Genetic diversity and population structure of Trichilia emetica Vahl in western Kenya using ISSR markers

Over the last 10 years plant pathologists have begun to realize that more knowledge about the genetic structure of populations of plant pathogens is needed to implement effective control strategies (48). Research on the genetic structure of fungal populations has mushroomed, and review papers that summarize these studies are numerous (7,27,33,34,38). Although the number of fungal studies has increased greatly, the most comprehensive work has focused on a small number of plant-pathogenic fungi. The majority of these fungi can be recognized easily by their fruiting bodies or disease symptoms on aboveground plant parts. It has proven more difficult to assess the genetic structure of fungal populations that exist mainly belowground, because the distribution of individuals cannot be visualized directly and appropriate sampling procedures are less obvious and more cumbersome. Nevertheless, substantial progress has been made in interpreting the population genetic structure of some soilborne fungi (1,17). The purpose of this paper is to provide an overview of the tools and techniques of fungal population genetics. I will try to emphasize approaches that may be applied to studies of soilborne fungi. Instead of providing detailed methods, I will cite recent references where appropriate. There are many opinions regarding which techniques and tools are best suited to studies of fungal populations. I will give a personal and biased viewpoint, which I believe will be most useful to those who are just entering the field.

The article listed below, published in journal Genetika has been retracted due to evidence indicating that the peer review of this paper was compromised, using of frauted data, high number of unfitting citation, overoll general misconduct related to professional codes of ethics. All papers which belong to this group have passed a regular review process. As part of the reviewing process, according to Journal policy, it is expected from reviewers to check all relevant data including citations probity. All papers were published after two positive reviewers? opinions. The journal Genetika condemns such an unethical behavior and will take all necessary measures to ensure that such incidents do not happen again in the future. Authors of those papers as well reviewers are barred from publishing in the journal Genetika in the future and will be blacklisted by the journal. The list of retracted articles is: 1. Bouzarisaravani Z., F. Sharifnia, F. Salimpour, S. Arbabian, A. Geran (2021). Molecular systematic studies in the genus Glaucium (Papaveraceae). - Genetika, Vol 53, No.3, 1179-1192 https://doi.org/10.2298/GENSR2103179B 2. Hang L., L. Pan, T. Yong, L. Jianguo, X. Xingmin, Faisal (2021). Population genetic structure and gene flow in Alcea aucheri (boiss.) Alef.: a potential medicinal plant- Genetika, Vol 53, No.2, 867-882. https://doi.org/10.2298/GENSR2102867H 3. Jiao L., H. Xiao, X. Zhao, F. M. Abarghuei (2021). RAPD profiling in detecting genetic variation in Glaucium (Papaveraceae) species: Edible and Medicinal plant. - Genetika, Vol 53, No.3,1081 - 1092. https://doi.org/10.2298/GENSR2103081J 4. Li H., H. Yu, X. Zeng, S. Hussein Hamarashid (2021). Study on genetic diversity between Malva L. (Malvaceae): a high value medicinal plant using SCoT molecular markers.- Genetika, Vol 53, No.2, 895-910 https://doi.org/10.2298/GENSR2102895L 5. Li H., Y. Wang, R, Iqbal (2021). SCoT molecular markers and population differentiation in Hedera helix L.. - Genetika, Vol 53, No.2, 739-756. https://doi.org/10.2298/GENSR2102739L 6. Li J., X. Yang, S.Mehri (2021). Genetic diversity in Stellaria L. (Caryophyllaceae) using sequence related amplified polymorphism. - Genetika, Vol 53, No.3, 1369 - 1377. https://doi.org/10.2298/GENSR2103369L 7. Lin L., L. Lin, A.Waheed (2021). Assessment of genetic structure and diversity of Erodium (Geranaiceae) species. - Genetika, Vol 53, No.2, 507-520. https://doi.org/10.2298/GENSR2102507L 8. Li S. X. Jiang, S. Mehri (2021). Genetic diversity and gene-pool of Aegilops tauschii coss. (Poaceae) based on retrotransposon-based markers. - Genetika, Vol 53, No.3, 1331- 1340. https://doi.org/10.2298/GENSR2103331L 9. Ma X., H. Tian, H. Xia, Zeenat (2021). Genetic diversity of Lonicera L. (caprifoliaceae) estimated by molecular markers and morphological characters. - Genetika, Vol 53, No.2, 651-662. https://doi.org/10.2298/GENSR2102651M 10. Mahdavi M., F. Sharifnia, F.Salimpour, A. Esmaeili, M. Larypoor (2021). Genetic diversity and population structure of Iranian pistachio (Pistacia vera L.) cultivars.