Identification and Validation of a Core Single-Nucleotide Polymorphism Marker Set for Genetic Diversity Assessment, Fingerprinting Identification, and Core Collection Development in Bottle Gourd

Establishment and application of a SNP molecular identification system in Grifola frondosa

Germplasm resources of edible mushrooms are essential for the breeding of varieties with improved traits. Analysis of the genetic diversity of Grifola frondosa germplasm resources and clarification of the genetic relationships among strains can provide valuable information for the selection of breeding parents. A total of 829,488 high-quality SNP loci were screened from 2,125,382 SNPs obtained by sequencing 60 G. frondose. Phylogenetic analysis, PCA, and population structure analysis based on the high-quality SNPs showed that the 60 strains could be divided into five subgroups, and the clustering results were consistent with the geographical distributions of these strains. Based on high-quality SNP loci, a core collection containing 18 representative germplasm resources was constructed, and 1,473 Kompetitive Allele-Specific PCR markers were obtained. A total of 722 SNP markers in the exonic regions were screened using KASP-genotyping experiments, and 50 candidate SNP markers and 12 core SNP markers were obtained. Genetic fingerprints of G. frondosa germplasm resources were constructed based on the selected SNP markers; these fingerprints provide an accurate, rapid, convenient, and efficient method for the identification of G. frondosa germplasm resources. The results of this study have important implications for the preservation and utilization of G. frondosa germplasm resources and the identification of varieties.

Genome characterization and taxonomy of Actinomyces acetigenes sp. nov., and Actinomyces stomatis sp. nov., previously isolated from the human oral cavity

BACKGROUND

Actinomyces strains are commonly found as part of the normal microflora on human tissue surfaces, including the oropharynx, gastrointestinal tract, and female genital tract. Understanding the diversity and characterization of Actinomyces species is crucial for human health, as they play an important role in dental plaque formation and biofilm-related infections. Two Actinomyces strains ATCC 49340 T and ATCC 51655 T have been utilized in various studies, but their accurate species classification and description remain unresolved.

RESULTS

To investigate the genomic properties and taxonomic status of these strains, we employed both 16S rRNA Sanger sequencing and whole-genome sequencing using the Illumina HiSeq X Ten platform with PE151 (paired-end) sequencing. Our analyses revealed that the draft genome of Actinomyces acetigenes ATCC 49340 T was 3.27 Mbp with a 68.0% GC content, and Actinomyces stomatis ATCC 51655 T has a genome size of 3.08 Mbp with a 68.1% GC content. Multi-locus (atpA, rpoB, pgi, metG, gltA, gyrA, and core genome SNPs) sequence analysis supported the phylogenetic placement of strains ATCC 51655 T and ATCC 49340 T as independent lineages. Digital DNA-DNA hybridization (dDDH), average nucleotide identity (ANI), and average amino acid identity (AAI) analyses indicated that both strains represented novel Actinomyces species, with values below the threshold for species demarcation (70% dDDH, 95% ANI and AAI). Pangenome analysis identified 5,731 gene clusters with strains ATCC 49340 T and ATCC 51655 T possessing 1,515 and 1,518 unique gene clusters, respectively. Additionally, genomic islands (GIs) prediction uncovered 24 putative GIs in strain ATCC 49340 T and 16 in strain ATCC 51655 T, contributing to their genetic diversity and potential adaptive capabilities. Pathogenicity analysis highlighted the potential human pathogenicity risk associated with both strains, with several virulence-associated factors identified. CRISPR-Cas analysis exposed the presence of CRISPR and Cas genes in both strains, indicating these strains might evolve a robust defense mechanism against them.

CONCLUSION

This study supports the classification of strains ATCC 49340 T and ATCC 51655 T as novel species within the Actinomyces, in which the name Actinomyces acetigenes sp. nov. (type strain ATCC 49340 T = VPI D163E-3 T = CCUG 34286 T = CCUG 35339 T) and Actinomyces stomatis sp. nov. (type strain ATCC 51655 T = PK606T = CCUG 33930 T) are proposed.

CoreSNP: an efficient pipeline for core marker profile selection from genome-wide SNP datasets in crops

BACKGROUND

DNA marker profiles play a crucial role in the identification and registration of germplasm, as well as in the distinctness, uniformity, and stability (DUS) testing of new plant variety protection. However, selecting minimal marker sets from large-scale SNP dataset can be challenging to distinguish a maximum number of samples.

RESULTS

Here, we developed the CoreSNP pipeline using a "divide and conquer" strategy and a "greedy" algorithm. The pipeline offers adjustable parameters to guarantee the distinction of each sample pair with at least two markers. Additionally, it allows datasets with missing loci as input. The pipeline was tested in barley, soybean, wheat, rice and maize. A few dozen of core SNPs were efficiently selected in different crops with SNP array, GBS, and WGS dataset, which can differentiate thousands of individual samples. The core SNPs were distributed across all chromosomes, exhibiting lower pairwise linkage disequilibrium (LD) and higher polymorphism information content (PIC) and minor allele frequencies (MAF). It was shown that both the genetic diversity of the population and the characteristics of the original dataset can significantly influence the number of core markers. In addition, the core SNPs capture a certain level of the original population structure.

