As a comprehensive environmental regulation, the low-carbon city pilot policy (LCCP) may have an impact on haze pollution. The evaluation of the effectiveness of LCCP on haze pollution is greatly significant for air pollution prevention and control. Taking LCCP as the starting point, in this study we constructed DID, PSM-DID, and intermediary effect models to empirically test the impact and mechanism of LCCP on haze pollution, based on the panel data of 271 cities in China from 2005 to 2018. The findings show that (1) LCCP has significantly reduced the urban haze pollution, and the average annual concentration of PM2.5 in pilot cities decreased by 14.29%. (2) LCCP can inhibit haze pollution by promoting technological innovation, upgrading the industrial structure, and reducing energy consumption. Among these impacts, the effect of technological innovation is the strongest, followed by industrial structure, and energy consumption. (3) LCCP has significantly curbed the haze pollution of non-resource dependent cities, Eastern cities, and large cities, but exerted little impact on resource-dependent cities, Central and Western regions, and small and medium-sized cities. (4) LCCP has a spatial spillover effect. It can inhibit the haze pollution of adjacent cities through demonstration and warning effects. This study enriches the relevant research on LCCP and provides empirical support and policy enlightenment for pollution reduction. Among these, only 157 cities achieved the air quality standard . Although the average annual concentration of PM2.5 in below-standard cities is 40 μg/m3, and is decreasing by 2.4% year-on-year, below-standard cities still account for 53.4% of all cities  from fossil energy consumption, especially the combustion of coal .5 from f,4. GlobaThe possible contributions of this paper encompass four aspects: (1) LCCP and haze pollution are included in the same research framework, which provides new research ideas for reducing haze pollution. (2) From the multiple perspectives of technological innovation, industrial structure, and energy consumption, this paper theoretically explains the internal transmission mechanism and empirically tests the specific channels of the effect of LCCP on haze pollution, so as to provide a path choice for further optimizing LCCP. (3) The multi-dimensional heterogeneity analysis of urban resource dependence, regional characteristics, and scale characteristics are undertaken to determine the differential impact of LCCP on haze pollution. (4) Considering the spatial attribute of haze pollution, in this study we adopted spatial econometric methods to further investigate whether LCCP has a spatial spillover effect on haze pollution in neighboring areas.Following this introduction section, Many studies have found that air pollution not only affects the health of residents, but also may reduce residents’ subjective well-being, damage cognitive function, and produce negative emotions and behaviors ,6. The eUrban construction policy is an important factor affecting environmental pollution . PreviouIn summary, the existing research has provided good ideas for this study. As a comprehensive environmental policy tool, LCCP may have an impact on haze pollution. However, previous studies have paid less attention to this aspect. Accordingly, in this study, we took LCCP as the starting point, and constructed DID, PSM-DID, and intermediary effect models to empirically test the impact and mechanism of LCCP on haze pollution. This was based on the panel data of 271 cities in China from 2005 to 2018. The study enriches the relevant research on LCCP and haze pollution, providing empirical support and policy enlightenment for pollution reduction.LCCP is an important part of China’s national environmental governance strategy system . It aimsAccordingly, the following hypothesis is proposed:Hypothesis (H1). LCCP can effectively reduce haze pollution.The above analysis shows that LCCP may effectively reduce haze pollution. If the effect of haze reduction does exist, what is the mechanism by which haze pollution is reduced?According to the research of Grossman and Krueger  and Broc(1) LCCP can reduce haze pollution by promoting technological innovation. The “innovation compensation” theory states that rigid environmental supervision policies enable enterprises to raise technological R&D investment and change production methods to compensate for the economic loss caused by environmental protection costs . The essHypothesis (H2). LCCP can reduce haze pollution by promoting technological innovation.(2) LCCP can inhibit haze pollution by optimizing the industrial structure. The structure effect of LCCP is primarily manifested in forcing the transformation and upgrading of industrial structure  and imprHypothesis (H3). LCCP can reduce haze pollution by upgrading industrial structure.(3) LCCP can reduce haze pollution by encouraging market players to reduce energy consumption in various ways. LCCP is an environmental regulation tool aimed at reducing the environmental pollution. Under the constraints of LCCP, local governments, production enterprises, and the public will reduce energy consumption. Specifically, local governments will adopt a scientific and efficient management model for urban consumption, transportation, and living systems to improve energy efficiency . Facing Hypothesis (H4). LCCP can reduce haze pollution by decreasing energy consumption.i is the city and t is the year; LCCP is a dummy variable, indicating whether the low-carbon pilot policy is implemented; X represents a series of control variables; LCCP was implemented as a quasi-natural experiment, because the first batch of pilot cities was mostly selected from provincial administrative regions, and the third batch was launched later. Therefore, based on the second batch, which was selected in 2012, we construct two dummy variables, taking pilot cities as the treated group, and non-pilot cities as the control group. The model is constructed as follows:LCCP may reduce the level of urban haze pollution. According to the above theoretical mechanism analysis, we assume that LCCP can reduce haze pollution through technological innovation, industrial structure, and energy consumption. In order to verify these assumptions, in this study we used the three-step verification method proposed by Baron and Kenny , and theHaze pollution (PM2.5)—In contrast to the use of “three industrial wastes” and other indicators to measure haze pollution, as used in most literature, and considering that the main “culprit” of haze pollution is PM2.5, in this study we used the concentration of fine particulate matter PM2.5 to measure haze pollution, so as to more accurately and objectively measure the environmental situation of a region, particularly the atmospheric environmental pollution. In this study, according to the annual World PM2.5 density data from 2005 to 2018 shared by the atmospheric composition analysis group (ACAG) of Dalhousie University, after grid processing and mask processing in line with the map of China in ArcGIS, the annual average data of PM2.5 concentration in prefecture-level cities in China was calculated.Low carbon city pilot policy (LCCP)—LCCP is defined as the value of 1 in the year in which a city implements LCCP and each year after that; otherwise, it is 0. This definition automatically produces the treated group and the control groups, in addition to the double differences before and after the implementation of the policy, which is equivalent to the cross term of the treated city variable(1) Economic development level (RGDP) is measured by per capita GDP . RGDP ca(1) Technological innovation (PATENT)—Technological innovation aims to improve the utilization of resources, and achieve energy conservation and emission reduction, which has reached a consensus in academic circles. It is represented by the number of patent applications authorized.(2) Industrial structure (IND)—Industrial structure connects production activities with the environment, and determines the energy consumption mode and pollutant emission level in the economic system, and thus has a substantial impact on the environment. It is denoted by the proportion of the output value of the tertiary and secondary industries.(3) Energy consumption (PELE)—China’s traditional coal-based energy structure determines that energy consumption will emit a large number of pollutants, resulting in the deterioration in urban environmental quality. Therefore, the degree of energy consumption will have a significant impact on environmental pollution. It is measured by the per capita power consumption of each city. Due to the lack of data on energy consumption at the urban level, and considering the high correlation between power consumption and energy consumption, in this study we measured energy consumption by the per capita power consumption .Restricted by the availability of data and consistency of the statistical indicators, this study selected 271 cities in China from 2005 to 2018. Among these, data relating to the low-carbon pilot cities were taken from the data released by the NDRC. Other data were from the National Statistical Yearbook and the statistical yearbooks of provinces and cities for various years. In addition, in order to control the heteroscedasticity of the model, all variables were processed by a natural logarithm. The descriptive statistics of relevant data are shown in In order to ensure the effectiveness of the regression results, the DID model requires that the treated and control groups have the same change trend before the implementation of the policy . In viewp-value is less than 0.05, rejecting the original hypothesis, so the fixed effect model is suitable for regression. In Firstly, the Hausman test was conducted. The result shows that the In order to reduce the estimation error, the DID method was used to address the systematic differences in the changing trend between pilot cities and non-pilot cities . ThroughIn order to solve endogenous problems, the PSM-DID method was again used for regression. The results are shown in The above empirical results indicate LCCP can significantly reduce the level of urban haze pollution, but how does LCCP reduce haze pollution? The three-step verification method in Equations (2)–(4) was conducted to test the influencing mechanism of LCCP on haze pollution. In order to improve the robustness of this research conclusion, in this study we carried out a robustness test considering the following four aspects: ① The placebo test—The hypothesis is that if the pilot city is not affected by LCCP, the changing trend of pollution in the control and treated groups will not have a systematic difference over time. The regression is then conducted again based on this