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CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies 1-6 . However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency 7,8 . Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements 9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

γδ T cells are potent anticancer effectors with the potential to target tumours broadly, independent of patient-specific neoantigens or human leukocyte antigen background 1-5 . γδ T cells can sense conserved cell stress signals prevalent in transformed cells 2,3 , although the mechanisms behind the targeting of stressed target cells remain poorly characterized. Vγ9Vδ2 T cells-the most abundant subset of human γδ T cells 4 -recognize a protein complex containing butyrophilin 2A1 (BTN2A1) and BTN3A1 (refs. 6-8 ), a widely expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumour cells. Here we combined genome-wide CRISPR screens in target cancer cells to identify pathways that regulate γδ T cell killing and BTN3A cell surface expression. The screens showed previously unappreciated multilayered regulation of BTN3A abundance on the cell surface and triggering of γδ T cells through transcription, post-translational modifications and membrane trafficking. In addition, diverse genetic perturbations and inhibitors disrupting metabolic pathways in the cancer cells, particularly ATP-producing processes, were found to alter BTN3A levels. This induction of both BTN3A and BTN2A1 during metabolic crises is dependent on AMP-activated protein kinase (AMPK). Finally, small-molecule activation of AMPK in a cell line model and in patient-derived tumour organoids led to increased expression of the BTN2A1-BTN3A complex and increased Vγ9Vδ2 T cell receptor-mediated killing. This AMPK-dependent mechanism of metabolic stress-induced ligand upregulation deepens our understanding of γδ T cell stress surveillance and suggests new avenues available to enhance γδ T cell anticancer activity., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

A major challenge in human genetics is to identify the molecular mechanisms of trait-associated and disease-associated variants. To achieve this, quantitative trait locus (QTL) mapping of genetic variants with intermediate molecular phenotypes such as gene expression and splicing have been widely adopted 1,2 . However, despite successes, the molecular basis for a considerable fraction of trait-associated and disease-associated variants remains unclear 3,4 . Here we show that ADAR-mediated adenosine-to-inosine RNA editing, a post-transcriptional event vital for suppressing cellular double-stranded RNA (dsRNA)-mediated innate immune interferon responses 5-11 , is an important potential mechanism underlying genetic variants associated with common inflammatory diseases. We identified and characterized 30,319 cis-RNA editing QTLs (edQTLs) across 49 human tissues. These edQTLs were significantly enriched in genome-wide association study signals for autoimmune and immune-mediated diseases. Colocalization analysis of edQTLs with disease risk loci further pinpointed key, putatively immunogenic dsRNAs formed by expected inverted repeat Alu elements as well as unexpected, highly over-represented cis-natural antisense transcripts. Furthermore, inflammatory disease risk variants, in aggregate, were associated with reduced editing of nearby dsRNAs and induced interferon responses in inflammatory diseases. This unique directional effect agrees with the established mechanism that lack of RNA editing by ADAR1 leads to the specific activation of the dsRNA sensor MDA5 and subsequent interferon responses and inflammation 7-9 . Our findings implicate cellular dsRNA editing and sensing as a previously underappreciated mechanism of common inflammatory diseases., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Although germline mutation rates and spectra can vary within and between species, common genetic modifiers of the mutation rate have not been identified in nature 1 . Here we searched for loci that influence germline mutagenesis using a uniquely powerful resource: a panel of recombinant inbred mouse lines known as the BXD, descended from the laboratory strains C57BL/6J (B haplotype) and DBA/2J (D haplotype). Each BXD lineage has been maintained by brother-sister mating in the near absence of natural selection, accumulating de novo mutations for up to 50 years on a known genetic background that is a unique linear mosaic of B and D haplotypes 2 . We show that mice inheriting D haplotypes at a quantitative trait locus on chromosome 4 accumulate C>A germline mutations at a 50% higher rate than those inheriting B haplotypes, primarily owing to the activity of a C>A-dominated mutational signature known as SBS18. The B and D quantitative trait locus haplotypes encode different alleles of Mutyh, a DNA repair gene that underlies the heritable cancer predisposition syndrome that causes colorectal tumors with a high SBS18 mutation load 3,4 . Both B and D Mutyh alleles are present in wild populations of Mus musculus domesticus, providing evidence that common genetic variation modulates germline mutagenesis in a model mammalian species., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Metagenomic analysis is a highly promising technique in paleogenetic research that allows analysis of the complete genomic make-up of a sample. This technique has successfully been employed to archaeological sediments, but possible leaching of DNA through the sequence limits interpretation. We applied this technique to the analysis of ancient DNA (aDNA) from Late Quaternary stalagmites from two caves in Western Georgia, Melouri Cave and Solkota. Stalagmites form closed systems, limiting the effect of leaching, and can be securely dated with U-series. The analyses of the sequence data from the Melouri Cave stalagmite revealed potential contamination and low preservation of DNA. However, the two Solkota stalagmites preserved ancient DNA molecules of mammals (bear, roe deer, bats) and plants (chestnut, hazelnut, flax). The aDNA bearing layers from one of the two Solkota stalagmites were dated to between ~84 ka and ~56 ka BP by U-series. The second Solkota stalagmite contained excessive detrital clay obstructing U-series dating, but it also contained bear bones with a minimum age of ~50 BP uncalibrated years and ancient DNA molecules. The preservation of authentic ancient DNA molecules in Late Quaternary speleothems opens up a new paleogenetic archive for archaeological, paleontological and paleoenvironmental research.

