Seasonal differences in Varroa destructor population growth in western honey bee (Apis mellifera) colonies

Varroa destructor is a major threat for apiculture worldwide. A successful approach to control this parasite must include the application of effective treatments at the correct time. To understand the effect that treatment timing has on Varroa populations at different seasons, we conducted an experiment using a dataset comprising two separate field trials over multiple years, both trials containing four apiary sites composed of 20 honey bee colonies across an area representative of north central Florida environments. Before the start of the season, colonies were treated with two acaricides simultaneously to bring the Varroa populations to ∼0.25 mites/100 bees. Following treatment, we monitored the mite populations monthly via alcohol washes. Our results show that the temporal efficacy of Varroa treatments varies across seasons. We observed that it takes about 4–5 months after treatment in winter and spring for mite populations to return to the standard economical threshold (3 mites/100 bees). Nevertheless, there is a steeper increase in mite populations (<3 months to exceed the economic threshold) after treating colonies in summer and fall. The level of infestation that leads to colony collapse and the rate of colony decline also varied by season. To our knowledge, this is the first study evaluating seasonal effects on Varroa population growth and the first model of Varroa population growth in Florida, USA. Our results serve as a foundation for Varroa treatment models, aiding beekeepers in the future as a part of a holistic approach to control this devastating honey bee parasite

