Xavier Hernandez Alias

@biochem.mpg.de

Max Planck Institute of Biochemistry / Technical University of Munich

Xavier Hernandez Alias


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https://researchid.co/xavier_heal

RESEARCH, TEACHING, or OTHER INTERESTS

Biochemistry, Genetics and Molecular Biology, Strategy and Management
12

Scopus Publications

375

Scholar Citations

10

Scholar h-index

10

Scholar i10-index

Scopus Publications

  • Nucleotide dependency analysis of genomic language models detects functional elements
    Pedro Tomaz da Silva, Alexander Karollus, Johannes Hingerl, Gihanna Sta. Teresa Galindez, Nils Wagner, Xavier Hernandez-Alias, Danny Incarnato, Julien Gagneur
    Nature Genetics, 2025
    Deciphering how nucleotides in genomes encode regulatory instructions and molecular machines is a long-standing goal. Genomic language models (gLMs) implicitly capture functional elements and their organization from genomic sequences alone by modeling probabilities of each nucleotide given its sequence context. However, discovering functional genomic elements from gLMs has been challenging due to the lack of interpretable methods. Here we introduce nucleotide dependencies, which quantify how nucleotide substitutions at one genomic position affect the probabilities of nucleotides at other positions. We demonstrate that nucleotide dependencies are more effective at indicating the deleteriousness of genetic variants than alignment-based conservation and gLM reconstruction. Dependency analysis accurately detects regulatory motifs and highlights bases in contact within RNAs, including pseudoknots and tertiary structure contacts, revealing new, experimentally validated RNA structures. Finally, we leverage dependency maps to reveal critical limitations of several gLM architectures and training strategies. Altogether, nucleotide dependency analysis opens a new avenue for discovering and studying functional elements and their interactions in genomes.
  • Using protein-per-mRNA differences among human tissues in codon optimization
    Xavier Hernandez-Alias, Hannah Benisty, Leandro G. Radusky, Luis Serrano, Martin H. Schaefer
    Genome Biology, 2023
    Background Codon usage and nucleotide composition of coding sequences have profound effects on protein expression. However, while it is recognized that different tissues have distinct tRNA profiles and codon usages in their transcriptomes, the effect of tissue-specific codon optimality on protein synthesis remains elusive. Results We leverage existing state-of-the-art transcriptomics and proteomics datasets from the GTEx project and the Human Protein Atlas to compute the protein-to-mRNA ratios of 36 human tissues. Using this as a proxy of translational efficiency, we build a machine learning model that identifies codons enriched or depleted in specific tissues. We detect two clusters of tissues with an opposite pattern of codon preferences. We then use these identified patterns for the development of CUSTOM, a codon optimizer algorithm which suggests a synonymous codon design in order to optimize protein production in a tissue-specific manner. In human cell-line models, we provide evidence that codon optimization should take into account particularities of the translational machinery of the tissues in which the target proteins are expressed and that our approach can design genes with tissue-optimized expression profiles. Conclusions We provide proof-of-concept evidence that codon preferences exist in tissue-specific protein synthesis and demonstrate its application to synthetic gene design. We show that CUSTOM can be of benefit in biological and biotechnological applications, such as in the design of tissue-targeted therapies and vaccines.
  • Genes enriched in A/T-ending codons are co-regulated and conserved across mammals
    Hannah Benisty, Xavier Hernandez-Alias, Marc Weber, Miquel Anglada-Girotto, Federica Mantica, Leandro Radusky, Gökçe Senger, Ferriol Calvet, Donate Weghorn, Manuel Irimia, Martin H. Schaefer, Luis Serrano
    Cell Systems, 2023
  • Single-read tRNA-seq analysis reveals coordination of tRNA modification and aminoacylation and fragmentation
    Xavier Hernandez-Alias, Christopher D Katanski, Wen Zhang, Mahdi Assari, Christopher P Watkins, Martin H Schaefer, Luis Serrano, Tao Pan
    Nucleic Acids Research, 2023
