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1.
PLoS One ; 16(4): e0249773, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33831079

RESUMEN

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.


Asunto(s)
/genética , Genoma Humano , Filogenia , Polimorfismo de Nucleótido Simple , Secuenciación Completa del Genoma , /epidemiología , /genética , Bases de Datos de Ácidos Nucleicos , Femenino , Humanos , Masculino , México/epidemiología , México/etnología
2.
Nat Commun ; 12(1): 2076, 2021 04 06.
Artículo en Inglés | MEDLINE | ID: mdl-33824317

RESUMEN

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer's disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease.


Asunto(s)
Apolipoproteínas E/genética , Genoma Humano , Enfermedades Neurodegenerativas/genética , Filogenia , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/patología , Encéfalo/patología , Cromosomas Humanos Par 19/genética , Secuencia Conservada/genética , ADN Intergénico/genética , Ontología de Genes , Humanos , Intrones/genética , Desequilibrio de Ligamiento/genética , Anotación de Secuencia Molecular , Fenotipo , Polimorfismo de Nucleótido Simple/genética , ARN Largo no Codificante/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Análisis de Regresión
3.
Nat Commun ; 12(1): 2337, 2021 04 20.
Artículo en Inglés | MEDLINE | ID: mdl-33879782

RESUMEN

While recent advancements in computation and modelling have improved the analysis of complex traits, our understanding of the genetic basis of the time at symptom onset remains limited. Here, we develop a Bayesian approach (BayesW) that provides probabilistic inference of the genetic architecture of age-at-onset phenotypes in a sampling scheme that facilitates biobank-scale time-to-event analyses. We show in extensive simulation work the benefits BayesW provides in terms of number of discoveries, model performance and genomic prediction. In the UK Biobank, we find many thousands of common genomic regions underlying the age-at-onset of high blood pressure (HBP), cardiac disease (CAD), and type-2 diabetes (T2D), and for the genetic basis of onset reflecting the underlying genetic liability to disease. Age-at-menopause and age-at-menarche are also highly polygenic, but with higher variance contributed by low frequency variants. Genomic prediction into the Estonian Biobank data shows that BayesW gives higher prediction accuracy than other approaches.


Asunto(s)
Edad de Inicio , Genoma Humano , Modelos Genéticos , Herencia Multifactorial , Factores de Edad , Algoritmos , Teorema de Bayes , Enfermedades Cardiovasculares/genética , Simulación por Computador , Bases de Datos Genéticas , Diabetes Mellitus Tipo 2/genética , Estonia , Femenino , Estudios de Asociación Genética , Estudio de Asociación del Genoma Completo , Genómica , Humanos , Hipertensión/genética , Menarquia/genética , Menopausia/genética , Fenotipo , Polimorfismo de Nucleótido Simple , Reino Unido
4.
Nat Commun ; 12(1): 2345, 2021 04 20.
Artículo en Inglés | MEDLINE | ID: mdl-33879792

RESUMEN

Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients' age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.


Asunto(s)
Envejecimiento/genética , Neoplasias/etiología , Neoplasias/genética , Factores de Edad , Envejecimiento/metabolismo , Variaciones en el Número de Copia de ADN , Metilación de ADN , Bases de Datos Genéticas , Epigénesis Genética , Femenino , Duplicación de Gen , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Genoma Humano , Inestabilidad Genómica , Genómica , Humanos , Pérdida de Heterocigocidad , Masculino , Mutación , Neoplasias/metabolismo , Oncogenes , Factores de Riesgo , Transducción de Señal/genética , Secuenciación Completa del Genoma
5.
Int J Mol Sci ; 22(6)2021 Mar 11.
Artículo en Inglés | MEDLINE | ID: mdl-33799581

RESUMEN

A palindrome in DNA consists of two closely spaced or adjacent inverted repeats. Certain palindromes have important biological functions as parts of various cis-acting elements and protein binding sites. However, many palindromes are known as fragile sites in the genome, sites prone to chromosome breakage which can lead to various genetic rearrangements or even cell death. The ability of certain palindromes to initiate genetic recombination lies in their ability to form secondary structures in DNA which can cause replication stalling and double-strand breaks. Given their recombinogenic nature, it is not surprising that palindromes in the human genome are involved in genetic rearrangements in cancer cells as well as other known recurrent translocations and deletions associated with certain syndromes in humans. Here, we bring an overview of current understanding and knowledge on molecular mechanisms of palindrome recombinogenicity and discuss possible implications of DNA palindromes in carcinogenesis. Furthermore, we overview the data on known palindromic sequences in the human genome and efforts to estimate their number and distribution, as well as underlying mechanisms of genetic rearrangements specific palindromic sequences cause.


