Exploring the Phylogeography of Ancient Platycladus orientalis in China by Specific-Locus Amplified Fragment Sequencing

Understory vegetation diversity patterns of Platycladus orientalis and Pinus elliottii communities in Central and Southern China

As a vital component of arbor forests, understory vegetation serves as an essential buffer zone for storing carbon due to its strong capacity for community regeneration. This study aimed to identify the diversity pattern and construction mechanism of Platycladus orientalis and Pinus elliottii understory vegetation based on large-scale sample surveys. The Bayesian Information Criterion value of species abundance distribution (SAD) indicated that the Zipf and Zipf-Mandelbrot models were the best-fitting models. The SAD and gambin fitting results suggested that the Pi. elliottii community had a more balanced structure, with most species being relatively abundant. The multiple regression tree model detected four and six indicator species in P. orientalis and Pi. elliottii communities, respectively. The α-diversity index increased with a rise in altitude and showed a wavy curve with latitude. Linear regression between the β diversity and environmental and geographic distance indicated that the P. orientalis and Pi. elliottii understory communities tended to be dominated by different ecological processes. The partition of β diversity indicated that both communities were dominated by turnover processes, which were caused by environmental classification or spatial constraints. This study helped to understand the diversity maintenance in the P. orientalis and Pi. elliottii understory vegetation communities, and will benefit for diversity restoration and conservation of pure conifer forests.

Comparison of genetic diversity between ancient and common populations of Docynia delavayi (Franch.) Schneid

Docynia delavayi (Franch.) Schneid. (D. delavayi), is a wild fruit tree which combines edible, medicinal, ecological and ornamental uses. In this study, ancient and common populations of D. delavayi were examined for genetic diversity and structure using SSR markers. As a result, a total of 136 alleles were detected at 18 SSR loci, with the mean of 7.56 alleles. The value of Na, Ne, I, He and Nm of the ancient populations were lower than those of the common populations except for Ho and Fst. It indicates that the genetic diversity of the common populations is higher than that in ancient populations. The genetic differences between ancient populations were slightly greater than those between common populations, which demonstrated less gene flow between ancient populations. According to the analysis of molecular variance (AMOVA), the genetic variation within the common population was greater than that in the ancient population, indicating that there was a higher genetic diversity within the common population. Also, the clustering heatmap results are partially consistent with the principal coordinate analysis (PCoA) results. Moreover, the mantel test showed an extremely significant correlation between genetic and geography distance (r = 0.214, p < 0.0001). Based on this work, we proposed strategies for protecting, which offers a theoretical basis for their effective utilization and conservation of D. delavayi ancient tree resources.

Chloroplast and Nuclear Genetic Diversity Explain the Limited Distribution of Endangered and Endemic Thuja sutchuenensis in China

Narrow-ranged species face challenges from natural disasters and human activities, and to address why species distributes only in a limited region is of great significance. Here we investigated the genetic diversity, gene flow, and genetic differentiation in six wild and three cultivated populations of Thuja sutchuenensis, a species that survive only in the Daba mountain chain, using chloroplast simple sequence repeats (cpSSR) and nuclear restriction site-associated DNA sequencing (nRAD-seq). Wild T. sutchuenensis populations were from a common ancestral population at 203 ka, indicating they reached the Daba mountain chain before the start of population contraction at the Last Interglacial (LIG, ∼120-140 ka). T. sutchuenensis populations showed relatively high chloroplast but low nuclear genetic diversity. The genetic differentiation of nRAD-seq in any pairwise comparisons were low, while the cpSSR genetic differentiation values varied with pairwise comparisons of populations. High gene flow and low genetic differentiation resulted in a weak isolation-by-distance effect. The genetic diversity and differentiation of T. sutchuenensis explained its survival in the Daba mountain chain, while its narrow ecological niche from the relatively isolated and unique environment in the "refugia" limited its distribution.

Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods

BACKGROUND

Radiomics has shown promising results in the diagnosis, efficacy, and prognostic assessments of multiple myeloma (MM). However, little evidence exists on the utility of radiomics in predicting a high-risk cytogenetic (HRC) status in MM.

PURPOSE

To develop and test a magnetic resonance imaging (MRI)-based radiomics model for predicting an HRC status in MM patients.

STUDY TYPE

Retrospective.

POPULATION

Eighty-nine MM patients (HRC [n: 37] and non-HRC [n: 52]).

FIELD STRENGTH/SEQUENCE

A 3.0 T; fast spin-echo (FSE): T1-weighted image (T1WI) and fat-suppression T2WI (FS-T2WI).

ASSESSMENT

Overall, 1409 radiomics features were extracted from each volume of interest drawn by radiologists. Three sequential feature selection steps-variance threshold, SelectKBest, and least absolute shrinkage selection operator-were repeated 10 times with 5-fold cross-validation. Radiomics models were constructed with the top three frequency features of T₁ WI/T₂ WI/two-sequence MRI (T₁ WI and FS-T₂ WI). Radiomics models, clinical data (age and visually assessed MRI pattern), or radiomics combined with clinical data were used with six classifiers to distinguish between HRC and non-HRC statuses. Six classifiers used were support vector machine, random forest, logistic regression (LR), decision tree, k-nearest neighbor, and XGBoost. Model performance was evaluated with area under the curve (AUC) values.

STATISTICAL TESTS

Mann-Whitney U-test, Chi-squared test, Z test, and DeLong method.

RESULTS

The LR classifier performed better than the other classifiers based on different data (AUC: 0.65-0.82; P < 0.05). The two-sequence MRI models performed better than the other data models using different classifiers (AUC: 0.68-0.82; P < 0.05). Thus, the LR two-sequence model yielded the best performance (AUC: 0.82 ± 0.02; sensitivity: 84.1%; specificity: 68.1%; accuracy: 74.7%; P < 0.05).

CONCLUSION

The LR-based machine learning method appears superior to other classifier methods for assessing HRC in MM. Radiomics features based on two-sequence MRI showed good performance in differentiating HRC and non-HRC statuses in MM.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Genetic Diversity and Population Genetic Structure of Ancient Platycladus orientalis L. (Cupressaceae) in the Middle Reaches of the Yellow River by Chloroplast Microsatellite Markers

Ancient trees are famous for their life spans of hundreds or even thousands of years. These trees are rare, a testament to history and are important for scientific research. Platycladus orientalis, with the longest life span and a beautiful trunk, has become the most widely planted tree species and is believed to be sacred in China. Extensive declines in habitat area and quality pose the greatest threats to the loss of genetic diversity of ancient P. orientalis trees in the middle reaches of the Yellow River. Strengthening the protection of P. orientalis genetic resources is of great significance for the long-term development of reasonable conservation and breeding strategies. To better understand the genetic diversity and population structure of P. orientalis, we successfully analyzed four polymorphic chloroplast simple sequence repeat (cpSSR) loci and applied them to diversity and population structure analyses of 202 individuals from 13 populations in the middle reaches of the Yellow River. Based on the cpSSR data, 16 alleles were detected across 202 individuals, and a moderate level of genetic diversity was inferred from the genetic diversity parameters (H = 0.367 and AR = 1.964). The mean pairwise genetic differentiation coefficient (Fst) between populations was 0.153, indicating relatively high genetic population differentiations. Analysis of molecular variance (AMOVA) showed that only 8% of the variation occurred among populations. Structure analysis divided the 13 P. orientalis populations into two groups with no significant geographic population structure, which was consistent with the unweighted pair group method with arithmetic mean (UPGMA) and Mantel test results. These results may indicate that transplanting and cultivation by ancient human activities are the main factors responsible for the revealed pattern of genetic differentiation of ancient P. orientalis populations. Our research is of great significance for the future establishment of protection schemes and scientific breeding of P. orientalis.