To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.
Summary Packaging of DNA into chromatin has a profound impact on gene expression. To understand how changes in chromatin influence transcription, we analyzed 165 mutants of chromatin machinery components in Saccharomyces cerevisiae. mRNA expression patterns change in 80% of mutants, always with specific effects, even for loss of widespread histone marks. The data is assembled into a network of chromatin interaction pathways. The network is function-based, has a branched, interconnected topology and lacks strict one-to-one relationships between complexes. Chromatin pathways are not separate entities for different gene sets, but share many components. The study evaluates which interactions are important for which genes and predicts new interactions, for example between Paf1C and Set3C, as well as a role for Mediator in subtelomeric silencing. The results indicate the presence of gene-dependent effects that go beyond context-dependent binding of chromatin factors and provide a framework for understanding how specificity is achieved through regulating chromatin.
SUMMARY To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.
The Saccharomyces cerevisiae Slx5/8 complex is the founding member of a recently defined class of SUMO-targeted ubiquitin ligases (STUbLs). Slx5/8 has been implicated in genome stability and transcription, but the precise contribution is unclear. To characterise Slx5/8 function, we determined genome-wide changes in gene expression upon loss of either subunit. The majority of mRNA changes are part of a general stress response, also exhibited by mutants of other genome integrity pathways and therefore indicative of an indirect effect on transcription. Genome-wide binding analysis reveals a uniquely centromeric location for Slx5. Detailed phenotype analyses of slx5Δ and slx8Δ mutants show severe mitotic defects that include aneuploidy, spindle mispositioning, fish hooks and aberrant spindle kinetics. This is associated with accumulation of the PP2A regulatory subunit Rts1 at centromeres prior to entry into anaphase. Knockdown of the human STUbL orthologue RNF4 also results in chromosome segregation errors due to chromosome bridges. The study shows that STUbLs have a conserved role in maintenance of chromosome stability and links SUMO-dependent ubiquitination to a centromere-specific function during mitosis.
Eplets are defined as distinct amino acid configurations on the surface of HLA molecules. The aim of this study was to estimate the immunogenicity of HLA-DQ eplets in a cohort of 221 pregnancies with HLA-DQ mismatches. We defined the immunogenicity of an eplet by the frequency of antibody responses against it. Around 90% of all listed DQB1 or DQA1 eplets were at least five times mismatched and thus included for the calculation of their immunogenicity. The DQB1 eplets with the five highest immunogenicity scores were 55PP, 52PR, 52PQ, 85VG and 45EV; 25% of all DQB1 eplets were not reacting. The DQA1 eplets with the five highest immunogenicity scores were 25YS, 47QL, 55RR, 187T and 18S; 17% of all DQA1 eplets were not reacting. The immunogenicity score had a slightly higher area under the curve to predict development of childspecific antibodies than various molecular mismatch scores (eg, eplet mismatch load, amino acid mismatch load). Overlapping eplets were identified as a barrier to unambiguously assign the immunogenicity score based on HLA antibody reaction patterns. In this conceptual study, we explored the immunogenicity of HLA-DQ eplets and created a map of potentially immunogenic regions on HLA-DQ molecules, which requires validation in clinical transplant cohorts.
Eplets are functional units of structural epitopes on donor HLA, potentially recognized by complementarity‐determining regions of the paratope of the recipients' B‐cell receptors or antibodies (Ab). Their individual immunogenicity is poorly described, yet this feature would be of clinical importance for pretransplant risk assessment. The aim of this study was to determine the relative immunogenicity of HLA class I eplets in the pregnancy setting, where mismatched eplets are present on paternal HLA antigens of the unborn child. One hundred fifty‐nine predominantly Caucasian mothers giving birth at the University Hospital Basel and their first newborns were HLA‐typed at high‐resolution by next‐generation sequencing (NGS) (NGSgo Workflow and NGSengine from GenDx; sequencing with a Miseq from Illumina) and eplets were determined using HLAMatchmaker. HLA class I specific IgG Ab was assessed in maternal sera drawn immediately after full‐term delivery, by OneLambda LABScreen single antigen ibeads. The Ab profile was subsequently evaluated for eplet‐associated patterns. All 72 currently Ab‐verified HLA class I eplets were examined for their immunogenicity according to the frequency of child‐specific HLA Ab (CSA) directed against their structures. Four hundred twelve of 477 (86.4%) paternal HLA‐A, ‐B or ‐C alleles were mismatched. CSA were present in 46 mothers (28.9%), directed against 80 (19.4%) of these mismatches. The 10 most immunogenic eplets were 62GK, 145KHA, 144TKH, 62GE, 107W, 80I, 82LR, 41T, 127K, 45KE with immunogenicity rates between 45.8% and 27.3%. This pregnancy study also identified five non‐reactive eplets: 62RR, 76ESN, 80TLR, 156DA, 163RW. Based on our results, immunogenic hot and cold spots on the surface of HLA class I molecules were localized and visualized on 3D models. This study strengthens the presumption that different eplets represent different immunogenic potentials. Validation of these results in the clinical transplant setting is an essential next step in identifying those eplets representing a particularly high‐risk potential.
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