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Phoresy is an interspecies interaction that facilitates spatial dispersal by attaching to a more mobile species. Hitchhiking species have evolved specific traits for physical contact and successful phoresy, but the regulatory mechanisms involved in such traits and their evolution are largely unexplored. The nematode Caenorhabditis elegans displays a hitchhiking behavior known as nictation during its stress-induced developmental stage. Dauer-specific nictation behavior has an important role in natural C. elegans populations, which experience boom-and-bust population dynamics. In this study, we investigated the nictation behavior of 137 wild C. elegans strains sampled throughout the world. We identified species-wide natural variation in nictation and performed a genome-wide association mapping. We show that the variants in the promoter of nta-1, encoding a putative steroidogenic enzyme, underlie differences in nictation. This difference is due to the changes in nta-1 expression in glial cells, which implies that glial steroid metabolism regulates phoretic behavior. Population genetic analysis and geographic distribution patterns suggest that balancing selection maintained two nta-1 haplotypes that existed in ancestral C. elegans populations. Our findings contribute to further understanding of the molecular mechanism of species interaction and the maintenance of genetic diversity within natural populations. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource.Analyses of multiregional tumour samples from 421 patients with non-small cell lung cancer prospectively enrolled to the TRACERx study reveal determinants of tumour evolution and relationships between intratumour heterogeneity and clinical outcome. [ABSTRACT FROM AUTHOR]

Summary RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning-based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events and how additional thresholding can be used to facilitate our models' use in a production pipeline. Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

Circular consensus sequencing with Pacific Biosciences (PacBio) technology generates long (10–25 kilobases), accurate 'HiFi' reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation, pbccs, uses a hidden Markov model. We introduce DeepConsensus, which uses an alignment-based loss to train a gap-aware transformer–encoder for sequence correction. Compared to pbccs, DeepConsensus reduces read errors by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27% and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity (NG50 4.9 megabases (Mb) to 17.2 Mb), increase gene completeness (94% to 97%), reduce the false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45) and reduce variant-calling errors by 24%. DeepConsensus models could be trained to the general problem of analyzing the alignment of other types of sequences, such as unique molecular identifiers or genome assemblies. Deep learning reduces errors in sequences from PacBio HiFi reads. [ABSTRACT FROM AUTHOR]

The nematode Caenorhabditis elegans is among the most widely studied organisms, but relatively little is known about its natural ecology. Genetic diversity is low across much of the globe but high in the Hawaiian Islands and across the Pacific Rim. To characterize the niche and genetic diversity of C. elegans on the Hawaiian Islands and to explore how genetic diversity might be influenced by local adaptation, we repeatedly sampled nematodes over a three‐year period, measured various environmental parameters at each sampling site, and whole‐genome sequenced the C. elegans isolates that we identified. We found that the typical Hawaiian C. elegans niche comprises moderately moist native forests at high elevations (500–1,500 m) where ambient air temperatures are cool (15–20°C). Compared to other Caenorhabditis species found on the Hawaiian Islands (e.g., Caenorhabditis briggsae and Caenorhabditis tropicalis), we found that C. elegans were enriched in native habitats. We measured levels of genetic diversity and differentiation among Hawaiian C. elegans and found evidence of seven genetically distinct groups distributed across the islands. Then, we scanned these genomes for signatures of local adaptation and identified 18 distinct regions that overlap with hyper‐divergent regions, which may be maintained by balancing selection and are enriched for genes related to environmental sensing, xenobiotic detoxification, and pathogen resistance. These results provide strong evidence of local adaptation among Hawaiian C. elegans and contribute to our understanding of the forces that shape genetic diversity on the most remote volcanic archipelago in the world. [ABSTRACT FROM AUTHOR]

Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it can be used with other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples. [ABSTRACT FROM AUTHOR]

Parasitic nematodes impose a debilitating health and economic burden across much of the world. Nematode resistance to anthelmintic drugs threatens parasite control efforts in both human and veterinary medicine. Despite this threat, the genetic landscape of potential resistance mechanisms to these critical drugs remains largely unexplored. Here, we exploit natural variation in the model nematodes Caenorhabditis elegans and Caenorhabditis briggsae to discover quantitative trait loci (QTL) that control sensitivity to benzimidazoles widely used in human and animal medicine. High-throughput phenotyping of albendazole, fenbendazole, mebendazole, and thiabendazole responses in panels of recombinant lines led to the discovery of over 15 QTL in C. elegans and four QTL in C. briggsae associated with divergent responses to these anthelmintics. Many of these QTL are conserved across benzimidazole derivatives, but others show drug and dose specificity. We used near-isogenic lines to recapitulate and narrow the C. elegans albendazole QTL of largest effect and identified candidate variants correlated with the resistance phenotype. These QTL do not overlap with known benzimidazole target resistance genes from parasitic nematodes and present specific new leads for the discovery of novel mechanisms of nematode benzimidazole resistance. Analyses of orthologous genes reveal conservation of candidate benzimidazole resistance genes in medically important parasitic nematodes. These data provide a basis for extending these approaches to other anthelmintic drug classes and a pathway towards validating new markers for anthelmintic resistance that can be deployed to improve parasite disease control. [ABSTRACT FROM AUTHOR]