Asunto(s)
Carcinogénesis/genética , ADN de Neoplasias/genética , Secuencias Invertidas Repetidas , Neoplasias/genética , Recombinación Genética , Translocación Genética , Secuencia de Bases , Carcinogénesis/metabolismo , Carcinogénesis/patología , Biología Computacional/métodos , Replicación del ADN , ADN de Neoplasias/química , ADN de Neoplasias/metabolismo , Escherichia coli/genética , Escherichia coli/metabolismo , Genoma Humano , Inestabilidad Genómica , Humanos , Neoplasias/metabolismo , Neoplasias/patología , Conformación de Ácido Nucleico , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo
6.
Int J Mol Sci ; 22(6)2021 Mar 17.
Artículo en Inglés | MEDLINE | ID: mdl-33802957

RESUMEN

Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancers with poor prognosis. The etiology of triple-negative breast cancer (TNBC) is involved in various biological signal cascades and multifactorial aberrations of genetic, epigenetic and microenvironment. New therapeutic for TNBC is urgently needed because surgery and chemotherapy are the only available modalities nowadays. A better understanding of the molecular mechanisms would be a great challenge because they are triggered by cascade signaling pathways, genetic and epigenetic regulations, and drug-target interactions. This would allow the design of multi-molecule drugs for the TNBC and non-TNBC. In this study, in terms of systems biology approaches, we proposed a systematic procedure for systems medicine design toward TNBC and non-TNBC. For systems biology approaches, we constructed a candidate genome-wide genetic and epigenetic network (GWGEN) by big databases mining and identified real GWGENs of TNBC and non-TNBC assisting with corresponding microarray data by system identification and model order selection methods. After that, we applied the principal network projection (PNP) approach to obtain the core signaling pathways denoted by KEGG pathway of TNBC and non-TNBC. Comparing core signaling pathways of TNBC and non-TNBC, essential carcinogenic biomarkers resulting in multiple cellular dysfunctions including cell proliferation, autophagy, immune response, apoptosis, metastasis, angiogenesis, epithelial-mesenchymal transition (EMT), and cell differentiation could be found. In order to propose potential candidate drugs for the selected biomarkers, we designed filters considering toxicity and regulation ability. With the proposed systematic procedure, we not only shed a light on the differences between carcinogenetic molecular mechanisms of TNBC and non-TNBC but also efficiently proposed candidate multi-molecule drugs including resveratrol, sirolimus, and prednisolone for TNBC and resveratrol, sirolimus, carbamazepine, and verapamil for non-TNBC.


Asunto(s)
Carcinogénesis/patología , Análisis de Sistemas , Neoplasias de la Mama Triple Negativas/terapia , Epigénesis Genética , Regulación Neoplásica de la Expresión Génica , Genoma Humano , Humanos , Transducción de Señal/genética , Neoplasias de la Mama Triple Negativas/genética
7.
Am J Hum Genet ; 108(4): 535-548, 2021 04 01.
Artículo en Inglés | MEDLINE | ID: mdl-33798442

RESUMEN

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.


Asunto(s)
Variación Genética/genética , Genética Médica , Genómica , Aprendizaje Automático , Errores Innatos del Metabolismo/genética , Farmacogenética , Medicina de Precisión , Genoma Humano/genética , Humanos , Recién Nacido
8.
Am J Hum Genet ; 108(4): 583-596, 2021 04 01.
Artículo en Inglés | MEDLINE | ID: mdl-33798444

RESUMEN

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.