    Transfer RNA (tRNA) utilizes multiple properties of abundance, modification, and aminoacylation in translational regulation. These properties were typically studied one-by-one; however, recent advance in high throughput tRNA sequencing enables their simultaneous assessment in the same sequencing data. How these properties are coordinated at the transcriptome level is an open question. Here, we develop a single-read tRNA analysis pipeline that takes advantage of the pseudo single-molecule nature of tRNA sequencing in NGS libraries. tRNAs are short enough that a single NGS read can represent one tRNA molecule, and can simultaneously report on the status of multiple modifications, aminoacylation, and fragmentation of each molecule. We find correlations among modification-modification, modification-aminoacylation and modification-fragmentation. We identify interdependencies among one of the most common tRNA modifications, m1A58, as coordinators of tissue-specific gene expression. Our method, SingLe-read Analysis of Crosstalks (SLAC), reveals tRNAome-wide networks of modifications, aminoacylation, and fragmentation. We observe changes of these networks under different stresses, and assign a function for tRNA modification in translational regulation and fragment biogenesis. SLAC leverages the richness of the tRNA-seq data and provides new insights on the coordination of tRNA properties.
  • Translational adaptation of human viruses to the tissues they infect
    Xavier Hernandez-Alias, Hannah Benisty, Martin H. Schaefer, Luis Serrano
    Cell Reports, 2021
    Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of 502 human-infecting viruses and determine that tropism explains changes in codon usage. Using the tRNA abundances across 23 human tissues from The Cancer Genome Atlas (TCGA), we build an in silico model of translational efficiency that validates the correspondence of the viral codon usage with the translational machinery of their tropism. For instance, we detect that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is specifically adapted to the upper respiratory tract and alveoli. Furthermore, this correspondence is specifically defined in early viral proteins. The observed tissue-specific translational efficiency could be useful for the development of antiviral therapies and vaccines.
  • Corrigendum to: Translational efficiency across healthy and tumor tissues is proliferation-related (Molecular Systems Biology, (2020), 16, 3, 10.15252/msb.20199275)
    Xavier Hernandez‐Alias, Hannah Benisty, Martin H Schaefer, Luis Serrano
    Molecular Systems Biology, 2021
    The authors noticed a mistake in the computation of wobble-base pairing rules of tRNAs with their respective codons, which affects some of the results. The mistake arises from a misinterpretation of the documentation of the tAI software by dos Reis et al (2003, 2004) (https://github.com/mariodosreis/tai), which led them to place STOP codons at the wrong position of the input list. As a result of this mistake, the codon–anticodon pairing rules were often incorrectly established, and therefore, codon efficiency estimates were partly affected. Although this error does not change the main conclusions, it is important that the corrected results are reported. The authors apologize for these errors and any confusion they may have caused. The specific corrections in the text are detailed below. Abstract From: Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ProCCA and GlyGGT, is associated with poor patient survival. To: Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ArgAGA, is associated with poor patient survival. Synopsis, third bullet point Introduction From: We discover multiple codons, including ProCCA and GlyGGT, whose translational efficiency is compromised and leads to poor prognosis in cancer. To: We discover multiple codons, including ArgAGA, whose translational efficiency is compromised and leads to poor prognosis in cancer. Results, section “tRNA repertoires determine tissue-specific translational efficiency” From: When analyzing the tissue medians of SDA weights per each codon (SDAw), we observe that most codons are optimally balanced (SDAw = 1), while 12.4 and 23.6% of codons are favored (SDAw > 2) and disfavored (SDAw < 0.5), respectively. To: When analyzing the tissue medians of SDA weights per each