- Genetika, Vol 53, No.2, 671-686 https://doi.org/10.2298/GENSR2102671M 11. Meng K., J. Yao, C.Y. He and H. Morabbi Heravi (2021). Gene flow and genetic structure between populations of Hesperis L. (Brassicaceae) species using molecular markers. - Genetika, Vol 53, No.2, 769-782. https://doi.org/10.2298/GENSR2102769M 12. Mowang S.-C., F.-J. Chen, Zeenat (2021). Study on genetic diversity between Erodium (Geranaiceae) species based on inter-simple sequence repeat markers- Genetika, Vol 53, No.2, 927-939. https://doi.org/10.2298/GENSR2102837M 13. Najafian S., I.Mehregan, A. Iranbakhsh, M. Assadi, S. Fici (2021). Species delimitation in Capparis (Capparaceae): morphological and molecular. - Genetika, Vol 53, No.2, 609-627. https://doi.org/10.2298/GENSR2102609N name mark red not autors of paper (corrigentdum) 14. Nikkhah M., S. Arbabian, A. Majd, F. Sharifnia (2022). Genetic diversity of Cordia myxa L. assessed by ISSR markers. - Genetika, Vol 54, No.1, 63-72. https://doi.org/10.2298/GENSR2201063N 15. Ou C., Z. Shen, Y. Liu, Z. Wang, M. Farshadfar (2021). Morphometric analysis and genetic diversity in Pistacia species populations using sequence related amplified polymorphism. - Genetika, Vol 53, No.3, 1193-1205 https://doi.org/10.2298/GENSR2103193O 16. Qian X. and S. Mehri (2021). Detecting DNA polymorphism and genetic diversity in a wide pistachio germplasm by RAPD markers- Genetika, Vol 53, No.2, 783-798 https://doi.org/10.2298/GENSR2102783Q 17. Xu P.,C. Xu, X.Huang, H.Wang, H. Morabbi Heravi (2021). Genetic diversity and genepool of Salicornia sinus-persica akhani based on retrotransposon-based markers. - Genetika, Vol 53, No.3, 1287 - 1296.https://doi.org/10.2298/GENSR2103287X 18. Garshasbi S., A. Iranbakhsh, Y. Asri, S. Z. Bostanabad (2021). Genetic diversity and population structure analysis in Lonicera L. (Caprifoliaceae) with the use of ISSR molecular markers. - Genetika, Vol 53, No.3, 1273 - 1286 https://doi.org/10.2298/GENSR2103273G name mark red not autors of paper (corrigentdum) 19. Sun Y., H. Jiang, F. Zeng, X. Pan, X. Wu, Y. Qi, X. Wu (2022). Species identification and genetic diversity of Alcea (Malvaceae) using SCOT molecular markers: medicinal plant. - Genetika, Vol 54, No.1, 369-378. https://doi.org/10.2298/GENSR2201369S 20. Ting S. and Y. Yibing (2022). Population differentiation and gene flow of Glaucium flavum (Papaveraceae). - Genetika, Vol 54, No.1, 275-288 https://doi.org/10.2298/GENSR2201275T 21. Xu P.,C. Xu, X.Huang, H.Wang, H. Morabbi Heravi (2021). Genetic diversity and genepool of Salicornia sinus-persica akhani based on retrotransposon-based markers. - Genetika, Vol 53, No.3, 1287 - 1296. https://doi.org/10.2298/GENSR2103287X 22. Yanpeng Z., W. Hongmei, L. Wei, M. Khayatnezhad, Faisal (2021). Genetic diversity and relationships among Salvia species by ISSR markers. - Genetika, Vol 53, No.2, 559-574. https://doi.org/10.2298/GENSR2102559Y 23. Yao X., R. Zhou, M.Farshadfar (2021). Comparison of individual based approaches using RAPD markers for identifying genetic relationships in Erodium (Geranaiceae)- Genetika, Vol 53, No.3, 1229 - 1238 https://doi.org/10.2298/GENSR2103229Y 24. Yin J. (2022). Evaluation of genetic variability Rindera using RAPD markers. - Genetika, Vol 54, No.1, 173-186. https://doi.org/10.2298/GENSR2201173Y 25. Zhang X. and A. Shakoor (2021). Strong genetic differentiation of the Paracaryum species (Boraginaceae) detected by inter-simple sequence repeats (ISSR).