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At present, many infectious pathogens, especially emerging/re-emerging pathogens, exist in the blood of voluntary blood donors and may be transmitted through blood transfusions. However, most of Chinese blood centers only routinely screen for HBV, HCV, HIV, and syphilis. We employed metagenomic next-generation sequencing (mNGS) to investigate the microbiome in healthy voluntary blood donors to help assess blood safety in China by identifying infectious pathogens presented in donations that could lead to transfusion-acquired infections. We collected 10,720 plasma samples from voluntary blood donors from seven blood centers in different cities during 2012–2018 in China. A total of 562 GB of clean data was obtained. By analyzing the sequencing data, it was found that the most commonly identified bacteria found in the healthy blood were Serratia spp. (5.0176%), Pseudomonas spp. (0.6637%), and Burkholderia spp. (0.5544%). The principal eukaryote were Leishmania spp (1.3723%), Toxoplasma gondii (0.6352%), and Candida dubliniensis (0.1848%). Among viruses, Human Parvovirus B19 (B19V) accounts for the highest proportion (0.1490%), followed by Torque teno midi virus (0.0032%) and Torque teno virus (0.0015%). Since that B19V is a non-negligible threat to blood safety, we evaluated the positive samples for B19V tested by mNGS using quantitative polymerase chain reaction, Sanger sequencing, and phylogenetic analysis to achieve a better understanding of B19V in Chinese blood donors. Subsequently, 9 (0.07%) donations were positive for B19V DNA. The quantitative DNA levels ranged from 5.58 × 102 to 7.24 × 104 IU/ml. The phylogenic analyses showed that prevalent genotypes belonged to the B19-1A subtype, which disclosed previously unknown regional variability in the B19V positivity rate. The investigation revealed that many microbes dwell in the blood of healthy donors, including some pathogens that may be dormant in the blood and only cause disease under specific conditions. Thus, investigating the range and nature of potential pathogens in the qualified donations provided a framework for targeted interventions to help prevent emerging and re-emerging infectious diseases.

Protection of populations comprising admixed genomes is a challenge under the Endangered Species Act (ESA), which is regarded as the most powerful species protection legislation ever passed in the United States but lacks specific provisions for hybrids. The eastern wolf is a newly recognized wolf-like species that is highly admixed and inhabits the Great Lakes and eastern United States, a region previously thought to be included in the geographic range of only the gray wolf. The U.S. Fish and Wildlife Service has argued that the presence of the eastern wolf, rather than the gray wolf, in this area is grounds for removing ESA protection (delisting) from the gray wolf across its geographic range. In contrast, the red wolf from the southeastern United States was one of the first species protected under the ESA and was protected despite admixture with coyotes. We use whole-genome sequence data to demonstrate a lack of unique ancestry in eastern and red wolves that would not be expected if they represented long divergent North American lineages. These results suggest that arguments for delisting the gray wolf are not valid. Our findings demonstrate how a strict designation of a species under the ESA that does not consider admixture can threaten the protection of endangered entities. We argue for a more balanced approach that focuses on the ecological context of admixture and allows for evolutionary processes to potentially restore historical patterns of genetic variation.

The golden jackal of Africa (Canis aureus) has long been considered a conspecific of jackals distributed throughout Eurasia, with the nearest source populations in the Middle East. However, two recent reports found that mitochondrial haplotypes of some African golden jackals aligned more closely to gray wolves (Canis lupus), which is surprising given the absence of gray wolves in Africa and the phenotypic divergence between the two species. Moreover, these results imply the existence of a previously unrecognized phylogenetically distinct species despite a long history of taxonomic work on African canids. To test the distinct-species hypothesis and understand the evolutionary history that would account for this puzzling result, we analyzed extensive genomic data including mitochondrial genome sequences, sequences from 20 autosomal loci (17 introns and 3 exon segments), microsatellite loci, X- and Y-linked zinc-finger protein gene (ZFX and ZFY) sequences, and whole-genome nuclear sequences in African and Eurasian golden jackals and gray wolves. Our results provide consistent and robust evidence that populations of golden jackals from Africa and Eurasia represent distinct monophyletic lineages separated for more than one million years, sufficient to merit formal recognition as different species: C. anthus (African golden wolf) and C. aureus (Eurasian golden jackal). Using morphologic data, we demonstrate a striking morphologic similarity between East African and Eurasian golden jackals, suggesting parallelism, which may have misled taxonomists and likely reflects uniquely intense interspecific competition in the East African carnivore guild. Our study shows how ecology can confound taxonomy if interspecific competition constrains size diversification.

Macaques (genus Macaca) are the most widely distributed non‐human primates, and their evolutionary history, gene expression profiles, and genetic differences have been extensively studied. However, the DNA methylomes of macaque species are not available in public databases, which hampers understanding of epigenetic differences among macaque species. Epigenetic modifications can potentially affect development, physiology, behavior, and evolution. Here, we investigated the methylation patterns of the Tibetan macaque (M. thibetana; TM), Chinese rhesus macaque (M. mulatta lasiota; CR), and crab‐eating macaque (M. fascicularis; CE) through whole‐genome bisulfite sequencing from peripheral blood. We compared genome‐wide methylation site information for the three species. We identified 12,128 (CR vs. CE), 59,165 (CR vs. TM), and 39,751 (CE vs. TM) differentially methylated regions (DMRs) in the three macaques. Furthermore, we obtained the differentially expressed genes (DEGs) among the three macaque species. The differences between CR and CE were smaller at both the methylome and transcriptome levels than compared with TM (CR vs. TM and CE vs. TM). We also found a change in the density of single nucleotide mutations in DMRs relative to their flanking regions, indicating a potential mechanism through which genomic alterations may modulate methylation landscapes, thereby influencing the transcriptome. Functional enrichment analyses showed the DMR‐related genes were enriched in developmental processes and neurological functions, such as the growth hormone‐related pathway, insulin secretion pathway, thyroid hormone synthesis pathway, morphine addiction, and GABAergic synapses. These differences may be associated with variations in physiology and habitat among the macaques. Our study provides one of the first genome‐wide comparisons of genetic, gene expression, and epigenetic variations across different macaques. Our results should facilitate further research on comparative genomic and genetic differences in macaque species. [ABSTRACT FROM AUTHOR]

FASTA and FASTQ are the most widely used biological data formats that have become the de facto standard to exchange sequence data between bioinformatics tools. With the avalanche of next-generation sequencing data, the amount of sequence data being deposited and accessed in FASTA/Q formats is increasing dramatically. However, the existing tools have very low efficiency at random retrieval of subsequences due to the requirement of loading the entire index into memory. In addition, most existing tools have no capability to build index for large FASTA/Q files because of the limited memory. Furthermore, the tools do not provide support to randomly accessing sequences from FASTA/Q files compressed by gzip, which is extensively adopted by most public databases to compress data for saving storage. In this study, we developed pyfastx as a versatile Python package with commonly used command-line tools to overcome the above limitations. Compared to other tools, pyfastx yielded the highest performance in terms of building index and random access to sequences, particularly when dealing with large FASTA/Q files with hundreds of millions of sequences. A key advantage of pyfastx over other tools is that it offers an efficient way to randomly extract subsequences directly from gzip compressed FASTA/Q files without needing to uncompress beforehand. Pyfastx can easily be installed from PyPI (https://pypi.org/project/pyfastx) and the source code is freely available at https://github.com/lmdu/pyfastx. [ABSTRACT FROM AUTHOR]