hypothesis. The results show that the estimation coefficient of the LCCP is negative, but not significant, indicating that the above benchmark regression is caused by the exogenous impact of LCCP, rather than the placebo effect caused by other factors. ② Replace the explained variable and re-regress with SO2 as the explained variable, and the coefficient and significance of the regression results were roughly consistent with the benchmark regression. ③ After excluding 31 key cities, such as provincial capital cities and sub-provincial cities, the results were still basically consistent with the previous conclusions. ④ All variables lagged for one period. Considering that LCCP may not have an immediate impact, in addition, in order to avoid the error of simultaneous equations, the lags for one period of LCCP and all control variables are substituted into the equation for regression. The regression results are roughly consistent with the previous text, verifying that the conclusions of this paper are robust. See Due to the significant differences in natural resource endowment, economic development, and industrial structure in Chinese cities, the impacts of LCCP on haze pollution may vary. In order to deeply investigate the heterogeneity of urban resource dependence, according to the national sustainable development plan of resource-based cities (2013–2020), prefecture-level cities in China were divided into resource-based cities and non-resource-based cities. The regression results are shown in Due to China’s unique geographical conditions and differences in resource endowment, the haze reduction effects of LCCP on China’s Eastern, Central, and Western regions may also be quite different. Because the number of cities with LCCP in the western region is relatively few, in this study we divided the research samples into two parts: the eastern regions and the central and western regions. The regression results are shown in In addition, the size of cities plays an important role in the impact of LCCP on reducing haze pollution, which may also lead to differences. Based on the data of permanent residents in urban areas of local cities in 2015, cities were divided into three sizes: large-sized, medium-sized, and small-sized cities according to the notice on adjusting the criteria for urban scale division issued by the State Council (GF [2014] No. 51). As shown in LCCP significantly reduces urban haze pollution and the average annual concentration of PM2.5 in pilot cities decreased by 14.29%. LCCP is aiming to promote the construction of an ecological civilization, and green and low-carbon development . Its corThe technological effect is a significant contributor to the improvement in environmental quality. Its function mainly lies in the good effect of energy conservation and emission reduction resulting from new technological progress . LCCP wiTransforming and upgrading the traditional industrial structure is one of the main tasks of LCCP to improve environmental quality. Most traditional industries depend on the massive investment of capital and labor factors. Guided by LCCP, these industries will be upgraded and transformed into industries characterized by advanced technology, high added value, and low pollution. In this manner, the high-polluting enterprises will be forced out of business, and some favorable policies and financial aid will be implemented for low-polluting enterprises. As a result, strategic emerging industries, such as new energy, will be further fostered and expanded, and ultimately a low-polluting and low-emitting green industrial system will be established .LCCP can reduce energy consumption. As an environmental regulation tool, LCCP is designed to reduce pollutant discharge. Due to the higher costs associated with pollution control and treatment, enterprises will be “forced” to reduce energy consumption and improve energy utilization. Specifically, energy consumption will emit a large number of pollutants, resulting in the deterioration of urban environmental quality. LCCP is dedicated to advocating the green and low-carbon concept and developing low-carbon transportation systems. In this manner, the energy structure is optimized and the energy consumption is reduced. Additionally, under the guidance of LCCP, citizens will adopt scientific and efficient forms of consumption, transportation, and lifestyle, thus reducing energy consumption and improving energy efficiency. Third, LCCP establishes a carbon credits system which specializes in the promotion of energy utilization and reduction of pollutant emissions.The impact of LCCP on haze pollution may vary due to the significant differences in natural resource endowments, stages of economic development, and industrial structures in Chinese cities.In terms of resource dependence heterogeneity, the possible reason for this is that cities that are highly dependent on natural resources tend to develop resource-based industries. Due to long-term and high-intensity mining, resource-based cities generally face problems such as environmental pollution and ecological destruction . In addiA possible reason for regional heterogeneity is that the Eastern regions have a high-level economic development and relatively complete infrastructure, which provides a material guarantee for the effective implementation of LCCP . In the Urban scale heterogeneity occurs because, compared with small and medium-sized cities, large-sized cities have greater R&D investment, and better implementation of relevant environmental protection systems and policies, which can enhance haze pollution control . In addiThe above empirical results use the general DID model to identify the causal relationship between LCCP and haze pollution without considering the spatial effect of LCCP on haze pollution. In this section, we present the results of spatial econometric methods to further investigate whether the local LCCP has a spatial spillover effect on haze pollution in adjacent cities.In this study, we selected the adjacency matrix and used the global Moran I to test the spatial correlation of haze pollution . The resBased on the verified spatial correlation, in this study, we initially set the model as a two-way fixed spatial Durbin model (SDM) and carried out a correlation test. The LM and robust LM tests rejected the original hypothesis of the non-spatial effect model. In addition, the LR test rejected the original hypothesis of joint non-significance of spatial and temporal fixed effects, the Hausman test rejected the random effect model, and the Wald test rejected the original hypothesis that the spatial Durbin model was transformed into a spatial lag and spatial error model. According to the test results in In Based on the panel data of 271 prefecture-level cities in China from 2005 to 2018, in this study we employed the DID and mediatory effect models to empirically test the impact and mechanism of LCCP on urban haze pollution. In addition, heterogeneity analysis was undertaken to further explore the differential impacts from urban resource dependence, geographic location, and scale. Finally, the spatial spillover effect of LCCP on haze pollution was further explored. The main conclusions are as follows: (1) LCCP has significantly inhibited urban haze pollution, reducing the average annual concentration of PM2.5 by 14.29%. After a series of robustness tests, this conclusion was found to be valid. (2) The mechanism analysis shows that LCCP reduces haze pollution through technological innovation, industrial structure, and energy consumption. Among these, technological innovation has the strongest effect, followed by industrial structure and energy consumption. (3) Heterogeneity analysis implies that LCCP has significantly reduced the haze pollution of non-resource dependent cities, Eastern cities, and large cities, but has had little impact on resource-dependent cities, Central and Western regions, and small and medium-sized cities. (4) Further analysis shows that LCCP has a spatial spillover effect; that is, it can inhibit the haze pollution of adjacent cities through demonstration and warning effects.Accordingly, the following policy implications are proposed:(1) The scope of low-carbon pilot cities should be further expanded to promote the construction of low-carbon cities. The government should summarize the successful experience of low-carbon city pilot construction, encourage the non-pilot cities to learn from the pilot cities, and constantly explore the new path of urban low-carbon development. (2) The government should fully utilize the role of LCCP in haze control. Specifically, the government should strengthen the assessment of environmental protection and energy consumption in the construction of low-carbon pilot cities, improve the intensity of environmental regulation, and actively implement fiscal and tax policies and relevant incentive policies that are conducive to enterprise scientific and technological innovation, industrial structure optimization, and upgrading of the energy structure, so as to improve the governance efficiency of haze pollution. (3) The government should further promote the construction of low-carbon pilot cities in an orderly manner, and give priority to the establishment of low-carbon cities in the Eastern region, and non-resource-based and large-scale cities. The cities in the Central and Western regions, in addition to small-scale and resource-based cities, should learn and absorb the haze controlling experience from the pilot cities in the Eastern region, and non-resource-based and large-scale cities. In addition, the government should give more policy preference and support to cities in the Central and Western regions and small-sized and resource-based cities, improve their pilot policy assessment system and environmental monitoring mechanism, and finally fully utilize the haze reduction effect of LCCP. (4) The cross-regional cooperation among pilot cities should be promoted for haze prevention and control. The government should abandon the traditional territorial management mode of “each doing its own thing” and “beggar thy neighbor”. Alternatively, it should create a “decentralized” and “networked” cross-regional joint prevention and control mode, and build a normalized regional feedback mechanism and information sharing platform, so as to strengthen cross-regional collaborative governance of haze prevention and control . AdditioAlthough this study explored the impact of LCCP on urban haze pollution and its impact mechanism, the exploration was not sufficient in terms of its depth and breadth due to the short time of implementation and the limitation in data. In the future, the long-term dynamic impact of the policy should be examined to further explore additional means to alleviate haze pollution.