- Genetika, Vol 53, No.2, 883-894 https://doi.org/10.2298/GENSR2102883Z 26. Zhang Z., H. Yu, S. Feng, A. A. Minaeifar (2021). Species identification and population structure analysis in Hesperis L. (Brassicaceae). - Genetika, Vol 53, No.3, 1357 - 1368 https://doi.org/10.2298/GENSR2103357Z 27. Zhou Y. and Z. Zheng (2022). Genetic Diversity and inter-relationship among Stellaria L. (Caryophyllaceae) species ISSR markers. - Genetika, Vol 54, No.1, 119-130. https://doi.org/10.2298/GENSR2201119Z In addition, Clarivate provided the publisher with evidence of inappropriate manipulation of citations of five paper published in journal Genetika in journal Bioscenece research: 1. Bi D., D. Chen, M. Khayatnezhad, Z. S. Hashjin, Z. Li, Y. Ma (2021). Genetic response of growth phases for abiotic environmental stress tolerance in cereal crop plants. - Genetika, Vol 53, No.1,393-405 https://doi.org/10.2298/GENSR2101393B 2. Chen W., M. Khayatnezhad, N, Sarhadi (2021). Gene flow and population structure in Allochrusa (Caryophylloideae, caryophyllaceae) with the use of molecular markers- Genetika, Vol 53, No.2, 799-812 https://doi.org/10.2298/GENSR2102799C 3. Jia Y., M. Khayatnezhad, S. Mehri (2020). Population differentiation and gene flow in Erodium cicutarium: a potential medicinal plant- Genetika, Vol 52, No.3, 1127-1144. https://doi.org/10.2298/GENSR2003127J 4. Peng X., M. Khayyatnezhad and L. Joudi Ghezeljehmeidan (2021). RAPD profiling in detecting genetic variation in Stellaria L. (Caryophyllaceae).- Genetika, Vol 53, No.1,349 -362. https://doi.org/10.2298/GENSR2101349P 5. Yin J., M. Khayatnezhad, A. Shakoor (2021). Evaluation of genetic diversity in geranium (Geraniaceae) using RAPD marker.- Genetika, Vol 53, No.1,363 -378. https://doi.org/10.2298/GENSR2101363Y Authors who misused the papers published in Genetika by citing them unjustifiably as well as authors of the cited papers are barred from publishing in that journal in the future and will be blacklisted by the journal. We would like to apologize authors, readers and all scientific community that we are having to make those retractions, and we will take all necessary steps to ensure our editorial and peer review processes keep pace with the evolving threat and advancements in scientific fraud. Snezana Mladenovic Drinic, editor <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103179B">10.2298/GENSR2103179B</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102867H">10.2298/GENSR2102867H</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103081J">10.2298/GENSR2103081J</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102895L">10.2298/GENSR2102895L</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102739L">10.2298/GENSR2102739L</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103369L">10.2298/GENSR2103369L</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102507L">10.2298/GENSR2102507L</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103331L">10.2298/GENSR2103331L</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102651M">10.2298/GENSR2102651M</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102671M">10.2298/GENSR2102671M</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102769M">10.2298/GENSR2102769M</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102837M">10.2298/GENSR2102837M</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102609N">10.2298/GENSR2102609N</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2201063N">10.2298/GENSR2201063N</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103193O">10.2298/GENSR2103193O</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102783Q">10.2298/GENSR2102783Q</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103287X">10.2298/GENSR2103287X</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103273G">10.2298/GENSR2103273G</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2201369S">10.2298/GENSR2201369S</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2201275T">10.2298/GENSR2201275T</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102559Y">10.2298/GENSR2102559Y</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103229Y">10.2298/GENSR2103229Y</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2201173Y">10.2298/GENSR2201173Y</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102883Z">10.2298/GENSR2102883Z</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2103357Z">10.2298/GENSR2103357Z</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2201119Z">10.2298/GENSR2201119Z</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2101393B">10.2298/GENSR2101393B</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2102799C">10.2298/GENSR2102799C</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2003127J">10.2298/GENSR2003127J</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2101349P">10.2298/GENSR2101349P</a></b></u> <br><br><font color="red"><b> Link to the retracted article <u><a href="http://dx.doi.org/10.2298/GENSR2101363Y">10.2298/GENSR2101363Y</a></b></u>

