Next-generation sequencing to generate interactome datasets

Yu, Haiyuan; Tardivo, Leah; Tam, Stanley; Weiner, Evan M.; Gebreab, Fana; Fan, Changyu; Svrzikapa, Nenad; Hirozane-Kishikawa, Tomoko; Rietman, Edward A.; Yang, Xinping; Sahalie, Julie M.; Salehi‐Ashtiani, Kourosh; Hao, Tong; Cusick, Michael E.; Hill, David E.; Roth, Frederick P.; Braun, Pascal; Vidal, Marc

doi:10.1038/nmeth.1597

Cited by 253 publications

(220 citation statements)

References 20 publications

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“…Despite recent conceptual and technical advances [1][2][3] , large-scale interactome mapping remains a daunting task, and for most species, only a small fraction of interactions have been mapped. Yeast two-hybrid (Y2H) analysis can be applied at high throughput and contributes substantially to high-quality interactome mapping [3][4][5] .…”

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confidence: 99%

A Y2H-seq approach defines the human protein methyltransferase interactome

et al. 2013

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A 'writer-reader-eraser' post-translational modification regulatory system consisting of a large number of methyltransferases 8,9 , methyl-recognition domain-containing proteins 10 and putative demethylases 11 are expressed in different subcellular locations in humans, an indication that protein methylation is involved in processes other than epigenetic regulation.We prepared 82 Y2H bait strains spanning human R-methyltransferases (PRMT1-PRMT8) 8 , 16 SET domaincontaining K-methyltransferases (PKMTs) 9 , 9 members of the JMJD domain-containing protein family of protein demethylases and AOF2 (LSD1) 11 (Supplementary Table 1). In our current matrix screening protocol 4,12 , we perform four replicates, testing every set of baits individually against each of the ~13,000 prey contained in the matrix. Interacting prey are identified by their position in the matrix. To increase the sensitivity of the approach while also reducing the workload, we used a pooled strategy to test each protein pair substantially more than four times. Baits were pooled with all prey strains and then assayed for interaction in more than 100,000 separate spots ( Fig. 1a and Supplementary Fig. 1). Using Y2H-seq, we obtained 4-10 times the number of positive colonies obtained with the matrix approach. To reveal the prey identities, we collected all colonies and performed a 36-base parallel sequencing run. More than 20 million reads mapped perfectly to human RefSeq coding sequences (open reading frames, ORFs), corresponding to more than 500,000 unique 36-base reads (Supplementary Table 2). To rank the potentially interacting proteins for subsequent interaction retesting, we calculated a 'SeqScore' that incorporates the number of total mappings and the number of unique reads matching the ORF ( Supplementary Fig. 2). Notably, >99.7% of the RefSeq mappings matched to the 400 top-ranked genes, thus allowing the identification of potentially interacting ORFs with an extremely high signal-tobackground ratio (Supplementary Table 2).We performed four biological replicates and demonstrated in statistical pairwise comparisons that they result in very similar ranked prey orders (Supplementary Fig. 3). Top-ranked prey in at least two replicate screens were retested against all baits in a pairwise manner (Supplementary Fig. 4) and yielded 463 protein interactions (Supplementary Table 3). The success rate of the retest-that is, the probability that the prey is interactingdecreased with decreasing SeqScore (Fig. 1b).We also performed a matrix screen in quadruplicate with a subset of the protein methyltransferase (PMT) and protein demethylase (PDeM) baits for direct method comparison. With the matrix approach, we found 151 interactions (Supplementary to accelerate high-density interactome mapping, we developed a yeast two-hybrid interaction screening approach involving short-read second-generation sequencing (Y2h-seq) with improved sensitivity and a quantitative scoring readout allowing rapid interaction validation. We applied Y2h-seq to investigate enzymes in...