Asunto(s)
Enfermedades Cardiovasculares/genética , Variación Estructural del Genoma/genética , Alelos , Colesterol/sangre , Variaciones en el Número de Copia de ADN/genética , Femenino , Finlandia , Genoma Humano/genética , Genotipo , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Masculino , Proteínas Mitocondriales/genética , Regiones Promotoras Genéticas/genética , Piruvato Deshidrogenasa (Lipoamida)-Fosfatasa/genética , Ácido Pirúvico/metabolismo , Albúmina Sérica Humana/genética
9.
Science ; 372(6540): 371-378, 2021 04 23.
Artículo en Inglés | MEDLINE | ID: mdl-33888635

RESUMEN

The temporal order of DNA replication [replication timing (RT)] is correlated with chromatin modifications and three-dimensional genome architecture; however, causal links have not been established, largely because of an inability to manipulate the global RT program. We show that loss of RIF1 causes near-complete elimination of the RT program by increasing heterogeneity between individual cells. RT changes are coupled with widespread alterations in chromatin modifications and genome compartmentalization. Conditional depletion of RIF1 causes replication-dependent disruption of histone modifications and alterations in genome architecture. These effects were magnified with successive cycles of altered RT. These results support models in which the timing of chromatin replication and thus assembly plays a key role in maintaining the global epigenetic state.


Asunto(s)
Momento de Replicación del ADN , Epigénesis Genética , Epigenoma , Proteínas de Unión a Telómeros/metabolismo , Línea Celular , Cromatina/metabolismo , Ensamble y Desensamble de Cromatina , Replicación del ADN , Expresión Génica , Técnicas de Inactivación de Genes , Genoma Humano , Heterocromatina/metabolismo , Código de Histonas , Histonas/metabolismo , Humanos , Proteínas de Unión a Telómeros/genética
10.
Nat Commun ; 12(1): 2187, 2021 04 12.
Artículo en Inglés | MEDLINE | ID: mdl-33846346

RESUMEN

The RNA-sensing pathway contributes to type I interferon (IFN) production induced by DNA damaging agents. However, the potential involvement of RNA sensors in DNA repair is unknown. Here, we found that retinoic acid-inducible gene I (RIG-I), a key cytosolic RNA sensor that recognizes RNA virus and initiates the MAVS-IRF3-type I IFN signaling cascade, is recruited to double-stranded breaks (DSBs) and suppresses non-homologous end joining (NHEJ). Mechanistically, RIG-I interacts with XRCC4, and the RIG-I/XRCC4 interaction impedes the formation of XRCC4/LIG4/XLF complex at DSBs. High expression of RIG-I compromises DNA repair and sensitizes cancer cells to irradiation treatment. In contrast, depletion of RIG-I renders cells resistant to irradiation in vitro and in vivo. In addition, this mechanism suggests a protective role of RIG-I in hindering retrovirus integration into the host genome by suppressing the NHEJ pathway. Reciprocally, XRCC4, while suppressed for its DNA repair function, has a critical role in RIG-I immune signaling through RIG-I interaction. XRCC4 promotes RIG-I signaling by enhancing oligomerization and ubiquitination of RIG-I, thereby suppressing RNA virus replication in host cells. In vivo, silencing XRCC4 in mouse lung promotes influenza virus replication in mice and these mice display faster body weight loss, poorer survival, and a greater degree of lung injury caused by influenza virus infection. This reciprocal regulation of RIG-I and XRCC4 reveals a new function of RIG-I in suppressing DNA repair and virus integration into the host genome, and meanwhile endues XRCC4 with a crucial role in potentiating innate immune response, thereby helping host to prevail in the battle against virus.