Long-term selection experiments are a powerful tool to understand the genetic background of complex traits. The longest of such experiments has been conducted in the Research Institute for Farm Animal Biology (FBN), generating extreme mouse lines with increased fertility, body mass, protein mass and endurance. For >140 generations, these lines have been maintained alongside an unselected control line, representing a valuable resource for understanding the genetic basis of polygenic traits. However, their history and genomes have not been reported in a comprehensive manner yet. Therefore, the aim of this study is to provide a summary of the breeding history and phenotypic traits of these lines along with their genomic characteristics. We further attempt to decipher the effects of the observed line-specific patterns of genetic variation on each of the selected traits.Over the course of >140 generations, selection on the control line has given rise to two extremely fertile lines (>20 pups per litter each), two giant growth lines  and one long-distance running line. Whole genome sequencing analysis on 25 animals per line revealed line-specific patterns of genetic variation among lines, as well as high levels of homozygosity within lines. This high degree of distinctiveness results from the combined effects of long-term continuous selection, genetic drift, population bottleneck and isolation. Detection of line-specific patterns of genetic differentiation and structural variation revealed multiple candidate genes behind the improvement of the selected traits.The genomes of the Dummerstorf trait-selected mouse lines display distinct patterns of genomic variation harbouring multiple trait-relevant genes. Low levels of within-line genetic diversity indicate that many of the beneficial alleles have arrived to fixation alongside with neutral alleles. This study represents the first step in deciphering the influence of selection and neutral evolutionary forces on the genomes of these extreme mouse lines and depicts the genetic complexity underlying polygenic traits.The online version contains supplementary material available at 10.1186/s12915-022-01248-9. Artificial selection is the selective breeding of organisms by which desired phenotypic traits evolve in a population . Farm anThe worldwide longest selection experiment on mice began in 1969 at the former Forschungszentrum für Tierproduktion (FZT), nowadays called Research Institute for Farm Animal Biology (FBN) located in Dummerstorf, Germany , 6. StarOther selection experiments have generated mice with increased litter size –14, as wThe Dummerstorf mouse lines expand the repertoire of polygenic mouse models to understand the genetic basis of fertility, body weight and endurance. Each of these lines arose from almost the same genetic diversity and has been maintained to this day for about half a century. Here we describe the selection history of this unique selection experiment, characterize line-specific patterns of genetic variation and identify genes that are likely associated to each selection trait.Over the course of more than 140 generations Table  have shoWith the exception of the obese line DU6 , each onAfter quality filtering and trimming, >90% of the raw reads were mapped to the genome as pairs, with a mean insert size of ~380 bp. For samples sequenced at a target coverage of 30×, mean genome-wide coverage averaged ~24×, with ~95% of genome territory covered at least 5×; samples sequenced at a target coverage of 5× averaged ~8× and ~72%, respectively  and 766,655 insertions-deletions (INDELs)  INDELs were no longer than 10 bp  Fig. B. The li.3K Fig. Almost all SNPs and INDELs (~97%) occurred in non-coding regions . This is not an unexpected outcome considering that only ~2% of the genome codes for proteins and genetic variation is widespread. Inter-genic variants could affect regulatory elements of gene expression, as well as transcripts not yet described , whereasBased on assessment of variant annotations, a very small number of variants  were classified as high-impact and moderate-impact mutations, and could interfere with gene transcription or translation. These “impact variants” were screened for (i) being private for any trait-selected line  were already fixed for either the reference or the alternative allele, in the control line FZTDU alleles were mostly (>75%) polymorphic  between pairs of SNP sites within min. 0.1 Mb and max. 5 Mb, can be classified into three patterns with decreasing decay strength; one for the three most homozygous trait-selected lines  and admixture analysis using the 5,099,945 SNPs obtained after variant calling. Samples formed a hierarchical group structure that represented each of the Dummerstorf lines  ranged from 0.44 to 0.61  = 0.61 and FST(DUC-DU6) = 0.59; Fig. FST(DUK-DUC) = 0.57; Fig. FST ~ 0.3), it was lowest in the pairwise comparison between the two most polymorphic lines (FST(DUhLB-FZTDU) = 0.26; Fig. Mean genome-wide pairwise genetic differentiation among trait-selected lines estimated with the genetic differentiation index  resulted in the detection of multiple loci in every chromosome  was also included, for a total of six FST Fig. A. Choosiome Fig. A. BecausThese thresholds were empirically determined based on a similar study comparing two extremely differentiated inbred maize lines . NeutralDespite primarily thought to be deleterious and implicated in disease phenotypes , 53, larAfter calling and filtering, only duplications, deletions and inversions remained in the final SV data set. Insertions did not occur in enough samples to be included in the analysis. Also, because of the lower detectability in the low sequencing coverage samples, most SVs were found in high coverage samples  where they could affect gene expression. Also, SVs Table  were morThe number of genes affected by fixed line-specific SVs varied from 1  to 5 (DUK), but went up to more than a thousand for genes affected by large polymorphic inversions  with Qsi5 mice [Ntm [Dio3 [Olfr279 , in theoh8 [Cel , 65). Fuice [Ntm ) and littm [Dio3 –69). IntPgr) carrying a missense mutation, which is fixed in and specific for DUC . InThe fertility lines DUK and DUC have been bred according to the same criteria, share the same evolutionary history, and both have been able to more than double the number of pups per litter since the beginning of selection. Despite these commonalities, improved fertility is achieved via different physiological pathways in each line . For exaTwo of the Dummerstorf trait-selected mouse lines have increased their body weight in response to selection. The “giant” DU6 line (selected for body mass at 6 weeks of age) exhibits an obese phenotype  while thHcrt [Wdr27 [Atp11b [Smad5, a modulator of bone formation [In line with the obese phenotype, DU6 candidate genes overlapping RDDs regulate energy metabolism and food intake (Hcrt ) and aret [Wdr27 ) and bod [Atp11b ). DU6 mi [Atp11b , and theormation , to be pormation . This isormation .Plag1 [Chchd7 [Impad1 [Fam92a, a gene that is involved in limb development [Piezo1 . In linelopment . Furtherormation , 89) andipocytes –92).Aldh3a1 and Aldh3a2, the later containing 3 missense SNPs . Only two DUhLB genes (le Srsf6 ), remova[Aldh3a2 ), mobili2 [Il15r ) and in  [Pfkfb3 , 97). Mo in mice . Interes in mice , highlig in mice ).There are five main weaknesses in this study. First, due to gaps in pedigree documentation over more than 140 generations, modelling neutrality was not feasible. In turn, the thresholds to evaluate line-specific genetic differentiation were chosen empirically by setting conservative limits that minimize the presence of false positives.Second, at its origin in 1969, the study was not designed to conduct genomic analyses. Thus, genetic material from the founders is not available. Unfortunately, this and the incomplete pedigree information hamper the detection of signatures of selection. However, the genomic data generated here still allows deriving biological interpretations based on the line-specific patterns of genetic differentiation, which is the subject of this study.Third, relocation of the mouse lines by embryo transfer resulted in a genetic bottleneck and random fixation events. This further obscures insight into the selection response mechanisms of these mouse lines. Still, the current strong phenotypic divergence of the lines is the result of long-term selection.Fourth, except for the fertility lines DUK and DUC, trait-selected lines were not replicated in order to identify overlapping genomic signatures. Interestingly, these two lines are markedly different both physiologically and genetically, despite having the same selection criteria.Finally, SVs were detected using short pair-end reads (150bp) and this is not an optimal approach for SV discovery. For this, long reads provide much greater accuracy and sensitivity , 100.The genomes of the Dummerstorf trait-selected mouse lines have evolved in response to selective breeding and neutral forces, exhibit low genetic diversity and display distinct patterns of genetic variation. Distinguishing between selection and neutral evolution is a challenging task and will require further research. However, by focusing on regions of distinct genetic differentiation, we were able to identify genes with important functions associated to the selected traits.Over the span of this selection experiment, traits have improved continuously and have not decayed despite the dramatic loss of genetic diversity within lines. This implies that many of the alleles that contribute to trait improvement have arrived to fixation and that these lines are highly enriched for such alleles. Therefore, a deeper understanding of the genomes of the trait-selected Dummerstorf mouse lines will provide valuable insights into the genetic basis of important polygenic traits and constitutes an unprecedented scientific resource for geneticists, physiologists and the wider biomedical research community.Forschungszentrum für Tierproduktion Dummerstorf) [The selection experiment started in 1969 (Tables erstorf) , 6 by syAll animal procedures were performed in accordance with national and international guidelines and approved by the Animal Protection Board of the Institute for Farm Animal Biology. Genomic DNA was purified from tail biopsy samples using QIAamp DNA Mini Kit  according to the manufacturer’s recommendations. A total of 25 females per line  were sampled at two different time-points (Table n = 60) were distributed in 9 lanes for a total of 540 pairs of read files. Ten of those samples had to be supplemented with extra sequencing data due to not reaching the expected 30× coverage. Samples sequenced at 5× were not lane-distributed, amounting to 90 pairs of read files. In total, 640 pairs of read files were produced. Sample-wise WGS data is summarized in