The common bean (Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

Lupin crops provide nutritious seeds as an excellent source of dietary protein. However, extensive genomic resources are needed for crop improvement, focusing on key traits such as nutritional value and climate resiliency, to ensure global food security based on sustainable and healthy diets for all. Such resources can be derived either from related lupin species or crop wild relatives, which represent a large and untapped source of genetic variation for crop improvement. Here, we report genome assemblies of the cross-compatible species Lupinus cosentinii (Mediterranean) and its pan-Saharan wild relative L. digitatus, which are well adapted to drought-prone environments and partially domesticated. We show that both species are tetraploids, and their repetitive DNA content differs considerably from that of the main lupin crops L. angustifolius and L. albus. We present the complex evolutionary process within the rough-seeded lupins as a species-based model involving polyploidization and rediploidization. Our data also provide the foundation for a systematic analysis of genomic diversity among lupin species to promote their exploitation for crop improvement and sustainable agriculture.

High-throughput chromosome conformation capture (Hi-C) is widely used for scaffolding in de novo assembly because it produces highly contiguous genomes, but its indirect statistical approach can introduce connection errors. We employed optical mapping (Bionano Genomics) as an orthogonal scaffolding technology to assess the structural solidity of Hi-C reconstructed scaffolds. Optical maps were used to assess the correctness of five de novo genome assemblies based on long-read sequencing for contig generation and Hi-C for scaffolding. Hundreds of inconsistencies were found between the reconstructions generated using the Hi-C and optical mapping approaches. Manual inspection, exploiting raw long-read sequencing data and optical maps, confirmed that several of these conflicts were derived from Hi-C joining errors. Such misjoins were widespread, involved the connection of both small and large contigs, and even overlapped annotated genes. We conclude that the integration of optical mapping data after, not before, Hi-C-based scaffolding, improves the quality of the assembly and limits reconstruction errors by highlighting misjoins that can then be subjected to further investigation.

In May 2022, an expedition was conducted in the Gobi Desert, Mongolia, to investigate the viral diversity of bats, recognized as reservoirs of emerging zoonotic viruses. Bats were captured in six oases using mist nets and were identified morphologically and molecularly. Fecal samples were collected and screened using molecular protocol targeting viral agents of relevance to human and animal health, including coronaviruses, orthoreoviruses, herpesviruses, adenoviruses, flaviviruses, phleboviruses, paramyxoviruses, pestiviruses, and Influenza A viruses. In total, 74 bats were sampled. The most represented bat genus was Plecotus, followed by Hypsugo, Vespertilio, and Myotis. Coronavirus RNA was detected in eleven samples (14.86%), Mammalian orthoreovirus RNA in two samples (2.70%), and herpesvirus DNA in three samples (4.05%). No other targeted viruses were detected. These data expand our understanding of viral circulation in bats from previously unstudied regions. By expanding our understanding of the viral diversity harbored by bats, this study contributes to ongoing efforts to better characterize their role in the ecology and evolution of emerging zoonotic viruses. Continuous surveillance in remote and biodiverse areas is essential to identify potential threats to public and animal health and to improve preparedness for future viral emergence.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and post-acute infection syndromes (PAIS) are multisystem disorders involving immune, vascular, neuroinflammatory, and metabolic abnormalities, yet the causal relevance of these processes remains unclear. Using genome-wide summary statistics from DecodeME (15,579 cases), we performed genetic correlation, pleiotropic heritability, and Mendelian randomization analyses. Across 22 auxiliary traits spanning five mechanistic domains, cellular energetics, neurovascular regulation, and barrier–microbiome function showed the strongest genetic overlap with ME/CFS, with migraine and irritable bowel syndrome contributing most to shared pleiotropy. Immunothrombotic related and inflammatory traits showed smaller but measurable genetic correlations. Energetics-related traits, including type 2 diabetes and blood lactate, displayed consistent genetic correlation but relatively low shared pleiotropy, suggesting that metabolic dysfunction may act through broader physiological networks. Mendelian randomization identified three biomarkers with evidence for causal effects on ME/CFS risk: higher mitochondrial DNA copy number was protective, whereas increased glycoprotein acetyls and mean platelet volume increased risk. Together, these findings indicate that ME/CFS susceptibility reflects interacting pathways involving barrier–microbiome dysfunction, neurovascular instability, inflammation, platelet activation, and impaired cellular energetics Main Text