CD20/TNFR1 dual-targeting antibody enhances lysosome rupture-mediated cell death in B cell lymphoma.

Obinutuzumab is a therapeutic antibody for B cell non-Hodgkin's Lymphoma (BNHL), which is a glyco-engineered anti-CD20 antibody with enhanced antibody-dependent cellular cytotoxicity (ADCC) and causes binding-induced direct cell death (DCD) through lysosome membrane permeabilization (LMP). Tumour necrosis factor receptor 1 (TNFR1), a pro-inflammatory death receptor, also evokes cell death, partly through lysosomal rupture. As both obinutuzumab- and TNFR1-induced cell deaths are mediated by LMP and combining TNFR1 and obinutuzumab can amplify LMP-mediated cell death, we made dual-targeting antibody for CD20 and TNFR1 to enhance DCD of obinutuzumab.Obinutuzumab treatment-induced CD20 and TNFR1 colocalisation, and TNFR1-overexpressing cells showed increased obinutuzumab-induced DCD. Two targeting modes, anti-CD20/TNFR1 bispecific antibodies (bsAbs), and obinutuzumab-TNFα fusion proteins (OBI-TNFαWT and OBI-TNFαMUT), were designed to cluster CD20 and TNFR1 on the plasma membrane. OBI-TNFαWT and OBI-TNFαMUT showed significantly enhanced LMP, DCD, and ADCC compared with that induced by obinutuzumab. TNFR1 expression is upregulated in many BNHL subtypes compared to that in normal B cells; OBI-TNFαMUT specifically increased DCD and ADCC in a B cell lymphoma cell line overexpressing TNFR1. Further, OBI-TNFαMUT blocked NF-κB activation in the presence of TNF-α, implying that it can antagonise the proliferative role of TNF-α in cancers.Our study suggests that dual targeting of CD20 and TNFR1 can be a new therapeutic strategy for improving BNHL treatment. The OBI-TNFαMUT fusion protein enhances DCD and ADCC and prevents the proliferating effect of TNFα signalling; therefore, it may provide precision treatment for patients with BNHL, especially those with upregulated TNFR1 expression.

SUITOR: Selecting the number of mutational signatures through cross-validation.

For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance.

Integrative molecular characterisation of gallbladder cancer reveals micro-environment-associated subtypes.

BACKGROUND & AIMS: Gallbladder cancer (GBC) is the most common type of biliary tract cancer, but the molecular mechanisms involved in gallbladder carcinogenesis remain poorly understood. In this study, we applied integrative genomics approaches to characterise GBC and explore molecular subtypes associated with patient survival. METHODS: We profiled the mutational landscape of GBC tumours (whole-exome sequencing on 92, targeted sequencing on 98, in total 190 patients). In a subset (n = 45), we interrogated the matched transcriptomes, DNA methylomes, and somatic copy number alterations. We explored molecular subtypes identified through clustering tumours by genes whose expression was associated with survival in 47 tumours and validated subtypes on 34 publicly available GBC cases. RESULTS: Exome analysis revealed TP53 was the most mutated gene. The overall mutation rate was low (median 0.82 Mut/Mb). APOBEC-mediated mutational signatures were more common in tumours with higher mutational burden. Aflatoxin-related signatures tended to be highly clonal (present in ≥50% of cancer cells). Transcriptome-wide survival association analysis revealed a 95-gene signature that stratified all GBC patients into 3 subtypes that suggested an association with overall survival post-resection. The 2 poor-survival subtypes were associated with adverse clinicopathologic features (advanced stage, pN1, pM1), immunosuppressive micro-environments (myeloid-derived suppressor cell accumulation, extensive desmoplasia, hypoxia) and T cell dysfunction, whereas the good-survival subtype showed the opposite features. CONCLUSION: These data suggest that the tumour micro-environment and immune profiles could play an important role in gallbladder carcinogenesis and should be evaluated in future clinical studies, along with mutational profiles. LAY SUMMARY: Gallbladder cancer is highly fatal, and its causes are poorly understood. We evaluated gallbladder tumours to see if there were differences between tumours in genetic information such as DNA and RNA. We found evidence of aflatoxin exposure in these tumours, and immune cells surrounding the tumours were associated with survival.

