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Population genomics and morphological features underlying the adaptive evolution of the eastern honey bee (Apis cerana)


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- Population genomics and morphological features underlying the adaptive evolution of the eastern honey bee ( Apis cerana.
- Bees can pollinate in various environments and climates and play important roles in maintaining the ecological balance of the earth..
- The ratios of the unique labels of all samples were .
- cerana in North China revealed that some physical obstacles, especially the overurbanization of the plains, have isolated the populations of this species..
- Understanding the im- pact of the environment on biological genetic diversity can not only clarify the course of evolution but can also provide information on how to protect the ecological en- vironment [1, 2].
- Bees have unique ecological value, and one-third of human food is derived from insect pollin- ation, which is critical for maintaining the dynamics of the ecosystem.
- cer- ana was defined as one of the most important pollina- tors in China, domesticating the region for more than 2000 years [8].
- 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0.
- Full list of author information is available at the end of the article.
- cerana is at the center of research in evolutionary biology, which at- tempts to understand how the population responds to climate change or environmental insults, thereby provid- ing basic knowledge of the evolution and adaptation of A.
- The accuracy of the division of A.
- cerana can also be used to determine the genetic variation of the adaptive and economic shape, thereby providing an in-depth un- derstanding of the genetic structure of A.
- The morphological measurements of the collected A..
- cerana from 31 populations col- lected from 11 regions in China (Mengyin (MY), Yiyuan (YY), Rizhao (RZ), Qingdao (QD), Linqu (LQ) and Zaozhuang (ZZ) Chongqing (WL), Sichuan (QC), Anhui (LA), Shanxi (HZ) and Hainan (WC)) and used the aver- age of the morphological data of A.
- In par- ticular, RZ, LQ, QD, and WC were relatively close in the four regions of the third group.
- We found that these re- gions were located in coastal areas, which seemed to be related to the color of the bees.
- in the size of the Hainan Bee (WC) compared to other bees, whereas clustering according to the angle of right forewing showed no difference between the 12 indicators of wing geometry and the total 39 traits..
- cerana ecological type of the sampling area.
- The results of the principal component analysis (PCA) scatter plot of principal factor 1 (variation 29%) and principal factor 2 (variation 20.21%) further sup- ported the patterns (Fig.
- MY, ZZ, and QD showed different degrees of pedigree, and approximately one- half of the MY area (MY1 and MY2) showed a special lineage with clear differences in the area.
- These results were further supported by the phylogenetic tree of the SNP data, as analyzed with Tessal 5.0 [28] (Fig.
- We studied the environmental characteristics of the bee sampling sites because they play important roles in the differentiation of A.
- Prior to genetic diversity analysis, we performed second- ary filtering of the SNP data.
- 3 Principal component analysis of the population structure in different regions of A.
- a Scatter plot of the main component 1 to 2 (PCA1 vs PCA2) from North China, Central China, and Hainan.
- b Scatter plot of the main component 1 to 2 (PCA1 vs.
- PCA2) from the 11 regions of LA, WC, LQ, MY, QD, RZ, HZ, QC, YY, ZZ, and WL (c) After removing the regions of RZ, ZZ, LQ, and QD, the RZ, ZZ, LQ, and QD regions were removed according to the sampling region in the scatter plot (d) of the main factor 1 and main factor 2.
- 0.15) were consistent with the overall heterogeneity of the population structure and gene flow.
- The Fst difference between the different regions of the.
- central mountainous region (HZ, WL, QC), the lowest Fst average value and the highest gene flow mean indi- cated that the genetic composition of the central moun- tainous region was similar, and the degree of differentiation was low, whereas A.
- Pic measured the de- gree of variation of the population DNA (the overall Pic average was 0.236).
- Among these regions, the QC region (QC1, QC2) has the lowest Pic at 0.209, whereas the average Pic of the QD region (QD1, QD2) was the high- est at 0.274.
- A comparison of the STRUCTURE stacking map with a K value of 3 (Fig.
- The results of the tree model were consistent with the population state and phylogenetic tree (Fig.
- Table S6) [33] to further understand the characteristics of the mixed population.
- We calculated the correspond- ing f3 statistic for all possible combinations of the three mixed populations.
- We used all sampled groups in- formation to generate a population maximum likelihood tree (Additional file 1: Figure S1), and the residual model was used to obtain a more intuitive understanding of the mixing between the populations (Fig.