codon (SDAw), we observe that most codons are optimally balanced (SDAw = 1), while 13.7 and 16.3% of codons are favored (SDAw > 2) and disfavored (SDAw < 0.5), respectively. From: Both the first and second components significantly correlate with the proliferation marker Ki67 (0.4 and 0.35; see Fig 3B). In agreement with the proliferation- and differentiation-related codons of Gingold et al (2014), such proliferative pattern is similarly reproduced by the codons contributing to the first PCA component, which has the strongest association to proliferation (Fig 3B). To: Figure 3. Original. Figure 3. Corrected. From: Consistent with our hypothesis, the results indicate that gut-optimized proteins are enriched in translation, DNA replication, and protein localization, whereas brain-optimized proteins are related to phospholipid production and neural function (Fig 3C, Table EV7). To: Consistent with our hypothesis, the results indicate that gut-optimized proteins are enriched in DNA replication, chromatin organization, and chemokine signaling, whereas brain-optimized proteins are related to tRNA metabolism and cilium morphogenesis (Fig 3C, Table EV7). Results, section “Aberrant translational efficiencies drive tumor progression” From: Among the most consistent changes, the ProCCA codon is significantly more favored in tumors for 8 out of 10 cancer types, while the ProCCG is disfavored in 14 out of 16 cancers (Fig 4B). In the case of glycine, GlyGGT is better adapted in healthy samples (13/13), whereas tumor mostly favors GlyGGC (9/12) and GlyGGG (7/9). To: Figure 4. Original. Figure 4. Corrected. Figure 5. Original. Figure 5. Corrected. From: Among others, and consistent with the previous analysis, high supply-to-demand weights of ProCCA are associated with poor prognosis in kidney renal clear cell carcinoma and kidney renal papillary cell carcinoma. Proline limitation in clear cell renal cell carcinoma has been shown to compromise CCA-decoding tRNAPro aminoacylation, leading to reduced tumor growth (Loayza-Puch et al, 2016). In contrast, high SDAw of GlyGGT and ValGTC lead to longer survival in kidney chromophobe and head and neck squamous cell carcinoma, respectively. To: Among others, and consistent with the previous analysis, high supply-to-demand weights of ArgAGA are associated with poor prognosis in kidney renal clear cell carcinoma and colon adenocarcinoma. Arginine limitation in the kidney cell line HEK293T has been shown to compromise tRNAArg aminoacylation, leading to codon pausing and reduced cell viability (Darnell et al, 2018). In addition, low SDAw of ArgAGG and SerAGT lead to longer survival in kidney renal clear cell carcinoma. From: To determine the impact of aberrant translational efficiencies in regulating an oncogenic translation program, we calculate the differential SDA for the whole genome based on the average SDAw of healthy and tumor samples in kidney renal clear cell carcinoma, since it is the cancer type with the most SDAw differences (Fig 4A). The GSEA of the resulting ΔSDA score indicates that cancer SDAw should favor the translation of proteins related to DNA replication and gene expression, whereas the healthy kidney samples favor development and differentiation processes (Table EV9). As the SDAw of the ProCCA is specifically disturbed in cancer, we also interrogate how this codon is distributed along the genome. We therefore perform a GSEA on the relative codon usage of ProCCA, which shows that DNA replication and cell cycle functions lie among the most CCA-enriched genes, while morphogenesis and differentiation terms are CCA-depleted (Table EV10). To: To determine the impact of aberrant translational efficiencies in regulating an oncogenic translation program, we calculate the differential SDA for the whole genome based on the average SDAw of healthy and tumor samples in kidney renal clear cell carcinoma, since it is the cancer type with the most prognostic differences (Fig 4A). The GSEA of the resulting ΔSDA score indicates that cancer SDAw should favor the translation of proteins related to DNA replication and gene expression, whereas the healthy kidney samples favor signals transduction and differentiation processes (Table EV9). As the SDAw of the ArgAGA is specifically disturbed in cancer, we also interrogate how this codon is distributed along the genome. We