CONCLUSIONS

CoreSNP is an efficiency way of core marker sets selection based on Genome-wide SNP datasets of crops. Combined with low-density SNP chip or genotyping technologies, it can be a cost-effective way to simplify and expedite the evaluation of genetic resources and differentiate different crop varieties. This tool is expected to have great application prospects in the rapid comparison of germplasm and intellectual property protection of new varieties.

Development of cassava core collections based on morphological and agronomic traits and SNPS markers

Cassava (Manihot esculenta Crantz) holds significant importance as one of the world's key starchy crop species. This study aimed to develop core collections by utilizing both phenotypic data (15 quantitative and 33 qualitative descriptors) and genotypic data (20,023 single-nucleotide polymorphisms) obtained from 1,486 cassava accessions. Six core collections were derived through two optimization strategies based on genetic distances: Average accession-to-nearest-entry and Average entry-to-nearest-entry, along with combinations of phenotypic and genotypic data. The quality of the core collections was evaluated by assessing genetic parameters such as genetic diversity Shannon-Weaver Index, inbreeding (Fis), observed (Ho), and expected (Hs) heterozygosity. While the selection of accessions varied among the six core collections, a seventh collection (consolidated collection) was developed, comprising accessions selected by at least two core collections. Most collections exhibited genetic parameters similar to the complete collection, except for those developed by the Average accession-to-nearest-entry algorithm. However, the variations in the maximum and minimum values of Ho, Hs, and Fis parameters closely resembled the complete collection. The consolidated collection and the collection constructed using genotypic data and the Average entry-to-nearest-entry algorithm (GenEN) retained the highest number of alleles (>97%). Although the differences were not statistically significant (above 5%), the consolidated collection demonstrated a distribution profile and mean trait values most similar to the complete collection, with a few exceptions. The Shannon-Weaver Index of qualitative traits exhibited variations exceeding ±10% when compared to the complete collection. Principal component analysis revealed that the consolidated collection selected cassava accessions with a more uniform dispersion in all four quadrants compared to the other core collections. These findings highlight the development of optimized and valuable core collections for efficient breeding programs and genomic association studies.

Construction of SNP fingerprint and population genetic analysis of honeysuckle germplasm resources in China

INTRODUCTION

The flower buds of Lonicera japonica Thunb. are widely used in Chinese medicine for their anti-inflammatory properties, and they have played an important role in the fight against SARS COVID-19 and other major epidemics. However, due to the lack of scientific and accurate variety identification methods and national unified standards, scattered and non-standardized management in flower bud production has led to mixed varieties that have caused significant difficulties in the cataloging and preservation of germplasm resources and the identification, promotion, and application of new L. japonica varieties.

METHODS

In this study, we evaluated the population structure, genetic relationships, and genetic fingerprints of 39 germplasm resources of Lonicera in China using simplified genome sequencing technology.

RESULTS

A total of 13,143,268 single nucleotide polymorphisms (SNPs) were identified. Thirty-nine samples of Lonicera were divided into four subgroups, and the population structure and genetic relationships among existing Lonicera germplasm resources were determined using principal component analysis, population structure analysis, and phylogenetic tree analysis. Through several stringent selection criteria, 15 additional streamlined, high-quality DNA fingerprints were filtered out of the validated 50 SNP loci and verified as being able to effectively identify the 39 Lonicera varieties.

DISCUSSION

To our knowledge, this is the first comprehensive study measuring the diversity and population structure of a large collection of Lonicera varieties in China. These results have greatly broadened our understanding of the diversity, phylogeny, and population structure of Lonicera. The results may enhance the future analysis of genetic diversity, species identification, property rights disputes, and molecular breeding by providing a scientific basis and reference data for these efforts.

Elucidation of the Flavor Aspects and Flavor-Associated Genomic Regions in Bottle Gourd (Lagenaria siceraria) by Metabolomic Analysis and QTL-seq

Bottle gourd (Lagenaria siceraria) is a commercially important cucurbitaceous vegetable with health-promoting properties whose collections and cultivars differ considerably in their flavor aspects. However, the metabolomic profile related to flavor has not yet been elucidated. In the present study, a comprehensive metabolite analysis revealed the metabolite profile of the strong-flavor collection “J120” and weak-flavor collection “G32”. The major differentially expressed metabolites included carboxylic acids, their derivatives, and organooxygen compounds, which are involved in amino acid biosynthesis and metabolism. QTL-seq was used to identify candidate genomic regions controlling flavor in a MAGIC population comprising 377 elite lines. Three significant genomic regions were identified, and candidate genes likely associated with flavor were screened. Our study provides useful information for understanding the metabolic causes of flavor variation among bottle gourd collections and cultivars. Furthermore, the identified candidate genomic regions may facilitate rational breeding programs to improve bottle gourd quality.