Asunto(s)
Proteína 58 DEAD Box/metabolismo , Reparación del ADN , Proteínas de Unión al ADN/metabolismo , Receptores Inmunológicos/metabolismo , Transducción de Señal/inmunología , Células A549 , Animales , Roturas del ADN de Doble Cadena/efectos de la radiación , Reparación del ADN por Unión de Extremidades/efectos de la radiación , Reparación del ADN/efectos de la radiación , Relación Dosis-Respuesta en la Radiación , Genoma Humano , Células HEK293 , Humanos , Ratones , Radiación Ionizante , Retroviridae/metabolismo , Replicación Viral/efectos de la radiación
11.
Nat Commun ; 12(1): 2217, 2021 04 13.
Artículo en Inglés | MEDLINE | ID: mdl-33850120

RESUMEN

Although major advances in genomics have initiated an exciting new era of research, a lack of information regarding cis-regulatory elements has limited the genetic improvement or manipulation of pigs as a meat source and biomedical model. Here, we systematically characterize cis-regulatory elements and their functions in 12 diverse tissues from four pig breeds by adopting similar strategies as the ENCODE and Roadmap Epigenomics projects, which include RNA-seq, ATAC-seq, and ChIP-seq. In total, we generate 199 datasets and identify more than 220,000 cis-regulatory elements in the pig genome. Surprisingly, we find higher conservation of cis-regulatory elements between human and pig genomes than those between human and mouse genomes. Furthermore, the differences of topologically associating domains between the pig and human genomes are associated with morphological evolution of the head and face. Beyond generating a major new benchmark resource for pig epigenetics, our study provides basic comparative epigenetic data relevant to using pigs as models in human biomedical research.


Asunto(s)
Epigenómica , Secuencias Reguladoras de Ácidos Nucleicos , Porcinos/genética , Animales , Secuenciación de Inmunoprecipitación de Cromatina , Epigénesis Genética , Expresión Génica , Genoma , Genoma Humano , Células HEK293 , Humanos , Ratones , RNA-Seq , Receptores Acoplados a Proteínas G/metabolismo , Transcriptoma
12.
Science ; 372(6537): 91-94, 2021 04 02.
Artículo en Inglés | MEDLINE | ID: mdl-33795458

RESUMEN

Neurons are the longest-lived cells in our bodies and lack DNA replication, which makes them reliant on a limited repertoire of DNA repair mechanisms to maintain genome fidelity. These repair mechanisms decline with age, but we have limited knowledge of how genome instability emerges and what strategies neurons and other long-lived cells may have evolved to protect their genomes over the human life span. A targeted sequencing approach in human embryonic stem cell-induced neurons shows that, in neurons, DNA repair is enriched at well-defined hotspots that protect essential genes. These hotspots are enriched with histone H2A isoforms and RNA binding proteins and are associated with evolutionarily conserved elements of the human genome. These findings provide a basis for understanding genome integrity as it relates to aging and disease in the nervous system.


Asunto(s)
Reparación del ADN , Genoma Humano , Inestabilidad Genómica , Neuronas/metabolismo , Envejecimiento/genética , Daño del ADN , ADN Intergénico , Desoxiuridina/análogos & derivados , Desoxiuridina/metabolismo , Células Madre Embrionarias , Histonas/metabolismo , Humanos , Mitosis , Mutación , Enfermedades del Sistema Nervioso/genética , Neuronas/citología , Regiones Promotoras Genéticas , Proteínas de Unión al ARN/metabolismo , Análisis de Secuencia de ADN , Transcripción Genética
13.
Science ; 372(6538)2021 04 09.
Artículo en Inglés | MEDLINE | ID: mdl-33833093

RESUMEN

DNA methylation is essential to mammalian development, and dysregulation can cause serious pathological conditions. Key enzymes responsible for deposition and removal of DNA methylation are known, but how they cooperate to regulate the methylation landscape remains a central question. Using a knockin DNA methylation reporter, we performed a genome-wide CRISPR-Cas9 screen in human embryonic stem cells to discover DNA methylation regulators. The top screen hit was an uncharacterized gene, QSER1, which proved to be a key guardian of bivalent promoters and poised enhancers of developmental genes, especially those residing in DNA methylation valleys (or canyons). We further demonstrate genetic and biochemical interactions of QSER1 and TET1, supporting their cooperation to safeguard transcriptional and developmental programs from DNMT3-mediated de novo methylation.