Additional file Library preparation and sequencing were carried out at the Competence Centre for Genomic Analysis (Kiel). Paired-end sequencing libraries were prepared using the TruSeq Nano DNA Library Prep kit following the manufacturer’s specifications . Out of the 150 libraries, 60 were sequenced on a HiSeq 4000 platform (Illumina Inc.), and 90 samples were sequenced on a NovaSeq 6000 (Illumina Inc.) platform. The target coverage was 30× (high coverage set) and 5× (low coverage set), respectively. Read length was 151 nucleotides. Samples sequenced at 30× (AddOrReplaceReadGroups), merging alignments from different read groups (MergeSamFiles), and by sorting (SortSam) and marking duplicated (MarkDuplicates) reads.Adapter removal and quality trimming were done using Trimmomatic v0.38  for HisSBaseRecalibrator and dbSNP [Mus musculus  were retained. Filtering was applied separately for SNPs and INDELs. Site-level filtering was done following the Variant Quality Score Recalibration (VQSR) procedure. This comprised an internal variant set used as truth-training resource, created after stringent site-level filtering of the bi-allelic variants obtained from joint genotype calling, plus an external pre-filtered training variant set provided by the Mouse Genomes Project (MGP version 5 [Short variants were detected according to GATK’s best practices for germline short variant discovery (GATK v 4.0.6.0) –127. Sysnd dbSNP  version rsion 93 ). For eaersion 5 ). Varianersion 5  were excersion 5  and missersion 5  to obtaiersion 5  and to pProcessed BAM files used for short variant calling were also used to detect large structural variants (SVs). SVs correspond to deletions, duplications, insertions, inversions and translocations of at least 50 bp in size . BecauseThree SV callers  weFST index [FST calculations are based on allele counts and not read counts, differences in depth between low and high coverage samples are not expected to have a direct effect in the estimation of genetic differentiation. The average number of SNP sites per window was ~ 125  were combined (pseudo-line: FERT) and compared to FZTDU as well. Since autosomes and the X-chromosomes have different effective population sizes, the X-chromosome was standardized individually. In order to identify RDDs, FST windows appearing simultaneously in the 95th percentile of a given contrast and in the bottom 10th percentile of all other contrast were identified. These thresholds are not derived from modelling neutrality, rather they were chosen empirically based on a previous study [π) [The genomes of the trait-selected lines were compared to the neutrally evolving control line (FZTDU). For this, genetic differentiation was estimated using the ST index  in slidiST index . Since Fus study  and afteus study , 146, whtudy [π)  in sliditudy [π) .Mus musculus gene set. In order to sort out the most relevant genes for each of the selected traits, thorough inspection of functional annotations, literature and SNP effects was conducted. This also included testing for enrichment of Gene Ontology Biological Processes (GOBP) [Genes overlapping RDDs were identified using GenomicRanges  and Enses (GOBP) , 150 ands (GOBP) –153 usins (GOBP) –157 usins (GOBP) , 159.Data processing and visualizations were done using R  and the Additional file 1. Establishment of the Dummerstorf mouse lines, Structural Variant Calling.Additional file 2: Figure S1. Response to selection throughout the selection experiment. Figure S2. Proportion of litters supplying parents for the next generation. Figure S3. Distribution of INDEL lengths. Figure S4. Number of private and shared INDELs among lines. Figure S5. SNP allele frequency state classification. Figure S6. Alternative allele frequency distribution. Figure S7. Nucleotide diversity (π) distribution in the Dummerstorf mouse lines. Figure S8. Example of one chromosome representative of the level of genetic diversity observed in the Dummerstorf mouse lines. Figure S9. Allele frequency heatmap of non-synonymous mutations in RDD genes. Figure S10. Allele frequency heatmap of non-synonymous mutations in RDD genes.Additional file 3: Table S1. Alternative names of the Dumemrstorf mouse lines. Table S2. Number of SNP and INDEL sites discovered in each line. Table S3. Number of private variants with predicted high/moderate effects according to SnpEff. Table S4. Counts per length up to the 90% most frequent INDELs sorted in decreasing order of frequency. Table S5. Significantly enriched terms based on RDD gene lists. Table S6. Proportion of line-specific fixed and polymorphic structural variants in genic regions. Table S7. Types and lengths of line-specific fixed structural variants in genic regions. Table S8. Number of genes affected by line-specific fixed and polymorphic structural variants. Table S9. Number of genes in functional groups affected by line-specific structural variants. Table S10. Summary of structural variants detected in low and high coverage variant calling sets for each mouse line. Table S11. Number of SNP sites per window analysed with FST.Additional file 4: Data S1. WGS data overview. Data S2. Significantly enriched terms for genes affected by line-specific SNPs and/or INDELs with high/moderate impact. Data S3. Genomic information of regions of distinct genetic differentiation for DUK. Data S4. Genomic information of regions of distinct genetic differentiation for DUC. Data S5. Genomic information of regions of distinct genetic differentiation for DU6. Data S6. Genomic information of regions of distinct genetic differentiation for DU6P. Data S7. Genomic information of regions of distinct genetic differentiation for DUhLB. Data S8. Genomic information of regions of distinct genetic differentiation for FERT. Data S9. Genes in regions of line-specific genetic differentiation associated to increased fertility (DUK). Data S10. Genes in regions of line-specific genetic differentiation associated to increased fertility (DUC). Data S11. Genes in regions of line-specific genetic differentiation associated to increased body mass (DU6). Data S12. Genes in regions of line-specific genetic differentiation associated to increased lean body mass (DU6P). Data S13. Genes in regions of line-specific genetic differentiation associated to increased treadmill endurance (DUhLB). Data S14. Genes in regions of specific genetic differentiation for the pseudo-line FERT (DUK and DUC combined). Data S15. Gene-spanning line-specific structural variants.


Obovaria olivaria is a species of freshwater mussel native to the Mississippi River and Laurentian Great Lakes‐St. Lawrence River drainages of North America. This mussel has experienced population declines across large parts of its distribution and is imperiled in many jurisdictions. Obovaria olivaria uses the similarly imperiled Acipenser fulvescens (Lake Sturgeon) as a host for its glochidia. We employed mitochondrial DNA sequencing and restriction site‐associated DNA sequencing (RAD‐seq) to assess patterns of genetic diversity and population structure of O. olivaria from 19 collection locations including the St. Lawrence River drainage, the Great Lakes drainage, the Upper Mississippi River drainage, the Ohioan River drainage, and the Mississippi Embayment. Heterozygosity was highest in Upper Mississippi and Great Lakes populations, followed by a reduction in diversity and relative effective population size in the St. Lawrence populations. Pairwise FST ranged from 0.00 to 0.20, and analyses of genetic structure revealed two major ancestral populations, one including all St. Lawrence River/Ottawa River sites and the other including remaining sites; however, significant admixture and isolation by river distance across the range were evident. The genetic diversity and structure of O. olivaria is consistent with the existing literature on Acipenser fulvescens and suggests that, although northern and southern O. olivaria populations are genetically distinct, genetic structure in O. olivaria is largely clinal rather than discrete across its range. Conservation and restoration efforts of O. olivaria should prioritize the maintenance and restoration of locations where O. olivaria remain, especially in northern rivers, and to ensure connectivity that will facilitate dispersal of Acipenser fulvescens and movement of encysted glochidia. Obovaria olivaria, that uses a similarly imperiled host fish, Acipenser fulvescens. We show that O. olivaria is partially subdivided into northern and southern groups by the Great Lakes, but that overall structure is largely continuous and driven by geographic (river) distance between populations.Using RADseq and mitochondrial sequencing, we investigated the genetic diversity and structure of an imperiled freshwater mussel species,  Lawrence drainage are only known from areas where A. fulvescens are present  in parts of its range  or more discrete genetic structure among rivers will be important. Beyond impacting gene flow and population genetic structure, recent and historical changes in connectivity among river drainages can leave signatures on levels of genetic diversity, and quantifying variation in diversity among less threatened populations  and endangered populations  could provide important information on how genetic diversity relates to conservation status.Understanding how genetic diversity is structured among  Fraser, . As disc Fraser, . Sturgeo Fraser, . Thus, tO. olivaria across its range and identify populations or regions harboring relatively low genetic diversity and (2) examine the genetic structure of O. olivaria across its range to identify patterns of connectivity or presence of discrete population structure and dispersal barriers that can assist in focal management planning. We employ two complementary molecular approaches, mitochondrial DNA (mtDNA) sequencing and restriction site‐associated DNA sequencing (RAD‐seq), to examine the phylogeography, genetic structure, and genetic diversity of O. olivaria populations throughout its range. Mitochondrial DNA has been widely used in range‐wide phylogeographic studies for decades  examine the genetic diversity of 22.1Obovaria olivaria samples were collected from 19 sites across its distribution in the upper Mississippi River system, the Ozark highlands, tributaries of the Great Lakes, and the St. Lawrence River system. Sampling locations included the Upper Mississippi River drainage , the Ohioan River drainage [Wabash River and White River (IN)], the Great Lakes drainage  the St. Lawrence River drainage   and protocol. Extracted DNA was stained with SYBR Green™ (Thermo Fisher Scientific) dye, and agarose gel electrophoresis was performed to confirm the presence of high‐quality, high molecular weight genomic DNA and concentrations were quantified using a Nanodrop spectrophotometer (Thermo Fisher model # ND‐1000).2.2.12O, 2 µl EXO, and 