therefore perform a GSEA on the relative codon usage of ArgAGA, which shows that proliferation and immune activation functions lie among the most AGA-enriched genes, while development and differentiation terms are AGA-depleted (Table EV10). From: In particular, ProCCA appears as an interesting codon candidate in favoring tumor progression, which we had also detected in healthy tissues to be associated with proliferation (Fig 3B, Table EV6). To: In particular, ArgAGA appears as an interesting codon candidate in favoring tumor progression, which we had also detected in healthy tissues to be associated with proliferation (PCA2 in Table EV6). Results, section “Promoter methylation and gene copy number regulate the tRNA abundance” From: Given the association of the codon ProCCA with cancer prognosis (Fig 4C), we explore the abundance pattern of tRNAPro in TCGA. While both tRNAProTGG and tRNAProAGG are able to decode ProCCA, the latter specifically appears overexpressed in 8 out of 9 cancer types (Fig EV5A), making it a candidate driver of the translational differences. To: Given the association of the codon ArgAGA with cancer prognosis (Fig 4C), we explore the abundance pattern of tRNAArg in TCGA. In agreement, the complementary tRNAArgTCT appears overexpressed in 13 out of 15 cancer types (Fig EV5A), making it a candidate driver of the translational differences. From: In total, tRNAProAGG genes stand among the most duplicated and least methylated proline isoacceptors in cancer (Fig EV6A and B), in particular at the chr6.tRNA12 and chr16.tRNA12 genes (Fig 5B). To: Figure EV4. Original. Figure EV4. Corrected. Figure EV6. Original. Figure EV6. Corrected. Discussion From: In particular, we detect the ProCCA codon to be significantly more favored in proliferative cells and leading to poor cancer prognosis in kidney carcinomas, specifically driven by an overexpression of tRNAProAGG in cancer. Proline limitation in clear cell renal cell carcinoma has indeed been shown to mostly compromise tRNAProAGG aminoacylation, leading to slower proline translation and reduced tumor growth (Loayza-Puch et al, 2016). Furthermore, in support of our approach for isoacceptor quantification and translational efficiency, similar studies of tRNA levels in TCGA have controversially claimed an opposite prognostic value for the ProCCA codon in clear renal cell carcinoma (Zhang et al, 2018, 2019). To: In particular, we detect the ArgAGA codon to be significantly more favored in proliferative cells and leading to poor cancer prognosis in kidney carcinoma, specifically driven by an overexpression of tRNAArgTCT in cancer. Arginine limitation in the kidney cell line HEK293T has indeed been shown to compromise tRNAArg aminoacylation, leading to arginine codon pausing and reduced cell viability (Darnell et al, 2018). Furthermore, in support of our approach for isoacceptor quantification and translational efficiency, similar studies of tRNA levels in TCGA have concordantly claimed a prognostic value for the ArgAGA codon in clear renal cell carcinoma (Zhang et al, 2018, 2019). From: Here, we specifically propose a role for DNA methylation in regulating the overexpression of tRNAProAGG in cancer, although no direct causal link can yet be established. To: Here, we specifically propose a role for DNA methylation in regulating the overexpression of tRNAArgTCT in cancer, although no direct causal link can yet be established. References The reference below has been added Darnell AM, Subramaniam AR & O’Shea EK (2018) Translational control through differential ribosome pausing during amino acid limitation in mammalian cells. Mol Cell 71: 229-243.e11 The reference below has been removed Loayza-Puch F, Rooijers K, Buil LC, Zijlstra J, Oude Vrielink JF, Lopes R, Ugalde AP, van Breugel P, Hofland I, Wesseling J et al (2016) Tumour-specific proline vulnerability uncovered by differential ribosome codon reading. Nature 530: 490–494 Figure 3C legend From: GSEA of the differential SDA between extreme tissues (ΔSDA = SDAColorectal - SDABrain), showing the top five GO terms with high (left) and low (right) SDA in colorectal versus glial tissues. To: GSEA of the differential SDA between extreme tissues (ΔSDA = SDAColorectal - SDABrain), showing five among the top ten GO terms with high (right) and low (left) SDA in colorectal versus glial tissues. Figure 