- The difference between the genetic distance and geo- graphical distance calculated by the paired Fst is one of the most common methods for assessing the spatial.
- The different regions are colored according to the geographical location, and the scale shows 10 times the average standard error of the sample covariance matrix W.
- c Residual map of the residual fit of the maximum likelihood tree calculated using 31 populations without migration.
- communication of the population structure [34–36].
- The re- sults show that the spatial structure is not strong, and the mixed terrain of the North China Plain and the mountain could be the cause of fluctuation.
- (Additional file 11: Table S10), indicating the importance of the processing of signals and responses when bees adapt to different environments.
- 7 Identifies the different SNP loci assumed under the selection of the direction of the Fst outlier method.
- We separately performed enrichment analysis of the genes under balanced selection and directed selection..
- Overall, the classification of the angle of right fore- wing was consistent with the classification that included all traits.
- The two migrations of the Treemix population phylo- genetic tree revealed signs of migration for QD, LQ, RZ and the central region, while the residual plot showed signs of mixing between ZZ and QD.
- mellifera subspecies of the same lineage was 0.05 to 0.15 [30].
- The results of the Mantel test showed that geographical distance had little effect on population differentiation, which is consistent with the results of studies using microsatellite markers [56, 57].
- The social behavior of bees helps the population maintain the homeostasis of the nest and counteract changes in the external environment [62, 63]..
- The re- sults of the enrichment analysis showed that equilibrium selection plays an important role in maintaining the di- versity of alleles and increasing the stability of the popu- lation.
- evolution of the population.
- cerana species, as well as morphological characteristics and genomic methods, to provide insights into the differentiation and adaptation of the species in China.
- We proposed a method for the rapid identification of the morph- ology of the wing and found some historical migra- tion between the North and Central regions.
- This test was carried out in accordance with the indica- tor project of the honeybee morphology researcher [68, 69] and the color standards of A.
- First, a picture of the entire body, which included the color pat- tern of the bee specimen, was taken, and tweezers were used to remove the front and rear wings from the chest..
- 10 The position of the sample in China, where the blue area represents the dense sampling site of the representative area of North China f10:2 (Shandong).
- Table 5 Geographical information of the A.
- and color aspect measurement of the lip base, upper lip, small scutellum SC area, K area, B area, second back board, third back board, and fourth back board (a total of 39 index).
- cerana was randomly selected from each of the sam- pled sites for sequencing, and a tag sequencing library of A.
- The sequential aggregation method classified all samples to obtain an intuitive understanding of the population structure..
- The ratio of the minor allele frequency (MAF) to the polymorphic SNP (Pic) was cal- culated using a custom Perl script.
- The Fis, Fst, and Fit values of the SNP locus in 243 samples were statistically analyzed using Genepop software (version .
- The Mantel test of the Fst matrix and distance matrix was performed using the ade4 package in R [37].
- The method constructed a differentiation tree of the population and then identified the potential events of the population mixture from the residual covariance matrix..
- The genome of each bee was located in a predeter- mined set K, and the variable ancestor ratio was deter- mined by the allele frequency of the population.
- was performed without prior knowledge of the demo- graphic identity by simulating 50,000 preburning steps and 100,000 iterations of the MCMC algorithm per run..
- Using TASSEL v5.0 [28] and SPSS 22 to perform PCA of the genetic and morphological traits of different individuals, respectively, enabled us to visualize the correlations be- tween individual bees in individuals/regions on a multi- dimensional scale..
- The average Fst of the set “ dis- tance level ” was calculated separately to generate a polyline “interference graph” that was combined with the Manchester correlation map for a more intuitive view..
- The layer- ing method we used was a modification of the FDIST method that was performed with Arlequin ver .
- A locus with an Fst value higher than the 0.99 limit of the neutral distribution was con- sidered to be a putative outlier under divergent selection [59].
- A 50-base sequence upstream and downstream of the ex- traction site was sequenced and aligned with the A.
- The author would like to thank all the members of the Animal Protection Laboratory, School of Animal Science and Technology, Shandong Agricultural University, who collected the whole sample of our experiment..
- The funders had no role in study design, data collection and analysis, decision to publish, or prepar- ation of the manuscript..
- All animal experiments were performed in accordance with the “ Guidelines for Experimental Animals ” of the Ministry of Science and Technology (Beijing, China), and approved by the Institutional Animal Care and Use Ethics Committee of Shandong Agricultural University..
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