize for the best report.


Pavel Burmistrov
MSc student
Victoria Kobets
PhD student
Anna Krasivskaya
MSc Student
Dmitrii Kriukov
PhD student
Ilya Pletenev
MSc student
Dmitrii Smirnov
PhD student
Alexander Cherkasov
Junior Research Scientist
Anastasiia Golova
Junior Research Scientist
Anna Kononkova
Junior Research Scientist
Artemy Shumskiy
MS student
Irina Zhegalova
Research Intern