4B legend From: Boxplot of the SDAw of ProCAA and AlaGCG codons across TCGA cancer types. To: Boxplot of the SDAw of ArgAGA and ThrACT codons across TCGA cancer types. Figure 4C legend From: Survival curves for the previous codons in KIRC, KIRP, and BLCA patients. To: Survival curves for the previous codons in KIRC and COAD patients. Figure 5B legend From: Differential promoter methylation (bisulfite sequencing) between healthy and tumor samples of genes expressing proline tRNAs, as measured by Δ%Me=(%MeTumor- %MeHealthy). To: Differential promoter methylation (bisulfite sequencing) between healthy and tumor samples of genes expressing arginine tRNAs, as measured by Δ%Me=(%MeTumor- %MeHealthy). Figure EV6C legend From: Differential gene copy number between healthy and tumor samples of genes expressing proline tRNAs, as measured by ΔCNA. To: Differential gene copy number between healthy and tumor samples of genes expressing arginine tRNAs, as measured by ΔCNA. Table EV10 description From: Table EV10. GSEA RCU ProcCCA. To: Table EV10. GSEA RCU ArgAGA.
  • Silencing of SRRM4 suppresses microexon inclusion and promotes tumor growth across cancers
    Sarah A. Head, Xavier Hernandez-Alias, Jae-Seong Yang, Ludovica Ciampi, Violeta Beltran-Sastre, Antonio Torres-Méndez, Manuel Irimia, Martin H. Schaefer, Luis Serrano
    Plos Biology, 2021
    RNA splicing is widely dysregulated in cancer, frequently due to altered expression or activity of splicing factors (SFs). Microexons are extremely small exons (3–27 nucleotides long) that are highly evolutionarily conserved and play critical roles in promoting neuronal differentiation and development. Inclusion of microexons in mRNA transcripts is mediated by the SF Serine/Arginine Repetitive Matrix 4 (SRRM4), whose expression is largely restricted to neural tissues. However, microexons have been largely overlooked in prior analyses of splicing in cancer, as their small size necessitates specialized computational approaches for their detection. Here, we demonstrate that despite having low expression in normal nonneural tissues, SRRM4 is further silenced in tumors, resulting in the suppression of normal microexon inclusion. Remarkably, SRRM4 is the most consistently silenced SF across all tumor types analyzed, implying a general advantage of microexon down-regulation in cancer independent of its tissue of origin. We show that this silencing is favorable for tumor growth, as decreased SRRM4 expression in tumors is correlated with an increase in mitotic gene expression, and up-regulation of SRRM4 in cancer cell lines dose-dependently inhibits proliferation in vitro and in a mouse xenograft model. Further, this proliferation inhibition is accompanied by induction of neural-like expression and splicing patterns in cancer cells, suggesting that SRRM4 expression shifts the cell state away from proliferation and toward differentiation. We therefore conclude that SRRM4 acts as a proliferation brake, and tumors gain a selective advantage by cutting off this brake.
  • Cysteine and folate metabolism are targetable vulnerabilities of metastatic colorectal cancer
    Josep Tarragó-Celada, Carles Foguet, Míriam Tarrado-Castellarnau, Silvia Marin, Xavier Hernández-Alias, Jordi Perarnau, Fionnuala Morrish, David Hockenbery, Roger R. Gomis, Eytan Ruppin, Mariia Yuneva, Pedro de Atauri, Marta Cascante
    Cancers, 2021
    With most cancer-related deaths resulting from metastasis, the development of new therapeutic approaches against metastatic colorectal cancer (mCRC) is essential to increasing patient survival. The metabolic adaptations that support mCRC remain undefined and their elucidation is crucial to identify potential therapeutic targets. Here, we employed a strategy for the rational identification of targetable metabolic vulnerabilities. This strategy involved first a thorough metabolic characterisation of same-patient-derived cell lines from primary colon adenocarcinoma (SW480), its lymph node metastasis (SW620) and a liver metastatic derivative (SW620-LiM2), and second, using a novel multi-omics integration workflow, identification of metabolic vulnerabilities specific to the metastatic cell lines. We discovered that the metastatic cell lines are selectively vulnerable to the inhibition of cystine import and folate metabolism, two key pathways in redox homeostasis. Specifically, we identified the system xCT and MTHFD1 genes as potential therapeutic targets, both individually and combined, for combating mCRC.
