Metabarcoding is a powerful tool to investigate community diversity in an economic and efficient way by amplifying a specific gene marker region. With the advancement of long-read sequencing technologies, the field of metabarcoding has entered a new phase.

Despite the importance of Lactobacillus iners and its unique characteristics for the study of vaginal adaption, its genome and genomic researches for identifying molecular backgrounds of these specific phenotypes are still limited. In this study, the first complete genome of L. iners was constructed using a cost-effective long-read sequencing platform, Flongle from Oxford Nanopore, and comparative genome analysis was conducted using a total of 1,046 strain genomes from 10 vaginal Lactobacillus species. Single-molecule sequencing using Flongle effectively resolved the limitation of the 2nd generation sequencing technologies in dealing with genomic regions of high GC contents, and comparative genome analysis identified three potential core genes (INY, ZnuA, and hsdR) of L. iners which was related to its specific adaption to the vaginal environment. In addition, we performed comparative prophage analysis for 1,046 strain genomes to further identify the species specificity. The number of prophages in L. iners genomes was significantly smaller than other vaginal Lactobacillus species, and one of the specific genes (hsdR) was suggested as the means for defense against bacteriophage. The first complete genome of L. iners and the three specific genes identified in this study will provide useful resources to further expand our knowledge of L. iners and its specific adaption to the vaginal econiche.

Simple SummaryChickens have been bred for meat and egg production as a source of animal protein. With the increase of productivity as the main purpose of domestication, factors such as metabolism and immunity were boosted, which are detectable signs of selection on the genome. This study focused on copy number variation (CNV) to find evidence of domestication on the genome. CNV was detected from whole-genome sequencing of 65 chickens including Red Jungle Fowl, broilers, and layers. After that, CNV region, the overlapping region of CNV between individuals, was made to identify which genomic regions showed copy number differentiation. The 663 domesticated-specific CNV regions were associated with various functions such as metabolism and organ development. Also, by performing population differentiation analyses such as clustering analysis and ANOVA test, we found that there are a lot of genomic regions with different copy number patterns between broilers and layers. This result indicates that different genetic variations can be found, depending on the purpose of artificial selection and provides considerations for future animal breeding.AbstractCopy number variation (CNV) has great significance both functionally and evolutionally. Various CNV studies are in progress to find the cause of human disease and to understand the population structure of livestock. Recent advances in next-generation sequencing (NGS) technology have made CNV detection more reliable and accurate at whole-genome level. However, there is a lack of CNV studies on chickens using NGS. Therefore, we obtained whole-genome sequencing data of 65 chickens including Red Jungle Fowl, Cornish (broiler), Rhode Island Red (hybrid), and White Leghorn (layer) from the public databases for CNV region (CNVR) detection. Using CNVnator, a read-depth based software, a total of 663 domesticated-specific CNVRs were identified across autosomes. Gene ontology analysis of genes annotated in CNVRs showed that mainly enriched terms involved in organ development, metabolism, and immune regulation. Population analysis revealed that CN and RIR are closer to each other than WL, and many genes (LOC772271, OR52R1, RD3, ADH6, TLR2B, PRSS2, TPK1, POPDC3, etc.) with different copy numbers between breeds found. In conclusion, this study has helped to understand the genetic characteristics of domestic chickens at CNV level, which may provide useful information for the development of breeding systems in chickens.

Identifying the microbes present in probiotic products is an important issue in product quality control and public health. The most common methods used to identify genera containing species that produce lactic acid are matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and 16S rRNA sequence analysis. However, the high cost of operation, difficulty in distinguishing between similar species, and limitations of the current sequencing technologies have made it difficult to obtain accurate results using these tools. To overcome these problems, a whole-genome shotgun sequencing approach has been developed along with various metagenomic classification tools. Widely used tools include the marker gene and k-mer methods, but their inevitable false-positives (FPs) hampered an accurate analysis. We therefore, designed a coverage-based pipeline to reduce the FP problem and to achieve a more reliable identification of species. The coverage-based pipeline described here not only shows higher accuracy for the detection of species and proportion analysis, based on mapping depth, but can be applied regardless of the sequencing platform. We believe that the coverage-based pipeline described in this study can provide appropriate support for probiotic quality control, addressing current labeling issues.