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Expression microarrays are powerful technology that allows large-scale analysis of RNA profiles in a tissue; these platforms include underexploited detection scores outputs. We developed an algorithm using the detection score, to generate a detection profile of shared elements in retinoblastoma as well as to determine its transcriptomic size and structure. We analyzed eight briefly cultured primary retinoblastomas with the Human transcriptome array 2.0 (HTA2.0). Transcripts and genes detection scores were determined using the Detection Above Background algorithm (DABG). We used unsupervised and supervised computational tools to analyze detected and undetected elements; WebGestalt was used to explore functions encoded by genes in relevant clusters and performed experimental validation. We found a core cluster with 7,513 genes detected and shared by all samples, 4,321 genes in a cluster that was commonly absent, and 7,681 genes variably detected across the samples accounting for tumor heterogeneity. Relevant pathways identified in the core cluster relate to cell cycle, RNA transport, and DNA replication. We performed a kinome analysis of the core cluster and found 4 potential therapeutic kinase targets. Through analysis of the variably detected genes, we discovered 123 differentially expressed transcripts between bilateral and unilateral cases. This novel analytical approach allowed determining the retinoblastoma transcriptomic size, a shared active transcriptomic core among the samples, potential therapeutic target kinases shared by all samples, transcripts related to inter tumor heterogeneity, and to determine transcriptomic profiles without the need of control tissues. This approach is useful to analyze other cancer or tissue types.

Here we studied HLA blocks and haplotypes in a group of 218 Lacandon Maya Native American using a high-resolution next generation sequencing (NGS) method. We assessed the genetic diversity of HLA class I and class II in this population, and determined the most probable ancestry of Lacandon Maya HLA class I and class II haplotypes. Importantly, this Native American group showed a high degree of both HLA homozygosity and linkage disequilibrium across the HLA region and also lower class II HLA allelic diversity than most previously reported populations (including other Native American groups). Distinctive alleles present in the Lacandon population include HLA-A*24:14 and HLA-B*40:08. Furthermore, in Lacandons we observed a high frequency of haplotypes containing the allele HLA-DRB1*04:11, a relatively frequent allele in comparison with other neighboring indigenous groups. The specific demographic history of the Lacandon population including inbreeding, as well as pathogen selection, may have elevated the frequencies of a small number of HLA class II alleles and DNA blocks. To assess the possible role of different selective pressures in determining Native American HLA diversity, we evaluated the relationship between genetic diversity at HLA-A, HLA-B and HLA-DRB1 and pathogen richness for a global dataset and for Native American populations alone. In keeping with previous studies of such relationships we included distance from Africa as a covariate. After correction for multiple comparisons we did not find any significant relationship between pathogen diversity and HLA genetic diversity (as measured by polymorphism information content) in either our global dataset or the Native American subset of the dataset. We found the expected negative relationship between genetic diversity and distance from Africa in the global dataset, but no relationship between HLA genetic diversity and distance from Africa when Native American populations were considered alone.

Systemic Lupus Erythematosus (SLE) is an autoimmune inflammatory disorder for which Major Histocompatibility Complex (MHC) genes are well identified as risk factors. SLE patients present different clinical phenotypes, which are partly explained by admixture patterns variation among Mexicans. Population genetic has insight into the high genetic variability of Mexicans, mainly described through HLA gene studies with anthropological and biomedical importance. A prospective, case-control study was performed. In this study, we recruited 146 SLE patients, and 234 healthy individuals were included as a control group; both groups were admixed Mexicans from Mexico City. The HLA typing methods were based on Next Generation Sequencing and Sequence-Based Typing (SBT). The data analysis was performed with population genetic programs and statistical packages. The admixture estimations based on HLA-B and -DRB1 revealed that SLE patients have a higher Southwestern European ancestry proportion (48 ± 8%) than healthy individuals (30 ± 7%). In contrast, Mexican Native American components are diminished in SLE patients (44 ± 1%) and augmented in Healthy individuals (63 ± 4%). HLA alleles and haplotypes’ frequency analysis found variants previously described in SLE patients from Mexico City. Moreover, a conserved extended haplotype that confers risk to develop SLE was found, the HLA-A∗29:02∼C∗16:01∼B∗44:03∼DRB1∗07:01∼DQB1∗02:02, pC = 0.02, OR = 1.41. Consistent with the admixture estimations, the origin of all risk alleles and haplotypes found in this study are European, while the protection alleles are Mexican Native American. The analysis of genetic distances supported that the SLE patient group is closer to the Southwestern European parental populace and farthest from Mexican Native Americans than healthy individuals. Heterogeneity of genetic admixture determines SLE susceptibility and protection in Mexicans. HLA sequencing is helpful to determine susceptibility alleles and haplotypes restricted to some populations.