  • In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species
    Javier Delgado Blanco, Xavier Hernandez-Alias, Damiano Cianferoni, Luis Serrano
    Plos Computational Biology, 2020
    The coronavirus disease COVID-19 constitutes the most severe pandemic of the last decades having caused more than 1 million deaths worldwide. The SARS-CoV-2 virus recognizes the angiotensin converting enzyme 2 (ACE2) on the surface of human cells through its spike protein. It has been reported that the coronavirus can mildly infect cats, and ferrets, and perhaps dogs while not pigs, mice, chicken and ducks. Differences in viral infectivity among different species or individuals could be due to amino acid differences at key positions of the host proteins that interact with the virus, the immune response, expression levels of host proteins and translation efficiency of the viral proteins among other factors. Here, first we have addressed the importance that sequence variants of different animal species, human individuals and virus isolates have on the interaction between the RBD domain of the SARS-CoV-2 spike S protein and human angiotensin converting enzyme 2 (ACE2). Second, we have looked at viral translation efficiency by using the tRNA adaptation index. We find that integration of both interaction energy with ACE2 and translational efficiency explains animal infectivity. Humans are the top species in which SARS-CoV-2 is both efficiently translated as well as optimally interacting with ACE2. We have found some viral mutations that increase affinity for hACE and some hACE2 variants affecting ACE2 stability and virus binding. These variants suggest that different sensitivities to coronavirus infection in humans could arise in some cases from allelic variability affecting ACE2 stability and virus binding.
  • Mutation bias within oncogene families is related to proliferation-specific codon usage
    Hannah Benisty, Marc Weber, Xavier Hernandez-Alias, Martin H. Schaefer, Luis Serrano
    Proceedings of the National Academy of Sciences of the United States of America, 2020
    Significance In light of the genetic code, combinations of three nucleotides which are known as synonymous codons, can give rise to the same amino acid. Despite the homology at the protein level, these different codons are recognized distinctly by the translational machinery. The unequal use of synonymous codons influences protein expression. Surprisingly, we find that the coding sequences of KRAS and other frequently mutated cancer genes are adapted to be efficiently translated in proliferating cells in comparison to their family counterparts. Our work contributes to the unsolved question of why in tumors some members of cancer gene families show a higher mutation rate than their family counterparts. Thus, our results elucidate the relationship between tRNA expression, codon usage, and oncogenicity.
  • Translational efficiency across healthy and tumor tissues is proliferation-related
    Xavier Hernandez‐Alias, Hannah Benisty, Martin H Schaefer, Luis Serrano
    Molecular Systems Biology, 2020
  • From research to rapid response: Mass COVID-19 testing by volunteers at the Centre for Genomic Regulation
    Ritobrata Ghose, Álvaro Aranguren-Ibáñez, Niccolò Arecco, Diego Balboa, Marc Bataller, Sergi Beltran, Hannah Benisty, Angèle Bénard, Edgar Bernardo, Sílvia Carbonell Sala, Eloi Casals, Ludovica Ciampi, Livia Condemi, Alberto Corvó, Marta Cosín-Tomás, Mirabai Cuenca-Ardura, Juan Manuel Duran Serrano, María Isabel Espejo Díaz, Marcos Fernandez Callejo, Antoni Gañez-Zapater, Raquel Garcia-Castellanos, Romina Garrido, Gil Henkin, Toni Hermoso Pulido, Xavier Hernandez-Alias, Jorge Herrero Vicente, Matthew Ingham, Wei Ming Lim, Sílvia Llonch, Elena Marmesat Bertoli, Irene Miguel-Escalada, Ariadna Montero-Blay, Cristina Navarrete Hernández, Maria Victoria Neguembor, Róisín-Ana Ní Chárthaigh, Natalia Pardo-Lorente, Laura Pascual-Reguant, Sílvia Pérez-Lluch, Reyes Perza, Martina Pesaresi, Daniel Picó Amador, Paula Pifarré, Davide Piscia, Marcos Plana-Carmona, Julia Ponomarenko, Leandro Radusky, Ezequiel Rivero, Malgorzata Rogalska, Guillem Torcal Garcia, José Wojnacki
    F1000research, 2020