20 µl SAP, and then, 2 µl of the mixture was added to each PCR product to remove primers, dNTPs, and other impurities, and were Sanger sequenced by Eton Bioscience  using the forward primer  region of the mitochondrial genome was amplified by polymerase chain reaction (PCR) using the primers and thermocycler conditions described by Campbell et al. . PCR pro2.2.2® dsDNA quantification assay  for precise standardization at 20 ng/µl for library preparation. Standardized DNA was digested with the restriction enzyme SbfI‐HF , followed by ligation of synthetic oligonucleotides containing unique 8 base pair Hamming barcodes for each individual. Barcoded samples were pooled and sonicated using the Covaris S2 Adaptive Focused Acoustic Disrupter  to randomly fragment barcoded DNA to an average size of 550 base pairs. RAD‐tag fragments were isolated with streptavidin beads and biotinylated groups were removed by Sbf‐1 digestion. Following digestion, a NEBNext Kit™ (New England Biolabs) was used to barcode and enrich the library for sequencing with 12 PCR cycles. Samples were sequenced on an Illumina HiSeq 4000 (Illumina Inc.) to produce 150‐bp paired‐end reads (Michigan State University Research Technology Support Facility).We used the Best‐RAD protocol . We used vcftools  of SNPs for each sampling location using the radiator package's summary_rad and private_alleles functions  determined by the value producing the lowest cross‐entropy  determined by the value producing the lowest Bayesian information criterion from k‐means clustering (find.clusters function). The DAPC scatterplot was created with ggplot2 and ggforce v0.3.1  were computed in the R package StAMPP v1.6.1  to account for lakes and short overland distances between drainages . After assigning the Mississippi (above STCR site) as the river mouth in riverdist, the detectroute function was used to measure the distances between points on the river network segment  Great Lakes basin populations, (3) Northern populations in St. Lawrence River basin (see Table e) and time to be a maximum of 2.5 million individuals for all regional populations and set a maximum divergence time of 50,000 generations. We also examined models constraining Ne to 1/10th this value (250k) to examine sensitivity to this prior. We tested seven potential scenarios of postglacial colonization , the Laurentian Great Lakes watershed (3 sites), Upper Mississippi River drainage (5 sites), and Mississippi Embayment  and individual collection sites  (Table ST) was generally low within each drainage and higher between drainages although Bonferroni‐corrected pairwise differentiation was only consistently observed with the White River site  Table . Pairwis3.2Obovaria olivaria BestRAD libraries yielded an average of 2,041,264  paired‐end reads per sample. The final filtered dataset included 1,237 polymorphic SNPs present in the 93 individuals from 19 collection locations  all the individuals from the St. Lawrence River drainage, (2) all individuals from the Mississippi watershed, Great Lakes watershed, the White River, Wabash, and White River in Illinois, but as above the Great Lakes mussels were intermediate   and among sites overall .The DAPC and snmf analyses of the SNP dataset both revealed two major clusters, but there was clear admixture at spatially intermediate sites Figure . For thee Figure . We repe1) Table , as wellFST) among most collection sites , consistent with the clusters identified by DAPC. However, also consistent with the DAPC and snmf clustering that suggested admixture among ancestral populations via intermediate sites, Mantel tests showed a strong isolation‐by‐distance relationship between pairwise FST and river distances at the range‐wide scale , but similar to geologic estimates of the Great Lakes formation of ~14,000 YBP  was the best fit model for the SNP and mitochondrial datasets, suggesting limited power in this system to resolve any directional colonization history. However, DIYABC models did consistently show that relative Nia Table . DIYABC Appendix . We thusze Table . The med Larsen,  in the l4O. olivaria provides evidence for ongoing or recent connectivity driven by spatial separation within and between regions, which also exhibit differences in genetic diversity. The patterns of range‐wide isolation‐by‐distance presented here imply that O. olivaria dispersal is distance‐limited, but such limitations occur at large scales and suggest the potential for long‐distance movement on host fish. We also find that O. olivaria exhibits notably reduced genetic diversity in northern sites (the St. Lawrence and Ottawa Rivers), which is especially concerning given the endangered status of these populations.Our combined analysis of mitochondrial and RAD‐tag sequences in ST values, the COI data indicate no extensive phylogeographic barriers across the O. olivaria range.In the mitochondrial DNA dataset, diversity declined from south to north, with reduced haplotype and nucleotide diversity in the Great Lakes and St. Lawrence drainages and the greatest number of haplotypes and unique haplotypes is found in the Mississippi River drainage. The White (AR) and Black River individuals had 4 unique haplotypes out of 5 haplotypes, which is consistent with other phylogeographic studies on freshwater taxa from this region that display similar endemism  and Great Lakes regions were high , suggesting that these populations have retained high levels of ancestral genetic diversity and may not have suffered the genetic impacts of any population declines.Patterns of genetic structure in freshwater mussel species often reflect changes in the patterns of hydrologic connections in the Great Lakes at the end of the last glacial period  was low, but significant , and FST among St. Lawrence River sampling locations was also low, but significant . The lack of discrete genetic structure in O. olivaria is likely linked to A. fulvescens and other host fish and therefore prioritizing management of habitats where both species coexist will likely ensure greater conservation success.Genetic differentiation and diversity of h et al.  also fou4.1O. olivaria range by utilizing the movement of their host fish and via movement through stream capture or isostatic rebound events during the changes in the configuration of the Great Lakes following deglaciation. However, O. olivaria are relatively long‐lived , have relatively long generation times ; Data curation (lead); Formal analysis (lead); Investigation (lead); Methodology (lead); Validation (lead); Visualization (lead); Writing – original draft (lead); Writing – review & editing (lead). Nicholas M. Sard: Data curation (supporting); Methodology ; Resources ; Supervision (supporting); Writing – original draft (supporting); Writing – review & editing (supporting). Nichelle M. VanTassel: Data curation (supporting); Writing – review & editing (supporting). Jeffrey D. Lozier: Resources ; Software ; Supervision (supporting); Validation (supporting); Visualization (supporting); Writing – original draft (supporting); Writing – review & editing (supporting). Todd J. Morris: Conceptualization (supporting); Data curation (supporting); Funding acquisition (supporting); Project administration (supporting); Writing – review & editing (supporting). Annie Paquet: Conceptualization (supporting); Data curation (supporting); Funding acquisition (supporting); Investigation (supporting); Project administration (supporting). David T. Zanatta: Conceptualization (lead); Data curation ; Formal analysis ; Funding acquisition (lead); Investigation ; Methodology ; Resources (lead); Software ; Supervision (lead); Validation (lead); Visualization (lead); Writing – original draft ; Writing – review & editing .Supplementary MaterialClick here for additional data file.


Orcaella brevirostris) is an endangered,small cetacean species which is widely distributed in rivers, estuaries, andcoastal waters throughout the tropical and subtropical Indo-Pacific. Despite theextensive distribution of this species, little is known of individual movementsor genetic exchange among regions in Thailand. Here, we evaluate the geneticdiversity and genetic structure of O. brevirostris in theeastern, northern and western Gulf of Thailand, and Andaman Sea. Althoughphylogenetic relationships and network analysis based on 15 haplotypes obtainedfrom 32 individuals reveal no obvious divergence, significant geneticdifferentiation in mitochondrial DNA  is apparent among regions. Of 18tested microsatellite loci, 10 are polymorphic and successfully characterized in28 individuals, revealing significant genetic differentiation  among the four sampling sites.Structure analysis reveals two inferred genetic clusters. Additionally, Mantelanalysis demonstrates individual-by-individual genetic distances and geographicdistances follow an isolation-by-distance model. We speculate that thesignificant genetic structure of O. brevirostris in Thailand isassociated with a combination of geographical distribution patterns,environmental and anthropogenic factors, and local adaptations.The Irrawaddy dolphin ( Orcaella brevirostris) is a small cetaceanspecies which is widely distributed in rivers, estuaries, and coastal watersthroughout the tropical and subtropical Indo-Pacific  at theconfluences of two rivers, or above and below rapids, while in estuaries and coastalwaters they frequent shallower depths  within a few kilometersof shore  evaluate genetic diversity of O. brevirostrisusing samples obtained from throughout the Gulf of Thailand and Andaman Sea coastusing mitochondrial control region sequences and nuclear microsatellite markers; and(3) estimate levels of genetic differentiation among these O.brevirostris individuals in Thailand for both marker types.Our research aims were to: (1) assess transferability and polymorphism ofmicrosatellite markers for SamplingAll fieldwork was under permits from the Ministry of Agriculture and Rural Affairs ofChina, and with approval from the Department of Marine and Coastal Resources ofThailand. The relevant CITES Permits (No. 2018CN/IC000475/CH) were obtained forimport of samples. There was no issue on ethics in this study.O. brevirostris individuals recovered from nine sites inThailand: Chachengsao (n = 1), Chonburi (n = 1), Chumporn (n = 2), Mueang Trat(n = 11), Phetchaburi (n = 1), Samut Sakorn (n = 9), Satun (n = 1), Surattani (n= 7), and Trang (n = 4). Geographic coordinates for all except one individualfrom Phetchaburi were recorded at the time of collection. Samples were groupedinto four general regions as described in From 2010 to 2018, muscle or skin samples were collected from 37 dead (stranded)2O to make up the final volume. The PCRprofile comprised an initial denaturation step at 94 ℃ for 3 min, 35 cycles of94 ℃ for 30 s, annealing at 50 ℃ for 1min, extension at 72 ℃ for 1min, and afinal extension