A test of homogeneity of distributions when observations are subject to measurement errors.

When the observed data are contaminated with errors, the standard two-sample testing approaches that ignore measurement errors may produce misleading results, including a higher type-I error rate than the nominal level. To tackle this inconsistency, a nonparametric test is proposed for testing equality of two distributions when the observed contaminated data follow the classical additive measurement error model. The proposed test takes into account the presence of errors in the observed data, and the test statistic is defined in terms of the (deconvoluted) characteristic functions of the latent variables. Proposed method is applicable to a wide range of scenarios as no parametric restrictions are imposed either on the distribution of the underlying latent variables or on the distribution of the measurement errors. Asymptotic null distribution of the test statistic is derived, which is given by an integral of a squared Gaussian process with a complicated covariance structure. For data-based calibration of the test, a new nonparametric Bootstrap method is developed under the two-sample measurement error framework and its validity is established. Finite sample performance of the proposed test is investigated through simulation studies, and the results show superior performance of the proposed method than the standard tests that exhibit inconsistent behavior. Finally, the proposed method was applied to real data sets from the National Health and Nutrition Examination Survey. An R package MEtest is available through CRAN.

GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies.

BACKGROUND: Seed location filtering is critical in DNA read mapping, a process where billions of DNA fragments (reads) sampled from a donor are mapped onto a reference genome to identify genomic variants of the donor. State-of-the-art read mappers 1) quickly generate possible mapping locations for seeds (i.e., smaller segments) within each read, 2) extract reference sequences at each of the mapping locations, and 3) check similarity between each read and its associated reference sequences with a computationally-expensive algorithm (i.e., sequence alignment) to determine the origin of the read. A seed location filter comes into play before alignment, discarding seed locations that alignment would deem a poor match. The ideal seed location filter would discard all poor match locations prior to alignment such that there is no wasted computation on unnecessary alignments. RESULTS: We propose a novel seed location filtering algorithm, GRIM-Filter, optimized to exploit 3D-stacked memory systems that integrate computation within a logic layer stacked under memory layers, to perform processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1) introducing a new representation of coarse-grained segments of the reference genome, and 2) using massively-parallel in-memory operations to identify read presence within each coarse-grained segment. Our evaluations show that for a sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false negative rate of filtering by 5.59x-6.41x, and 2) provides an end-to-end read mapper speedup of 1.81x-3.65x, compared to a state-of-the-art read mapper employing the best previous seed location filtering algorithm. CONCLUSION: GRIM-Filter exploits 3D-stacked memory, which enables the efficient use of processing-in-memory, to overcome the memory bandwidth bottleneck in seed location filtering. We show that GRIM-Filter significantly improves the performance of a state-of-the-art read mapper. GRIM-Filter is a universal seed location filter that can be applied to any read mapper. We hope that our results provide inspiration for new works to design other bioinformatics algorithms that take advantage of emerging technologies and new processing paradigms, such as processing-in-memory using 3D-stacked memory devices.

Phosphorylation of the Plant Immune Regulator RPM1-INTERACTING PROTEIN4 Enhances Plant Plasma Membrane H⁺-ATPase Activity and Inhibits Flagellin-Triggered Immune Responses in Arabidopsis.

The Pseudomonas syringae effector AvrB targets multiple host proteins during infection, including the plant immune regulator RPM1-INTERACTING PROTEIN4 (RIN4) and RPM1-INDUCED PROTEIN KINASE (RIPK). In the presence of AvrB, RIPK phosphorylates RIN4 at Thr-21, Ser-160, and Thr-166, leading to activation of the immune receptor RPM1. Here, we investigated the role of RIN4 phosphorylation in susceptible Arabidopsis thaliana genotypes. Using circular dichroism spectroscopy, we show that RIN4 is a disordered protein and phosphorylation affects protein flexibility. RIN4 T21D/S160D/T166D phosphomimetic mutants exhibited enhanced disease susceptibility upon surface inoculation with P. syringae, wider stomatal apertures, and enhanced plasma membrane H(+)-ATPase activity. The plasma membrane H(+)-ATPase AHA1 is highly expressed in guard cells, and its activation can induce stomatal opening. The ripk knockout also exhibited a strong defect in pathogen-induced stomatal opening. The basal level of RIN4 Thr-166 phosphorylation decreased in response to immune perception of bacterial flagellin. RIN4 Thr166D lines exhibited reduced flagellin-triggered immune responses. Flagellin perception did not lower RIN4 Thr-166 phosphorylation in the presence of strong ectopic expression of AvrB. Taken together, these results indicate that the AvrB effector targets RIN4 in order to enhance pathogen entry on the leaf surface as well as dampen responses to conserved microbial features.