There has been limited study of Native American whole genome diversity to date, which impairs effective implementation of personalized medicine and a detailed description of its demographic history. Here we report high coverage whole genome sequencing of 76 unrelated individuals, from 27 indigenous groups across Mexico, with more than 97% average Native American ancestry. On average, each individual has 3.26 million Single Nucleotide Variants and short indels, that together comprise a catalog of 9,737,152 variants, 44,118 of which are novel. We report 497 common Single Nucleotide Variants (with allele frequency > 5%) mapped to drug responses and 316,577 in enhancer or promoter elements; interestingly we found some of these enhancer variants in PPARG, a nuclear receptor involved in highly prevalent health problems in Mexican population, such as obesity, diabetes, and insulin resistance. By detecting signals of positive selection we report 24 enriched key pathways under selection, most of them related to immune mechanisms. No missense variants in ACE2, the receptor responsible for the entry of the SARS CoV-2 virus, were found in any individual. Population genomics and phylogenetic analyses demonstrated stratification in a Northern-Central-Southern axis, with major substructure in the Central region. The Seri, a northern group with the most genetic divergence in our study, showed a distinctive genomic context with the most novel variants, and the most population specific genotypes. Genome-wide analysis showed that the average haplotype blocks are longer in Native Mexicans than in other world populations. With this dataset we describe previously undetected population level variation in Native Mexicans, helping to reduce the gap in genomic data representation of such groups.

Studies have suggested a potential role of somatic mitochondrial mutations in cancer development. To analyze the landscape of somatic mitochondrial mutation in breast cancer and to determine whether mitochondrial DNA (mtDNA) mutational burden is correlated with overall survival (OS), we sequenced whole mtDNA from 92 matched-paired primary breast tumors and peripheral blood. A total of 324 germline variants and 173 somatic mutations were found in the tumors. The most common germline allele was 663G (12S), showing lower heteroplasmy levels in peripheral blood lymphocytes than in their matched tumors, even reaching homoplasmic status in several cases. The heteroplasmy load was higher in tumors than in their paired normal tissues. Somatic mtDNA mutations were found in 73.9% of breast tumors; 59% of these mutations were located in the coding region (66.7% non-synonymous and 33.3% synonymous). Although the CO1 gene presented the highest number of mutations, tRNA genes (T,C, and W), rRNA 12S, and CO1 and ATP6 exhibited the highest mutation rates. No specific mtDNA mutational profile was associated with molecular subtypes of breast cancer, and we found no correlation between mtDNA mutational burden and OS. Future investigations will provide insight into the molecular mechanisms through which mtDNA mutations and heteroplasmy shifting contribute to breast cancer development.