at 72 ℃ for 10 min. All PCR products were sequenced in bothdirections on an ABI 3730 automated DNA sequencer (Applied Biosystems).A fragment of the mitochondrial control region was amplified using forward primerCe-CRF 5′-GAATTCCCCGGTCTTGTAAACC-3′ and reverse primer Ce-CRR5′-TCTCGAGATTTTCAGTGTCTTGCTTT-3′ . Total PSousa chinensis, for this study. These loci were all‘perfect-type’ and long tandem repeat motifs ,and demonstrated high polymorphism in Thailand S. chinensispopulations (data unpublished). Microsatellites were allocated into 6 multiplexPCR panels using software MPprimer  were determined usingStructure 2.3.4 based onormation . The numormation  was usedormation . We usedormation  to summaormation .ST(FSTAT version 2.9.3.2 (ST among thST. In addiST was usedThe 18 tested microsatellite sequences and 32 obtained mtDNA control regionsequences (including 15 mtDNA haplotypes) reported in this paper have beendeposited into the GenBank database under the accession numbers ofMK766845-MK766870  and MT73No contamination was detected during PCRs, and no genotyping errors were observedwhen randomly retesting four individuals. Among the 18 loci tested, two (Sch5878and Sch5685) were excluded because of unsuccessful amplification, and six were excluded because theywere monomorphic. The remaining 10 loci were polymorphic in the four samplinglocations.Due to the low quality of some DNA samples, we obtained mtDNA sequences for 32individuals  only, inBased on mtDNA data, 15 haplotypes were found in the 32 individuals by aconsensus 883 bp sequences from the four geographic locations . Only onBased on microsatellite DNA data, genetic diversity estimates of Na, Ne, Ho, He,uHe, I and F values for each sampling site are summarized in 3, 36 = 3.279, P = 0.032), but Ne values didnot . There were no significantdifferences among He  and uHe  values. Additionally, no significantdifferences were found among Ho  and I values from any of the fourgeographic regions.ANOVA results revealed Na values differed significantly from each other amongsampled regions among Thailand O. brevirostris individuals. PairwiseFST and ΦST values revealed moderate to high levels ofgenetic differentiation between different region pairs, but some cases showed nosignificant differentiation between AS and other region pairs  among the fourgeographic regions. Low to moderate levels of genetic differentiation weredetected between different region pairs. Estimates of pairwise FSTare presented in ST =0.008, P > 0.05). Some pairwise FST values were moderatelydifferentiated, with the highest genetic differentiation found between WG and NG. AMOVA results for the degree ofvariance in O. brevirostris individuals are summarized in AMOVA results revealed significant high genetic differentiation in mtDNA  between the individual-by-individual genetic distances and geographicdistances, indicating a pattern of IBD among the four geographic regions  proved polymorphicin Mekong River O. brevirostris  are higher than those from Mekong River  reported by O.brevirostris populations may be associated with the differentpolymorphic microsatellite markers used in these two studies. However, our analysisof mtDNA data also reveals that the haplotype and nucleotide diversities ofO. brevirostris in Thailand  are muchhigher than those in Mekong River  and Chilika Lagoon  reported by O. brevirostris within the Gulf of Thailand remainshigh (Hd = 0.915 and π = 0.860 %), which is comparable to those in the Gulf ofThailand (Hd = 0.845 and π = 1.150 %) reported by Neophocaenaphocaenoides, for which the genetic diversity of a riverine populationwas lower than coastal populations , which is larger than individual dispersal distances.Although smaller geographic distances (mean 228.072 km) between EG and NG,significant genetic differentiation (both mtDNA and microsatellite data) remainedbetween them. No significant genetic differentiation was found between AS and otherregions based on different types of molecular markers, despite considerabledistances between them (mean 653.853 km) and obvious environmental breaks, such asthe Strait of Malacca. Perhaps this is an artefact of small sample sizes in AS, andthat more genetic data are needed to accurately determine population structurebetween this region and elsewhere.Our microsatellite data reveals the genetic structure of O. brevirostris in Thailand.Geographical barriers formed from oceanographic variables, such as ocean currents,upwelling, bathymetry, sea surface temperature, primary productivity, and salinity,can affect cetacean genetic structure . Our results, together with isotopevariability in teeth , indicat


Manilkara multifida Penn. populations, comparing the genetic parameters of adult and juvenile trees. In particular, we collected leaves from adults and juveniles of M. multifida in two protected areas, the Veracel Station (EVC) and the Una Biological Reserve (UBR), located in threatened Atlantic Forest fragments. We observed a substantial decay in genetic variability between generations in both areas i.e., adults’ HO values were higher  than juveniles’ (EVC = 0.463 and UBR = 0.560). Both juveniles and adults showed genetic structure between the two areas (θ = 0.017 for adults and θ = 0.109 for juveniles). Additionally, forest fragments indicated an unexpectedly short gene flow. Our results, therefore, highlight the pervasive effects of historical deforestation and other human disturbances on the genetic diversity of M. multifida populations within a key conservation region of the Atlantic Forest biodiversity hotspot. The Atlantic Forest remnants in southern Bahia, Brazil, contain large tree species that have suffered disturbances in recent decades. Anthropogenic activities have led to a decrease in the population of many tree species and a loss of alleles that can maintain the evolutionary fitness of their populations. This study assessed patterns of genetic diversity, spatial genetic structure, and genetic structure among  Tropical forests retain the greatest biodiversity on Earth, yet they have been drastically deforested and degraded due to anthropogenic activities ,2. CurreUnderstanding the effects of anthropogenic disturbances on ecological and evolutionary processes is vital to perceive the long-term viability of current populations, especially threatened and endemic ones. From this perspective, the importance is evident of integrating knowledge of the influence of habitat loss in a genetic approach to broaden the understanding of ecological and evolutionary processes. The population genetics approach allows inferences about connectivity between forest fragments by analyzing genetically distinct populations . EstimatThe decrease in species dispersion rate can affect the mating system and spatial genetic structure of trees. A decrease in species dispersion rate occurs because disconnection and increasing distance between populations increase the probability of mating between closely related individuals, leading to a reduction in genetic diversity due to inbreeding . AdditioSince gene flow indicates the movement of genetic material between populations, its interruption increases the genetic divergence between populations, likely leading to their isolated among habitats . TherefoAdditionally, inbreeding can generate drastic consequences for populations, such as increased homozygosity and decreased allele frequency, leading to allele fixation and inbreeding depression . GeneticIt is challenging to understand the effect of the environment and human activities on species’ past and current genetic diversity ,17. SpecDalbergia nigra (Vell.) Allemao ex Benth. Popularly known as Brazilian rosewood, it is an endemic Atlantic Forest species. Since 1998, it has been listed as “Vulnerable” due to overexploitation of trees for its high-quality timber. Some species affected by anthropogenic disturbances are likely to go extinct if they cannot adapt [Melanoxylon brauna), Bahia rosewood (D. nigra), and brazilwood (Paubrasilia echinata) have a declined [Molecular studies are widely used to provide insights on genetic structure, diversity, and relationships among species by investigating species at the population level. The Atlantic Forest in southern Bahia, Brazil, is a hotspot biome, including endemic and endangered species . Due to ot adapt . Despitedeclined ,27,28.According to previous studies ,26, botaM. multifida, in two protected Atlantic Forest fragments in southern Bahia. Our focal tree species belongs to the genus Manilkara (Sapotaceae family), which is exploited for its hard and heavy wood, edible fruits, and latex. The fruits are consumed by a wide range of forest vertebrates, providing key food resources, especially for primates [M. multifida is a large tree that can reach approximately 30 m in height, and only occurs in Bahia within remaining Atlantic Forest areas, classified as one of the most threatened biomes in the world. Due to the severe forest loss and fragmentation, the species is currently classified as “Endangered” by the International Union for Conservation of Nature (IUCN) [Therefore, these endemic plant species have high global priority for preservation ,32,33. Tprimates . M. multe (IUCN) , with reM. multifida populations in the two protected areas; (iii) estimated the gene flow of this tree species within and between protected areas, to evaluate the dispersal distance. In particular, we predicted (i) lower genetic diversity of juveniles than adults, given they represent the generation under the most intense impact of forest loss and anthropogenic disturbances; (ii) a high level of genetic structure between populations due to the intense history of human disturbances in the region combined with the long distance between the two sampled protected areas, causing us to believe that both populations are derived from expansion from an original gene pool with consecutive migration events; (iii) short distance of gene flow of the populations due to isolation of the protected areas. Based on our findings, we finally discuss the effects of human disturbances on the loss of genetic diversity and genetic structure of M. multifida populations, comparing genetic parameters of adult and juvenile trees, to account for the period before and after forest loss.In this study, we (i) compared the genetic patterns among juvenile and adult trees within each protected area; (ii) estimated the genetic structure among 2, ranging along the Brazilian Atlantic coast, with additional patches in Argentina and Paraguay [The Atlantic Forest is the second-largest tropical forest in South America. Its original area was approximately 1,500,000 kmParaguay . CurrentParaguay . We condParaguay . EVC hasParaguay . UBR is Paraguay . M. multifida in each protected area, keeping a minimum distance of 10 m from any sampled tree, since the genus is considered to be dispersed