Linkage disequilibrium and genomic selection analysis for sugarcane

Submitted by Erika Demachki ([email protected]) on 2017-03-02T18:02:56Z No. of bitstreams: 2 Dissertação - Ivone de Bem Oliveira - 2014.pdf: 5118960 bytes, checksum: 75535d885a75770e65014835502cc8cb (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Luciana Ferreira ([email protected]) on 2017-03-03T11:33:59Z (GMT) No. of bitstreams: 2 Dissertação - Ivone de Bem Oliveira - 2014.pdf: 5118960 bytes, checksum: 75535d885a75770e65014835502cc8cb (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Made available in DSpace on 2017-03-03T11:33:59Z (GMT). No. of bitstreams: 2 Dissertação - Ivone de Bem Oliveira - 2014.pdf: 5118960 bytes, checksum: 75535d885a75770e65014835502cc8cb (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2014-02-27Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESLinkage disequilibrium (LD) is a genetic phenomenon, since it directly interferes in the genetic dynamics of populations. Its effect is observed in the non independent segregation of alleles of different loci, resulting in a correlation between them during the haplotype formation. Any factor that alters allele frequencies can interfere in its dynamics. Both evolutionary factors considered in population genetics and the events used in breeding programs affect the linkage equilibrium/disequilibrium balance. As the microevolutionary factors are specific for each population (natural or from breeding), the LD should be assessed specifically in each population. Specific measures of LD were developed considering the different factors involved in order to mitigate their bias during measurement. Aiming to measure the LD in Ridesa breeding populations a model to predict the LD in polyploids was implemented, using the R platform, based on the Raboin et al. (2008) equations, that considers the sugarcane genome inherent attributes (polysomy and polyploidy). By using this model the LD decay profile was obtained for two breeding populations from Ridesa, the first one composed by 91 individuals from the cross between the RB97327 and RB72454 elite clones and the second from the 81 individuals derived from the selfing of the RB97327 clone. A total of 850 and 470 loci of DArT markers, respectively, were evaluated for each population. The populations showed a high LD, suggesting the existence of linkage disequilibrium even between loci that are 30cM apart. Based on the values found and on other sugarcane LD studies found in literature, the possible effect of the processes of genetic improvement on the dynamics of sugarcane LD were discussed. A second study was carried out associating the mendelian segregation analysis of loci and their effect on the LD pattern, that showed that the LD profiles over increasing distances between loci can be associated to the allelic dosage. Furthermore, aiming to illustrate one of the uses of LD in breeding programs a genomewide selection (GWS) study was developed using RR-BLUP methodology. This study was carried out as a proof of concept, in order to study the feasibility of the method of genome-wide selection in sugarcane. For this, the 132 genotypes were characterized for six different characters, namely: stalk weight (kg), stalk diameter (mm), stalk length (m), soluble solids concentration (Brix), internodes number and stalk number per plot. In addition to demonstrate the great potential of these studies in sugarcane using DArT, the results suggest the existence of a strong effect of intrapopulation structure and of the spurious associations between the loci in the accuracy of the model. These factors, usually ignored in this kind of analysis, should be further investigated in future studies.O desequilíbrio de ligação (LD) é um fenômeno genético que interfere diretamente na dinâmica genética das populações. Seu efeito é observado na segregação não independente dos alelos dos diferentes locos, resultando na correlação entre eles durante a formação dos haplótipos. Qualquer fator que altere as frequências alélicas interfere no LD. Assim, tanto os fatores evolutivos considerados em genética populacional, como a maioria dos eventos utilizados no melhoramento interferem na dinâmica equilíbrio/desequilíbrio de ligação. Como os fatores microevolutivos são específicos para cada população (natural ou de melhoramento), o LD deve ser avaliado em cada população, de maneira específica. Medidas de LD são desenvolvidas considerando os diferentes fatores evolutivos, afim de diminuir o viés gerado por eles durante sua mensuração. Com o intuito de mensurar o LD em populações de melhoramento da Ridesa foi implementado, no ambiente R, o modelo descrito por Raboin et al. (2008), que considera como fatores controlados para a diminuição de viés na mensuração do LD a polissomia e a poliploidia, características inerentes ao genoma da cana. Com o uso da modelagem implementada no ambiente R foram obtidos o perfil de decaimento para duas populações de melhoramento da Ridesa, a primeira compostas por 91 indivíduos provenientes do cruzamento biparental entre os clones-elite RB97327 e RB72454 e a segunda por 81 clones gerados por autofecundação do clone RB97327, a partir da análise de 850 e 470 locos DArT para cada população, respectivamente. As populações estudadas apresentaram alto LD, mostrando a existência de desequilíbrio mesmo entre locos separados por 30cM. Com base nos valores encontrados e nos estudos sobre LD existentes para cana na bibliografia foram discutidos os possíveis efeito dos processos de melhoramento sobre a dinâmica genética da cultura. Um segundo estudo foi realizado associando o padrão de segregação mendeliana dos locos e seu efeito no padrão de decaimento do desequilíbrio. Esta análise mostrou que os perfis de decaimento do desequilíbrio ao longo de distâncias crescentes entre locos pode estar associado à dosagem dos alelos sob análise. Além disso, afim de ilustrar um dos usos do LD no melhoramento de cana foi desenvolvido um estudo de seleção genômica ampla (GWS) com o uso da metodologia RR-BLUP. Esta análise foi realizada como uma prova de conceito, com o intuito de verificar a viabilidade do desenvolvimento do método de seleção genômica ampla para cana-de-açúcar. Para isto, os 132 genótipos foram caracterizados para seis diferentes caracteres, sendo eles: peso do feixe de colmos (Kg), diâmetro médio do colmo (mm), comprimento médio de colmo (m), concentração de sólidos solúveis (oBrix), número médio de internódios e número de colmos/touceira. Além de evidenciar o grande potencial de desenvolvimento de modelos desta natureza utilizando marcadores DArT em cana-de-açúcar, os resultados obtidos sugeriram a existência de forte efeito de estruturação intrapopulacional e existência de associações espúrias nas acurácias obtidas nos modelos. Mostrando que os efeitos desta estruturação, normalmente negligenciado durante as análises de calibração de modelos de seleção genômica ampla, devem ser melhor investigados em estudos posteriores

Insights Into the Genetic Basis of Blueberry Fruit-Related Traits Using Diploid and Polyploid Models in a GWAS Context

Polyploidization is an ancient and recurrent process in plant evolution, impacting the diversification of natural populations and plant breeding strategies. Polyploidization occurs in many important crops; however, its effects on inheritance of many agronomic traits are still poorly understood compared with diploid species. Higher levels of allelic dosage or more complex interactions between alleles could affect the phenotype expression. Hence, the present study aimed to dissect the genetic basis of fruit-related traits in autotetraploid blueberries and identify candidate genes affecting phenotypic variation. We performed a genome-wide association study (GWAS) assuming diploid and tetraploid inheritance, encompassing distinct models of gene action (additive, general, different orders of allelic interaction, and the corresponding diploidized models). A total of 1,575 southern highbush blueberry individuals from a breeding population of 117 full-sib families were genotyped using sequence capture and next-generation sequencing, and evaluated for eight fruit-related traits. For the diploid allele calling, 77,496 SNPs were detected; while 80,591 SNPs were obtained in tetraploid, with a high degree of overlap (95%) between them. A linear mixed model that accounted for population and family structure was used for the GWAS analyses. By modeling tetraploid genotypes, we detected 15 SNPs significantly associated with five fruit-related traits. Alternatively, seven significant SNPs were detected for only two traits using diploid genotypes, with two SNPs overlapping with the tetraploid scenario. Our results showed that the importance of tetraploid models varied by trait and that the use of diploid models has hindered the detection of SNP-trait associations and, consequently, the genetic architecture of some commercially important traits in autotetraploid species. Furthermore, 14 SNPs co-localized with candidate genes, five of which lead to non-synonymous amino acid changes. The potential functional significance of these SNPs is discussed