Frequentist Standard Errors of Bayes Estimators.

Frequentist standard errors are a measure of uncertainty of an estimator, and the basis for statistical inferences. Frequestist standard errors can also be derived for Bayes estimators. However, except in special cases, the computation of the standard error of Bayesian estimators requires bootstrapping, which in combination with Markov chain Monte Carlo (MCMC) can be highly time consuming. We discuss an alternative approach for computing frequentist standard errors of Bayesian estimators, including importance sampling. Through several numerical examples we show that our approach can be much more computationally efficient than the standard bootstrap.

Fast and accurate mapping of Complete Genomics reads.

Many recent advances in genomics and the expectations of personalized medicine are made possible thanks to power of high throughput sequencing (HTS) in sequencing large collections of human genomes. There are tens of different sequencing technologies currently available, and each HTS platform have different strengths and biases. This diversity both makes it possible to use different technologies to correct for shortcomings; but also requires to develop different algorithms for each platform due to the differences in data types and error models. The first problem to tackle in analyzing HTS data for resequencing applications is the read mapping stage, where many tools have been developed for the most popular HTS methods, but publicly available and open source aligners are still lacking for the Complete Genomics (CG) platform. Unfortunately, Burrows-Wheeler based methods are not practical for CG data due to the gapped nature of the reads generated by this method. Here we provide a sensitive read mapper (sirFAST) for the CG technology based on the seed-and-extend paradigm that can quickly map CG reads to a reference genome. We evaluate the performance and accuracy of sirFAST using both simulated and publicly available real data sets, showing high precision and recall rates.

Two serine residues in Pseudomonas syringae effector HopZ1a are required for acetyltransferase activity and association with the host co-factor.

Gram-negative bacteria inject type III secreted effectors (T3SEs) into host cells to manipulate the immune response. The YopJ family effector HopZ1a produced by the plant pathogen Pseudomonas syringae possesses acetyltransferase activity and acetylates plant proteins to facilitate infection. Using mass spectrometry, we identified a threonine residue, T346, as the main autoacetylation site of HopZ1a. Two neighboring serine residues, S349 and S351, are required for the acetyltransferase activity of HopZ1a in vitro and are indispensable for the virulence function of HopZ1a in Arabidopsis thaliana. Using proton nuclear magnetic resonance (NMR), we observed a conformational change of HopZ1a in the presence of inositol hexakisphosphate (IP6), which acts as a eukaryotic co-factor and significantly enhances the acetyltransferase activity of several YopJ family effectors. S349 and S351 are required for IP6-binding-mediated conformational change of HopZ1a. S349 and S351 are located in a conserved region in the C-terminal domain of YopJ family effectors. Mutations of the corresponding serine(s) in two other effectors, HopZ3 of P. syringae and PopP2 of Ralstonia solanacerum, also abolished their acetyltransferase activity. These results suggest that, in addition to the highly conserved catalytic residues, YopJ family effectors also require conserved serine(s) in the C-terminal domain for their enzymatic activity.

Practical approach to determine sample size for building logistic prediction models using high-throughput data.