The mitochondrial marker, COII, was employed to assess the genetic structure and diversity of Anopheles funestus, a very important malaria vector in Africa that adapt and colonize different ecological niches in western Kenya. Mosquitoes were collected using mechanical aspirators in four areas (Bungoma, Port Victoria, Kombewa, and Migori) in western Kenya. Following morphological identification, PCR was used to confirm the species. The COII gene was amplified, sequenced, and analyzed to determine genetic diversity and population structure. A total of 126 (Port Victoria-38, Migori-38, Bungoma-22, and Kombewa-28) sequences of COII were used for population genetic analysis. Anopheles funestus had a high haplotype diversity (Hd = 0.97 to 0.98) but low nucleotide diversity (Π = 0.004 to 0.005). The neutrality test revealed negative Tajima's D and Fs values indicating an excess of low-frequency variation. This could be attributed to either population expansion or negative selection pressure across all the populations. No genetic or structural differentiation (Fst = -0.01) and a high level of gene flow (Gamma St, Nm = 17.99 to 35.22) were observed among the populations. Population expansion suggests the high adaptability of this species to various ecological requirements, hence sustaining its vectorial capacity and malaria transmission.

Genetic variability analysis of 26 sheep breeds in the Czech Republic

Tall fescue is a perennial cool-season grass with economic importance especially in temperate regions of the northern hemisphere. This study was done to assess the genetic diversity and population structure of 90 tall fescue populations and cultivars using ISSR and EST-SSR markers in order to categorize valuable populations for breeding programs and to construct the core collection of tall fescue collection in Iran. The 10 EST-SSR primer pairs amplified 92 alleles. The allele numbers varied from 4 to 13 alleles per locus with an average of 9.2 alleles, of which 84 (90.6%) were polymorphic with an average of 8.4 polymorphic bands per primer. The 39 ISSR primers totally produced 387 scorable bands, of which 335 (86.6%) were polymorphic with an average of 8.6 polymorphic bands per primer. The amplified markers by ISSR primers varied from 6 to 14 markers per primer with an average of 9.92 markers per primer. The 90 tall fescue populations using both EST-SSR and ISSR data were classified into two clusters by UPGMA method that was coincide with PCA and structure analysis results. The turf-type and forage-type populations were clearly separated. Based on the results, the Iranian populations provide a valuable and novel germplasm to employ in tall fescue varietal improvement programs for both forage and turf-type applications. This progression is an important step to introduce this collection for development of a core collection of tall fescue germplasm in Iran.