over short distances [®, Schaffhausen, Switzerland). All told, we sampled leaves of 50 adults and 50 juveniles in EVC, and 45 adults and 34 juveniles in UBR. Our sampling corresponded to approximately 1/3 of the total area of EVC and 1/8 of the UBR area. The ratio between adults and juveniles in these natural forests is 1:1.We performed an active search for juveniles and adults of istances . We cons® or VIC®, and 1U of Taq polymerase. The PCR followed the conditions: 94 °C for 3:30 min; 30 cycles of 94 °C for 1 min; specific annealing temperature of each primer for 45 s [® .We used the CTAB protocol to extract DNA from leaf tissues , and genfor 45 s ; 72 °C fO), and genetic diversity (HE) under the Hardy–Weinberg equilibrium. The level of inbreeding within a population was assessed by the inbreeding coefficient (f). The mean values of the allelic richness, HE, HO, and f were estimated considering a 95% confidence interval (95% CI) for all loci. Additionally, we calculated the genetic structure for adults and juveniles in both conservation units considering the F-statistics. The fixation index f and differentiation index θ were determined by performing 1000 permutations for all loci with Bonferroni sequential correction for multiple comparisons (α = 0.05). The results of all parameters were estimated by the FSTAT v.2.9.3.2 software [For each generation from each protected area we first estimated the allelic richness, observed heterozygosity , and HO . Although the inbreeding coefficients (f) were also similar (EVC = 0.103 and UBR = 0.097), they were positive and significant for both populations . In general, our genetic diversity estimations showed no statistical significance, considering only adults from both protected areas. We observed that when comparing the number of alleles (Na) between generations, adults in both protected areas showed higher values (EVC = 12.9 and UBR = 10.9) than juveniles (EVC = 9.9 and UBR = 9.9). We also found that adults from EVC and UBR had similar values for allelic richness , HE (EVC = 0.731 and UBR = 0.729), and HO (EVC = 0.463 and UBR = 0.560). However, the inbreeding coefficient was higher for juveniles (f = EVC = 0.366 and UBR = 0.231) than adults (EVC = 0.103 and UBR = 0.097). Moreover, we detected a significant difference  of the f-value for juveniles between EVC = 0.366 and UBR = 0.231 , while juveniles showed accentuated differentiation between both areas .We also observed that juveniles of both protected areas presented similar values for allelic richness (EVC = 8.1 and UBR = 7.1), H = 0.231 . When coPaternity analysis revealed that 21 (49%) juveniles whose parents were detected showed positive LOD scores. We identified seven juveniles (16%) whose parents were detected with 95% confidence level. The remaining trees (84%) had low probability of paternity. The juveniles with the same parent label indicated that selfing has occurred in the sampled areas. We also observed that the maximum distance between individuals was 13.0 and 5.28 km in UBR and EVC, respectively. Additionally, the maximum distance between juveniles and adults of different populations was 127.64 km.We did not find any spatial genetic structure in any of the trees from both protected areas see .M. multifida, in two protected areas of the Brazilian Atlantic Forest hotspot. Additionally, we contrasted the genetic diversity among adults and juveniles, revealing a strong decay in genetic variability between generations in both protected areas. This has occurred due to habitat loss and fragmentation of the forest remnants in the region, which has led to reduction in their populations, with negative effects on heterozygosity. We also found that in studied fragments of Atlantic Forest, juveniles showed greater genetic structure than adults, likely reflecting the responses of young life stages to forest fragmentation and isolation of the populations. Finally, paternity analysis revealed that most identified parents of juveniles are in the same protected area, indicating that gene flow occurs mainly over a small distance. Our findings, therefore, highlight the pervasive effects of historical deforestation and fragmentation on the genetic diversity of M. multifida populations, a native Atlantic Forest species present in the areas for a long period and hypothetically contemplating two periods (before and after fragmentation). We detected novel results on the patterns of genetic diversity of an endemic and threatened tropical tree species, M. multifida inhabiting each surveyed area (Podocarpus sellowii (Klotz.), due to the small size of the remnant population [M. multifida. Indeed, adult trees often show responses of past landscape conditions on their genetic diversity [Analyses of genetic diversity revealed low observed heterozygosity among juveniles of yed area . As for pulation . Before pulation , it is liversity ,55,56.M. multifida in the studied region, since this species has been massively logged due to its high timber value [M. multifida future generations [A myriad of anthropogenic disturbances including deforestation, fragmentation, and overexploitation have likely affected the remaining populations of er value . The syner value , the negerations . Apart ferations ,59.Manilkara huberi (Ducke) [Prunus africana (Hook.f.) Kalkman in Kenya’s Kakamega Forest [Swietenia macrophylla King in the Brazilian Amazon [M. multifida. Studies in this respect exist in the Amazon Forest, revealing the interaction of M. huberi with bees of the genera Melipona, Trigona, Plebeia, Tetrapedia, and Augochloropsis [M. multifida with these pollinators. As for the potential dispersers [Manilkara interact with the golden-headed lion tamarin (Leontopithecus chrysomelas) in our region, given that species from this genus provide resources such as fruit and nectar [We found inbreeding of both adults and juveniles inhabiting both protected areas. However, juveniles belonged to the smallest gene pool that remained in the populations after human disturbances. Additionally, despite the fact that no spatial genetic structure was found in the sampled populations, high inbreeding values might be related to historical aggregated crossing between individuals due to small-scale dispersion, a phenomenon also observed in the Amazon Forest for  (Ducke) . We obse (Ducke) ,60. Othen Amazon . Inbreedloropsis . Thus, wloropsis , suggestspersers , reported nectar .M. multifida populations, isolating their individuals inside Atlantic Forest remnants. Other tropical trees have been found to have the same increase in differentiation index over a generation, such as the palm Euterpe edulis [M. multifida [Regarding population genetic structure, our results revealed that the differentiation of adult populations between the two protected areas is lower than that of juveniles. Despite the possible existence or homoplasy reported by Angers et al. (2000) , our rese edulis . The decultifida .Prunus mahaleb [Araucaria angustifolia [E. edulis was due to habitat loss [Our paternity analyses corroborated the inbreeding results, since most juveniles descended from adult trees inhabiting the same protected area . Further mahaleb  and Araustifolia . Moreovetat loss . The posM. multifida populations in the two protected areas still contain high levels of allelic richness. Nevertheless, anthropogenic disturbances have led to a reduction of heterozygosity in juveniles. This situation requires attention, since the diversity of the population can decline further over time even in the presence of adaptive potential to survive. Our results call attention to the importance of mitigation actions to contain deforestation in this region, since it is a key conservation area within the Atlantic Forest biodiversity hotspot. The low genetic diversity can be caused by the reduced effective population size of juveniles, which indicates the need to implement measures to improve habitat protection and expand forest cover via restoration projects in severely deforested landscapes.Our results show that the M. multifida. The choice native species that are ecologically appropriate and genetically diverse is an important part of rehabilitating degraded habitats. We evaluated whether populations of M. multifida growing in two protected areas had the desired genetic diversity, and thus can form a viable population likely to persist for a long time in a degraded landscape. Further studies are needed to understand the mating pattern of M. multifida to confirm the exact reasons for the restricted gene flow. However, we suggest that this species can be further used for restoration programs in threatened Atlantic Forest fragments.The inbreeding and high genetic structure caused by isolation can generate significant constraints on population sizes. The two protected areas should be appropriately managed to conserve high genetic diversity, which can help maximize conservation of the regional diversity of


Gallus domesticus, herein abbreviated BBCs) are well known for their unique appearance and medicinal properties and have a long breeding history in China. However, the genetic diversity and demographic history of BBCs remain unclear. In this study, we analyzed 844 mitochondrial DNA D-loop sequences, including 346 de novo sequences and 498 previously published sequences from 20 BBC breeds. We detected a generally high level of genetic diversity among the BBCs, with average haplotype and nucleotide diversities of 0.917 ± 0.0049 and 0.01422, respectively. Nucleotide diversity was highest in populations from Southwest China (0.01549 ± 0.00026), particularly in Yunnan Province (0.01624 ± 0.00025). Significant genetic divergence was detected between most breeds, particularly between Yunnan chickens and those from all other provinces. Haplogroups F and G had the highest levels of genetic diversity and were restricted to Southwest China, particularly Yunnan Province. Based on neutrality tests and mismatch distribution analyses, we did not obtain evidence for rapid population expansions and observed similar demographic histories in BBCs and local non-BBCs. Our results suggest that Chinese BBCs have complex breeding histories and may be selected in situ from local domestic chickens. These results improve our understanding of the genetic heritage and breeding histories of these desirable chickens.Black-boned chickens ( Gallus gallus domesticus; herein abbreviated BBCs), renowned for their characteristic black skin, bone, and muscle, have a long history, appearing in the ancient Chinese herbology volume “Bencao Gangmu” written around 1578 C.E. . Animal handling and experimentation followed the animal experimental procedures and guidelines approved by the Ethics Committee of Jiaying University (#20151103). Genomic DNA was extracted using the standard phenol–chloroform method, and the DNA concentration and purity were assessed by gel electrophoresis and using a NanoDrop Spectrophotometer 2000 . Additionally, 498 published mtDNA d-loop sequences for 15 BBC breeds in China (Table S2) as well as mtDNA d-loop sequences of local non-BBCs (Table S3) were retrieved from GenBank (www.ncbi.nlm.nih.gov).A total of 346 wing-vein blood samples were collected and stored at −80 °C in the sample database of Jiaying University. These samples were obtained from 13 BBC breeds distributed across nine provinces in China (d-loop was amplified using the primers L16750 (5′-AGGACTACGGCTTGAAAAGC-3′′) , 2.4 μL of dNTPs (2.5 mM), 0.3 μL of each primer (20 pmol/μL), 0.3 μL of rTaq polymerase , 23.2 μL of ddH2O, and 0.5 μL of genomic DNA (50–100 ng/μL). The cycling profile included a 4-min preliminary denaturation cycle at 94 °C, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 63 °C for 1 min, and extension at 72 °C for 50 s, with a final extension at 72 °C for 10 min.The The PCR products were separated by electrophoresis on a 1.5% agarose gel containing GelRed , and visualized under ultraviolet light. Sequencing of the D-loop was carried out at Guangzhou IGE Biotechnology Co., Ltd.  using an ABI 3730xl Analyzer .