An empirical method of sample size determination for building prediction models was proposed recently. Permutation method which is used in this procedure is a commonly used method to address the problem of overfitting during cross-validation while evaluating the performance of prediction models constructed from microarray data. But major drawback of such methods which include bootstrapping and full permutations is prohibitively high cost of computation required for calculating the sample size. In this paper, we propose that a single representative null distribution can be used instead of a full permutation by using both simulated and real data sets. During simulation, we have used a dataset with zero effect size and confirmed that the empirical type I error approaches to 0.05. Hence this method can be confidently applied to reduce overfitting problem during cross-validation. We have observed that pilot data set generated by random sampling from real data could be successfully used for sample size determination. We present our results using an experiment that was repeated for 300 times while producing results comparable to that of full permutation method. Since we eliminate full permutation, sample size estimation time is not a function of pilot data size. In our experiment we have observed that this process takes around 30min. With the increasing number of clinical studies, developing efficient sample size determination methods for building prediction models is critical. But empirical methods using bootstrap and permutation usually involve high computing costs. In this study, we propose a method that can reduce required computing time drastically by using representative null distribution of permutations. We use data from pilot experiments to apply this method for designing clinical studies efficiently for high throughput data.

Inhibitory effect of corn silk on skin pigmentation.

In this study, the inhibitory effect of corn silk on melanin production was evaluated. This study was performed to investigate the inhibitory effect of corn silk on melanin production in Melan-A cells by measuring melanin production and protein expression. The corn silk extract applied on Melan-A cells at a concentration of 100 ppm decreased melanin production by 37.2% without cytotoxicity. This was a better result than arbutin, a positive whitening agent, which exhibited a 26.8% melanin production inhibitory effect at the same concentration. The corn silk extract did not suppress tyrosinase activity but greatly reduced the expression of tyrosinase in Melan-A cells. In addition, corn silk extract was applied to the human face with hyperpigmentation, and skin color was measured to examine the degree of skin pigment reduction. The application of corn silk extract on faces with hyperpigmentation significantly reduced skin pigmentation without abnormal reactions. Based on the results above, corn silk has good prospects for use as a material for suppressing skin pigmentation.

Entosis: the core mechanism and crosstalk with other cell death programs.

Cell death pathways play critical roles in organism development and homeostasis as well as in the pathogenesis of various diseases. While studies over the last decade have elucidated numerous different forms of cell death that can eliminate cells in various contexts, how certain mechanisms impact physiology is still not well understood. Moreover, recent studies have shown that multiple forms cell death can occur in a cell population, with different forms of death eliminating individual cells. Here, we aim to describe the known molecular mechanisms of entosis, a non-apoptotic cell engulfment process, and discuss signaling mechanisms that control its induction as well as its possible crosstalk with other cell death mechanisms.

Pan-cancer mutational signature analysis of 111,711 targeted sequenced tumors using SATS.

Tumor mutational signatures have the potential to inform cancer diagnosis and treatment. However, their detection in targeted sequenced tumors is hampered by sparse mutations and variability in targeted gene panels. Here we present SATS, a scalable mutational signature analyzer addressing these challenges by leveraging tumor mutational burdens from targeted gene panels. Through analyzing simulated data, pseudo-targeted sequencing data generated by down-sampling whole exome and genome data, and samples with matched whole genome sequencing and targeted sequencing, we showed that SATS can accurately detect common mutational signatures and estimate signature burdens. Applying SATS to 111,711 targeted sequenced tumors from the AACR Project GENIE, we generated a pan-cancer catalogue of mutational signatures tailored to targeted sequencing, enabling estimation of signature burdens within individual tumors. Integrating signatures with clinical data, we demonstrated SATS's clinical utility, including identifying signatures enriched in early-onset hypermutated colorectal cancers and signatures associated with cancer prognosis and immunotherapy response.

Accelerating read mapping with FastHASH.

With the introduction of next-generation sequencing (NGS) technologies, we are facing an exponential increase in the amount of genomic sequence data. The success of all medical and genetic applications of next-generation sequencing critically depends on the existence of computational techniques that can process and analyze the enormous amount of sequence data quickly and accurately. Unfortunately, the current read mapping algorithms have difficulties in coping with the massive amounts of data generated by NGS.We propose a new algorithm, FastHASH, which drastically improves the performance of the seed-and-extend type hash table based read mapping algorithms, while maintaining the high sensitivity and comprehensiveness of such methods. FastHASH is a generic algorithm compatible with all seed-and-extend class read mapping algorithms. It introduces two main techniques, namely Adjacency Filtering, and Cheap K-mer Selection.We implemented FastHASH and merged it into the codebase of the popular read mapping program, mrFAST. Depending on the edit distance cutoffs, we observed up to 19-fold speedup while still maintaining 100% sensitivity and high comprehensiveness.