RECENT SCHOLAR PUBLICATIONS

  • Nucleotide dependency analysis of genomic language models detects functional elements
    P Tomaz da Silva, A Karollus, J Hingerl, GST Galindez, N Wagner, ...
    Nature genetics 57 (10), 2589-2602 , 2025
    2025
    Citations: 23
  • Translational repression of viral RNA mediates arbovirus persistence in mosquitoes
    M Talló-Parra, M Puig-Torrents, G Pérez-Vilaró, SR Pons, ...
    bioRxiv, 2025.07. 10.664053 , 2025
    2025
  • Genes enriched in A/T-ending codons are co-regulated and conserved across mammals
    H Benisty, X Hernandez-Alias, M Weber, M Anglada-Girotto, F Mantica, ...
    Cell systems 14 (4), 312-323. e3 , 2023
    2023
    Citations: 24
  • Using protein-per-mRNA differences among human tissues in codon optimization
    X Hernandez-Alias, H Benisty, LG Radusky, L Serrano, MH Schaefer
    Genome Biology 24 (1), 34 , 2023
    2023
    Citations: 26
  • Translational control by differential expression of tRNAs
    X Hernandez Alias
    Universitat Pompeu Fabra , 2023
    2023
  • Single-read tRNA-seq analysis reveals coordination of tRNA modification and aminoacylation and fragmentation
    X Hernandez-Alias, CD Katanski, W Zhang, M Assari, CP Watkins, ...
    Nucleic Acids Research 51 (3), e17-e17 , 2023
    2023
    Citations: 46
  • Translational adaptation of human viruses to the tissues they infect
    X Hernandez-Alias, H Benisty, MH Schaefer, L Serrano
    Cell reports 34 (11) , 2021
    2021
    Citations: 41
  • Silencing of SRRM4 suppresses microexon inclusion and promotes tumor growth across cancers
    SA Head, X Hernandez-Alias, JS Yang, L Ciampi, V Beltran-Sastre, ...
    PLoS Biology 19 (2), e3001138 , 2021
    2021
    Citations: 37
  • Cysteine and folate metabolism are targetable vulnerabilities of metastatic colorectal cancer
    J Tarrago-Celada, C Foguet, M Tarrado-Castellarnau, S Marin, ...
    Cancers 13 (3), 425 , 2021
    2021
    Citations: 30
  • In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species
    J Delgado Blanco, X Hernandez-Alias, D Cianferoni, L Serrano
    PLoS Computational Biology 16 (12), e1008450 , 2020
    2020
    Citations: 38
  • Mutation bias within oncogene families is related to proliferation-specific codon usage
    H Benisty, M Weber, X Hernandez-Alias, MH Schaefer, L Serrano
    Proceedings of the National Academy of Sciences 117 (48), 30848-30856 , 2020
    2020
    Citations: 30
  • From research to rapid response: mass COVID-19 testing by volunteers at the Centre for Genomic Regulation
    R Ghose, Á Aranguren-Ibáñez, N Arecco, D Balboa, M Bataller, S Beltran, ...
    F1000Research 9, 1336 , 2020
    2020
  • Translational efficiency across healthy and tumor tissues is proliferation‐related
    X Hernandez‐Alias, H Benisty, MH Schaefer, L Serrano
    Molecular systems biology 16 (3), MSB199275 , 2020
    2020
    Citations: 80