Knowledge about genetic diversity and population structure among goat populations is essential for understanding environmental adaptation and fostering efficient utilization, development, and conservation of goat breeds. Uganda's indigenous goats exist in three phenotypic groups: Mubende, Kigezi, and Small East African. However, a limited understanding of their genetic attributes and population structure hinders the development and sustainable utilization of the goats. Using the Goat Illumina 60k chip International Goat Genome Consortium V2, the whole-genome data for 1,021 indigenous goats sourced from 10 agroecological zones in Uganda were analyzed for genetic diversity and population structure. A total of 49,337 (82.6%) single-nucleotide polymorphism markers were aligned to the ARS-1 goat genome and used to assess the genetic diversity, population structure, and kinship relationships of Uganda's indigenous goats. Moderate genetic diversity was observed. The observed and expected heterozygosities were 0.378 and 0.383, the average genetic distance was 0.390, and the average minor allele frequency was 0.30. The average inbreeding coefficient (Fis) was 0.014, and the average fixation index (Fst) was 0.016. Principal component analysis, admixture analysis, and discriminant analysis of principal components grouped the 1,021 goat genotypes into three genetically distinct populations that did not conform to the known phenotypic populations but varied across environmental conditions. Population 1, comprising Mubende (90%) and Kigezi (8.1%) goats, is located in southwest and central Uganda, a warm and humid environment. Population 2, which is 59% Mubende and 49% Small East African goats, is located along the Nile Delta in northwestern Uganda and around the Albertine region, a hot and humid savannah grassland. Population 3, comprising 78.4% Small East African and 21.1% Mubende goats, is found in northeastern to eastern Uganda, a hot and dry Commiphora woodlands. Genetic diversity and population structure information from this study will be a basis for future development, conservation, and sustainable utilization of Uganda's goat genetic resources.

Genetic diversity and population structure of Venturia inaequalis isolates in apple orchards from Turkey

Indian willow (Salix tetrasperma) is an agriculturally useful tree which occurs over a wide geographic area across South Asia and bears importance. So far, this species has never been studied for molecular genetic diversity. The present study was, therefore, carried out to assess the genetic diversity and population structure analysis using RAPD and ISSR molecular markers in diverse genotypes from five populations covering North India. The mean number of effective alleles, Shannon information index and gene diversity i.e., 1.38 ± 0.013, 0.35 ± 0.010 and 0.23 ± 0.007, respectively were obtained with RAPD + ISSR markers. The analysis of molecular variance generated by RAPD + ISSR revealed a higher genetic variation (87%) within population as compared to that of among population (13%). Nei genetic distance was maximum (0.185) between Jammu and Kashmir and Punjab populations. Significant Mantel correlation (r=0.551,) was obtained between RAPD and ISSR markers. Bayesian clustering pattern obtained through STRUCTURE software showed four gene pools. Based on the genetic information obtained with regards to Indian willow by combining the RAPD and ISSR marker systems, it is proposed that an individual tree be selected within populations rather than among populations for the improvement of economic traits of Indian willow alongwith conservation of entire ecological populations.

Climate change is predicted to increase forest fires in boreal forests, which can threaten the sustainability of forest genetic resources. Wildfires can potentially impact genetic diversity and population structure in forest trees by creating population bottlenecks, and influencing demography, effective population size (Ne) and various evolutionary processes. We have investigated this critical issue in a widely-distributed, transcontinental, ecologically and economically important and fire-intolerant boreal conifer, white spruce (Picea glauca (Moench) Voss). We tested the hypothesis that in a predominantly outcrossing species with long distance gene flow, such as white spruce, located in primary undisturbed forests, normal forest fires do not adversely affect genetic diversity and population structure. We used 10 nuclear genic and genomic microsatellite loci to examine genetic diversity and population structure of post-fire pristine old-growth (PF-OG) and adjacent post-fire naturally regenerated young (PF-YR) stands. The genetic diversity, inbreeding and genetic differentiation levels, Bayesian population structure, Ne and latent genetic potential were statistically similar between the PF-OG and PF-YR populations. None of the microsatellites showed any signature of selection. Our study demonstrates that normal wild forest fires do not adversely affect genetic diversity, differentiation, and population genetic structure in white spruce. The results should have wide significance for sustainable forest management.

Genetic diversity and population structure of the mangrove lime (Merope angulata) in India revealed by AFLP and ISSR markers

