This study was undertaken to investigate the genetic characteristics of Berkshire (BS), Landrace (LR), and Yorkshire (YS) pig breeds raised in the Great Grandparents pig farms using the single nucleotide polymorphisms (SNP) information.HE), polymorphism information content, F-statistics (FST), linkage disequilibrium (LD) and effective population size (Ne).A total of 25,921 common SNP genotype markers in three pig breeds were used to estimate the expected heterozygosity  for the BS, LR, and YS breeds was estimated to be approximately 0.41. This study also found an average Ne of 19.9 (BS), 31.4 (LR), and 34.1 (YS) over the last 5th generations. The effective population size for the BS, LR, and YS breeds decreased at a consistent rate from 50th to 10th generations ago. With a relatively faster Ne decline rate in the past 10th generations, there exists possible evidence for intensive selection practices in pigs in the recent past.The chromosome-wise distribution of To develop customized chips for the genomic selection of various breeds, it is important to select and utilize SNP based on the genetic characteristics of each breed. Since the improvement efficiency of breed pigs increases sharply by the population size, it is important to increase test units for the improvement and it is desirable to establish the pig improvement network system to expand the unit of breed pig improvement through the genetic connection among breed pig farms. An investigation of the genetic architecture is the first important step towards genomic selection for the improvement of pig breeds. Today, the genetic information on breeding pigs has been accumulating. If the reference population is entirely established in the future, genomic selection can be possible and used to increase selection accuracy through the use of genomic and phenotypic data along with pedigree information .A comprehensive information on the genetic diversity and introgression is essential for an improvement of national breeding as well as the design of conservation programs. In the past, the genetic diversity in pigs was mostly reported using information on both microsatellite markers ,3 and mtLinkage disequilibrium (LD), on the other hand, existing within population could assist in determining the relationship among the SNPs which affect the economic traits, mapping the quantitative trait locus (QTL), and selecting the tagging SNP. Additionally, the LD between SNP among specific physical distance can be used to estimate the effective population size, and to identify the genetic diversity through genetic characteristics . FurtherThis experiment was conducted to investigate the genetic characteristics and effective population sizes of Berkshire, Landrace, and Yorkshire pig breeds raised in the great grandparent (GGP) farms using the SNP information.A total of 3,710 pigs of consisting of the Berkshire , Landrace , and Yorkshire  were genotyped using Porcine SNP 60k and 61,565 SNP were collected.−6) of Hardy-Weinberg disequilibrium chi-squared value, and animals with more than 10% of SNP missing rate were excluded from the analysis.To ensure the quality of the genotypic data, SNP on the sex chromosomes, SNP without information on chromosome, SNP with higher than 10% of missing rate, SNP without polymorphism , SNP with less than 1% of minor allele frequency and SNP with more than 23.93  after quality control in Berkshire, Landrace and Yorkshire were 1,585 , 1,038 , and 1,035  pigs, respectively. In this study, only the 25,921 common SNPs among three breeds were used for analyses.HE) of a locus is defined as the probability that an individual is heterozygous in the population.The expected heterozygosity  refers to the value of a marker for detecting polymorphism with a population, depending on the number of detectable alleles and the distribution of their frequency .n is the total number of alleles, pi and pj are frequency of the ith and jth alleles in the population, respectively [where ectively . The PICectively .The F-statistics were used for comparing the genetic characteristics among the breeds.F is the correlation of genes within individuals, Ø is the correlation of genes of different individuals in the same population, and f is the correlation of genes within individuals within populations. These parameters are related to Wright’s F-statistics [F = FIT, Ø = FST, f = FIS.where atistics  as: F = FIT represents the degree of genetic fixation of a breed, FIS represents the degree of inbreeding of individuals in a population, and FST indicates the degree of genetic segregation of the populations. By using F-statistics, paired t-tests analyses with entirely SNP among breeds were performed.For F-statistics, Linkage disequilibrium:2 [2, which is less dependent on allele frequencies.The LD between SNP pairs was used to calculate the standardized LD value D′  and r2 [2 . But, D′2 [2. The measure of LD was expressed as the square (r2) of the correlation coefficient between SNP pairs, and was calculated between each allele at locus A and each allele at locus B [r2) was calculated by the formula:The amount of LD is the value for the linkage between two different alleles and can be estimated by the standardized D (D′)  or r2 [22 . However locus B . The corPAB–PAPB and PA, Pa, PB, and Pb are the frequencies of alleles A, a, B, and b, respectively. PAB is the frequency of the genotype AB.where D = 1B1/A2B2) and repulsion (A1B2/A2B1) by the DNA chip analysis. Therefore, using the EM algorithm [1B1/A2B2) and repulsion (A1B2/A2B1) were calculated and the value of LD was estimated through the repeated arithmetic calculation until the amount of change reaches less than 10−5 [Haplotypes within haploblocks were obtained using the expectation maximization (EM) algorithm, similar to the partition/ligation . When thlgorithm  that dethan 10−5 .Effective population size:Ne at recent generations [The effective population size was determined based on a simple expectation from the amount of LD and a given chromosome segment. Since LD breaks down more rapidly over the generations for loci that are further apart, LD at large distances reflects erations .Ne is the effective population size t generations ago, c is the recombination distance between the SNP in Morgan, c = (1/2t), r2 for markers that are c Morgan apart. It was assumed that 1 cM of physical distance and 1 Mb of genetic distance were identical.where, HE estimates. The estimates of the average HE in the Berkshire, Landrace, and Yorkshire were 0.33±0.15, 0.36±0.14, and 0.36±0.14, respectively. While the estimates of the average HE were low in Berkshire, they were the same in Landrace and Yorkshire. Ai et al [HE were found to be highest in Sus scrofa chromosome 6 (SSC6 (0.36±0.15) of Berkshire, SSC18 (0.38±0.12) of Landrace, and SSC14 (0.38± 0.13) and SSC16 (0.38±0.13) of Yorkshire. On the other hand, the lowest HE estimates, in contrast, were found in SSC15 (0.29± 0.16), SSC10 (0.34±0.13), and SSC1 (0.34±0.14) in Berkshire, Landrace, and Yorkshire pigs  of Berkshire, SSC18 (0.30± 0.08) of Landrace, and SSC14 and 16 (0.30±0.09) of Yorkshire. On the other hand, the lowest values of PIC were observed for SSC15 (0.23±0.12) in Berkshire, for SSC10 (0.27±0.09) in Landrace, and for SSC1 (0.27±0.10) in Yorkshire. Overall, the estimates of PIC were lower than those of the average HE .HE and PIC in each breed, pairwise t-tests were performed, across the breeds.Using the estimates of the average HE estimates, there was no significant (p<0.05) difference in SSC1 and SSC8 in the comparison between Berkshire and Landrace, and in SSC6 and SSC8 in the comparison between Berkshire and Yorkshire, and in SSC2, SSC3, SSC8, SSC10, SSC12, SSC15, and SSC17 in the comparison between Landrace and Yorkshire. For the PIC estimates of the average, there was no significant (p<0.05) difference in SSC1 and SSC8 in the comparison between Berkshire and Landrace, and in SSC6 and SSC8 in the comparison between Berkshire and Yorkshire, and in SSC1, SSC2, SSC3, SSC8, SSC10, SSC12, and SSC17 in the comparison between Landrace and Yorkshire , highest in Landrace breed (0.42±0.22), while that of Yorkshire breed was reported to be 0.35±0.17. The results of this study were consistent with those of the study [However, the pairwise t-tests using all SNP revealed significant differences (p<0.01) in the estimates of the average e breeds . Accordihe study , and theFST by chromosome among breeds were in the range of 0 to 0.36, and the distributions of FST for chromosome-wise SNP were shown FST among Berkshire, Landrace, and Yorkshire breeds are 0.22 for Berkshire vs Landrace, 0.24 for Berkshire vs Yorkshire, and 0.20 for Landrace vs Yorkshire [FST value by chromosome among breeds increased, the frequency of SNP definitely decreased, and the same trend was shown in all chromosomes.To investigate differences in the genetic characteristics, F-statistics were estimated among Berkshire, Landrace, and Yorkshire populations. The estimates of orkshire . As the FST value among breeds was less than 0.05, the number of SNPs was 12,008 (46.3%), while it was 12,901 (49.8%) when the FST value was between 0.05 and 0.2. Also, when the FST value among breeds was more than 0.2, it was 1,012 (3.9%). The average FST in all chromosomes was 0.07±0.06. This result indicated that some genetic segregation has occurred partly.When the 2). The estimates of the average r2 between adjacent SNP were 0.411, 0.408, and 0.413 in Berkshire, Landrace, and Yorkshire, respectively. Similar results were reported in Landrace, Yorkshire, Hampshire and Duroc in the USA and their estimates were 0.36, 0.39, 0.44, and 0.46 [2 between adjacent markers was highest in SSC1 of the Berkshire breed (0.47), SSC14 of the Landrace breed (0.49), and SSC1, SSC13 and SSC14 (0.47) of the Yorkshire breed , smallest in SSC14 (66.73 kb) and the overall average distance was 94.09 kb . A totaland 0.46 . Howeverand 0.46  reportedre breed .2 decreased with increasing distance between SNP pairs  between SNP located within close physical distances is low, genetic recombination at that locus occurred a long time ago. Similarly, when the r2 between SNP located within far physical distances is high, genetic recombination at that locus occurred recently. The extent of genetic recombination can be estimated by the population size, while the Ne across the generations can be estimated from the r2 [Ne for the Berkshire, Landrace, and Yorkshire over 1st–5th generation was estimated to consist of 19.87, 31.41, and 34.09 pigs, respectively . Similarly, Ne declines were also observed in Landrace (100.2 to 50) and Yorkshire (102.3 to 34.1) pigs, followed by a somewhat similar declining rate. The Ne for the Berkshire, Landrace, and Yorkshire decreased at constant slope from 50th generations ago to 10th generations ago, with a sharp decrease in the recent 10th generations. Similar results were reported in a study by Uimari and Tapio [In Berkshire, the size of past nd Tapio . From thIn order to develop customized chips for the genomic selection of various breeds, it is important to select and utilize SNP based on the genetic characteristics of each breed. Since the improvement efficiency of breed pigs increases sharply by the population size, it is important to increase test units for the improvement and it is desirable to establish the pig improvement network system to expand the unit of breed pig improvement through the genetic connection among breed pig farms.