MOST CITED SCHOLAR PUBLICATIONS

  • Translational efficiency across healthy and tumor tissues is proliferation‐related
    X Hernandez‐Alias, H Benisty, MH Schaefer, L Serrano
    Molecular systems biology 16 (3), MSB199275 , 2020
    2020
    Citations: 80
  • Single-read tRNA-seq analysis reveals coordination of tRNA modification and aminoacylation and fragmentation
    X Hernandez-Alias, CD Katanski, W Zhang, M Assari, CP Watkins, ...
    Nucleic Acids Research 51 (3), e17-e17 , 2023
    2023
    Citations: 46
  • Translational adaptation of human viruses to the tissues they infect
    X Hernandez-Alias, H Benisty, MH Schaefer, L Serrano
    Cell reports 34 (11) , 2021
    2021
    Citations: 41
  • In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species
    J Delgado Blanco, X Hernandez-Alias, D Cianferoni, L Serrano
    PLoS Computational Biology 16 (12), e1008450 , 2020
    2020
    Citations: 38
  • Silencing of SRRM4 suppresses microexon inclusion and promotes tumor growth across cancers
    SA Head, X Hernandez-Alias, JS Yang, L Ciampi, V Beltran-Sastre, ...
    PLoS Biology 19 (2), e3001138 , 2021
    2021
    Citations: 37
  • Cysteine and folate metabolism are targetable vulnerabilities of metastatic colorectal cancer
    J Tarrago-Celada, C Foguet, M Tarrado-Castellarnau, S Marin, ...
    Cancers 13 (3), 425 , 2021
    2021
    Citations: 30
  • Mutation bias within oncogene families is related to proliferation-specific codon usage
    H Benisty, M Weber, X Hernandez-Alias, MH Schaefer, L Serrano
    Proceedings of the National Academy of Sciences 117 (48), 30848-30856 , 2020
    2020
    Citations: 30
  • Using protein-per-mRNA differences among human tissues in codon optimization
    X Hernandez-Alias, H Benisty, LG Radusky, L Serrano, MH Schaefer
    Genome Biology 24 (1), 34 , 2023
    2023
    Citations: 26
  • Genes enriched in A/T-ending codons are co-regulated and conserved across mammals
    H Benisty, X Hernandez-Alias, M Weber, M Anglada-Girotto, F Mantica, ...
    Cell systems 14 (4), 312-323. e3 , 2023
    2023
    Citations: 24
  • Nucleotide dependency analysis of genomic language models detects functional elements
    P Tomaz da Silva, A Karollus, J Hingerl, GST Galindez, N Wagner, ...
    Nature genetics 57 (10), 2589-2602 , 2025
    2025
    Citations: 23
  • Translational repression of viral RNA mediates arbovirus persistence in mosquitoes
    M Talló-Parra, M Puig-Torrents, G Pérez-Vilaró, SR Pons, ...
    bioRxiv, 2025.07. 10.664053 , 2025
    2025
  • Translational control by differential expression of tRNAs
    X Hernandez Alias
    Universitat Pompeu Fabra , 2023
    2023
  • From research to rapid response: mass COVID-19 testing by volunteers at the Centre for Genomic Regulation
    R Ghose, Á Aranguren-Ibáñez, N Arecco, D Balboa, M Bataller, S Beltran, ...
    F1000Research 9, 1336 , 2020
    2020