Phylogeography and genetic diversity of East Asian Neolitsea sericea (Lauraceae) based on variations in chloroplast DNA sequences.

Neolitsea sericea is an evergreen broad leaved tree in the warm-temperate regions of East Asia. This area is a hotspot for plant species richness and endemism caused by dynamic changes in land configuration during the Quaternary. However, the historical migration of such evergreen tree species is still poorly understood. In an attempt to reconstruct the phylogeographic history of N. sericea during the Quaternary, we identified the chloroplast DNA haplotypes of 287 individuals from 33 populations covering almost all of its geographic range. Analyses were based on sequence data from the trnL-F, psbC-trnS, and rps16 regions. Nine haplotypes were identified. The majority included ancestral types in the southwestern part of the main islands of Japan, with other region-specific haplotypes being found in populations on the Korean Peninsula, Taiwan (Isl. Lanyu), and elsewhere in Japan. A statistical parsimony network revealed two lineages derived from Japanese main islands. One was represented on the Korean Peninsula, the other on Isl. Lanyu. The current distribution of N. sericea has been shaped by colonization via land bridges. During the glacial periods, two primary, but separate migration routes were followed--from the southwestern part of the Japanese main islands to either the Korean Peninsula or Taiwan. In addition, we believe the Zhoushan populations were shaped by post-glacial processes through an ECS land bridge (East China Sea basin) from northern refugia that existed during the late Pleistocene.

Purification and Detection of Ubiquitinated Plant Proteins Using Tandem Ubiquitin Binding Entities.

The timing and amplitude of plant signaling are frequently regulated through posttranslational modification of key signaling sectors, which facilitates rapid and flexible responses. Protein ubiquitination can serve as a degradation marker, influence subcellular localization, alter protein-protein interactions, and affect protein activity. Identification of polyubiquitinated proteins has been challenging due to their rapid degradation by the proteasome or removal of modifications by deubiquitination enzymes (DUBs). Tandem ubiquitin binding entities (TUBEs) are based on ubiquitin-associated domains and protect against both proteasomal degradation and DUBs. Here, we provide a protocol for purification of ubiquitinated plant proteins using TUBEs after transient expression in Nicotiana benthamiana. This protocol can also be applied to other plants to purify multiple ubiquitinated proteins or track ubiquitination of a target protein. This methodology provides an effective method for identification of ubiquitin ligase substrates and can be coupled with TUBEs targeting specific ubiquitination linkages.

Nitrated Polycyclic Aromatic Hydrocarbon (Nitro-PAH) Signatures and Somatic Mutations in Diesel Exhaust-Exposed Bladder Tumors.

BACKGROUND: Diesel exhaust is a complex mixture, including polycyclic aromatic hydrocarbons (PAH) and nitrated PAHs (nitro-PAH), many of which are potent mutagens and possible bladder carcinogens. To explore the association between diesel exposure and bladder carcinogenesis, we examined the relationship between exposure and somatic mutations and mutational signatures in bladder tumors. METHODS: Targeted sequencing was conducted in bladder tumors from the New England Bladder Cancer Study. Using data on 797 cases and 1,418 controls, two-stage polytomous logistic regression was used to evaluate etiologic heterogeneity between bladder cancer subtypes and quantitative, lifetime estimates of respirable elemental carbon (REC), a surrogate for diesel exposure. Poisson regression was used to evaluate associations between REC and mutational signatures. RESULTS: We observed significant heterogeneity in the diesel-bladder cancer risk relationship, with a strong positive association among cases with high-grade, nonmuscle invasive TP53-mutated tumors compared with controls [ORTop Tertile vs.Unexposed, 4.8; 95% confidence interval (CI), 2.2-10.5; Ptrend < 0.001; Pheterogeneity = 0.002]. In muscle-invasive tumors, we observed a positive association between diesel exposure and the nitro-PAH signatures of 1,6-dintropyrene (RR, 1.93; 95% CI, 1.28-2.92) and 3-nitrobenzoic acid (RR, 1.97; 95% CI, 1.33-2.92). CONCLUSIONS: The relationship between diesel exhaust and bladder cancer was heterogeneous based on the presence of TP53 mutations in tumors, further supporting the link between PAH exposure and TP53 mutations in carcinogenesis. Future studies that can identify nitro-PAH signatures in exposed tumors are warranted to add human data supporting the link between diesel and bladder cancer. IMPACT: This study provides additional insight into the etiology and possible mechanisms related to diesel exhaust-induced bladder cancer.

