Qinba area has a long history of tea planting and is a northernmost region in China where Camellia sinensis L. is grown. In order to provide basic data for selection and optimization of molecular markers of tea plants. 118 markers, including 40 EST-SSR, 40 SRAP and 38 SCoT markers were used to evaluate the genetic diversity of 50 tea plant (Camellia sinensis.) samples collected from Qinb. tea germplasm, assess population structure. In this study, a total of 414 alleles were obtained using 38 pairs of SCoT primers, with an average of 10.89 alleles per primer. The percentage of polymorphic bands (PPB), polymorphism information content (PIC), resolving power (Rp), effective multiplex ratio (EMR), average band informativeness (Ibav), and marker index (MI) were 96.14%, 0.79, 6.71, 10.47, 0.58, and 6.07 respectively. 338 alleles were amplified via 40 pairs of SRAP (8.45 per primer), with PPB, PIC, Rp, EMR, Ibav, and MI values of 89.35%, 0.77, 5.11, 7.55, 0.61, and 4.61, respectively. Furthermore, 320 alleles have been detected using 40 EST-SSR primers (8.00 per primer), with PPB, PIC, Rp, EMR, Ibav, and MI values of 94.06%, 0.85, 4.48, 7.53, 0.56, and 4.22 respectively. These results indicated that SCoT markers had higher efficiency. Mantel test was used to analyze the genetic distance matrix generated by EST-SSRs, SRAPs and SCoTs. The results showed that the correlation between the genetic distance matrix based on EST-SSR and that based on SRAP was very small (r = 0.01), followed by SCoT and SRAP (r = 0.17), then by SCoT and EST-SSR (r = 0.19). The 50 tea samples were divided into two sub-populations using STRUCTURE, Neighbor-joining (NJ) method and principal component analyses (PCA). The results produced by STRUCTURE were completely consistent with the PCA analysis. Furthermore, there is no obvious relationship between the results produced using sub-populational and geographical data. Among the three types of markers, SCoT markers has many advantages in terms of NPB, PPB, Rp, EMR, and MI. Nevertheless, the values of PIC showed different trends, with the highest values generated with EST-SSR, followed by SCoT and SRAP. The average band informativeness showed similar trends. Correlation between genetic distances produced by three different molecular markers were very small, thus it is not recommended to use a single marker to evaluate genetic diversity and population structure. It is hence suggested that combining of different types of molecular markers should be used to evaluate the genetic diversity and population structure. It also seems crucial to screen out, for each type of molecular markers, core markers of Camellia sinensis. This study revealed that genes of exotic plant varieties have been constantly integrated into the gene pool of Qinba area tea. A low level of genetic diversity was observed; this is shown by an average coefficient of genetic similarity of 0.74.

Background: The Qinba region is the transition region between Indica and Japonica varieties in China. It has a long history of Indica rice planting of more than 7000 years and is also a planting area for fine-quality Indica rice. The aims of this study are to explore different genetic markers applied to the analysis population structure, genetic diversity, selection and optimization of molecular markers of Indica rice, thus providing more information for the protection and utilization on germplasm resources of Indica rice. Methods: Fifteen phenotypic traits, a core set of 48 SSR markers which originated protocol for identification of rice varieties-SSR marker method in agricultural industry standard of the People's Republic of China (Ministry of Agriculture of the PRC, NY/T1433-2014, Protocol for identification of rice varieties-SSR marker method, 2014), and SNPs data obtained by genotyping-by-sequencing (GBS, NlaIII and MseI digestion, referred to as SNPs-NlaIII and SNPs-MseI, respectively) for this panel of 93 samples using the Illumina HiSeq2000 sequencing platform, were employed to explore the genetic diversity and population structure of 93 samples. Results: The average of coefficient of variation (CV) and diversity index (H_e) were 29.72% and 1.83 ranging from 3.07% to 137.43%, and from 1.45 to 2.03, respectively. The correlation coefficient between 15 phenotypic traits ranged from 0.984 to -0.604. The first four PCs accounted for 70.693% phenotypic variation based on phenotypic analysis. A total of 379 alleles were obtained using SSR markers, encompassing an average of 8.0 alleles per primer. Polymorphic bands (PPB) and polymorphism information content (PIC) was 88.65% and 0.77, respectively. The Mantel test showed that the correlation between the genetic distance matrix based on SNPs-NlaIII and SNPs-MseI was the largest (R²=0.88), and that based on 15 phenotypic traits and SSR was the smallest (R²=0.09). The 93 samples could be clustered into two subgroups by 3 types of genetic markers. Molecular variance analysis revealed that the genetic variation was 2% among populations and 98% within populations (the Nm was 0.16), Tajima’s D value was 1.66, the FST between the two populations was 0.61 based on 72,824 SNPs. Conclusions: The population genetic variation explained by SNPs was larger than that explained by SSRs. The gene flow of 93 samples used in this study was larger than that of naturally self-pollinated crops, which may be caused by long-term breeding selection of Indica rice in the Qinba region. The genetic structure of the 93 samples was simple and lacked rare alleles.

