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Long-range energetic communication underlies protein regulation, yet its conservation across homologues is unclear. Here, the authors map 21,802 folding and binding free-energy changes across five human PDZ domains, revealing general principles and protein-specific functional hotspots

How mutations shape signal processing in protein switches is not well defined. Here, the authors use GluePCA to profile thousands of PYL1 variants, uncovering modular control of sensitivity, basal activity and maximal response, novel inverter and band-stop mutations, and identifying stability‑driven mechanisms.

Independently folding domains can be seen as the functional and evolutionary structural units of proteins. Here, the authors assess effects of >7000 mutations in a model PDZ domain, to quantify how two small extensions to a protein domain reshape its energetic and allosteric landscape.

Altered pre-mRNA splicing frequently causes disease, yet how sequence variants alter splicing remains enigmatic. Here the authors use deep indel mutagenesis and deep learning tools to reveal the regulatory architecture of human exons and identify splicing-modulating antisense oligonucleotides.

By comprehensively mapping the impact that different classes of mutations (substitutions, insertions, deletions) have on the ability of the amyloid beta peptide to nucleate amyloids, the authors identify a large set of likely pathogenic variants of amyloid beta that are specifically enriched at its polar N-terminal region.

TDP43 aggregates are a hallmark of amyotrophic lateral sclerosis. By using deep mutagenesis to measure the toxicity of more than 50,000 mutations in the prion domain of TDP43, the authors conclude that mutations that increase toxicity promote formation of liquid-like condensates, while aggregation of TDP43 is protective for the cell.

By experimentally sampling from sequence spaces larger than 10¹⁰ and using thermodynamic models, the genetic structure of at least some proteins can be well described, indicating that protein genetics is simpler than anticipated.

Analysis of the effects of more than 26,000 KRAS mutations on abundance and interactions with six other proteins is used to construct an energy landscape of KRAS and identify allosteric drug target sites.

The effects of insertions and deletions on protein stability are not well understood and are poorly predicted. Here, the authors perform large-scale experiments and present INDELi, a method to predict the effects of amino acid insertions and deletions on protein stability and pathogenicity.

Many mutations cause disease because they destabilize proteins. Here, Mighell and Lehner show that a single small molecule can correct the destabilization caused by nearly all pathogenic mutations in a human GPCR.

Large-scale experimental analysis of Human Domainome 1, a library containing more than 500,000 missense mutation variants across more than 500 human protein domains, reveals that 60% of pathogenic missense variants reduce stability of protein domains.

Mutation rates in cancer genomes are closely related to chromatin organization, indicating that the arrangement of the genome into heterochromatin- and euchromatin-like domains may be a dominant influence on variation in regional mutation rate in human somatic cells.

Ben Lehner and colleagues report an analysis of the published genome sequences of 19 S. cerevisiae strains together with the results of growth experiments using 15 strains across 20 environmental conditions. They define sets of genes influencing growth under these different conditions and use their data to make predictions about the phenotypes of individual strains.

Here, the authors build a map of how mutations alter the binding of JUN to all 54 human bZIP proteins, revealing how affinity and specificity can be tuned and how determinants of specificity distribute in a protein interaction interface.

Small molecules can promote translational readthrough of premature termination codons, reducing their pathological effect. This study quantifies the readthrough of ~5,800 human pathogenic stop codons by eight drugs and builds models to predict drug-induced readthrough genome-wide.

Studying how genetic variants in different genes interact and their combinatorial output is experimentally and analytically challenging. Here, the authors quantify the effects of more than 5000 mutation pairs in the yeast GAL regulatory system, finding that many combinations can be predicted with statistical models.

A study of SARS-CoV-2 variants examining their transmission, infectivity, and potential resistance to therapies provides insights into the biology of the Delta variant and its role in the global pandemic.

An approach that combines deep mutational scanning with neural network-based thermodynamic modelling is used to provide comprehensive maps of the energetic and allosteric effects of mutations in two common protein domains.

Quantifying the effects of noise in gene expression is difficult since noise and mean expression are coupled. Here the authors determine fitness landscapes in mean-noise expression space to uncouple these two parameters and show that changes in noise and mean expression are similarly detrimental to fitness.

The spike protein of the Omicron variant of SARS-CoV-2 has a higher affinity for ACE2 than Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic and vaccine-elicited neutralizing antibodies.

Maternal age is found to be a major source of phenotypic variation in isogenic C. elegans populations living in a controlled environment, with the progeny of young mothers impaired for multiple fitness traits.