Advances in the sequencing and the analysis of the genomes of both modern and ancient peoples have facilitated a number of breakthroughs in our understanding of human evolutionary history. These include the discovery of interbreeding between anatomically modern humans and extinct hominins; the development of an increasingly detailed description of the complex dispersal of modern humans out of Africa and their population expansion worldwide; and the characterization of many of the genetic adaptions of humans to local environmental conditions. Our interpretation of the evolutionary history and adaptation of humans is being transformed by analyses of these new genomic data.

Single-cell RNA sequencing (scRNA-seq) can be used to characterize variation in gene expression levels at high resolution. However, the sources of experimental noise in scRNA-seq are not yet well understood. We investigated the technical variation associated with sample processing using the single-cell Fluidigm C1 platform. To do so, we processed three C1 replicates from three human induced pluripotent stem cell (iPSC) lines. We added unique molecular identifiers (UMIs) to all samples, to account for amplification bias. We found that the major source of variation in the gene expression data was driven by genotype, but we also observed substantial variation between the technical replicates. We observed that the conversion of reads to molecules using the UMIs was impacted by both biological and technical variation, indicating that UMI counts are not an unbiased estimator of gene expression levels. Based on our results, we suggest a framework for effective scRNA-seq studies.

The mapping of expression quantitative trait loci (eQTLs) has emerged as an important tool for linking genetic variation to changes in gene regulation. However, it remains difficult to identify the causal variants underlying eQTLs, and little is known about the regulatory mechanisms by which they act. Here we show that genetic variants that modify chromatin accessibility and transcription factor binding are a major mechanism through which genetic variation leads to gene expression differences among humans. We used DNase I sequencing to measure chromatin accessibility in 70 Yoruba lymphoblastoid cell lines, for which genome-wide genotypes and estimates of gene expression levels are also available. We obtained a total of 2.7 billion uniquely mapped DNase I-sequencing (DNase-seq) reads, which allowed us to produce genome-wide maps of chromatin accessibility for each individual. We identified 8,902 locations at which the DNase-seq read depth correlated significantly with genotype at a nearby single nucleotide polymorphism or insertion/deletion (false discovery rate = 10%). We call such variants 'DNase I sensitivity quantitative trait loci' (dsQTLs). We found that dsQTLs are strongly enriched within inferred transcription factor binding sites and are frequently associated with allele-specific changes in transcription factor binding. A substantial fraction (16%) of dsQTLs are also associated with variation in the expression levels of nearby genes (that is, these loci are also classified as eQTLs). Conversely, we estimate that as many as 55% of eQTL single nucleotide polymorphisms are also dsQTLs. Our observations indicate that dsQTLs are highly abundant in the human genome and are likely to be important contributors to phenotypic variation.

Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. Although all eQTL studies so far have assayed messenger RNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. By pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated untranslated regions and more than 100 new putative protein-coding exons. Using the genotypes from the HapMap project, we identified more than a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act by a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within and near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing and allele-specific expression across individuals.