A total of 74,936 SNPs were employed to carry out population structure and genome-wide association studies and post-GWAS for hairiness character of the fifty-six samples including thirty-six Actinidia chinensis var. deliciosa, eighteen A. chinensis var. chinensis, and two A. polygama in the light of morphological observations. The percentage of heterozygous sites of A. chinensis var. deliciosa is higher than that of A. chinensis var. chinensis, which could be one of the reasons for A. chinensis var. deliciosa high disease resistance. Fifty-six samples were divided into two subgroups, in which the genetic distance, ranged from 0.17 to 0.99, according to their genetic divergence. Analysis of molecular variance shows that the frequency of genetic variations within the population is 83.53% and 16.47% between populations. F_st between the two populations is 0.14, and N_m is 1.60. Set at α ≤ 0.05, a total of 327 SNPs and 260 haplotypes were related to the hairiness character. A total of 246 proteins were annotated using GO and KEGG analyses, which indicated the membrane-related genes and stress-resistant metabolic pathways are related to the hairiness character of leaves, stems, and peels of kiwifruit. Protein interaction analysis showed that DNA-directed RNA polymerase was an important node protein that interacted with many proteins. The genetic basic in the fifty-six genotypes was rich. The results of clustering and morphological observations are not completely consistent, indicating the hairiness character play an important role in the classification of kiwifruit, in which two A. polygama were clustered together with those of A. chinensis var. chinensis. Phylogeny and haplotype analysis showed that the evolution of A. chinensis var. chinensis is later than that of A. chinensis var. deliciosa in A. chinesis. The loss of hairiness character on leaves, stems and peels of A. chinensis var. chinensis compare with A. chinensis var. deliciosa, which is also the result of its poor resistance.

Quantitative trait locus (QTL) mapping often yields associations with dissimilar loci/genes as a consequence of diverse factors. One trait for which very limited agreement between mapping studies has been observed is resistance to white mold in soybean. To explore whether different approaches applied to a single data set could lead to more consistent results, haplotype-trait association and epistasis interaction effects were explored as a complement to a more conventional marker-trait analysis. At least 10 genomic regions were significantly associated with Sclerotinia sclerotiorum resistance in soybean, which have not been previously reported. At a significance level of α = 0.05, haplotype-trait association showed that the most prominent signal originated from a haplotype with 4-SNP (single nucleotide polymorphism) on chromosome 17, and single SNP-trait analysis located a nucleotide polymorphism at position rs34387780 on chromosome 3. All of the peak-SNPs (p-value < 0.05) of each chromosome also appeared in their respective haplotypes. Samples with extreme phenotypes were singled-out for association studies, 25–30% from each end of the phenotypic spectrum appeared in the present investigation to be the most appropriate sample size. Some key genes were identified by epistasis interaction analysis. By combining information on the nearest positional genes indicated that most loci have not been previously reported. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggest potential candidate genes underlying callose deposition in the cell wall and mitogen-activated protein kinase (MAPK) signaling pathway-plant, as well as plant-pathogen interaction pathway, were activated. Integration of multi-method genome-wide association study (GWAS) revealed novel genomic regions and promising candidate genes in novel regions, which include Glyma.01g048500, Glyma.03g129100, Glyma.17g072200, and the Dishevelled (Dvl) family of proteins on chromosomes 1, 3, 17, and 20, respectively.

Background: Kiwifruit (Actinidiaceae family) is an economically important fruit tree in China and New Zealand. It is a typical dioecious plant that has undergone frequent natural hybridization, along with chromosomal ploidy diversity within the genus Actinidia, resulting in higher genetic differences and horticultural diversity between interspecific and intraspecific traits. This diversity provides a rich genetic base for breeding. China is not only the original center of speciation for the Actinidia genus but also its distribution center, housing the most domesticated species: A. chinensis var. chinensis, A. chinensis var. deliciosa, A. arguta, and A. polygama. However, there have been relatively few studies on the application of DNA markers and the genetic basis of kiwifruit plants. By combining information from chloroplast-specific SNPs and nuclear SCoT (nSCoT) markers, we can uncover complementary aspects of genetic variation, population structure, and evolutionary relationships. In this study, one chloroplast DNA (cpDNA) marker pair was selected out of nine cpDNA candidate pairs. Twenty nSCoT markers were selected and used to assess the population structure and chloroplast-specific DNA haplotype diversity in 55 kiwifruit plants (Actinidia), including 20 samples of A. chinensis var. chinensis, 22 samples of A. chinensis var. deliciosa, 11 samples of A. arguta, and two samples of A. polygama, based on morphological observations collected from China. Results: The average genetic distance among the 55 samples was 0.26 with chloroplast-specific SNP markers and 0.57 with nSCoT markers. The Mantel test revealed a very small correlation (r = 0.21). The 55 samples were categorized into different sub-populations using Bayesian analysis, the Unweighted Pair Group Method with the Arithmetic Mean (UPGMA), and the Principal Component Analysis (PCA) method, respectively. Based on the analysis of 205 variable sites, a total of 15 chloroplast-specific DNA haplotypes were observed, contributing to a higher level of polymorphism with an Hd of 0.78. Most of the chloroplast-specific DNA haplotype diversity was distributed among populations, but significant diversity was also observed within populations. H1 was shared by 24 samples, including 12 of A. chinensis var. chinensis and 12 of A. chinensis var. deliciosa, indicating that H1 is an ancient and dominant haplotype among the 55 chloroplast-specific sequences. H2 may not have evolved further.The remaining haplotypes were rare and unique, with some appearing to be exclusive to a particular variety and often detected in single individuals. For example, the H15 haplotype was found exclusively in A. polygama. Conclusion: The population genetic variation explained by chloroplast-specific SNP markers has greater power than that explained by nSCoTs, with chloroplast-specific DNA haplotypes being the most efficient. Gene flow appears to be more evident between A. chinensis var. chinensis and A. chinensis var. deliciosa, as they share chloroplast-specific DNA haplotypes, In contrast, A.arguta and A. polygama possess their own characteristic haplotypes, derived from the haplotype of A. chinensis var. chinensis. Compared with A. chinensis, the A.arguta and A. polygama showed better grouping. It also seems crucial to screen out, for each type of molecular marker, especially haplotypes, the core markers of the Actinidia genus.