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Environmental changes could dramatically affect biodiversity and the distribution of species. Predicting and understanding the dynamics of vegetation distribution can provide valuable insights into ecosystems’ response to climatic and environmental changes. Opisthopappus(containing two species Opisthopappus taihangensisand Opisthopappus longilobus) is an endangered and endemic genus in the Taihang Mountains of China, which is regarded as a center of distribution and diversity for many plant genera. However, little is known about climatic and environmental changes impact on the distribution of Opisthopappus. Thus, based on maximum entropy model (MaxEnt), we predicted the potential distribution under past, current and future climate conditions, explored the niche difference between the two species and determined the critical environmental factors. Our findings revealed that the distribution areas of O. taihangensisincreased from the last interglacial to the last glacial maximum (LGM) periods, while that of O. longilobusdecreased gradually. Compared to LGM, O. taihangensisand O. longilobusdecreased their distribution ranges in the mid-Holocene period, which are generally similar to the current distribution areas of two species. In the future periods, the predicted distribution areas increased for both species and presented a trend toward the center areas of the Taihang Mountains. Meanwhile, precipitation of wettest month and isothermality were the most important factors influencing the distribution of Opisthopappus. Significant niche differentiation between O. taihangensisand O. longilobusoccurred gradually with time. These results provide useful information for understanding evolution and conservation of O. taihangensisand O. longilobusin Taihang Mountains.

Genetic diversity of high‐molecular‐weight (HMW) glutenin subunits is often used for wheat improvement because of its correlation with end‐use quality of wheat. The objectives were (a) to characterize and analyze the HMW‐GS composition of common wheat, (b) determine the diversity of high‐molecular‐weight glutenin subunits, and (c) elucidate the distribution characteristics of wheat good‐quality subunit and quality classification. The results revealed a total of 15 different alleles (3 at Glu‐A1, 8 at Glu‐B1, and 4 at Glu‐D1) and 35 allele combinations. Glu‐A1c(57.92%), Glu‐A1a(62.94%), Glu‐A1c(55.86%) appeared to be the most frequent alleles at Glu‐A1in Hebei, Henan, and Sichuan provinces, respectively. The Glu‐B1cwas the most common allele at the Glu‐B1locus in all three provinces, with frequencies of 48.75%, 55.24%, and 29.66%, respectively. Glu‐D1a(66.25%), Glu‐D1d(53.85%), Glu‐D1a(55.17%) at the Glu‐D1locus appeared to be the common alleles in Hebei, Henan, and Sichuan provinces, respectively. Cluster analysis based on allelic similarity of Glu‐1 loci classified the 528 wheat cultivars into two major categories. These results indicated that the HMW glutenin allele compositions are not optimal for the current varieties in these provinces. A high level of quality improvement may be implemented by increasing the frequencies of Glu‐A1a(1) or Glu‐A1b(2*), Glu‐B1i(17 + 18), Glu‐D1d(5 + 10). Our results revealed clear directions for wheat quality improvement in these provinces.

Seed size is one of the vital traits determining seed appearance, quality, and yield. Untangling the genetic mechanisms regulating soybean 100-seed weight (100-SW), seed length and seed width across environments may provide a theoretical basis for improving seed yield. However, there are few reports related to QTL mapping of 100-SW across multiple ecological regions. In this study, 21 loci associated with seed size traits were identified using a genome-wide association of 5361 single nucleotide polymorphisms (SNPs) across three ecoregions in China, which could explain 8.12%–14.25% of the phenotypic variance respectively. A new locus, named as SW9-1on chromosome 9 that explained 10.05%–10.93% of the seed weight variance was found significantly related to seed size traits, and was not previously reported. The selection effect analysis showed that SW9-1locus has a relatively high phenotypic effect (13.67) on 100-SW, with a greater contribution by the accessions with bigger seeds (3.69) than the accessions with small seeds (1.66). Increases in seed weight were accompanied by increases in the frequency of SW9-1Tallele, with >90% of the bred varieties with a 100-SW >30 g carrying SW9-1T. Analysis of SW9-1allelic variation in additional soybean accessions showed that SW9-1Tallele accounting for 13.83% of the wild accessions, while in 46.55% and 51.57% of the landraces and bred accessions, respectively, this results indicating that the SW9-1locus has been subjected to artificial selection during the early stages of soybean breeding, especially the utilization of SW9-1Tin edamame for big seed. These results suggest that SW9-1is a novel and reliable locus associated with seed size traits, and might have an important implication for increasing soybean seed weight in molecular design breeding. Cloning this locus in future may provide new insights into the genetic mechanisms underlying soybean seed size traits.

Abstract: The morphological similarity of Elymus trachycaulus to the Eurasian E. caninus has often been noted. This has lead to controversial and contradicting taxonomic treatments. Nevertheless, there has been no systematic investigation on molecular genetic similarity between E. trachycaulus and E. caninus. In this study, random amplified polymorphic DNA (RAPD) analysis was used to study the similarity between the two species. RAPD analysis of 38 samples representing E. caninus and E. trachycaulus complex yielded 111 interpretable RAPD bands. The Jaccard’s similarity values for E. caninus ranged from 0.38 between accessions H10345 and H10353 to 0.97 between accessions H8745 and H10096, with an average of 0.67. The Jaccard’s similarity values for E. trachycaulus complex ranged from 0.09 between E. trachycaulus ssp. subsecundus (PI 537321) and E. trachycaulus ssp. violaceus (PI 272612) to 0.78 between accessions PI 315368 and PI 372644, with an average of 0.43. The results from different analyses (NJ and PCA) were similar but not identical. The molecular genetic separation between E. caninus and E. trachycaulus was consistent. The PCA analysis clearly separated all E. caninus accessions from E. trachycaulus and its subspecies. The NJ analysis also showed separation between most accessions of E. caninus and E. trachycaulus. Further analysis excluding E. trachycaulus ssp. subsecundus and ssp. violaceus revealed that E. caninus species and E. trachycaulus species were clearly separated into two distinct groups. The RAPD data thus support the treatment of E. caninus and E. trachycaulus as distinct species. The analyses further indicate that E. violaceus is nested within E. trachycaulus, and more related to E. trachycaulus complex rather than to E. caninus.