Sedum sarmentosum is an important Chinese medicinal herb that exhibits anti-inflammatory, anti-angiogenic and anti-nociceptive properties. However, little is known about its genetic background. The first set of 14 microsatellite markers were isolated and characterized for S. sarmentosum using an SSR-enriched library. Fourteen polymorphic microsatellite markers were acquired with satisfactory amplifications and a polymorphic pattern in 48 S. sarmentosum individuals. The number of alleles ranged from 3 to 15. The observed and expected heterozygosities varied from 0.0833 to 0.8750 and 0.2168 to 0.9063, respectively. Two loci showed significant departure from the Hardy-Weinberg equilibrium. Cross-species amplification was carried out in other Sedum species. High rates of cross-species amplification were observed. The transferability value ranged from 85.7% in S. lineare to 64.3% in S. ellacombianum. These markers will be valuable for studying the genetic variation, population structure and germplasm characterization of S. sarmentosum and related Sedum species. Sedum L. genus in the Crassulaceae family consists of 470 species that are distributed in the Northern Hemisphere, Africa and Latin America of Southern Hemisphere [Sedum L. species are widely used in folk medicine, especially Sedum sarmentosum, which has been frequently used for the treatment of chronic hepatitis in China [S. sarmentosum exhibits anti-angiogenic, anti-cancer, anti-viral and anti-nociceptive properties [S. sarmentosum for medicinal uses has led to overexploitation of the wild populations, driving them close to local extinction in the wild [S. sarmentosum are difficult to identify because of the large variety and close resemblance in closely related genera. For example, it is usually morphologically confused with S. lineare [Sedum L. genus usually differ in components and activities, and therefore classification and identification of the medicinal plant species is critical to ensure quality and therapeutic efficacy. Accurate evaluation of its genetic diversity is necessary for the conservation and molecular identification of this species.The misphere . Sedum Lin China ,3. Furththe wild . Further lineare . Plants Sedum genus [Sedum species [Sedum genus. DNA markers, such as random amplified polymorphic DNA, have been established to study the genetic relationship of six Sedum species. However, the RAPD marker had limited ability to provide stable genetic relationship [Sedum species.Earlier morphological and chemical composition studies have been performed for identification and classification of um genus ,8. Alloz species . Howevertionship . More reSedum species. In the absence of sequenced genomes, microsatellite-enrichment of genomic libraries has been shown to be effective at developing molecular markers for genetic studies [S. sarmentosum have been developed using a microsatellite-enriched library and tested for transferability across five other Sedum species. The polymorphic microsatellite markers might have important implications for the identification, genetic diversity and population genetic structure of Sedum genus.Microsatellite or simple sequence repeat (SSR) markers are considered to be effective in accessing genetic diversity and structure of plant population due to their abundance, high level of polymorphism, co-dominance, bi-parentally inheritance, and reproducibility of the results ,12. Howe studies ,14. In tRubus coreanus at 84.5% [From the 198 colonies screened for inserts, 82 positive colonies were randomly chosen and 68 colonies were successfully sequenced, 7 colonies were duplicates. Fifty-three microsatellite motifs were discovered in 61 singleton sequences. The enrichment efficiency of microsatellites (86.9%) was higher than for at 84.5% , groundnat 84.5% , and Japat 84.5% . Most ofS. sarmentosum. After preliminary screening, 14 polymorphic microsatellite loci yielded satisfactory amplifications with a polymorphic pattern. The number of polymorphic microsatellite loci observed with respect to amplified loci in S. sarmentosum (36.8%) is higher than that obtained by enriched libraries constructed from other medicinal herb, such as the Dendrobium huoshanense (30.6%) [Rhodiola (25.8%) [Bletilla striata (13.2%) [38 fragments containing microsatellite motifs that showed flanking regions were used to design primers  , Rhodiol (25.8%) , and Ble (13.2%) . Several (13.2%) ,22,23.S. sarmentosum and summarized in HO) ranged from 0.0833 to 0.8750 and the expected heterozygosity (HE) varied from 0.2168 to 0.9063. After sequential Bonferroni correction, two of the loci (Ssa10 and Ssa 60) showed significant departure from Hardy-Weinberg equilibrium (HWE), because of an excess of homozygotes. Null alleles, inbreeding, Wahlund effect, and small population size might lead to the excess of homozygotes [S. sarmentosum. Among the 14 microsatellite loci, no significant linkage disequilibrium was identified between loci.The genetic diversity parameters of the 14 polymorphic microsatellite loci were calculated for ozygotes ,25. The ozygotes ) and theS. lineare, which is morphologically close to S. sarmentosum. Twelve of the 14 microsatellite markers were amplified successfully and only six showed polymorphism in 12 S. lineare individuals , followed by S. bulbiferum (71.4%) and S. aizoo (71.4%)  . S. ellaer clade . The traer clade ,28,29.S. sarmentosum were collected from a single population located in Hongshan District, Wuhan, China . Leaves were randomly sampled and immediately put into the plastic sealed bags with silica gel for fast drying and then stored at room temperature until use. Genomic DNA was extracted from silica-gel-dried leaves using a 2% CTAB protocol with minor modification [Forty-eight individuals of MseI  and the digested DNA was ligated to a double-strand linker by T4 DNA ligase . Then linker-ligated DNA was amplified by 17 cycles of pre-hybridization polymerase chain reaction (PCR) using one strand of the linker as primer. The enriched DNA fragments were denatured and hybridized to biotinylated probes (AC)15 followed by incubation with Streptavidin MagneSphere Paramagnetic Particles . The captured DNA fragments were used as templates for 33 cycles of PCR amplification using an adaptor as primers. Following amplification, DNA fragments were size-selected (200 to 1000 bp) and purified on agarose gels. The fragments were ligated to pMD18-T vectors and transformed into Escherichia coli DH5a competent cells to construct an enriched microsatellite library. Recombinant colonies, identified as white colonies on an LB plate containing ampicillin were screened for inserts using M13 primers and we randomly chose 82 positive colonies to sequence. Tandem Repeats Finder [DNA was digested using the restriction enzyme s Finder  was useds Finder  was used2), 2 pmol of M13-tailed-forward primer, 4 pmol of the fluorescently labeled M13 universal primer (5′-TGT AAA ACG GCC AGT-3′), 6 pmol of a normal reverse primer, and 1 U of DNA Polymerase . The temperature profile was as follows: 5 min initial denaturation at 95 °C, followed by 34 cycles of denaturation at 94 °C for 30 s, annealing at 51–57 °C for 30 s, extension at 72 °C for 1 min and the final extension step of 7 min at 72 °C. The PCR products were electrophoresed on an ABI 3730 genetic analyzer and allele sizes were determined using GeneMapper v4.0 software (Applied Biosystems). The number of alleles per locus (A) and observed (HO) and expected (HE) levels of heterozygosity were calculated using the Arlequin program Version 3.5 [The M13-tailed primer method, in which the M13 sequence is attached to the 5′-end of the forward primer, was used to determine the sizes of the amplified products . Microsasion 3.5 .S. lineare (n = 12), S. emarginatum (n = 3), S. bulbiferum (n = 3), S. aizoo (n = 3), and S. ellacombianum (n = 3). The PCR conditions of each loci and the calculation of the genetic diversity parameters were the same as described earlier.Cross-species amplification tests were performed in randomly selected S. sarmentosum, an important Chinese medicinal herb. A total of 14 polymorphic SSR markers were ultimately screened and proved in S. sarmentosum. The SSR primer pairs displayed a high amplification frequency across Sedum species. These markers will be valuable for studying the genetic variation, population structure and germplasm characterization of S. sarmentosum and related Sedum species and aid in the development of conservation practices for S. sarmentosum.This is the first set of microsatellite markers developed for


The goal of the present study was to identify glycoproteins associated with the postoperative relapse of hepatocellular carcinoma (HCC) and to investigate their potential role in HCC metastasis. A method for quantitating N-glycoproteome was used to screen for, and identify, recurrence-related N-linked glycoproteins from 100 serum samples taken from patients with early-stage HCC. The prognostic significance of candidate glycoproteins was then validated in 193 HCC tissues using immunohistochemical staining. Serum core fucosylated quiescin sulfhydryl oxidase 1 (cf-QSOX1) was identified as a leading prognostic glycoprotein that significantly correlated with HCC recurrence. Patients with high serum cf-QSOX1 levels had a significantly longer time to recurrence (TTR) as compared with those with low serum cf-QSOX1. As was seen with serum cf-QSOX1, QSOX1 in HCC tissues was further shown to be significantly associated with good patient outcome. Gain-functional and loss-functional analyses of QSOX1-S were performed in vitro and in vivo. QSOX1-S overexpression significantly increased in vitro apoptosis, but decreased the invasive capacity of HCC cells, and reduced lung metastasis in nude mice models bearing human HCC. Furthermore, overexpression of a mutant version of QSOX1-S, which had eliminated the core-fucosylated glycan at Asn-130, showed no demonstrable effect on invasion or metastasis of HCC cells. Our study suggests that serum cf-QSOX1-S and tumor QSOX1 levels are helpful for predicting recurrence in HCC patients, and its core-fucosylated glycan at Asn-130 is critical for the inhibitory effects of QSOX1-S on invasion and metastasis of HCC The general prognosis of this disease is still extremely poor despite improved clinical diagnosis and treatment strategies that have emerged during the past few decades. The poor patient outcome seen is largely attributed to the high frequency of metastatic recurrence after curative treatments5. An expansion of the prognostic markers available, and identifying pathophysiologic mechanisms linked to metastatic recurrence, would help in the development of adjuvant therapies after resection and also provide potential targets for combating HCC metastasis.Hepatocellular carcinoma (HCC) is one of the most common and aggressive human malignancies worldwide6. It has been suggested that N-glycan β1,6-GlcNAc branching structures, bisecting GlcNAc, and core fucose have been linked to cancer biology7. The accumulating data strongly suggests that glycosylation may play fundamental roles in key pathological steps of tumor development and progression12. To this end, glycosylation has been shown to be involved in tumor cell–cell adhesion, cell–matrix interaction, cancer metabolism, and tumor immune surveillance6. More recently, an aberrant glycosylation