Neuromyelitis Optica (NMO) is an autoimmune disease with a higher prevalence in non-European populations. Because the Mexican population resulted from the admixture between mainly Native American and European populations, we used genome-wide microarray, HLA high-resolution typing and AQP4 gene sequencing data to analyze genetic ancestry and to seek genetic variants conferring NMO susceptibility in admixed Mexican patients. A total of 164 Mexican NMO patients and 1,208 controls were included. On average, NMO patients had a higher proportion of Native American ancestry than controls (68.1% vs 58.6%; p = 5 × 10–6). GWAS identified a HLA region associated with NMO, led by rs9272219 (OR = 2.48, P = 8 × 10–10). Class II HLA alleles HLA-DQB1*03:01, -DRB1*08:02, -DRB1*16:02, -DRB1*14:06 and -DQB1*04:02 showed the most significant associations with NMO risk. Local ancestry estimates suggest that all the NMO-associated alleles within the HLA region are of Native American origin. No novel or missense variants in the AQP4 gene were found in Mexican patients with NMO or multiple sclerosis. To our knowledge, this is the first study supporting the notion that Native American ancestry significantly contributes to NMO susceptibility in an admixed population, and is consistent with differences in NMO epidemiology in Mexico and Latin America. Fil: Romero Hidalgo, Sandra. Instituto Nacional de Medicina Genómica; México Fil: Flores Rivera, José. Instituto Nacional de Neurología y Neurocirugía; México Fil: Rivas Alonso, Verónica. Instituto Nacional de Neurología y Neurocirugía; México Fil: Barquera, Rodrigo. Max Planck Institute For The Science Of Human History; Alemania. Instituto Nacional de Antropología e Historia; México Fil: Villarreal Molina, María Teresa. Instituto Nacional de Medicina Genómica; México Fil: Antuna Puente, Bárbara. Instituto Nacional de Medicina Genómica; México Fil: Macias Kauffer, Luis Rodrigo. Universidad Nacional Autónoma de México; México Fil: Villalobos Comparán, Marisela. Instituto Nacional de Medicina Genómica; México Fil: Ortiz Maldonado, Jair. Instituto Nacional de Neurología y Neurocirugía; México Fil: Yu, Neng. American Red Cross; Estados Unidos Fil: Lebedeva, Tatiana V.. American Red Cross; Estados Unidos Fil: Alosco, Sharon M.. American Red Cross; Estados Unidos Fil: García Rodríguez, Juan Daniel. Instituto Nacional de Medicina Genómica; México Fil: González Torres, Carolina. Instituto Nacional de Medicina Genómica; México Fil: Rosas Madrigal, Sandra. Instituto Nacional de Medicina Genómica; México Fil: Ordoñez, Graciela. Neuroimmunología, Instituto Nacional de Neurología y Neurocirugía; México Fil: Guerrero Camacho, Jorge Luis. Instituto Nacional de Neurología y Neurocirugía; México Fil: Treviño Frenk, Irene. American British Cowdray Medical Center; México. Instituto Nacional de la Nutrición Salvador Zubiran; México Fil: Escamilla Tilch, Monica. Instituto Nacional de la Nutrición Salvador Zubiran; México Fil: García Lechuga, Maricela. Instituto Nacional de la Nutrición Salvador Zubiran; México Fil: Tovar Méndez, Víctor Hugo. Instituto Nacional de la Nutrición Salvador Zubiran; México Fil: Pacheco Ubaldo, Hanna. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Acuña Alonzo, Victor. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Bortolini, María Cátira. Universidade Federal do Rio Grande do Sul; Brasil Fil: Gallo, Carla. Universidad Peruana Cayetano Heredia; Perú Fil: Bedoya Berrío, Gabriel. Universidad de Antioquia; Colombia Fil: Rothhammer, Francisco. Universidad de Tarapacá; Chile Fil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina Fil: Ruiz Linares, Andrés. Colegio Universitario de Londres; Reino Unido Fil: Canizales Quinteros, Samuel. Universidad Nacional Autónoma de México; México Fil: Yunis, Edmond. Dana Farber Cancer Institute; Estados Unidos Fil: Granados, Julio. Instituto Nacional de la Nutrición Salvador Zubiran; México Fil: Corona, Teresa. Instituto Nacional de Neurología y Neurocirugía; México