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confidence: 99%

A Y2H-seq approach defines the human protein methyltransferase interactome

et al. 2013

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“…4,[21][22][23] We manually checked the evidence code of the experiments that were used to detect the interactions in order to filter out low-confidence and non-binary interactions. Any interaction detected by experiments that cannot generate binary interactions was removed.…”

Section: Data and Calculation Of Biochemical And Functional Featuresmentioning

confidence: 99%

“…1,2 With the advance of genome-wide association studies (GWAS), detection of molecular interactions and especially the ongoing cancer genome sequencing projects, an impressive list of disordergene associations and their mutations has been generated. 3,4 Researchers have begun to explore human diseases on a large scale by genome-wide analysis using complex cellular networks on the basis that disease genes have distinct biochemical characteristics and function by interacting with other genes. 1,5 One important piece of information about human Mendelian diseases is the mode of inheritance, which is usually the first step toward understanding the molecular mechanism of inherited human diseases.…”

Section: Introductionmentioning

confidence: 99%

Systematic large-scale study of the inheritance mode of Mendelian disorders provides new insight into human diseasome

et al. 2014

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One important piece of information about the human Mendelian disorders is the mode of inheritance. Recent studies of human genetic diseases on a large scale have provided many novel insights into the underlying molecular mechanisms. However, most successful analyses ignored the mode of inheritance of diseases, which severely limits our understanding of human disease mechanisms relating to the mode of inheritance at the large scale. Therefore, we here conducted a systematic large-scale study of the inheritance mode of Mendelian disorders, to bring new insight into human diseases. Our analyses include the comparison between dominant and recessive disease genes on both genomic and proteomic characteristics, Mendelian mutations, protein network properties and disease connections on both the genetic and the population levels. We found that dominant disease genes are more functionally central, topological central and more sensitive to disease outcome. On the basis of these findings, we suggested that dominant diseases should have higher genetic heterogeneity and should have more comprehensive connections with each other compared with recessive diseases, a prediction we confirm by disease network and disease comorbidity.

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“…Thus, in order to reach complete coverage of the human interactome, the parallel use of complementary screening methods will be required. The recently developed Stitch-Seq interactome mapping protocol that combines PCR stitching (placing a pair of interacting proteins on the same PCR amplicon) with NGS will drastically increase the throughput and efficiency of interactome mapping projects [110]. An accurate view on the extent and complexity of the human interactome will be vital for further progress in drug discovery, both as a supply of novel PPI targets and as a source of information to increase our insight in disease-related processes, as illustrated in the next paragraph.…”

Section: Construction Of the Human Interactomementioning

confidence: 99%

Protein-protein Interactions: Network Analysis and Applications in Drug Discovery

Bultinck¹,

Lievens²,

Tavernier

2012

CPD

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Physical interactions among proteins constitute the backbone of cellular function, making them an attractive source of therapeutic targets. Although the challenges associated with targeting proteinprotein interactions (PPIs) -in particular with small molecules -are considerable, a growing number of functional PPI modulators is being reported and clinically evaluated. An essential starting point for PPI inhibitor screening or design projects is the generation of a detailed map of the human interactome and the interactions between human and pathogen proteins. Different routes to produce these biological networks are being combined, including literature curation and computational methods. Experimental approaches to map PPIs mainly rely on the yeast two-hybrid (Y2H) technology, which have recently shown to produce reliable protein networks. However, other genetic and biochemical methods will be essential to increase both coverage and resolution of current protein networks in order to increase their utility towards the identification of novel disease-related proteins and PPIs, and their potential use as therapeutic targets.

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Next-generation sequencing to generate interactome datasets

Cited by 253 publications

References 20 publications

A Y2H-seq approach defines the human protein methyltransferase interactome

A Y2H-seq approach defines the human protein methyltransferase interactome

Systematic large-scale study of the inheritance mode of Mendelian disorders provides new insight into human diseasome

Protein-protein Interactions: Network Analysis and Applications in Drug Discovery

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