that helps drive melanoma metastasis has been reported. The study also strongly underscored the urgent need for more systematic analyses of glycosylation in clinical tumor samples13.Glycosylation occurs as a post-transcriptional modification of proteins during their biogenesis. Glycoproteins carry one or more glycans that are covalently attached to the polypeptide backbone, this occurs usually via nitrogen or oxygen linkages, referred to as N-glycans or O-glycans, respectively17. Glycan biomarkers detectable in serum or plasma could potentially enhance cancer diagnosis and prognosis. For example, serum AFP is a marker used in the diagnosis of HCC, but its relatively low specificity for discrimination between HCC and the benign liver diseases has limited its broad clinical application. By contrast, serum fucosylated AFP‐L3 fraction has been shown to help distinguish liver fibrosis from HCC18.Many established tumor biomarkers including: alpha-fetoprotein (AFP), carcinomaembryonic antigen (CEA), CA125 and prostate-specific antigen (PSA), are glycosylated proteins19. The goal of the present study was to identify potential serum glycoproteins linked to HCC recurrence. New systematic glycoproteomic approaches now allow the discovery of specific protein glycosylation information occurring in cancer. In a previous study, we described the development of a method for quantifying the N-glycoproteome in blood samples using lectin affinity chromatography combined with enzyme-catalyzed 18O3− or 16O3− labeling. The potential feasibility of using this approach for the identification of disease-related N-linked glycoproteins using serum samples from HCC patients and healthy individuals was proposed20.Since the majority of blood glycoproteins are synthesized in the liver, serum, or plasma represent a good source for identifying potential glycoprotein biomarkers for characterizing liver diseases21. We screened serum samples, and identified a potential recurrence-related N-linked glycoprotein from HCC patients with BCLC 0 or A stage disease (cohort A). Serum core-fucosylated quiescin sulfhydryl oxidase 1 (cf-QSOX1) was found to be significantly associated with postoperative recurrence of HCC, and serum QSOX1 was shown to be completely represented by the 67 kDa short isoform of QSOX1 (QSOX1-S). We further validated the prognostic significance of QSOX1 in tumor tissues for HCC patients after curative resection. A significant positive correlation was found between serum cf-QSOX1 and tumor expressed QSOX1. The functional roles of QSOX1-S and its glycosylation in HCC metastasis were further investigated. We show that QSOX1-S expression can inhibit HCC tumor invasion and metastasis. Glycosylation at residue Asn-130 was further shown to be required for the inhibitory effects on invasion and metastasis of HCC. A flowchart of experimental plan is shown in Supplemental Fig. In the present study, our previous method was used to screen for HCC recurrence-related N-linked glycoproteins in the serum of HCC patients. A major challenge in the treatment of HCC is the identification of patients who are at a greater risk for tumor recurrence after treatment, particularly for patients with early stage disease who do not show significant vascular invasion, regional lymph node, or distant metastasis22. A lectin microarray analysis was performed on 40 tumor tissue samples from patients who had undergone curative surgical resections for HCC  to identify potential glycan structures linked to metastatic recurrence of HCC. Glycoproteins from the tumor tissues that could bind lectin ConA, LCA, WGA, or MPL, were found to be significantly differentially expressed between patients who had undergone postoperative HCC recurrence (recurrence group) and those without tumor-recurrence (non-recurrence group) during the follow-up period  when the median expression level of serum cf-QSOX1 was used as the cutoff value  based on the strategy shown in Supplemental Fig. lue Fig. . Patientlue Fig. . Levels lue Fig. .Fig. 1BoP = 0.006) for recurrence   . Tumor tissue samples from 193 HCC patients (cohort B) were used for this analysis. As shown in Fig. 44) Fig. . These rUsing univariate analysis, tumor QSOX1, HBsAg, microvascular invasion, tumor differentiation, and tumor encapsulation were found to be significantly associated with OS during follow-up studies; while tumor QSOX1, HBsAg, and liver cirrhosis correlated with TTR during the 3-year follow up after surgery. In multivariate analyses, the prognostic values of tumor QSOX1 for OS and 3-year-TTR follow up were independent of the other clinical variables tested Table .Table 2Up = 0.024).To validate the association of serum cf-QSOX1 with tumor QSOX1, the correlation between serum cf-QSOX1 levels and tumor QSOX1 densities in 12 patients was analyzed using paired serum and tumor tissues samples. A significant positive correlation between the values was found  and homogenous cytoplasm staining (type II). The perinuclear distribution is suggestive of Golgi or ER staining and thought to represent QSOX1-L localization, whereas homogenous cytoplasmic staining of QSOX1 may reflect the localization of QSOX1-S. However, specific antibodies against QSOX1 isoform are not commercially available. To test this hypothesis, Western blot was performed to determine expression levels of the two QSOX1 isoforms in 12 HCC tissues showing typical type I or type II immunostaining. As shown in Supplemental Fig. n = 105) from cohort B. As shown in Supplemental Fig. Previous reports have suggested that QSOX1-S may function as a secreted oxidase and is present in most bodily fluids, whereas QSOX1-L is a transmembrane protein localized primarily in the Golgi or ER apparatusWe then examined whether expression levels of QSOX1-S in HCC cell lines correlated with metastatic potential. As shown in Fig. To further verify the role of QSOX1-S in HCC tumor growth and metastasis in vivo, orthotopic implantation models were established using the MHCC97-H and Hep3B cells that had been stably engineered for QSOX1-S-overexpression or QSOX1-S knockdown using shRNA lentiviruses. The incidence of lung metastasis of the MHCC97-H cells in orthotopic models in the QSOX1-S overexpression group was remarkably decreased as compared with the control group (25% vs. 75%). The total number and grade of lung metastatic lesions in the QSOX1-S overexpression group was also significantly lower than that seen in the control (Mock group) Fig. . By cont27. To investigate the biologic effect of core-fucosylated glycan at Asn-130 on QSOX1-S action, an MHCC97-H cell line was established stably overexpressing a mutated version of QSOX1-S (mQSOX1-S) with a mutation in the core-fucosylated glycan-binding region at Asn-130 -130 residue of QSOX1  was used to identify serum recurrence-associated glycoproteins. The specimens from this cohort included 40 tumor tissues samples (set A) and 100 serum samples (sets B and C). Cohort B (n = 193) was used to validate the prognostic values of the glycoproteins identified in the HCC patients. The specimens from cohort B consisted of 193 tumor tissue samples. A total of 12 patients in this study had paired serum (from set C) with tumor tissue samples (from cohort B). The clinicopathological characteristics are summarized in Supplemental Table A total of 321 HCC patients who had undergone curative resection  from January 2003 to December 2010 were enrolled in the study. The diagnosis of HCC was confirmed by two pathologists. Curative resection for HCC is defined as complete resection of the tumor when the margins are free of cancer by histological examination. All patients were assigned into two cohorts. Cohort A  at 37 °C for 16 h. The digested serum samples were subjected to lectin affinity chromatography for separating the glycopeptides with specific glycan structure using ConA-based, LCH-based, and WGA-based isolation kits.The experiments were performed as previously described21. The density of positive staining was evaluated using a Leica CCD camera DFC420 connected to a Leica DM IRE2 microscope . The QSOX1 densities were counted by Image-Pro Plus v5.0 software 21. A uniform setting was applied for QSOX1 antibody staining. The integrated optical density (IOD) of all positive staining in each photograph was measured; the mean QSOX1 density was calculated as the product of IOD/total area.Tissue microarrays were constructed and immunohistochemistry (IHC) was performed as described previouslyDetailed methods can be found in the 42. Briefly, 5 × 104 cells in serum-free medium were seeded on a membrane (8.0-μm pores) in a 24-well plate. Medium containing 10% fetal bovine serum was added to the lower chamber of each well. After 48 h incubation, cells that migrated to the underside of the membrane were stained with Giemsa , imaged, and counted with a microscope  at ×200 magnification. All experiments were performed in triplicate.The invasive ability of HCC cells was determined using 24-well transwell chambers  coated with Matrigel  as described in previous study6 HCC cells into nude mice  . Subcutaneous tumors were removed and dissected into 1-mm3 sections, which were implanted into the left hepatic lobe of BALB/c nude mice to establish orthotopic implantation models. Tumor growth was monitored, and the mice were sacrificed at 6 weeks. The tumors, livers, and lungs were removed, fixed in formalin, and embedded in paraffin. Consecutive sections were made for every lung tissue block and stained with hematoxylin and eosin. The number of lung metastases was calculated and evaluated independently by two pathologists. Based on the number of HCC cells in the maximal section of the metastatic lesion, lung metastases were classified into four grades. Grade I was defined as having ≤20 tumor cells; grade II had 20–50 tumor cells; grade III had 50–100 tumor cells; grade IV had >100 tumor cells.All experimental procedures involving animals were approved by The Animal Care and Use Committee of Fudan University, China. Flank xenografts were established by subcutaneous implantation of 2 × 10t-test. Multiple comparisons were analyzed by one-way analysis of variance. The log-rank (Mantel–Cox) test was used for patient survival and recurrence analysis. Univariate and multivariate analyses were based on the Cox proportional hazards regression model. For all immunohistochemical variables, the median value (0.01064) of QSOX1 density (IOD) was used as the cutoff for defining patient subgroups of high or low QSOX1 expression. Two-tailed p-values < 0.05 were considered significant.Statistical analysis was performed using SPSS version 15.0 . Comparison of two groups was conducted using the Student Additional details are provided in the supplement.Additional details are provided in revised-supplemental materal