Forest harvesting of increasing intensities is expected to have intensifying impacts on the genetic diversity and population structure of postharvest naturally regenerated stands by affecting the magnitude of evolutionary processes, such as genetic drift, gene flow, mating system, and selection. We have tested this hypothesis for the first time by employing widely distributed boreal white spruce (Picea glauca) as a model and controlled, replicated experimental harvesting and regeneration experiment at the EMEND project site (http://www.emendproject.org). We used two approaches. First, genetic diversity and population structure of postharvest natural regeneration after five harvesting treatments (green tree retention of 75%, 50%, 20%, and 10%, and clearcut) were assessed and compared with those of the unharvested control (pristine preharvest old‐growth) in two replicates each of conifer‐dominated (CD) and mixed‐wood (MW) forest, using 10 (six EST (expressed sequence tag) and four genomic) microsatellite markers. Second, genetic diversity and population structure of preharvest old‐growth were compared with those of postharvest natural regeneration after five harvesting treatments in the same treatment blocks in one replicate each of CD and MW forests. Contrary to our expectations, genetic diversity, inbreeding levels, and population genetic structure were similar between unharvested control or preharvest old‐growth and postharvest natural regeneration after five harvesting treatments, with clearcut showing no negative genetic impacts. The potential effects of genetic drift and inbreeding resulting from harvesting bottlenecks were counterbalanced by predominantly outcrossing mating system and high gene flow from the residual and/or surrounding white spruce. CD and MW forests responded similarly to harvesting of increasing intensities. Simulated data for 10, 50, and 100 microsatellite markers showed the same results as obtained empirically from 10 microsatellite markers. Similar patterns of genetic diversity and population structure were observed for EST and genomic microsatellites. In conclusion, harvesting of increasing intensities did not show any significant negative impact on genetic diversity, population structure, and evolutionary potential of white spruce in CD and MW forests. Our first of its kind of study addresses the broad central forest management question how forest harvesting and regeneration practices can best maintain genetic biodiversity and ecosystem integrity.

The Suffolk is the primary terminal sire breed in the U.S. As a breed that participates in the National Sheep Improvement Program (NSIP), Suffolk breeders are attempting to accumulate enough genomic information to provide genomic-enhanced estimated breeding values as part of the national genetic evaluations. The effective implementation of genomic selection and management of genetic diversity in the breed require a comprehensive assessment of current genetic diversity and population structure. Therefore, the primary objective of this study is to assess the genetic diversity and population structure present in U.S. Suffolk sheep included in the NSIP using both pedigree- and genomic-based methods. A secondary objective is to compare the levels of genomic diversity of U.S. Suffolk to those from other selected countries. Based on pedigree (n = 75,161) analyses, the generation interval was 2.8 years, and the effective number of founders and ancestors were 504 and 300, respectively. Effective population size ranged from 28 to 194 based on pedigree-based measures and 75 to 85 based on genomic-based metrics. When the mean inbreeding was compared for the 1,878 genotyped animals (GGP Ovine 50K BeadChip) that passed quality control, pedigree-based inbreeding; and, inbreeding based on heterozygosity, runs of homozygosity, diagonal of the genomic relationship matrix, and homozygous-by-descent segments were 4.8%, 3.3%, 4.6%, 3.3%, and 3.4%, respectively. Of the 16 flocks with genotyped animals, four had fixation index values that exceeded 0.10, but the model-based population structure showed admixture across all flocks. For the principal component analysis and the model-based population structure with international genomic datasets, the U.S. Suffolks were distinct, the United Kingdom Suffolks were placed in-between but distinct from the other countries, and the Australian, Irish, and New Zealand Suffolks were grouped together. The current level of genetic diversity and population structure was quantified for the U.S. Suffolk breed. While the rate of inbreeding was at an acceptable level, the effective population size was modest, indicating that monitoring of genetic diversity and strategic mating of less related animals in the breed should continue. As the sheep industry moves forward, regular assessments of genetic diversity and population structure are needed.

