More than 200 proteins copurify with spliceosomes, the compositionally dynamic RNPs catalyzing pre-mRNA splicing. To better understand protein - protein interactions governing splicing, we systematically investigated interactions between human spliceosomal proteins. A comprehensive Y2H interaction matrix screen generated a protein interaction map comprising 632 interactions between 196 proteins. Among these, 242 interactions were found between spliceosomal core proteins and largely validated by coimmunoprecipitation. To reveal dynamic changes in protein interactions, we integrated spliceosomal complex purification information with our interaction data and performed link clustering. These data, together with interaction competition experiments, suggest that during step 1 of splicing, hPRP8 interactions with SF3b proteins are replaced by hSLU7, positioning this second step factor close to the active site, and that the DEAH-box helicases hPRP2 and hPRP16 cooperate through ordered interactions with GPKOW. Our data provide extensive information about the spliceosomal protein interaction network and its dynamics.
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...
The yeast two-hybrid (Y2H) system is currently one of the most important techniques for protein-protein interaction (PPI) discovery. Here, we describe a stringent three-step Y2H matrix interaction approach that is suitable for systematic PPI screening on a proteome scale. We start with the identification and elimination of autoactivating strains that would lead to false-positive signals and prevent the identification of interactions. Nonautoactivating strains are used for the primary PPI screen that is carried out in quadruplicate with arrayed preys. Interacting pairs of baits and preys are identified in a pairwise retest step. Only PPI pairs that pass the retest step are regarded as potentially biologically relevant interactions and are considered for further analysis.
10 different oligonucleotide probes were evaluated for DNA fingerprinting in horses. Five probes were able to detect polymorphic bands. The probes (GT)(8) , (GTG)(5) and (GGAT)(4) are most informative for individual identification and were used to analyze a population of Hannoveranian horses. The probability that two individuals have the same DNA fingerprint pattern is 1.2 × 10(-8) , 5.2 × 10(-10) and 1.5 × 10(-7) respectively. Using a combination of the three probes, paternity tests were performed with exclusion probabilities between 0.08% and 4%. ZUSAMMENFASSUNG: Oligonukleotide-Sonden für DNS-Fingerprints von Pferden Zur Darstellung von DNA-Fingerprints beim Pferd wurden zehn verschiedene Oligonukleotid-Sonden verglichen. Mit fünf Sonden konnten polymorphe Banden nachgewiesen werden. Die Sonden (GT)(8) , (GTG)(5) und (GGAT)(4) besaßen die größte Informativität für den Identitätsnachweis und wurden für die Analyse einer Population von Hannoverschen Pferden benutzt. Die Wahrscheinlichkeit, daß zwei Individuen dieselben Fingerprint-Muster aufweisen, liegt bei 1,2 × 10(-8) , 5,2 × 10(-10) bzw. 1,5 × 10(-7) . Bei Verwendung einer Kombination der drei Sonden wurden Vaterschaftskontrollen mit Ausschlußwahrscheinlichkeiten zwischen 0,08% und 4% erreicht.
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