Sympetrum obtrusum from eight locations, four aquatic, and four terrestrial, at the Pierce Cedar Creek Institute in Southwest Michigan over two summers. We performed AFLP genetic analysis and used the Bayesian analysis program STRUCTURE to detect genetic clusters from sampled individuals. STRUCTURE detected k = u4 populations, in which nymphs and adults from the same locations collected in different years did not necessarily fall into the same clusters. We also evaluated grouping using the statistical clustering analyses NMDS and MRPP. The results of these confirmed findings from STRUCTURE and emphasized differences between adults collected in 2012 and all other generations. These results suggest that both dispersal and a temporal cycle of emergence of nymphs from unique clusters every other year could be influential in structuring dragonfly populations, although our methods were not able to fully distinguish the influences of either force. This study provides a better understanding of local dragonfly metapopulation structure and provides a starting point for future studies to investigate the spatial and temporal mechanisms controlling metapopulation structure. The results of the study should prove informative for managers working to preserve genetic diversity in connected dragonfly metapopulations, especially in the face of increasing anthropogenic landscape changes.Dragonflies reside in both aquatic and terrestrial environments, depending on their life stage, necessitating the conservation of drastically different habitats; however, little is understood about how nymph and adult dragonflies function as metapopulations within connected habitat. We used genetic techniques to examine nymphs and adults within a single metapopulation both spatially and temporally to better understand metapopulation structure and the processes that might influence said structure. We sampled 97 nymphs and 149 adult  Despite increasing alteration and destruction of both terrestrial and aquatic habitats, relatively little is understood about the genetic relationship between populations of nymph and adult dragonflies in a given area. Previous studies have generally examined either the spatial distribution of dragonfly nymphs , nature preserve in southwest Michigan, during the summers of 2012 and 2013 . We collected samples from two lakes, Aurohn Lake (AUR), a man‐made, spring‐fed lake, and Brewster Lake (BRW), a large natural lake. In addition, we collected from Hyla Wetlands (HYL), which includes a small pond, and Tallgrass Swamp (TAL), which is a temporary, seasonal wetland that does not experience wet conditions in every year. These sites represented all potential sites for dragonfly natal waters on the property owned by the institute. TYL, HYL, and BRW were clustered closer to each other in relation to AUR, allowing us to examine movement at different distances within our metapopulation. We expected that the more distant AUR would exhibit greater isolation from the other natal populations. All sites were sampled in both years, but individuals were not found at all sites in both years. We genetically sampled 29 nymphs and 19 adults from AUR in 2012 and 17 nymphs and 22 adults in 2013. From TAL, we sampled 23 nymphs and 16 adults in 2012. Because the Tallgrass swamp had dried up, we found no nymphs in summer 2013, but still sampled 29 adults from the prairie. We sampled 28 nymphs and 22 adults from HYL in 2013, although none were found in the area in 2012. Finally, we genetically sampled 24 adults from BRW in 2012 and 17 in 2013. We found no evidence of nymphs within Brewster Lake. In total, we genotyped 97 nymphs and 149 adult dragonflies from across the PCCI property. Although sample sizes were small, we feel sampling accurately represented the available individuals based on the number of samples collected and sampling efforts . We analyzed the samples using amplified fragment‐length polymorphisms (AFLPs) according to the Plant Mapping Protocol , but increased the number of cycles to 30 for the selective amplification polymerase chain reaction (PCR) to increase the number of amplicons. We used the enzymes Mse1 and EcoR1. We used one primer‐pair combination, E‐TAG with M‐CGC  with the selective EcoR1 primer tagged with fluorescent dye (5~HEX), to amplify DNA for PCR. The PCR products were analyzed with an automated DNA sequencer , and the bands were scored using GeneMapper 4.0 software . We only accepted peaks that were between 50 and 400 base pairs in size and had a height that was above 70 fluorescent units. For each individual, we scored each band as present (1) or absent (0).2.3ST values, as calculated in AFLP Surv , which allows for the visual representation of individuals grouped, in this case, on genetic parameters. NMDS uses the Sorenson–Bray–Curtis distance measure, which is appropriate for data that does not meet assumptions of multivariate normality, as is the case with presence–absence data. We determined the strength of these groups using multiresponse permutation procedures (MRPP). Both analyses were performed in PC‐ORD  analysis of dragonflies at PCCI based on location and year, as well as life stage and year Figure . Monte CT = −65.3, delta = 0.042, A = 0.311, p < 0.001). Amongst the 55 pairwise comparisons, almost all sampling locations differed significantly from each other after Bonferroni correction . In pairwise comparisons, all life stage groups were significantly different from each other. Pairwise T values ranged from −18.6, for a comparison of nymphs in both years, to −78.3, for a comparison of adults in both years. Pairwise A values ranged from 0.057, again for the comparison of nymphs in both years, to 0.235 for a comparison of adults in both years. Pairwise comparisons involving adults sampled in 2012 had consistently high A values and more negative T values than comparisons not involving those adults . All pairwise comparisons were significantly different (p < 0.001) at a Bonferroni‐corrected alpha of 0.008. The highest number of unique bands (9.5) was found in Cluster 2, followed by Clusters 4 and 3, with 9.2 and 8.7, respectively. The lowest number of unique bands (7.5) was found in Cluster 1, which contained 2012 adults.We found a significant difference in the number of unique bands sampled across genetic clusters, when corrected for sample size , while pairwise values for Nei's Coefficient of Genetic Identity ranged from 0.01 to 0.41 , while pairwise Nei's values ranged from 0.003 to 0.34 (Table When all sites, separated by collection year and life stage, were compared individually, 4S. obtrusum at PCCI appears to exist as a strongly differentiated metapopulation structure. STRUCTURE detected four genetic clusters across the area. These genetic clusters were grouped not only by location, but also by collection year, with all adults collected in 2012 grouping distinctly from all other groups. The remaining groups were mixes of adults and nymphs collected in 2012 and 2013, with the exception of the final group, which contained only the nymphs from Tallgrass Swamp collected in 2012. In terms of FST, the clusters were moderately to strongly differentiated, suggesting low exchange of individuals between these genetic clusters. Pairwise comparisons of all individual sampling locations loosely confirm these findings. Once again, the 2012 adult populations were not significantly different from each other but were significantly different from all other locations.The population of FST tests. When grouped by life stage and year collected, the 2012 adults were most strongly differentiated from all other groups. The nymphs collected in 2012 and 2013 were the least differentiated from each other and from all other groups. This suggests that nymphs in this population experience variable timing of emergence, as might be expected given that semivoltinism can vary due to environmental conditions (Corbet, Sympetrum species, may overwinter for multiple years prior to transitioning from nymph to adult dragonflies, creating overlapping generations within the same emergence (Kormondy & Gower, The results of the NMDS and MRPP analyses followed the same general patterns at the structure analysis. Pairwise comparisons showed the same statistical patterns as pairwise  Corbet, . DragonfS. obtrusum. However, other mechanisms, including adult dispersal and breeding behavior, are likely at play in the population. Our results support findings that adult S. obtrusum move away from their natal body of water to forage after emergence. The movement of adult dragonflies to a new area for breeding and foraging supports previous mark–recapture studies which showed high percentages of nonlocal dragonflies at closely aggregated ponds (Michiels & Dhondt, Sympetrum species have shown that up to 47% of adults move away from their natal pond when other ponds were less than 1 km apart (Conrad et al., Variable semivoltinism could explain some of the patterns observed in the metapopulation of S. obtrusum have the capacity to fly great distances and utilize large home ranges, their ability to reach different locations on the landscape may be hindered by factors other than distance. For instance, the assemblage of dragonfly species at ponds is influenced by agricultural land management, as mowing may cause direct mortality and reduce available roosting habitat (Raebel et al., The differentiation of sampling locations in pairwise comparisons suggests that, although Sympetrum breeding biology. Dragonflies are known to mate with multiple individuals. Although male dragonflies are often territorial and practice mate guarding to prevent females from mating with other males, some males do fail to completely protect their females from intruding males. Likewise, some males will mate with additional females (Harvey & Hubbard, Finally, the dragonfly metapopulation structure at PCCI may be influenced by Sympetrum species have an evolutionary history of using temporary and annual pools for egg laying (Corbet et al., Sympetrum lay their eggs. However, for long‐term metapopulation survival, the maintenance of landscape connectivity is crucial for maintaining genetic diversity in dragonfly metapopulations, especially in the face of climatic change and anthropogenic land use changes.Understanding the patterns of population structure and dragonfly movement within a metapopulation can have important implications for dragonfly conservation. Anthropogenic land use can drastically alter landscapes, removing critical habitat for both nymphs and adult dragonflies. The loss of individual foraging grounds or natal waters could represent a disruption of metapopulation structure and the loss of unique genetic material in the overall population. In our study, the potential for the loss of unique genetic information was evidenced by the loss of the Tallgrass Swamp population. Nymphs were sampled in the swamp in 2012, but the swamp dried up prior to sampling in 2013. The nymphs sampled from this area in 2012 represented a unique genetic cluster and contained the second highest number of unique AFLP bands in the population. While adults were sampled in the nearby prairie in both 2012 and 2013, they were not part of the same genetic cluster as the nymphs, again suggesting movement away from the natal area, at least for foraging. Although we were unable to sample any eggs or larvae from Tallgrass swamp in 2013, it is possible that the genetic material from these nymphs survives in adults elsewhere. As part of the flexible semivoltine strategies exhibited by dragonfly populations, Habitat degradation, including the loss of connected habitat, is a leading force in recent declines in local biodiversity (Pimm & Raven, None declared.Payton Phillips analyzed data and wrote the manuscript. Bradley J. Swanson designed the research, supervised the fieldwork, provided guidance on data analysis, and edited the manuscript. Click here for additional data file.