Asunto(s)
Metilación de ADN , ADN/metabolismo , Células Madre Embrionarias Humanas/metabolismo , Sistemas CRISPR-Cas , ADN (Citosina-5-)-Metiltransferasas/metabolismo , Elementos de Facilitación Genéticos , Regulación del Desarrollo de la Expresión Génica , Técnicas de Sustitución del Gen , Técnicas de Inactivación de Genes , Genoma Humano , Humanos , Oxigenasas de Función Mixta/genética , Oxigenasas de Función Mixta/metabolismo , Regiones Promotoras Genéticas , Unión Proteica , Proteínas Proto-Oncogénicas/genética , Proteínas Proto-Oncogénicas/metabolismo , Transcripción Genética
15.
Int J Mol Sci ; 22(4)2021 Feb 19.
Artículo en Inglés | MEDLINE | ID: mdl-33669810

RESUMEN

Repetitive DNA in humans is still widely considered to be meaningless, and variations within this part of the genome are generally considered to be harmless to the carrier. In contrast, for euchromatic variation, one becomes more careful in classifying inter-individual differences as meaningless and rather tends to see them as possible influencers of the so-called 'genetic background', being able to at least potentially influence disease susceptibilities. Here, the known 'bad boys' among repetitive DNAs are reviewed. Variable numbers of tandem repeats (VNTRs = micro- and minisatellites), small-scale repetitive elements (SSREs) and even chromosomal heteromorphisms (CHs) may therefore have direct or indirect influences on human diseases and susceptibilities. Summarizing this specific aspect here for the first time should contribute to stimulating more research on human repetitive DNA. It should also become clear that these kinds of studies must be done at all available levels of resolution, i.e., from the base pair to chromosomal level and, importantly, the epigenetic level, as well.


Asunto(s)
Secuencias Repetitivas de Ácidos Nucleicos/genética , Cromosomas Humanos/genética , ADN Satélite/genética , Genoma Humano , Humanos , Repeticiones de Microsatélite/genética , Repeticiones de Minisatélite/genética
16.
Methods Mol Biol ; 2212: 69-92, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733351

RESUMEN

Undiscovered gene-to-gene interaction (epistasis) is a possible explanation for the "missing heritability" of complex traits and diseases. On a genome-wide scale, screening for epistatic effects among all possible pairs of genetic markers faces two main complications. Firstly, the classical statistical methods for modeling epistasis are computationally very expensive, which makes them impractical on such large scale. Secondly, straightforward corrections for multiple testing using the classical methods tend to be too coarse and inefficient at discovering the epistatic effects in such a large scale application. In this chapter, we describe both the underlying framework and practical examples of two-stage statistical testing methods that alleviate both of the aforementioned complications.


Asunto(s)
Epistasis Genética , Pruebas Genéticas/métodos , Modelos Genéticos , Polimorfismo de Nucleótido Simple , Carácter Cuantitativo Heredable , Programas Informáticos , Estudios de Asociación Genética , Genoma Humano , Genotipo , Humanos , Patrón de Herencia , Fenotipo , Sitios de Carácter Cuantitativo
17.
Methods Mol Biol ; 2212: 93-103, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733352

RESUMEN

Transcriptome-wide association studies (TWASs) integrate expression quantitative trait loci (eQTLs) studies with genome-wide association studies (GWASs) to prioritize candidate target genes for complex traits. TWASs have become increasingly popular. They have been used to analyze many complex traits with expression profiles from different tissues, successfully enhancing the discovery of genetic risk loci for complex traits. Though conceptually straightforward, some steps are required to perform the TWAS properly. Here we provide a step-by-step guide to integrate eQTL data with both GWAS individual-level data and GWAS summary statistics from complex traits.


