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1.
Cell ; 164(4): 805-17, 2016 02 11.
Artículo en Inglés | MEDLINE | ID: mdl-26871637

RESUMEN

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").


Asunto(s)
Empalme Alternativo , Isoformas de Proteínas/metabolismo , Proteoma/metabolismo , Animales , Clonación Molecular , Evolución Molecular , Humanos , Modelos Moleculares , Sistemas de Lectura Abierta , Dominios y Motivos de Interacción de Proteínas , Mapas de Interacción de Proteínas , Proteoma/análisis
2.
Cell ; 159(5): 1212-1226, 2014 11 20.
Artículo en Inglés | MEDLINE | ID: mdl-25416956

RESUMEN

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.


Asunto(s)
Mapas de Interacción de Proteínas , Proteoma/metabolismo , Animales , Bases de Datos de Proteínas , Estudio de Asociación del Genoma Completo , Humanos , Ratones , Neoplasias/metabolismo
4.
Nat Methods ; 14(8): 819-825, 2017 08.
Artículo en Inglés | MEDLINE | ID: mdl-28650476

RESUMEN

Broad-scale protein-protein interaction mapping is a major challenge given the cost, time, and sensitivity constraints of existing technologies. Here, we present a massively multiplexed yeast two-hybrid method, CrY2H-seq, which uses a Cre recombinase interaction reporter to intracellularly fuse the coding sequences of two interacting proteins and next-generation DNA sequencing to identify these interactions en masse. We applied CrY2H-seq to investigate sparsely annotated Arabidopsis thaliana transcription factors interactions. By performing ten independent screens testing a total of 36 million binary interaction combinations, and uncovering a network of 8,577 interactions among 1,453 transcription factors, we demonstrate CrY2H-seq's improved screening capacity, efficiency, and sensitivity over those of existing technologies. The deep-coverage network resource we call AtTFIN-1 recapitulates one-third of previously reported interactions derived from diverse methods, expands the number of known plant transcription factor interactions by three-fold, and reveals previously unknown family-specific interaction module associations with plant reproductive development, root architecture, and circadian coordination.


Asunto(s)
Arabidopsis/metabolismo , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Mapeo de Interacción de Proteínas/métodos , Proteoma/metabolismo , Factores de Transcripción/metabolismo , Técnicas del Sistema de Dos Híbridos , Arabidopsis/genética , Proteoma/genética , Análisis de Secuencia de ADN , Factores de Transcripción/genética
5.
Mol Syst Biol ; 12(4): 865, 2016 Apr 22.
Artículo en Inglés | MEDLINE | ID: mdl-27107014

RESUMEN

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical-versus-functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an "inter-interactome" approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter-interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra-species networks. Although substantially reduced relative to intra-species networks, the levels of functional overlap in the yeast-human inter-interactome network uncover significant remnants of co-functionality widely preserved in the two proteomes beyond human-yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co-functionality. Such non-functional interactions, however, represent a reservoir from which nascent functional interactions may arise.


Asunto(s)
Proteínas Fúngicas/metabolismo , Mapeo de Interacción de Proteínas/métodos , Proteoma/metabolismo , Biología Computacional/métodos , Bases de Datos de Proteínas , Evolución Molecular , Humanos
6.
Nat Methods ; 8(12): 1050-2, 2011 Oct 30.
Artículo en Inglés | MEDLINE | ID: mdl-22037702

RESUMEN

Gateway-compatible yeast one-hybrid (Y1H) assays provide a convenient gene-centered (DNA to protein) approach to identify transcription factors that can bind a DNA sequence of interest. We present Y1H resources, including clones for 988 of 1,434 (69%) predicted human transcription factors, that can be used to detect both known and new interactions between human DNA regions and transcription factors.


Asunto(s)
Redes Reguladoras de Genes/genética , Genes/genética , Técnicas del Sistema de Dos Híbridos , Sitios de Unión , ADN/genética , Humanos , Programas Informáticos , Factores de Transcripción/metabolismo
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