The present study aimed to systematically evaluate the genetic diversity of Chinese domestic duck breeds and ensure the most effective allocation and usage of conservation funds. We first performed an analysis of DNA genetic distance in 21 duck breeds by measuring short tandem repeats. Then, we calculated the extinction probability, contribution rate, and marginal diversity for each breed. The results showed that the extinction rate of the Zhongshan duck, Guangxi duck, and Ji’an duck were the highest at 0.67, 0.59, and 0.59, respectively, and that of the Linwu duck, Jinding duck, and Gaoyou duck were the lowest at 0.15, 0.18, and 0.19, respectively. The current diversity of populations was 7.72 and the expected diversity in five hundred years is 5.14 ± 1.15. The marginal diversity of the Chinese Muscovy duck was the largest (−2.20), accounting for 42.61% of the expected diversity, followed by the Guangxi duck , whereas the Jinding duck was the smallest . The protection potency of the Chinese Muscovy duck was the largest (0.61), followed by Guangxi duck (0.29), whereas the Jinding duck was the smallest (0.02). This study provides a reference for determining the conservation priority of Chinese domestic duck breeds or genetic resources. Two systematic and comprehensive surveys were conducted on animal genetic resources: one from 1970 to 1980, and the other in 2004. According to the Report on Domestic Animal Genetic Resource in China (edited in 2012)5, 777 breeds of animal genetic resources have been formally named in China, including 556 local breeds, 109 cultivated breeds, 104 introduced breeds, and eight other breeds. With respect to breeds of poultry, there are 116 chickens, 34 ducks, 31 geese, three turkeys, three pigeons, and two species of quail.Animal genetic resources are the basis of the sustainable development of animal husbandryin vivo conservation, loss of animal genetic resources, and large-scale adoption of breeding and intensification processes6. In particular, the large number of imported breeds, and their wide promotion, have greatly threatened Chinese domestic animal genetic resources7. As examples, the Guping chicken, Lintao chicken, Wenshan goose, and Simao goose have all become extinct and, in total, 44 breeds are on the edge of extinction and 15 are endangered9. In response to this crisis, the departments responsible for managing Chinese animal genetic resources have allocated yearly funds toward conservation efforts. Since these funds are limited, both conservation strategy and fund allocation are determined by the economic value and population size of a breed10. However, the subjectivity of this system could result in ineffective conservation of precious and endangered genetic resources. Therefore, a better system is needed to determine priority in these conservation efforts and achieve optimal allocation of funds12.However, animal genetic resources have shown an overall decline in China since 1970s, due to unknown resources in some areas, low 13 as a mechanism for measuring genetic diversity. The concept uses genetic and non-genetic factors to calculate a “maximum-likelihood tree”14 and the current diversity of breeds, and estimates the expected variations in diversity over a certain time. This approach defines criteria of diversity and relies on quantitative assessments of different strategies, providing concrete reasoning for breed conservation. At present, marginal diversity has been applied in studies on European pigs15 and cows16; however, no systematic assessment with this approach has been conducted in Chinese domestic duck breeds and the managers also do not know how to allocate funds for breed insurance. Here, we use short tandem repeat profiling to perform a marginal diversity analysis of 21 Chinese domestic duck breeds or genetic resources, which can be used to determine conservation priority.One option is through marginal diversity, which was defined by Weitzman in 1992All animal experiments were performed in accordance with the Regulations for the Administration of Experimental Animals issued by the Ministry of Science and Technology . All experiments were approved by the Animal Care and Use Committee of Yangzhou University.et al.17.The objects of the study were Chinese domestic duck breeds or their genetic resources. Their name, sample size, and origin are shown in Table 18. A total of 1802 ducks were genotyped and the population genetic parameters calculated were described in a published paper18. The standard genetic distance between populations was calculated with Microsatellite-Toolkit19 and Dispan (http://www.softpedia.com/get/Science-CAD/DISPAN.shtml).Twelve pairs of microsatellite primers with rich polymorphism were selected as follows: APH01, APL2, AJ272579, AJ272578, AJ272577, AJ415887, AJ515884, AJ515893, AY493256, AY493289, AY493313, and CMO11. The Sequences, combination, and optimal reaction condition have been reported previously20, and Structure 2.0 (http://rosenberglab.bioinformatics.med.umich.edu/distruct.htm) software was used for genetic Structure analysis of 21 populations.In this study, SPSS13.0 software was used for principal component analysis (PCA) of all the detected alleles21. In Weitzman’s approach, the extinction probability (Zi) of each set is a variable that needs special attention. There are various methods for calculating Zi; however, we adopted the method proposed by Reust-Marti11. This method uses seven variables: the total population size (POS), its change over the past 10 years (CHA), distribution of the breed (DIS), risk of indiscriminate crossing (CRO), organization and conservation measures of breeding (ORG), special traits (SPE), and threat of production transition (PRO) (Table i) were given to different variables to estimate Zi in the future 500 years. The estimate formula and correction formula are as follows:i is the weight of each variable  and xi is the estimate of the ith indicator. The seven parameters for this analysis were attained by on-site observation, literature review, and estimation, in order to calculate the Zi of each breed and genetic resource in the next 500 years. For the convenience of calculation, Zia of each breed or genetic resource was corrected to 0.1–0.9, according to the formula below22.Extinction probability is an important index for genetic resource diversity. Future changes in the diversity of local breeds or genetic resources can be measured as the extinction probability over time (500 years)i, the distance of j ∈ S can be expressed as dij. According to Weitzman’s recursive algorithm, the diversity variable D (S) can be calculated by an N × N distance matrix. The probability of a breed’s existence in 500 years is 1-Zi, if Z is an N-dimensional vector containing Zi of N sets. K is an N-dimensional vector containing the indicator variable Ki . Ki = 1 if the set i exists, whereas Ki = 0 if the set i is extinct. Therefore, K represents an overview of the status in which a subset of breeds exists and its complementary subset is extinct. The formula of the existence probability of a subset of breeds is as follows:For the set (S) containing a certain number (N) of breeds and genetic resources, and a breed K is the diversity of the subsets safe from extinction. The expected diversity at the end of the time horizon (500 years) is calculated as:DThe variance of the expected diversity is:The marginal diversity of a breed or genetic resource reflects the variation of the expected diversity when the extinction probability is increased by one unit. The marginal diversity is calculated as follows:Based on the extinction probability and expected diversity of a breed or genetic resource, Weitzman suggested conservation potency as the optimal parameter to assess the genetic diversity over a given time horizon. The conservation potency (CP) is calculated as follows:CPi represents a possible increase in the expected diversity of a breed or genetic resource when the threat is completely removed. According to previous work by Simianer et al.10, CPi is the optimal parameter for determining conservation schemes, with the highest CPirequiring a minimum amount of capital required for the protection scheme22. The breed or genetic resource with the highest CPi should be allocated the least funds in breeding conservation efforts23.24. According to the genetic distance matrix  form three large sets. The distance between GY and JA was the shortest, and the distance between FY and GX was the longest First bullet.Twelve simple sequence repeats were detected in the 21 duck breeds. Nei’s standard genetic distance was estimated using Microsatellite-Toolkit and Dispanix Table  and clusPCA was performed on the gene frequencies of all alleles detected in 12 SSR seats in 21 populations. The plane distance graph constructed according to the first two principal components was shown in Fig. Structure 2.0 program can group individuals with similar genotypes on multiple SSR seats without prior knowledge of the fusion or evolutionary history of the populations  is anticipated.The term “contributions” is defined as the percentage of contribution of each breed to overall diversity. The contributions and marginal diversities of each of the 21 breeds are shown in Table 26. Conservation of genetic diversity plays an important role in sustaining the livestock breeds27. At present, Weitzman marginal diversity method has attracted more and more attention in the research on rational allocation of livestock and poultry resources protection funds, and has become one of the most dynamic theories in the field of livestock genetic resources protection and utilization29. There were many researches on animal genetic diversity in the world32, but few of them analyze the application of marginal diversity method To our knowledge, Reist-Marti et al.(2003) have estimated extinction probability in livestock breeds11. Bennewitz (2005) estimated the extinction probabilities of 5 German dual-purpose cattle breeds by population viability analysis33. And then (2006) he analyzed 44 North Eurasian cattle breeds using simplified determined extinction probabilities. The results show that the expected loss of diversity within the next 50 years is between 1 and 3% of the actual diversity34. The marginal diversity analysis of goat29, sheep35, cattle36, pigs37 has been completed in China, which provides a reliable data reference for the division of conservation funds. After years of investigation of domestic duck resources and collection of blood samples, this paper analyzed the marginal diversity and extinction probability of local duck breeds in China for the first time.There are numerous domestic duck breeds in China including 27 indigenous breeds, two introduced breeds, and a few developing breeds. However, with the introduction and promotion of cherry valley duck, the number of local duck species in China has dropped sharply, and many species are facing the danger of extinction38. The expected number of classification  of the detected group was set at runtime, which can be used to divide all individuals and reflect the genetic structure of the group. It is especially suitable for the study of the genetic structure, the differentiation and migration of individuals. In this paper, the population Structure diagram and the maximum-likelihood tree39 obtained based on Structure 2.0 program were consistent with the results from PCA, verifying the accuracy of population Structure inference.In this paper, the PCA was used to explain the molecular genetic relationships among the populations and a plane distance map was constructed, reflecting the real genetic information and genetic relationships of the 21 populations. Structure cluster analysis use allelic and genotype data from multiple loci, such as SSR loci, to construct a cluster model. Structure 2.0 program was based on Bayesian probability theory, adopt Markov-Monte Carlo simulation algorithm, and used mixed model when running the program to reveal the unknown population genetic relationship and potential population Structure from all population levels40. However, due to the political and economic situation in China, as well as the distribution of indigenous duck breeds and resources, some factors were not considered in this study, such as natural disasters, reliability of the information source, and development of reasonable storage approaches. For this measurement, seven variables  were assigned to different weights as major factors. These variables have been proved to be important factors reflecting population diversity. Here, we calculated the current and expected population diversities of a total of 21 Chinese duck breeds, respectively. Importantly, we found that the expected diversity (within 500 years) were 33.43% lower than current diversity.The calculation for extinction probability considers all factors that might cause change in a breed or genetic resource, making it an accurate and reliable estimation41. If limited breeding conservation funding is allocated based on extinction probability parameters, it may not be the most beneficial solution for the entire population, especially if that population includes numerous breeds and strains. Instead, the breed with the largest contribution should be given the highest priority43. In this study, the largest contributor was FY, followed by GX.Some variables for calculating the extinction probability, such as CHA and CRO, only consider the conservation of a single breed or genetic resource, and do not account for the effect of the conserved breed on the genetic diversity of the entire population44. Conserving the breed with the largest conservation potency is the most effective way to maintain overall genetic diversity. Therefore, the first two breeds prioritized should be FY and GX, followed by CH, JC, JS, JX, JA, PT, TW, LC, DY, SS, ZS, JJ, SM, MW, BJ, YX, LW, GY, and JD.However, breed contribution is not the only consideration for conservation planning efforts, and its calculation does not consider extinction probability. In contrast, marginal diversity considers both contribution and the extinction probability, and can therefore act as a comprehensive measurement of the importance of each breed. According to Weitzman, marginal diversity parameters should be considered the preferred reference during breeding conversation planningBased on the marginal diversity parameters, we identified the conservation priority of 21 local duck breeds and genetic resources. FY and GX are the first two breeds that should be protected. The conservation priority in this study can provide a reference for breed conservation planning.