Facilitation by tussocks is common in high-altitude tropical environments. It is thought that facilitation results from stress amelioration, but it is unclear which of the many stressors acting in these environments is ameliorated. We aimed at determining the relative importance of different stressors as drivers of facilitation by the tussock Festuca tolucensis in Mexico. We manipulated five stressors in the field: minimum temperatures by using electric radiators that kept plants warm; maximum temperatures by means of reflective sand that precluded temperature build-up during the day; UV radiation by using screens opaque to UV; poor soil properties by comparing soils from beneath tussocks and from bare ground; and low water availability by adding vermiculite to the soil. The performance (survival and growth) of Mexerion sarmentosum (a plant usually associated with Festuca) in these treatments was compared to that recorded under tussocks and in bare ground. Amelioration of extreme temperatures had the largest positive effects on Mexerion survival. UV radiation and increased soil humidity did not affect survival, although humidity increased growth rates. Nevertheless, tussocks reduced the growth of Mexerion, which is consistent with observations of competition between plants and soil microorganisms favoured by tussocks. Our results highlight the importance of the extreme daily fluctuations in temperature that characterise tropical mountains as fundamental drivers of their dynamics.

Transcription factors are responsible for both tissue-specific gene expression and the regulation of gene activity in response to specific stimuli. Analysis of whole genome gene expression data and studies on the specificities of transcription factor binding to genomic DNA sequences are common ways of inferring transcriptional regulatory networks. The interplay between different levels of regulation occurs when a series of transcription factors triggers a gene cascade that controls the whole regulatory program for cells under associated phenotypes. In this chapter, we discuss the role that transcription factors and other related molecules have on the intricate series of processes leading to genome-wide transcriptional regulatory programs. Experimental, computational, and modeling approaches to this problem are presented, and some general methods and algorithms are described in greater detail. Finally, we present an overview section on how to incorporate epigenomic and other regulatory processes in the context of networks of transcription factors.

Analysis of gene regulatory networks allows the identification of master transcriptional factors that control specific groups of genes. In this work, we inferred a gene regulatory network from a large dataset of breast cancer samples to identify the master transcriptional factors that control the genes within signal transduction pathways. The focus in a particular subset of relevant genes constitutes an extension of the original Master Regulator Inference Algorithm (MARINa) analysis. This modified version of MARINa utilizes a restricted molecular signature containing genes from the 25 human pathways in KEGG's signal transduction category. Our breast cancer RNAseq expression dataset consists of 881 samples comprising tumors and normal mammary gland tissue. The top 10 master transcriptional factors found to regulate signal transduction pathways in breast cancer we identified are: TSHZ2, HOXA2, MEIS2, HOXA3, HAND2, HOXA5, TBX18, PEG3, GLI2, and CLOCK. The functional enrichment of the regulons of these master transcriptional factors showed an important proportion of processes related to morphogenesis. Our results suggest that, as part of the aberrant regulation of signaling pathways in breast cancer, pathways similar to the regulation of cell differentiation, cardiovascular system development, and vasculature development may be dysregulated and co-opted in favor of tumor development through the action of these transcription factors.

Facilitation by tussocks is common in high-altitude tropical environments. It is thought that facilitation results from stress amelioration, but it is unclear which of the many stressors acting in these environments is ameliorated. We aimed at determining the relative importance of different stressors as drivers of facilitation by the tussock Festuca tolucensis in Mexico. We employed eight experimental treatments to manipulate five stressors in the field: minimum temperatures by using electric radiators that kept plants warm; maximum temperatures by means of reflective sand that precluded temperature build-up during the day; UV radiation by using screens opaque to UV; poor soil properties by comparing soils from beneath tussocks and from bare ground; and low water availability by adding vermiculite to the soil. The performance (survival and growth) of Mexerion sarmentosum (a plant usually associated with Festuca) in these treatments was compared to that recorded under tussocks and in bare ground. Amelioration of extreme temperatures had the largest positive effects on Mexerion survival. UV radiation and increased soil humidity did not affect survival, although humidity increased growth rates. Nevertheless, tussocks reduced the growth of Mexerion, which is consistent with observations of competition between plants and soil microorganisms favoured by tussocks. Our results highlight the importance of the extreme daily fluctuations in temperature that characterise tropical mountains as fundamental drivers of their dynamics.