Complex parasite life cycles frequently require trophic transfer of parasites from an intermediate host prey to a definitive host predator. This results in aggregated distributions of parasites in predator host populations, which are subsequently expected to host more genetically diverse parasite infrapopulations than lower trophic level hosts. Host dispersal and seasonal population dynamics, particularly in the case of first-intermediate hosts, are also expected to drive population genetic patterns within and across populations. To examine how parasite life history and host ecology influence parasite genetic patterns, we characterized the genetic diversity of within-host infrapopulations, as well as overall population genetic structure, of sympatric tongueworm (Halipegus occidualis) and lungworm (Haematoloechus complexus) freshwater trematode parasite populations. Parasites were collected across three host stages (snail, odonate insect, and frog) and sequenced at the cytochrome oxidase I (COI) mitochondrial region (519 bp for lungworms; 526 bp for tongueworms) to characterize genetic variation within and across hosts. Infection abundance per host and genetic diversity of within-host parasite infrapopulations generally increased with host trophic level, as expected. Additionally, tongueworm assemblages in odonate hosts were essentially equally as genetically diverse (depending on the index used) as those in definitive host frogs; tongueworms have an additional trophic transfer in their life cycle before the odonate stage, which highlights how trophic transmission and multi-host life cycle structure can benefit parasites by increasing genetic diversity of sexually reproducing adult assemblages. We also found that tongueworm populations, which infect a long-lived snail as a first-intermediate host, had higher population genetic diversity than lungworms, which infect a much shorter-lived snail with highly unstable population dynamics. Thus, we expect that first-intermediate host dynamics and dispersal ability played a large role in predicting population-level parasite genetic diversity and genetic structure in this system. This study investigates the effects of small- and large-scale processes on parasite genetic population structure and diversity and provides critical genetic data for future studies on these genera.

BackgroundGlossina pallidipes has been implicated in the spread of sleeping sickness from southeastern Uganda into Kenya. Recent studies indicated resurgence of G. pallidipes in Lambwe Valley and southeastern Uganda after what were deemed to be effective control efforts. It is unknown whether the G. pallidipes belt in southeastern Uganda extends into western Kenya. We investigated the genetic diversity and population structure of G. pallidipes in Uganda and western Kenya.ResultsAMOVA indicated that differences among sampling sites explained a significant proportion of the genetic variation. Principal component analysis and Bayesian assignment of microsatellite genotypes identified three distinct clusters: western Uganda, southeastern Uganda/Lambwe Valley, and Nguruman in central-southern Kenya. Analyses of mtDNA confirmed the results of microsatellite analysis, except in western Uganda, where Kabunkanga and Murchison Falls populations exhibited haplotypes that differed despite homogeneous microsatellite signatures. To better understand possible causes of the contrast between mitochondrial and nuclear markers we tested for sex-biased dispersal. Mean pairwise relatedness was significantly higher in females than in males within populations, while mean genetic distance was lower and relatedness higher in males than females in between-population comparisons. Two populations sampled on the Kenya/Uganda border, exhibited the lowest levels of genetic diversity. Microsatellite alleles and mtDNA haplotypes in these two populations were a subset of those found in neighboring Lambwe Valley, suggesting that Lambwe was the source population for flies in southeastern Uganda. The relatively high genetic diversity of G. pallidipes in Lambwe Valley suggest large relict populations remained even after repeated control efforts.ConclusionOur research demonstrated that G. pallidipes populations in Kenya and Uganda do not form a contiguous tsetse belt. While Lambwe Valley appears to be a source population for flies colonizing southeastern Uganda, this dispersal does not extend to western Uganda. The complicated phylogeography of G. pallidipes warrants further efforts to distinguish the role of historical and modern gene flow and possible sex-biased dispersal in structuring populations.

Kenya has, in the last decade, made tremendous progress in the fight against malaria. Nevertheless, continued surveillance of the genetic diversity and population structure of Plasmodium falciparum is required to refine malaria control and to adapt and improve elimination strategies. Twelve neutral microsatellite loci were genotyped in 201 P.falciparum isolates obtained from the Kenyan-Ugandan border (Busia) and from two inland malaria-endemic sites situated in western (Nyando) and coastal (Msambweni) Kenya. Analyses were done to assess the genetic diversity (allelic richness and expected heterozygosity, [He ]), multilocus linkage disequilibrium ( ) and population structure. A similarly high degree of genetic diversity was observed among the three parasite populations surveyed (mean He =0.76; P>0.05). Except in Msambweni, random association of microsatellite loci was observed, indicating high parasite out-breeding. Low to moderate genetic structure (FST =0.022-0.076; P<0.0001) was observed with only 5% variance in allele frequencies observed among the populations. This study shows that the genetic diversity of P.falciparum populations at the Kenyan-Ugandan border is comparable to the parasite populations from inland Kenya. In addition, high genetic diversity, panmixia and weak population structure in this study highlight the fitness of Kenyan P.falciparum populations to successfully withstand malaria control interventions.