Tursiops aduncus) populations in Western Australia—one apparently viable population with high reproductive output (Shark Bay) and one with lower reproductive output that was forecast to decline (Bunbury). We assessed genetic variation in the two populations by sequencing the MHC class II DQB, which encompasses the functionally important peptide binding regions (PBR). Neutral genetic diversity was assessed by genotyping twenty‐three microsatellite loci.Genetic diversity is essential for populations to adapt to changing environments. Measures of genetic diversity are often based on selectively neutral markers, such as microsatellites. Genetic diversity to guide conservation management, however, is better reflected by adaptive markers, including genes of the major histocompatibility complex (MHC). Our aim was to assess MHC and neutral genetic diversity in two contrasting bottlenose dolphin (We confirmed that MHC is an adaptive marker in both populations. Overall, the Shark Bay population exhibited greater MHC diversity than the Bunbury population—for example, it displayed greater MHC nucleotide diversity. In contrast, the difference in microsatellite diversity between the two populations was comparatively low.Our findings are consistent with the hypothesis that viable populations typically display greater genetic diversity than less viable populations. The results also suggest that MHC variation is more closely associated with population viability than neutral genetic variation. Although the inferences from our findings are limited, because we only compared two populations, our results add to a growing number of studies that highlight the usefulness of MHC as a potentially suitable genetic marker for animal conservation. The Shark Bay population, which carries greater adaptive genetic diversity than the Bunbury population, is thus likely more robust to natural or human‐induced changes to the coastal ecosystem it inhabits. Tissue χ2 = 0.42, p = 0.515; BB: χ2 = 0.16, p = 0.693) nor were the ratios of sampled individuals significantly different from 50:50 . To assess whether it was justified to pool samples collected from eastern and western SB, we estimated subpopulation fixation index (STF) based on microsatellite data, using genalex 6.501  licensed by the Western Australian Department of Environment and Conservation . This study was carried out in accordance with the Murdoch University Animal Ethics Committee approval .2.2To characterize MHC genetic variants of the two populations, we amplified and sequenced the MHC II DQB exon 2 (hereafter MHC DQB), which encompasses the functionally important PBR , and 20–100 ng (5 μl) of template DNA in a total volume of 25 μl. Thermal cycling was conducted on an Eppendorf Mastercycler (ep gradient S) with an initial denaturing temperature of 95°C for 15 min, 30–35 cycles of denaturation at 95°C (1 min), and annealing at 55°C (30 s), followed by an elongation step at 72°C for 1 min.PCR for MHC DQB was performed using 1.25 μM primers, 0.2 mM dNTPs, 1.0 mM MgClPCR products were visualized by electrophoresis on a 1.5% agarose gel (1× TBE buffer) stained with GelRed™ (Biotium). All MHC amplicons were sequenced in the forward and reverse direction using Big Dye 3.1 on a 3730xl DNA Analyzer (Applied Bioscience) at the Ramaciotti Centre of the University of New South Wales.clustalw  based on the default threshold of 50% peak height and double‐checked by visual inspection. Subsequently, MHC DQB sequence variants were inferred by reconstructing haplotype phases from the unphased sequence alignment data using the coalescent‐based Bayesian method phase  were aligned with 2.3Nd) and synonymous (Sd) substitutions within the 172‐bp MHC DQB region. We used the Nei–Gojobori method  implemented in MEGA version 7.08  all codons of the entire sequence; (b) codons of the putative peptide binding region (PBR), that is, variable codons that code for amino acids that have been reported to bind to antigens; and (c) putative nonpeptide binding regions (non‐PBR). Variance estimation for the z‐test was based on 1,000 bootstrap replicates. Additionally, we used DNASP to perform Tajima's D test , as described by Nei (Hd) , according to Watterson (EtaӨ) per nucleotide site from the total number of mutations  and the microsatellite plugin for geneious 6.0 , expected heterozygosity relative to HWE (eH), the number of effective alleles (eA), and Shannon's Index (1H)  and sexes that were found in the conservative BB sample  subsamples for SB and 5 × 11 (55) subsamples for BB.Due to the sample‐size difference between SB and BB, we used three sampling approaches to compare genetic diversity between the two populations:Other methods, such as rarefaction, are often used to investigate the effect of sample size, but we believe our three sampling approaches address this more thoroughly.3STF) comparing the two sampling sites in SB showed very little differentiation  were analyzed. Totals of 186 and 43 MHC DQB sequence variants were inferred by haplotype reconstruction for SB and BB, respectively. We did not detect any patterns in the sequences that indicated multiple allelism , gene duplications, stop codons, or frameshifts. Comparing MHC DQB sequences of seven mother–father–offspring trios Kopps,  did not 3.2Nd) substitution rates were significantly greater than the synonymous (Sd) substitutions rates in the entire 172‐bp region and in the putative PBR, but not in the non‐PBR  when considering only nonsynonymous substitutions , substantially greater than that of BB  was substantially larger for SB  than for BB , dolphins of SB showed greater MHC DQB diversity than those of BB, except with respect to e Figure ; Table 33.4Neither population showed evidence for scoring errors due to stuttering or large‐allele dropouts for any of the microsatellite loci. We also did not detect evidence for null alleles for any of the loci. Linkage disequilibrium tests with Genepop showed that, among all comparisons of pairs of microsatellite loci, one pair appeared linked (Tur4_105 & MK8), but this linkage was only observed for BB, so it was unlikely to be a result of physical linkage. Departures from HWE expectations were observed for two microsatellite loci, Tur4_98 (SB) and KWM12 (SB & BB), after Bonferroni correction. Those two loci were removed from subsequent analysis. Consequently, all subsequent results are based on 23 loci.oH, eH, eA, and 1H  for SB and 2.70 (SE = 0.23) for BB  on the Bunbury dolphins. J.M., R.C.C., C.F., M.K., A.M.K., and S.J.A. contributed data  on the Shark Bay dolphins. W.B.S. supervised O.M. on this project and contributed to the genetic analyses. All authors reviewed and edited the manuscript. Click here for additional data file.