Asunto(s)
Epistasis Genética , Pruebas Genéticas/métodos , Modelos Genéticos , Herencia Multifactorial , Programas Informáticos , Transcriptoma , Genoma Humano , Estudio de Asociación del Genoma Completo , Genotipo , Humanos , Fenotipo , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Incertidumbre
18.
Methods Mol Biol ; 2212: 169-179, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733356

RESUMEN

In biology, the term "epistasis" indicates the effect of the interaction of a gene with another gene. A gene can interact with an independently sorted gene, located far away on the chromosome or on an entirely different chromosome, and this interaction can have a strong effect on the function of the two genes. These changes then can alter the consequences of the biological processes, influencing the organism's phenotype. Machine learning is an area of computer science that develops statistical methods able to recognize patterns from data. A typical machine learning algorithm consists of a training phase, where the model learns to recognize specific trends in the data, and a test phase, where the trained model applies its learned intelligence to recognize trends in external data. Scientists have applied machine learning to epistasis problems multiple times, especially to identify gene-gene interactions from genome-wide association study (GWAS) data. In this brief survey, we report and describe the main scientific articles published in data mining and epistasis. Our article confirms the effectiveness of machine learning in this genetics subfield.


Asunto(s)
Biología Computacional/métodos , Minería de Datos/métodos , Epistasis Genética , Aprendizaje Automático , Carácter Cuantitativo Heredable , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/patología , Enfermedad de Crohn/genética , Enfermedad de Crohn/metabolismo , Enfermedad de Crohn/patología , Genoma Humano , Estudio de Asociación del Genoma Completo , Humanos , Patrón de Herencia , Degeneración Macular/genética , Degeneración Macular/metabolismo , Degeneración Macular/patología , Neoplasias/genética , Neoplasias/metabolismo , Neoplasias/patología , Fenotipo , Plantas/genética , Polimorfismo de Nucleótido Simple
19.
Methods Mol Biol ; 2212: 291-305, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733363

RESUMEN

To develop medical treatments and prevention, the association between disease and genetic variants needs to be identified. The main goal of genome-wide association study (GWAS) is to discover the underlying reason for vulnerability to disease and utilize this knowledge for the development of prevention and treatment against these diseases. Given the methods available to address the scientific problems involved in the search for epistasis, there is not any standard for detecting epistasis, and this remains a problem due to limited statistical power. The GenEpi package is a Python package that uses a two-level workflow machine learning model to detect within-gene and cross-gene epistasis. This protocol chapter shows the usage of GenEpi with example data. The package uses a three-step procedure to reduce dimensionality, select the within-gene epistasis, and select the cross-gene epistasis. The package also provides a medium to build prediction models with the combination of genetic features and environmental influences.


Asunto(s)
Biología Computacional/métodos , Epistasis Genética , Estudios de Asociación Genética , Aprendizaje Automático , Programas Informáticos , Bases de Datos Genéticas , Genoma Humano , Estudio de Asociación del Genoma Completo , Genotipo , Humanos , Fenotipo , Polimorfismo de Nucleótido Simple
20.
Methods Mol Biol ; 2212: 347-376, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733367

RESUMEN

As practitioners, we aim to provide a consolidated introduction of tidy data science along with routine packages for relational data representation and interpretation, with the focus on analytics related to human genetic interactions. We describe three showcases (also made available at https://23verse.github.io/gini ), all done so via the R one-liner, in this chapter defined as a sequential pipeline of elementary functions chained together achieving a complex task. We guide the readers through step-by-step instructions on (case 1) performing network module analysis of genetic interactions, followed by visualization and interpretation; (case 2) implementing a practical strategy of how to identify and interpret tissue-specific genetic interactions; and (case 3) carrying out interaction-based tissue clustering and differential interaction analysis. All showcases demonstrate simplistic beauty and efficient nature of this analytics. We anticipate that mastering a dozen of one-liners to efficiently interpret genetic interactions is very timely now; opportunities for computational translational research are arising for data scientists to harness therapeutic potential of human genetic interaction data that are ever-increasingly available.


Asunto(s)
Algoritmos , Ciencia de los Datos/estadística & datos numéricos , Epistasis Genética , Redes Reguladoras de Genes , Programas Informáticos , Animales , Proteína BRCA1/genética , Proteína BRCA1/metabolismo , Proteína BRCA2/genética , Proteína BRCA2/metabolismo , Interpretación Estadística de Datos , Genoma Humano , Genotipo , Humanos , Ratones , Especificidad de Órganos , Fenotipo , Poli(ADP-Ribosa) Polimerasa-1/genética , Poli(ADP-Ribosa) Polimerasa-1/metabolismo , Mapeo de Interacción de Proteínas
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