An analysis of how regional mutation rates vary across 652 tumours identifies variable DNA mismatch repair as the basis of the characteristic regional variation in mutation rates seen across the human genome; the results show that differential DNA repair, rather than differential mutation supply, is likely to be the primary cause of this variation.

Mutations sometimes only affect a subset of genetically identical individuals; here, variation in the expression of chaperones and gene duplicates is shown to predict mutation outcome in C. elegans.

This method predicts three-dimensional protein structures based on the activity of mutant variants. The approach relies on quantifying genetic interactions between mutations to infer direct contacts between residues.

Genotype–phenotype landscapes are an important characteristic for understanding the evolution of traits. Here the authors construct the local landscape for the alternative splicing of FAS/CD95 exon 6, revealing the regulation of splicing and the evolution of regulatory information between species.

In quantitative genetics, it is widely assumed that mutations combine additively or epistasis can be predicted with statistical or mechanistic models. Here, the authors use the phage lambda repressor model to show how biophysical ambiguity and non-monotonic functions confound phenotypic prediction.

Ben Lehner and colleagues analyze data from matched exomes and transcriptomes from tumors across 27 cancer types to elucidate rules linking premature termination codon location to nonsense-mediated mRNA decay (NMD). They propose a model that explains variability in NMD efficiency and find evidence of positive and negative selection on NMD-initiating mutations in tumors.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

The impact of germline variants on somatic alterations in cancer remains to be explored in large-scale datasets. Here, the authors study the association of rare germline variants with somatic mutational processes in more than 15,000 tumors, and reveal that damaging variants in newly-identifed genes are prevalent in the population.

Non-additive genetic interactions are plastic and can complicate genetic prediction. Here, using deep mutagenesis of the lambda repressor, Li et al. reveal that changes in gene expression can alter the strength and direction of genetic interactions between mutations in many genes and develop mathematical models for predicting them.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

In the classic two-hit model, both alleles of a tumour suppressor gene need to be inactivated in order to promote cancer. Here, the authors challenge this model, finding that many cancer genes can be either one-hit or two-hit drivers depending on the context and other mutations in a tumor.

In this study, Aggarwal and colleagues perform prospective sequencing of SARS-CoV-2 isolates derived from asymptomatic student screening and symptomatic testing of students and staff at the University of Cambridge. They identify important factors that contributed to within university transmission and onward spread into the wider community.

Chronic infection with SARS-CoV-2 leads to the emergence of viral variants that show reduced susceptibility to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma.

Sera from vaccinated individuals and some monoclonal antibodies show a modest reduction in neutralizing activity against the B.1.1.7 variant of SARS-CoV-2; but the E484K substitution leads to a considerable loss of neutralizing activity.

The effects of mutations in proteins can depend on the occurrence of previous mutations. It emerges that such historical contingency is also important during the evolution of gene regulatory networks. See Letter p.361

Some mutations in tumour cells play no part in causing cancer, but they generate cellular weak spots that may allow tumour cells to be selectively killed by drugs. See Article p.337

Inherited germline variants and somatic mutations contribute to cancer. Here, the authors present the statistical method ALFRED that tests the two-hit hypothesis of tumorigenesis and apply it to ~10,000 tumor exomes to identify rare germline variants that affect putative cancer predisposition genes, contributing substantially to cancer risk.

Perez and Lehner summarize recent discoveries regarding epigenetic inheritance across generations and review the molecular mechanisms underlying non-DNA sequence-based transmissions.

A microchip-based DNA synthesis method enables scalable production of complex DNA constructs.

A gene conferring puromycin resistance can be used for antibiotic selection in C. elegans and C. briggsae. This will permit easy maintenance of transgenic lines and facilitate single-copy insertion of transgenes. Also in this issue, a related paper reports nematode selection using neomycin.

The authors examine how mutations combine to alter phenotypes in biophysical models of proteins and conclude that non-additive interactions (epistasis and dominance) are frequent, context-dependent and so challenging to predict in even the simplest of biological systems.

Avgustinova et al. report that targeting the H3K9 methyltransferase G9a in skin cancer does not affect single nucleotide variant profiles, but leads to increased tumour aggressiveness after a prolonged latency.

Zhu et al. discover that in human brain there is widespread anatomic distribution of low-frequency somatic, mosaic L1 insertions, using deep whole-genome sequencing of neuronal and glial fractions and machine-learning analysis.