Cells sense their environment and adapt to it by fine-tuning their transcriptome. Wired into this network of gene expression control are mechanisms to compensate for gene dosage. The increasing use of reverse genetics in zebrafish, and other model systems, has revealed profound differences between the phenotypes caused by genetic mutations and those caused by gene knockdowns at many loci, an observation previously reported in mouse and Arabidopsis. To identify the reasons underlying the phenotypic differences between mutants and knockdowns, we generated mutations in zebrafish egfl7, an endothelial extracellular matrix gene of therapeutic interest, as well as in vegfaa. Here we show that egfl7 mutants do not show any obvious phenotypes while animals injected with egfl7 morpholino (morphants) exhibit severe vascular defects. We further observe that egfl7 mutants are less sensitive than their wild-type siblings to Egfl7 knockdown, arguing against residual protein function in the mutants or significant off-target effects of the morpholinos when used at a moderate dose. Comparing egfl7 mutant and morphant proteomes and transcriptomes, we identify a set of proteins and genes that are upregulated in mutants but not in morphants. Among them are extracellular matrix genes that can rescue egfl7 morphants, indicating that they could be compensating for the loss of Egfl7 function in the phenotypically wild-type egfl7 mutants. Moreover, egfl7 CRISPR interference, which obstructs transcript elongation and causes severe vascular defects, does not cause the upregulation of these genes. Similarly, vegfaa mutants but not morphants show an upregulation of vegfab. Taken together, these data reveal the activation of a compensatory network to buffer against deleterious mutations, which was not observed after translational or transcriptional knockdown.

Genetic robustness, or the ability of an organism to maintain fitness in the presence of mutations, can be achieved via protein feedback loops. Recent evidence suggests that organisms may also respond to mutations by upregulating related gene(s) independently of protein feedback loops, a phenomenon called transcriptional adaptation. However, the prevalence of transcriptional adaptation and its underlying molecular mechanisms are unknown. Here, by analyzing several models of transcriptional adaptation in zebrafish and mouse, we show a requirement for mRNA degradation. Alleles that fail to transcribe the mutated gene do not display transcriptional adaptation and exhibit more severe phenotypes than alleles displaying mutant mRNA decay. Transcriptome analysis reveals the upregulation of a substantial proportion of the genes that exhibit sequence similarity with the mutated gene’s mRNA, suggesting a sequence dependent mechanism. Besides implications for our understanding of disease-causing mutations, these findings will help design mutant alleles with minimal transcriptional adaptation-derived compensation.

Antibody drug conjugates (ADCs) are a therapeutic class offering promise for cancer therapy. The attachment of cytotoxic drugs to antibodies can result in an effective therapy with better safety potential than nontargeted cytotoxics. To understand the role of conjugation site, we developed an enzymatic method for site-specific antibody drug conjugation using microbial transglutaminase. This allowed us to attach diverse compounds at multiple positions and investigate how the site influences stability, toxicity, and efficacy. We show that the conjugation site has significant impact on ADC stability and pharmacokinetics in a species-dependent manner. These differences can be directly attributed to the position of the linkage rather than the chemical instability, as was observed with a maleimide linkage. With this method, it is possible to produce homogeneous ADCs and tune their properties to maximize the therapeutic window.

Genetic compensation by transcriptional modulation of related gene(s) (also known astranscriptional adaptation) has been reported in numerous systems 1-3 ; however, whether and how such a response can be activated in the absence of protein feedback loops is unknown. Here, we develop and analyze several models of transcriptional adaptation in zebrafish and mouse that we show are not caused by loss of protein function. We find that the increase in transcript levels is due to enhanced transcription, and observe a correlation between the levels of mutant mRNA decay and transcriptional upregulation of related genes. To assess the role of mutant mRNA degradation in triggering transcriptional adaptation, we use genetic and pharmacological approaches and find that mRNA degradation is indeed required for this process. Notably, uncapped RNAs, themselves subjected to rapid degradation, can also induce transcriptional adaptation. Next, we generate alleles that fail to transcribe the mutated gene and find that they do not show transcriptional adaptation, and exhibit more severe phenotypes than those observed in alleles displaying mutant mRNA decay. Transcriptome analysis of these different alleles reveals the upregulation of hundreds of genes with enrichment for those showing sequence similarity with the mutated gene's mRNA, suggesting a model whereby mRNA degradation products induce the response via sequence similarity. These results expand the role of the mRNA surveillance machinery in buffering against mutations by triggering the transcriptional upregulation of related genes. Besides implications for our understanding of disease-causing mutations, our findings will help design mutant alleles with minimal transcriptional adaptation-derived compensation.Recent advances in reverse genetic tools have greatly enhanced our ability to study gene function in a much wider range of organisms. These studies have reinforced previous observations that many engineered mutants do not exhibit an obvious phenotype, reviving interest in the concept of