π) and haplotype diversities (Hd) were calculated using DnaSP 6.10.01 . To further explore geographical structure, an analysis of molecular variance (AMOVA) was also calculated in ARLEQUIN 3.5 (Excoffier and Lischer Fs and Tajima’s D) were calculated using ARLEQUIN 3.5  belonging to 20 BBC breeds in China. In total, 116 haplotypes were identified (nps 1–518), including 90 haplotypes exclusive to a single breed and 26 haplotypes shared by two or more breeds. Yunnan Province had the most haplotypes (54), followed by Zhejiang (33), Guizhou (24), and Sichuan (15). BBCs from Yunnan and Zhejiang provinces had more private haplotypes (Table S4). The 116 haplotypes belonged to haplogroups A–G and Z (Table S4). The geographical distribution of mtDNA haplogroups of BBCs is shown in Table S5. Interestingly, a similar pattern (haplogroups F and G) was also observed in non-BBCs in China (Table S6). Overall, all seven haplogroups were found in Yunnan Province, whereas the other provinces lacked two or more haplogroups.Our analysis included 844 mtDNA D-loop sequences (346 d-loop sequences for BBCs (n = 844) and local non-BBCs (n = 1663) did not demonstrate BBC-specific or non-BBC-specific patterns, and the two groups shared the same haplogroups or major haplotypes .A median-joining phylogenetic network based on 844 mtDNA D-loop sequences showed a clear geographical pattern . HaplogrHd and π values, and the average number of nucleotide differences (K) for all samples were 0.917 ± 0.0049, 0.01442, and 7.365, respectively , while the Silkies breed had the lowest (0.00733 ± 0.00063). With respect to the 11 provinces, BBCs from Yunnan Province had the highest π value (0.01624 ± 0.00025), while those from Jiangxi Province had the lowest (0.01024 ± 0.00062). Regionally, the highest π value was detected in Southwest China (0.01549 ± 0.00026) and the lowest was detected in Northwest China (0.01162 ± 0.00081). Regarding Hd, Yunnan, Guangxi, Henan, and Zhejiang Provinces showed the highest values (>0.9), while Fujian and Jiangxi Provinces had the lowest (<0.8) . Estimates of genetic diversity for major haplogroups are presented in Table S8. Briefly, π values were the highest in haplogroups F and G in Southwest China.The ectively . The Wult (<0.8) . CombiniFST values were computed using ARLEQUIN 3.5 according to chicken breeds and provinces. A non-metric multidimensional scaling plot was subsequently generated based on the pairwise FST values to ascertain population/province relationships . The Yunxian Black-boned breed showed the greatest differentiation from other breeds, while Silkies, Hubei Silky black, and Sichuan Silky breeds were clustered together . The BBC populations from Yunnan Province were significantly divergent from those from other provinces .To evaluate genetic differentiation among chickens, pairwise Table S9). This suggests that the molecular variance mainly exists within breeds, followed by provinces, and finally regions. These results are generally in accordance with the results of FST analyses.The AMOVA showed that variance was higher within populations than among populations within groups or among groups . The mismatch distribution graph is in accord with the results of neutrality tests .Neutrality tests and a mismatch distribution analysis of BBCs and non-BBCs were performed to detect population trajectories of BBCs. As determined by Fu’s utrality . All Tajutrality . In the d-loop sequences for 20 breeds from 11 provinces across China, we characterized genetic diversity and genetic differentiation in Chinese BBCs, which show interesting geographical patterns. Haplogroups A–G were disproportionately observed among the 844 chickens. Additionally, these haplogroups showed differential geographical endemicity. Common haplogroups, including A, B, and E, were found in all eleven provinces. However, haplogroup C was absent in Northwest China, haplogroup D occurred in Central and East China, while haplogroups F and G were restricted to Southwest China. Interestingly, non-BBCs in China showed a similar geographical distribution pattern to those of haplogroups F and G.Based on the most comprehensive dataset to date, including 844 mtDNA Specific mitochondrial haplogroups are widely used as candidate genetic markers to trace the demographic history of chickens (Lan et al. To evaluate this possibility, we performed detailed genetic analyses of mtDNA D-loop sequence data for Chinese BBCs. Compared with that of other indigenous Chinese chickens, such as chicken breeds from Guangdong Province and its adjacent regions (Huang et al. in situ from local domestic chickens (Weng et al. Neutrality tests indicated that BBCs in China have not undergone rapid population expansion. The mismatch distribution graph showed that BBCs and non-BBCs share similar demographic trajectories, except for those from Henan and Hubei provinces. This finding is in accordance with the results of Huang et al. a. A neigFs and pairwise FST values indicated that no breed deviates from neutrality, whereas deviations were detected at the province/region level. It is noteworthy that genetic analyses by haplogroups showed that F and G, privatized to Southwest China, have higher π values than those of other haplogroups, including A and C. Although previous research has reported that the chickens from Yunnan Province display high levels of genetic diversity and multiple unique mtDNA haplogroups (Liu et al. The significant differentiation between chickens from Southwest China, particularly Yunnan Province, and those from other regions suggests that BBCs of Southwest China experienced limited gene flow with each other and with chicken from other regions, with only weak genetic selection (Miao et al.


Guladentiasubtussulcata . The auxiliary copulatory organ of this species is very peculiar, similar to that of Jeanneretia L. Pfeiffer, 1877, and different from that of other cepolids. It consists of an elongate, pedunculate mucus gland inserted apically on a muscular papilla and an atrial sac, all covered by a sheath. A sheath-like accessory gland is inserted at the base of the atrial sac. Another similarity with Jeanneretia is the presence of a fertilization pouch-spermatheca complex with a single exposed spermatheca. Like Jeanneretia, G.subtussulcata has an oxygnath, highly arched jaw with slight striae over the entire surface and a broad, well-developed median projection. The radula has triangular and monocuspid central and lateral teeth . The marginal teeth are multicuspid with the mesocone and ectocones smaller than the endocones. The similar structures of the auxiliary copulatory organ (without dart sac) and spermatheca (simple) strongly suggest that G.subtussulcata and Jeanneretia spp. are closely related. As such, it remains to be decided whether Guladentia Clench & Aguayo, 1951 and Jeanneretia should continue to be treated as separate genera.This study provides the first data on the genital anatomy, jaw and radula of  Guladentia Clench & Aguayo, 1951, is a Cuban endemic terrestrial snail genus of the family Cepolidae. It was originally described as subgenus of Jeanneretia L. Pfeiffer, 1877  modica Clench & Aguayo, 1951 and J. (G.) gundlachi Clench & Aguayo, 1951. While Guladentia was explicitly maintained as a subgenus by Guladentia differs conchologically from Jeanneretia by (1) possessing a shell with a well-defined “gular” fold, which is an invagination of the shell on the base of the body whorl, curved and parallel with the whorl about midway between the whorl periphery and the columella, and by (2) having a long and curved tooth on the base of the shell within the aperture. Thus, according to Guladentia would resemble that of the genus Cepolis Montfort, 1810 .Species of ite rare , yet, G.Cepolidae taxa, including the genus Guladentia, is still unknown. The present contribution, therefore, aims to provide the very first data on the genital anatomy, jaw, and radula of the type species of this genus, viz. G.subtussulcata, and on the basis of these new data it also briefly reflects on the (sub)generic status of Guladentia.G.subtussulcata were collected from three localities in Viñales, Pinar del Río Province, Cuba. The material examined is deposited in the Malacological Collection of the Institute of Ecology and Systematics .Nine live specimens of Material examined • 7 specimens; Mogote El Valle; 22°37'9.3"N, 83°41'33.09"W; 20 May 2014; M. Hernández Leg.; CZACC8. A.0300 to 0307 • 1 specimen; Mogote Dos Hermanas; 22°37'05"N, 83°44'38"W; 5 July 2014; M. Hernández Leg.; CZACC8. A.0308 • 1 specimen; Sierra de Viñales; 22°38'36"N, 83°44'46"W; 6 July 2014; M. Hernández Leg.; CZACC8. A.0309.Specimens were drowned for 12 h in an airtight jar filled with water, after which they were removed from their shells and fixed in 70% ethanol. Specimens were dissected using a Carl Zeiss Stemi 2000 stereomicroscope. The reproductive tracts were photographed with a Nikon 5100 camera. Radula and jaw were extracted manually, cleaned by soaking in 10% KOH solution for about 6 h followed by rinsing in ethanol. They were mounted for scanning electron microscopy with a Thermo Fisher Quanta 200 scanning electron microscope.The terminology of the reproductive apparatus follows The complete genitalia is shown in Fig. The jaw is oxygnath Fig. , solid, Guladentiasubtussulcata is similar to that of other cepolid species by, amongst other features, the presence of an auxiliary copulatory organ. Yet, while in other cepolids this auxiliary copulatory organ contains a dart sac (on top of the muscular papilla), there is no dart sac in G.subtussulcata  and the spermatheca (simple) strongly suggests that old Fig.  and the old Fig.  of Gulad