Bell Beaker pottery spread across western and central Europe beginning around 2750 BCE before disappearing between 2200–1800 BCE. The mechanism of its expansion is a topic of long-standing debate, with support for both cultural diffusion and human migration. We present new genome-wide ancient DNA data from 170 Neolithic, Copper Age and Bronze Age Europeans, including 100 Beaker-associated individuals. In contrast to the Corded Ware Complex, which has previously been identified as arriving in central Europe following migration from the east, we observe limited genetic affinity between Iberian and central European Beaker Complex-associated individuals, and thus exclude migration as a significant mechanism of spread between these two regions. However, human migration did have an important role in the further dissemination of the Beaker Complex, which we document most clearly in Britain using data from 80 newly reported individuals dating to 3900–1200 BCE. British Neolithic farmers were genetically similar to contemporary populations in continental Europe and in particular to Neolithic Iberians, suggesting that a portion of the farmer ancestry in Britain came from the Mediterranean rather than the Danubian route of farming expansion. Beginning with the Beaker period, and continuing through the Bronze Age, all British individuals harboured high proportions of Steppe ancestry and were genetically closely related to Beaker-associated individuals from the Lower Rhine area. We use these observations to show that the spread of the Beaker Complex to Britain was mediated by migration from the continent that replaced >90% of Britain’s Neolithic gene pool within a few hundred years, continuing the process that brought Steppe ancestry into central and northern Europe 400 years earlier.

The roles of migration, admixture and acculturation in the European transition to farming have been debated for over 100 years. Genome-wide ancient DNA studies indicate predominantly Aegean ancestry for continental Neolithic farmers, but also variable admixture with local Mesolithic hunter-gatherers. Neolithic cultures first appear in Britain ca. 4000 BCE, a millennium after they appear in adjacent areas of continental Europe. The pattern and process of this delayed British Neolithic transition remains unclear. We assembled genome-wide data from six Mesolithic and 67 Neolithic individuals found in Britain, dating from 8500-2500 BCE. Our analyses reveal persistent genetic affinities between Mesolithic British and Western European hunter-gatherers. We find overwhelming support for agriculture being introduced to Britain by incoming continental farmers, with small, geographically-structured levels of hunter-gatherer ancestry. Unlike other European Neolithic populations, we detect no resurgence of hunter-gatherer ancestry at any time during the Neolithic in Britain. Genetic affinities with Iberian Neolithic individuals indicate that British Neolithic people were mostly descended from Aegean farmers who followed the Mediterranean route of dispersal. We also infer considerable variation in pigmentation levels in Europe by ca. 6000 BCE.

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

Motivation Genes involved in coordinated biological pathways, including metabolism, drug resistance and virulence, are often collocalised as gene clusters. Identifying homologous gene clusters aids in the study of their function and evolution, however existing tools are limited to searching local sequence databases. Tools for remotely searching public databases are necessary to keep pace with the rapid growth of online genomic data. Results Here, we present cblaster, a Python based tool to rapidly detect collocated genes in local and remote databases. cblaster is easy to use, offering both a command line and a user-friendly graphical user interface (GUI). It generates outputs that enable intuitive visualisations of large datasets, and can be readily incorporated into larger bioinformatic pipelines. cblaster is a significant update to the comparative genomics toolbox. Availability cblaster source code and documentation is freely available from GitHub under the MIT license (github.com/gamcil/cblaster). Supplementary information Supplementary data are available at Bioinformatics Advances online.

Study Design. Retrospective comparative study. Objective. The purpose of this study was to investigate whether preoperative depressive symptoms, measured by mental component score of the Short Form-12 survey (MCS-12), influence patient-reported outcome measurements (PROMs) following an anterior cervical discectomy and fusion (ACDF) surgery for cervical degeneration. Summary of Background Data. There is a paucity of literature regarding preoperative depression and PROMs following ACDF surgery for cervical degenerative disease. Methods. Patients who underwent an ACDF for degenerative cervical pathology were identified. A score of 45.6 on the MCS-12 was used as the threshold for depression symptoms, and patients were divided into two groups based on this value: depression (MCS-12 ≤45.6) and nondepression (MCS-12 >45.6) groups. Outcomes including Neck Disability Index (NDI), physical component score of the Short Form-12 survey (PCS-12), and Visual Analogue Scale Neck (VAS Neck), and Arm (VAS Arm) pain scores were evaluated using independent sample t test, recovery ratios, percentage of patients reaching the minimum clinically important difference, and multiple linear regression – controlling for factors such as age, sex, and BMI. Results. The depression group was found to have significantly worse baseline pain and disability than the nondepression group in NDI (P < 0.001), VAS Neck pain (P < 0.001), and VAS Arm pain (P < 0.001) scores. Postoperatively, both groups improved to a similar amount with surgery based on the recovery ratio analysis. The depression group continued to have worse scores than the nondepression group in NDI (P = 0.010), PCS-12 (P = 0.026), and VAS Arm pain (P = 0.001) scores. Depression was not a significant predictor of change in any PROMs based on regression analysis. Conclusion. Patients who presented with preoperative depression reported more pain and disability symptoms preoperatively and postoperatively; however, both groups achieved similar degrees of improvement. Level of Evidence: 3

We are a group of archaeologists, anthropologists, curators and geneticists representing diverse global communities and 31 countries. All of us met in a virtual workshop dedicated to ethics in ancient DNA research held in November 2020. There was widespread agreement that globally applicable ethical guidelines are needed, but that recent recommendations grounded in discussion about research on human remains from North America are not always generalizable worldwide. Here we propose the following globally applicable guidelines, taking into consideration diverse contexts. These hold that: (1) researchers must ensure that all regulations were followed in the places where they work and from which the human remains derived; (2) researchers must prepare a detailed plan prior to beginning any study; (3)

Abstract

Genes involved in coordinated biological pathways, including metabolism, drug resistance and virulence, are often collocalised as gene clusters. Identifying homologous gene clusters aids in the study of their function and evolution, however existing tools are limited to searching local sequence databases. Tools for remotely searching public databases are necessary to keep pace with the rapid growth of online genomic data. Here, we present cblaster, a Python based tool to rapidly detect collocated genes in local and remote databases. cblaster is easy to use, offering both a command line and a user-friendly graphical user interface (GUI). It generates outputs that enable intuitive visualisations of large datasets, and can be readily incorporated into larger bioinformatic pipelines. cblaster is a significant update to the comparative genomics toolbox. cblaster source code and documentation is freely available from GitHub under the MIT license (github.com/gamcil/cblaster).