Coastal wetlands are susceptible to loss in both health and extent via stressors associated with global climate change and anthropogenic disturbance. Peat collapse may represent an additional phenomenon contributing to coastal wetland loss in organic‐rich soils through rapid vertical elevation decline. However, the term “peat collapse” has been inconsistently used in the literature, leading to ambiguities regarding the mechanisms, timing, and spatial extent of its contribution to coastal wetland loss. For example, it is unclear whether peat collapse is distinct from general subsidence, or what biogeochemical changes or sequence of events may constitute peat collapse. A critical analysis of peer‐reviewed literature related to peat collapse was supplemented with fundamental principles of soil physics and biogeochemistry to develop a conceptual framework for coastal wetland peat collapse. We propose that coastal wetland peat collapse is a specific type of shallow subsidence unique to highly organic soils in which a loss of soil strength and structural integrity contributes to a decline in elevation, over the course of a few months to a few years, below the lower limit for emergent plant growth and natural recovery. We further posit that coastal wetland peat collapse is driven by severe stress or death of the vegetation, which compromises the supportive structure roots provide to low‐density organic soils and shifts the carbon balance of the ecosystem toward a net source, as mineralization is no longer offset by sequestration. Under these conditions, four mechanisms may contribute to peat collapse: (1) compression of gas‐filled pore spaces within the soil during dry‐down conditions; (2) deconsolidation of excessively waterlogged peat, followed by transport; (3) compaction of aerenchyma tissue in wetland plant roots, and possibly collapse of root channels; and (4) acceleration of soil mineralization due to the addition of labile carbon (dying roots), oxygen (decreased flooding), nutrients (eutrophication), or sulfate . Scientists and land managers should focus efforts on monitoring vegetation health across the coastal landscape as an indicator for peat collapse vulnerability and move toward codifying the term “peat collapse” in the scientific literature. Once clarified, the contribution of peat collapse to coastal wetland loss can be evaluated. Coastal wetlands are highly vulnerable to sea level rise, with estimates of 22–30% global areal loss by 2100  and nitrogen (N) and phosphorus (P) release  discuss the meaning of the term “peat collapse,” (2) examine the peer‐reviewed literature related to peat collapse, (3) critically evaluate the possible mechanisms leading to peat collapse in coastal wetlands, (4) develop a conceptual framework of the most likely scenarios for wetland loss via peat collapse, (5) present a working definition of coastal wetland peat collapse, and (6) suggest future research directions and management implications. Scientists and resource managers can only evaluate the ecological ramifications and determine the best management practices for remediating collapsed/collapsing wetlands after a consensus has been reached on what constitutes peat collapse, how it occurs, and how to correctly identify it in the field.When searching for peer‐reviewed literature relevant to coastal wetland peat collapse, the inconsistency in the use of the term is readily apparent. Only five publications were found using the term “peat collapse” in reference to their original research findings  dominated by undecomposed to slightly decomposed plant tissue , potentially resulting in elevation loss due to the sloughing and transport of this loose, unconsolidated material.Quantification of a loss in soil strength or structure is also limited in the peat collapse literature and often does not co‐occur with measurements of soil elevation, hindering our ability to connect these two concepts as key foundations of peat collapse. Approaches for assessing changes in soil structure and strength focus on (1) identifying changes in soil bulk density  and (2) the use of geotechnical engineering tools, such as shear stress vanes Whelan  and coneSignificantly lower soil shear strength in deteriorating wetlands relative to reference wetlands has been observed, particularly in the root zone , making it difficult to identify the precise timescale when the elevation loss occurred. The most rapid rates of elevation loss published are ~2.8 cm within 5 months in an excessively flooded Texas marsh  some type of non‐erosional (often interior wetland) soil elevation loss. The majority of studies we evaluated were identified by starting with a published paper that made clear reference to “peat collapse”  and excessive flooding. Measurements before and after the treatment revealed a 9–15 cm decrease in hummock surface elevation. Additionally, a reduction in soil depth above the 137Cs 1963 depth horizon without a corresponding loss of the 137Cs inventory indicated that the volume loss was non‐erosional. Rather, the authors suggest the elevation loss was due to the “collapse of the living root network,” possibly in combination with accelerated decomposition and loss of root turgor and porosity  has been observed in coastal Louisiana (USA), where several studies document the rapid loss of large areas of marsh, despite an adequate sediment supply and negligible wave energy , or the mass of the soil itself decreases .To date, studies investigating peat collapse in coastal wetlands have focused almost exclusively on th Table . AlthougCoastal wetland peat, like all soils, is composed of three components: mineral (inorganic) material, organic matter, and pore spaces (filled with gas and/or water). The contribution of mineral material to coastal wetland soils tends to increase with proximity to the coast, tidal creeks, and/or rivers, while wetland areas that are further removed from high‐energy hydrologic exchanges are typically dominated by organic‐rich soils originating from undecomposed plant litter Odum . These lThe exceptionally high contribution of pore spaces to the overall volume of organic coastal wetland soils may suggest a reduction in the void space occupied by gas and/or water is an obvious mechanism for peat collapse. However, upon further evaluation, there is one critical caveat to the compression of pore space as a viable and widespread explanation: under normal temperature and pressure, water is essentially incompressible  penetration into waterlogged soils, resulting in the reliance on slower, less efficient microbial respiration pathways .In organic wetland soils, mineralization rates are generally limited by the rate of oxygen  on coastal wetland systems, which combines the addition of an alternative electron acceptor with commonly limiting nutrients. Outcomes of these fertilization experiments are often site specific. Several have found accelerated decomposition rates and/or CO2 flux rates under fertilization  would accelerate respiration significantly enough, or quickly enough, to account for abrupt measureable elevation loss in coastal wetlands. However, these additions may contribute to soil mass loss and destabilization in combination with vegetation death and other mechanisms of elevation loss.To test if accelerated SOM mineralization due to labile C or electron acceptor addition is a plausible mechanism of peat collapse, COe et al.  found tht et al.  observedBased on the nature of peat soils, inorganic mineral matter should comprise no more than 4–20% of the soil volume , or drought conditions, and would result in decreased soil volume and increased surface bulk density.Destabilization of excessively water‐logged SOM following the loss of structurally supportive live roots. This scenario is likely in systems experiencing sea level rise or increased flooding due to hydrologic modifications, and in highly organic soils composed of partially or undecomposed detritus prone to dilation and dispersion. Under these conditions, surface soils and new detrital inputs produce an unconsolidated floc characterized by low soil shear strength. This material can disperse throughout the water column, resulting in a loss of soil mass, and be susceptible to transport off‐site with minimal currents or wave energy.Compaction of gas‐filled aerenchyma tissue in wetland plant roots, and possibly root channels, due to severe vegetation stress  and/or vegetation death. This may occur under any hydrologic regime if aerenchyma and root channels retain their status as gas‐filled spaces. Elevation loss could result from a decrease in soil volume (and subsequent increase in surface soil bulk density) if the gas‐filled spaces collapse and the soil consolidates, or from a loss of soil mass (and subsequent decrease in soil shear strength) if root contraction destabilizes soil material.2 from drying or mixing with open water; NO3− from anthropogenic inputs or internal cycling; or SO42− from saltwater intrusion). This scenario is possible under any hydrologic regime and would result in a loss of soil mass to the atmosphere, likely accompanied by decreased soil shear strength.Acceleration of soil mineralization due to the addition of a limiting electron donor , or electron acceptor  the soils must have a high organic matter content, (2) there is a concomitant decrease in soil strength and structural integrity with the elevation loss, and (3) the resulting elevation and conditions are unconducive to natural recovery . For comparison, reports of elevation loss in the root‐zone of organic soils caused by drops in the water table and soil shrinkage  has already occurred  may be diagnostic of pore space compaction or root channel collapse in intertidal locations. At sites that are predominately subtidal, or remain saturated nearly continuously, a loose, flocculent layer above the marsh platform with reduced soil shear strength, may be observed. This suggests destabilization of waterlogged peat or mineralization, both of which result in mass loss of SOM. It is also important to note that shallow, open‐water pools in coastal wetlands can be a natural feature in the landscape  unique to organic soils that is initiated by severe stress or death of the existing plant community. Following root decline, aerenchyma contracts and the loss of the structural support provided by live roots allows for possible pore space or root channel compression, SOM swelling and deconsolidation, or accelerated mineralization. Without significant autotrophic C sequestration, the area becomes a net C source, which may be further exacerbated if the site is also experiencing saltwater intrusion, nutrient enrichment, or decreased water level. The elevation loss is likely to manifest within 5 months to 3 yr of vegetation decline and could range from 1 to 15 cm. Additional research is needed to experimentally test the validity of each proposed mechanism of coastal wetland peat collapse. Management efforts should focus on landscape‐scale monitoring of vegetation health as a precursor to elevation loss. Moreover, as new research investigates processes and case studies related to coastal wetland peat collapse, it is critical that terminology be codified and consistently applied so the knowledge base can be expanded and made easily accessible to new researchers.


Melilotus is an important forage legume, with high values as feed and medicine, and widely used as green manure, honey plant, and wildlife habitat enhancer. The genetic diversity, structure and subdivision of this forage crop remain unclear, and plant genetic resources are the basis of biodiversity and ecosystem diversity and have attracted increasing attention. In this study, the whole collection of 573 accessions from the National Gene Bank of Forage Germplasm  and 48 accessions from the National Plant Germplasm System  in genus Melilotus were measured with respect to five seed characters: seed length, width, width-to-length ratio, circumference and 100-seed weight. Shannon’ genetic diversity index (H’) and phenotypic differentiation (Pst) were calculated to better describe the genetic diversity. The ITS and matK sequences were used to construct phylogenetic trees and study the genetic relationships within genus Melilotu. Based on seed morphology and molecular marker data, we preliminarily developed core collections and the sampling rates of M. albus and M. officinalis were determined to be 15% and 25%, respectively. The results obtained here provide preliminary sorting and supplemental information for the Melilotus collections in NGBFG, China, and establish a reference for further genetic breeding and other related projects. Melilotus is a forage legume of family, including 19 annual and biennial species, and three of the species have been cultivated: M. albus, M. officinalis, and M. indicus3. In comparison with most other forages, Melilotus has the advantages of tolerating extreme environmental conditions and providing high seed yields5. The nitrogen fixation rate of Melilotus is superior to those of other legumes, and it is beneficial in crop rotations6. Additionally, Melilotus can be used as a crop fertilizer7 as well as nectar plants8 and has important medicinal value due to the biological activity of their coumarins, which have many biological and pharmacological activities, including anti-HIV and anti-tumor effects9. During the past few years, Melilotus, as a good leguminous forage, has received much attention11. Plant genetic resources are the most essential of the world’s natural resources and are of paramount importance for genetic improvement, germplasm innovation, and plant biology research; they play an important role in guaranteeing the food and nutrition security of an increasing population13. Abundant genetic resources have great potential to provide novel beneficial genes14.16. Although a large number of plant germplasm materials have been conserved in gene banks, their use is limited because of their overwhelming amount and lack of management17. According to Food and Agriculture Organization (FAO) estimates, only 1 million to 2 million of the 7.4 million germplasm accessions are specific and non-repetitive, while the remaining germplasm accessions contain different levels of repetition. An assessment and classification of the diversity is essential for effective utilization of the germplasm, and core germplasm development has been proposed for better management and use of the collections available in gene banks19. A core collection can