Signal transduction pathways allow cells to respond to environmental cues and can induce intracellular changes. In some contexts, like embryonic development, signal transduction plays crucial roles in cell fate determination and differentiation, while in developed organisms some of this processes contribute in the maintenance of the structural integrity of tissues.Tumor cells are recognized as having deregulated signaling which leads to a series of abnormal behaviors known as the hallmarks of cancer. Although gene regulation is often viewed as the last step in signal transduction, transcriptional regulation of the components of a pathway may impact in the long term deregulation observed in tumors. The study of gene regulatory networks centered around genes of the signal transduction pathways allows the identification of transcriptional regulators with the greatest influence over the signal transduction gene signature, also denominated Master Regulators.In this work we identify, the master regulators that regulate the expression of genes of 25 relevant pathways grouped in KEGG within the category of signal transduction in a breast cancer dataset. For this purpose we implemented a modified MARINa algorithm that identifies, from a network of regulons, those that possess more differentially expressed genes related to the process to be studied. We identified CLOCK, TSHZ2, HOXA2, MEIS2, HOXA3, HAND2, HOXA5, TBX18, PEG3 and GLI2 as the top 10 master regulators of signaling pathways in breast cancer. Nine of them are recognized for taking part in embryonic development associated processes.Individual enrichment GO biological function for each TMR regulons showed to be significantly enriched in embryonic development related processes. Hedgehog signaling pathway was shown as enriched and also highly deregulated. The genes of the HOXA family are shared among most of the TMRs. Overall, this suggests the importance of the aberrant reprogramming of mechanisms present during embryonic development, being coopted in favor of tumor development.

Graphical abstractDisplay Omitted Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology.

Gene expression in eukaryotic cells is an extremely complex and interesting phenomenon whose dynamics are controlled by a large number of subtle physicochemical processes commonly described by means of gene regulatory networks. Such networks consist in a series of coupled chemical reactions, conformational changes, and other biomolecular processes involving the interaction of the DNA molecule itself with a number of proteins usually called transcription factors as well as enzymes and other components. The kinetics behind the functioning of such gene regulatory networks are largely unknown, though its description in terms of non-equilibrium thermodynamics has been discussed recently. In this work we will derive general kinetic equations for a gene regulatory network from a non-equilibrium thermodynamical description and discuss its use in understanding the free energy constrains imposed in the network structure. We also will discuss explicit expressions for the kinetics of a simple model of gene regulation and show that the kinetic role of mRNA decay during the RNA synthesis stage (or transcription) is somehow limited due to the comparatively low values of decay rates. At the level discussed here, this implies a decoupling of the kinetics of mRNA synthesis and degradation a fact that may become quite useful when modeling gene regulatory networks from experimental data on whole genome gene expression.

Gene regulatory networks present a wide variety of dynamical responses to intrinsic and extrinsic perturbations. An outstanding case of such coordinated responses is that of transcriptional amplification cascades, in which activation of a few key-responsive transcription factors (termed master regulators) leads to a large series of transcriptional activation events. Recent studies have pointed to the protein called myocyte enhancing factor 2C (MEF2C) as being one of such master regulators involved in the pathogenesis of primary breast cancer. A systems biology analysis of the transcriptional regulation activity of MEF2C and its target genes, has revealed that this molecule induces collective responses leading to system-level gene expression deregulation and carcinogenesis. We found extensive evidence for this. Being this the case, one may wonder what set of physicochemical, structural and thermodynamic constrains need to be satisfied if a protein is to become a transcription factor, and moreover a master regulator? Some hints will be discussed.