Many chemotherapeutic drugs are differentially effective from one patient to the next. Understanding the causes of this variability is a critical step towards the development of personalized treatments and improvements to existing medications. Here, we investigate sensitivity to a group of anti-neoplastic drugs that target topoisomerase II using the model organism Caenorhabditis elegans. We show that wild strains of C. elegans vary in their sensitivity to these drugs, and we use an unbiased genetic approach to demonstrate that this natural variation is explained by a methionine-to-glutamine substitution in topoisomerase II (TOP-2). The presence of a non-polar methionine at this residue increases hydrophobic interactions between TOP-2 and its poison etoposide, as compared to a polar glutamine. We hypothesize that this stabilizing interaction results in increased genomic instability in strains that contain a methionine residue. The residue affected by this substitution is conserved from yeast to humans and is one of the few differences between the two human topoisomerase II isoforms (methionine in hTOPIIα and glutamine in hTOPIIβ). We go on to show that this amino acid difference between the two human topoisomerase isoforms influences cytotoxicity of topoisomerase II poisons in human cell lines. These results explain why hTOPIIα and hTOPIIβ are differentially affected by various poisons and demonstrate the utility of C. elegans in understanding the genetics of drug responses. [ABSTRACT FROM AUTHOR]

Objective: Measurements of neonatal metabolites are commonly used in newborn screening (NBS) programs to detect inborn errors of metabolism. Variation in these metabolites, particularly in infants born preterm (<37 weeks gestation), can result from multiple etiologies. We sought to evaluate the impact of maternal complications of pregnancy and environmental stressors on NBS metabolites. Methods: We examined 49 metabolic biomarkers obtained from routine NBS in 452 infants born preterm for association with maternal environmental stressors and complications of pregnancy. Results: Neonatal free carnitine (C0, p = 1.4 × 10−7), acetylcarnitine (C2, p = 2.7 × 10−7), octenoylcarnitine (C8:1, p = 5.2 × 10−11) and linoleoylcarnitine (C18:2, p = 9.1 × 10−7) were elevated in infants born to preeclamptic mothers. Similar elevations were observed in small for gestational age infants and in infants where labor was not initiated prior to delivery. When accounting for all three factors, associations remained strongest between acylcarnitines and preeclampsia. Conclusion: We observed that maternal conditions, particularly preeclampsia, influence NBS biomarkers. This is important for identifying maternal conditions that influence metabolites measured during routine NBS that are also markers of fetal growth and overall health. [ABSTRACT FROM AUTHOR]

Genome-wide association studies hold the potential for discovering genetic causes for a wide range of diseases, traits, and behaviors. However, the incredible amount of data handling, advanced statistics, and visualization have made conducting these studies difficult for researchers. Here we provide a tool, manhattan, for helping investigators easily visualize genome-wide association studies data in Stata. [ABSTRACT FROM AUTHOR]

Nationally, newborn screening programs use 17-hydroxyprogesterone (17-OHP) as the biomarker to detect the rare but potentially fatal inherited disease, congenital adrenal hyperplasia. However, this biomarker is highly variable, with a high false-positive rate of detection, particularly in neonates born preterm. Several studies have examined various clinical and genetic factors to explain the variability of 17-OHP in preterm infants. The purpose of this study was to replicate previous clinical and genetic associations with 17-OHP in a well-characterized cohort of 762 preterm infants. We replicated previous findings that respiratory distress syndrome (p=2×10-3) is associated with higher 17-OHP. Higher 17-OHP and false positives were significantly associated with lower gestational age and birth weight, as previously reported. Incorporating gestational age and birth weight together decreases the false-positive rate. [ABSTRACT FROM AUTHOR]

Summary: The variant call format (VCF) is a popular standard for storing genetic variation data. As a result, a large collection of tools has been developed that perform diverse analyses using VCF files. However, some tasks common to statistical and population geneticists have not been created yet. To streamline these types of analyses, we created novel tools that analyze or annotate VCF files and organized these tools into a command-line based utility named VCF-kit. VCF-kit adds essential utilities to process and analyze VCF files, including primer generation for variant validation, dendrogram production, genotype imputation from sequence data in linkage studies, and additional tools. [ABSTRACT FROM AUTHOR]