be defined as a minimum set of accessions representing maximum genetic diversity, and collections of the core set are described accurately and evaluated and managed carefully, for better conservation and utilization of germplasm accessions20. The common method of constructing a core set is to group the whole collection by morphological or molecular characteristics, then selecting the representative core accessions to form subcore groups and combining all subcore groups to construct the final core set22. The described core accessions could be more efficiently used for pre-breeding, genomic studies and conservation programs in gene banks.During the last 3–4 decades, major advances have been made in conserving these resourcesMelilotus species, including the whole collection of 573 accessions from NGBFG, China, and 48 accessions from NPGS, USA, was analyzed to present a comprehensive view of the genetic diversity and phylogenetic structure among these accessions and provide the basis for constructing a core germplasm set. In our previous study, we selected 199 accessions to assess the genetic diversity in Melilotus and gain an initial understanding23. Seed morphology and the sequences of ITS and matK were adopted to analyze genetic diversity and form core collections of Melilotus. Using seed traits to assess genetic diversity in the germplasm is advantageous in comparison with the use of other plant organs, as seeds are easy to collect and store24. More importantly, seed morphological traits can be utilized for species identification as well as selection criteria in crop improvement programs26. The nuclear DNA ITS and chloroplast DNA matK have been widely applied in studies of inferring phylogenetic relationships at lower taxonomic levels and have been successfully used to analyze plant systematics29. The previous studies in Fabaceae indicated that the rate and pattern of ITS sequence mutation are appropriate for resolving relationships among species and genera30, as well as revealed that matK sequence can be used in phylogenetic analyses to successfully resolve relationships even at the species level31. Additionally, these sequences showed high stability and discrimination in Melilotus32. Examining both sequences and seed morphology might be an efficient method to analyze variation among Melilotus accessions and construct core sets.Here, a total of 621 accessions of 18 p < 0.05) differences among species, but the values of all traits overlapped a lot in range for many species .The morphologic traits in seeds are presented in Fig. ies Fig. . The boxmatK sequences also performed well, with a high amplification rate of 99.3%. Based on these sequences, we constructed four phylogenetic trees to analyze the genetic diversity and phylogenetic structure of 18 species in Melilotus.A total of 1145 sequences were newly amplified for this study. The nuclear DNA ITS sequences were successfully amplified for all 621 accessions, and the Vicia sativa, Medicago sativa and Trifolium repens as outgroups. Most species showed distinct diversity, and the result was similar to that of the previous study, in which 18 species formed two groups23. Ten species, which were M. albus, M. suaveolens, M. altissimus, M. dentatus, M. elegans, M. hirsutus, M. officinalis, M. polonicus, M. tauricus and M. wolgicus, formed a clade as the first group, and the others formed the second group. Most species showed small intraspecific distances, and several species, including M. albus, M. suaveolens and M. dentatus, have a very close genetic relationship. Nevertheless, not all accessions of M. suaveolens gather in a subclade, since several accessions came together with M. polonicus. It might be caused by gene flow and the pervious study indicated M. suaveolens could successfully crossed with M. albus and M. polonicus33. In contrast, the matK sequences didn’t perform well in assessing phylogenetic relationships in interspecific level. The diversity among 18 species revealed by matK sequences was smaller, especially in the species M. albus, M. altissimus, M. elegans, M. officinalis, M. polonicus, M. suaveolens and M. wolgicus, as shown by their similar branch lengths  of range and the variable rate (VR%) for the coefficient of variation could evaluate the property of core collections35. We tried two different sampling methods, multiple clustering random sampling and multiple clustering preferred sampling. The core sets based on different sampling methods have different characteristics and are suitable for different studies. Random sampling can represent the genetic diversity structure of the initial collections and preferred sampling can keep the accessions with special or valuable characteristics in the initial collection35.Two species, M. albus did not change significantly as the sampling ratio reached 15%, and then genetic diversity of seed morphology declined smoothly as the sampling proportion increases. For M. officinalis, the proper sampling ratio was 25% or 20% based on the values of MD% and CR%, but the nucleotide diversity and haplotype diversity changed steadily until sampling proportion reached 25%. According to multiple clustering preferred sampling, nearly all MD% values are 0 and CR% values are 100%, and the VR% values changed steadily until sampling proportions of M. albus and M. officinalis reached 15% and 25%, respectively. However, through analysis of H’, nucleotide diversity and haplotype diversity, the variation of M. officinalis changed steadily from 20% sampling ratio. The core sets that have a good representativeness of the initial collection wouldn’t have rapid changes about diversity. To obtain more genetic diversity, the sampling ratios of M. albus and M. officinalis were determined to be 15% and 25%, respectively.According to multiple clustering random sampling Table , the valM. officinalis is higher than that of M. albus, as shown in Table Overall, the coefficient of variation, genetic diversity index and sequence diversity were increased in the core collections, which was expected because diversity increased after the elimination of similar accessions during the development of the core germplasm sets. Additionally, the genetic diversity of 36. As a high-quality forage species, Melilotus has many advantages and grows widely in China, and nearly 600 accessions of Melilotus were collected in NGBFG, China. In our previous study, we employed 199 accessions of 18 species to analyze genetic diversity36. The results indicated that Melilotus had high genetic variation among species, and thus, we further studied the genetic diversity and phylogenetic relationships of all Melilotus accessions in NGBFG, China. To better protect and utilize these resources, we analyzed the diversity of all accessions in NGBFG based on morphological and molecular data and developed core collections of two species. Morphological and molecular data can be analyzed separately or in combination to determine genetic diversity37. In addition, when constructing a core collection, a combination of both phenotypic and genotypic data is thought to be more useful than either one of these individually38. Based on seed morphological traits and the ITS and matK sequences of Melilotus, we analyzed the genetic diversity of this genus and developed core sets to conserve and utilize germplasm resources efficiently.Conservation of plant genetic diversity is essential for present and future human well-being. Over the past few years, there have been many welcome developments in the conservation of forage germplasm resourcesMelilotus showed a larger Pst parameter than some agronomic traits, such as plant height and dry matter yield39. These traits are important for seed establishment and survival40. Small-seeded species could produce more seeds for a given amount of energy than large-seeded species; however, large-seeded species, such as M. italicus and M. speciosus, develop seedlings that can better tolerate the many stresses encountered during establishment41. The variations in seed morphology could also reflect the wide range of habitats in Melilotus. This information on seed trait variation among accessions could also enhance cultivar development programs that focus on improving seedling survival or seed yield42. According to the phylogenetic trees based on the ITS sequences, almost all accessions could be divided by species. The first group, including M. albus, M. suaveolens was the recently diverged lineages, within the Melilotus genus. Additionally, the ITS sequences showed high discrimination in Melilotus in this study, while the results revealed that the matK sequences did not perform as well as the ITS sequences. The matK sequences might be more suitable for analyzing relationship at higher taxonomic levels43, but they can also reflect the variation among and within species to a certain degree44. Eighteen species included many subclades, but many accessions within each species showed the same branch lengths in both trees. Although the number of M. albus accessions was large, many repetitions were present, because of the frequent exchange of germplasm resources or resubmission of the same accessions. Clarifying the phylogenetic relationship and evaluating the genetic diversity of these accessions will provide a foundation for effective utilization of Melilotus accessions in NGBFG.According to Fig. Melilotus, M. albus and M. officinalis are widely used in forage production and herbal medicine due to the biological activity of their coumarins39. Comparing M. albus with M. officinalis, the seed morphologies are similar  are required to prefect the development of core germplasm collections. Although many rare alleles might not be captured in the core collections, developing core collections could help breeders increase efficiency and utilize genetic resources since cultivar development in Melilotus were evaluated in the study, and the details of these accessions are presented in Supplementary Table Melilotus. To extract DNA, approximately 25 seeds of each accession were polished because of their hardness and then germinated at 24 °C after incubation in a 16-h light/8-h dark cycle. After two weeks, the seedlings were rinsed by distilled water, collected separately, frozen in liquid nitrogen and maintained at −80 °C until extracted.A total 621 accessions of Five characters of seeds were measured, including length, width, width-to-length ratio, circumference and 100-seed weight. We selected 100 seeds of each accession at random and measure their morphology using an analytical balance and WinSEEDLE, an image analysis system for morphological and disease analysis of seeds and needles.49. The target DNA fragments, the internal transcribed spacer (ITS) and chloroplast locus matK, were amplified and sequenced51. Amplification was performed by polymerase chain reactions (PCR) in 25-µL mixtures containing 12.25 µL of 2× reaction mix, 2 μL of each primer (1 μmol/mL), 2 μL of template genomic DNA (50 ng/μL), 0.25 µL of Golden DNA polymerase and 6.5 μL of deionized water. The primers and details of amplification programs were listed in Supplementary Table Total genomic DNA was extracted from whole seedling material according to the SDS (sodium dodecyl sulfate) method53. The haplotype diversity and nucleotide diversity were computed by DnaSP 6.1154. The phylogenetic trees were drawn by ClustalW of MEGA 6.0 and MrBayes 3.2 software. The Bayesian method was adopted with the default settings and the GTR model with gamma-distributed rate variation across sites and a proportion of invariable sites 55 and operational generation number and sampling frequency were set to 100000000 and 100000, with Medicago sativa, Trifolium repens and Vicia sativa as outgroups. The morphological traits were analyzed using the statistical software package SPSS v16.037. The coefficient of variation, phenotypic differentiation and Shannon’ genetic diversity index (H’) were calculated to analyze seed morphological diversity. The phenotypic differentiation coefficient (Pst) was calculated as follows: Pst = (σ2t/s)/(σ2t/s + σ2s), where σ2t/s is the variance portion among populations and σ2s is the variance portion within populations56. Shannon’s diversity index was calculated as follows: H’ = − ∑ pi Ln pi, where pi is the proportion of each phenotypic trait57.Both ends of the DNA sequences were trimmed to remove unalignable sequences upstream and downstream of the homologous sites by the Contig Express module of Vector NTI Suite 6.0  and aligned by DNAMAN 7.058, and Hu et al. (2000) suggested that standardized Euclidean distance combined with nearest distance method was an appropriate genetic distance for constructing core collections in this strategy35. We tried two sampling methods, multiple clustering random sampling and multiple clustering preferred sampling, to determine the appropriate sampling method and proportions35. Multiple clustering random sampling: one accession from each subgroup with two accessions at the lowest level of sorting is randomly selected. If there is only one accession in a subgroup, it is directly sampled for the next cluster. Multiple clustering preferred sampling: accessions with maximum or minimum values of traits are preferred to select from each subgroup at the lowest level of sorting. Both accessions are selected if two accessions in a subgroup have maximum or minimum values of the traits. The other procedures are similar to the random sampling strategy.We used QGAStation 2.0, a software for classical quantitative genetics, to construct a core set according to the seed morphology. The strategy for constructing core collections adopted the least distance stepwise sampling based on genotypic values58: mean difference percentage (MD%), variance difference percentage (VD%), coincidence rate of range (CR%) and changeable rate of coefficient of variation (VR%). Additionally, the Shannon’ genetic diversity index of seed morphology and the haplotype diversity and nucleotide diversity of sequences were calculated to assess the genetic diversity of the core collections. According to the genetic diversity comparison of these core collections, we could determine the best sampling proportion, which was considered to be representative while maintaining a high level of genetic diversity.Six sampling proportions were chosen in the study, which were 5%, 10%, 15%, 20%, 25% and 30%. We calculated four parameters to evaluate the representation of the core germplasm at different sampling ratesSupplementary Information