Nontargeted metabolomics approach for age differentiation and structure interpretation of age-dependent key constituents in hairy roots of Panax ginseng.

The age of the ginseng plant has been considered as an important criterion to determine the quality of this species. For age differentiation and structure interpretation of age-dependent key constituents of Panax ginseng, hairy root (fine root) extracts aged from four to six years were analyzed using a nontargeted approach with ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS). Various classification methods were used to determine an optimal method to best describe ginseng age by selecting influential metabolites of different ages. Through the metabolite selection process, several age-dependent key constituents having the potential to be biomarkers were determined, and their structures were identified according to tandem mass spectrometry and accurate mass spectrometry by comparing them with an in-house ginsenoside library and with literature data. This proposed method applied to the hairy roots of P. ginseng showed an improved efficiency of age differentiation when compared to previous results on the main roots and increases the possibility of the identification of key metabolites that can be used as biomarker candidates for quality assurance in ginseng.

LC-MS-based chemotaxonomic classification of wild-type Lespedeza sp. and its correlation with genotype.

In this study, 39 specimens belonging to Lespedeza species (Lespedeza cyrtobotrya, L. bicolor, L. maximowiczii, and Lespedeza cuneata) (Leguminosae) were classified phenotypically and genotypically. We constructed a phylogenetic tree based on the combined nrDNA (internal transcribed spacer; ITS) and cpDNA (trnL-trnF) sequences with the aim of classifying the genotypes. Samples were mainly divided into three genotypes. Samples of L. cyrtobotrya and L. bicolor were mixed in a single branch, whereas samples of L. maximowiczii and L. cuneata were clustered within species, respectively. We performed a liquid chromatography-electrospray ionization-mass spectrometry-based metabolite profiling analysis to classify the phenotypes. Multivariate statistical analyses such as principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used for the clustering pattern analysis and distance analysis between species, respectively. According to the PCA and HCA results, leaves were classified into four phenotypes according to species. In both the genetic and chemotaxonomic classification methods, the distance between L. cyrtobotrya and L. bicolor was the closest between species, and L. cuneata was the farthest away from the other three species. Additionally, orthogonal partial least squares-discriminant analysis was employed to identify significantly different phytochemicals between species. We classified L. cyrtobotrya and L. bicolor by identifying significantly different phytochemicals. Interestingly, leaves and stems showed different phenotypic classifications based on the chemotaxonomic classification. Stem samples of the other three species were mixed regardless of species, whereas L. cyrtobotrya stem samples were clustered within species. The phenotypic classification of leaves coincided more with the genotypic classification than that of stems. Key message We classified four wild-type Lespedeza sp. by analyzing the combined nrDNA (ITS) and cpDNA (trnL-trnF) sequences. We also classified leaves and stems of Lespedeza sp. by applying liquid chromatography-mass spectroscopy-based metabolite profiling.

Isolation and characterization of 13 microsatellite loci from a Korean Endemic Species, Sophora koreensis (Fabaceae).

To evaluate the population genetics structure as a means of devising conservation strategies, we developed microsatellite primers for Sophora koreensis, a narrowly endemic and endangered species in Korea. Thirteen polymorphic microsatellite markers were developed in Korean populations of S. koreensis. Genetic diversity was analyzed in 40 individuals from two populations. The number of alleles per locus ranged from 4 to 14, with observed and expected heterozygosities ranging from 0.200 to 1.000 and from 0.189 to 0.864, respectively. The microsatellite markers described here are valuable tools for the population genetics research of S. koreensis. They can be used to obtain information for creating suitable management strategies to conserve this endemic and endangered species.