Evaluating Wild Germplasm Introgression into Autotetraploid Blueberry

Wild germplasm can be classified as the raw material essential for crop improvement. Introgression of wild germplasm is normally used in breeding to increase crop quality or resilience to evolving biotic and abiotic threats. Here, we explore the potential of introgressing Vaccinium elliottii into commercial blueberry germplasm. Vaccinium elliottii is a wild diploid blueberry species endemic to the southeastern United States that possesses highly desirable and economically important traits for blueberry breeding such as: short bloom to ripe period, adaptation to upland sandy soils, disease resistance, firmness, and pleasant flavor. To examine the potential of hybridization, we evaluated populations of interspecific hybrids across multiple stages of breeding (i.e., F1, F2, and backcrosses) in two crop seasons. We used our extensive pedigree data to generate breeding values for pre-breeding blueberry hybrid populations. Hybrid performance was evaluated considering fitness (i.e., plant vigor and plant height) in addition to evaluating six fruit-quality and marketable-related traits (i.e., size, firmness, acidity, soluble solids, weight, and yield). Overall, F2 and backcrosses rapidly achieved market thresholds, presenting values not significantly different from commercial blueberry germplasm. Our results confirmed the potential of exploiting the high genetic variability contained in V. elliottii for interspecific hybridization. Additionally, we developed germplasm resources that can be further evaluated and utilized in the breeding process, advancing selections for fruit quality and environmental adaptation

Image_1_Seasonal differences in Varroa destructor population growth in western honey bee (Apis mellifera) colonies.pdf

Varroa destructor is a major threat for apiculture worldwide. A successful approach to control this parasite must include the application of effective treatments at the correct time. To understand the effect that treatment timing has on Varroa populations at different seasons, we conducted an experiment using a dataset comprising two separate field trials over multiple years, both trials containing four apiary sites composed of 20 honey bee colonies across an area representative of north central Florida environments. Before the start of the season, colonies were treated with two acaricides simultaneously to bring the Varroa populations to ∼0.25 mites/100 bees. Following treatment, we monitored the mite populations monthly via alcohol washes. Our results show that the temporal efficacy of Varroa treatments varies across seasons. We observed that it takes about 4–5 months after treatment in winter and spring for mite populations to return to the standard economical threshold (3 mites/100 bees). Nevertheless, there is a steeper increase in mite populations (<3 months to exceed the economic threshold) after treating colonies in summer and fall. The level of infestation that leads to colony collapse and the rate of colony decline also varied by season. To our knowledge, this is the first study evaluating seasonal effects on Varroa population growth and the first model of Varroa population growth in Florida, USA. Our results serve as a foundation for Varroa treatment models, aiding beekeepers in the future as a part of a holistic approach to control this devastating honey bee parasite.</p

Table_1_Seasonal differences in Varroa destructor population growth in western honey bee (Apis mellifera) colonies.pdf

Varroa destructor is a major threat for apiculture worldwide. A successful approach to control this parasite must include the application of effective treatments at the correct time. To understand the effect that treatment timing has on Varroa populations at different seasons, we conducted an experiment using a dataset comprising two separate field trials over multiple years, both trials containing four apiary sites composed of 20 honey bee colonies across an area representative of north central Florida environments. Before the start of the season, colonies were treated with two acaricides simultaneously to bring the Varroa populations to ∼0.25 mites/100 bees. Following treatment, we monitored the mite populations monthly via alcohol washes. Our results show that the temporal efficacy of Varroa treatments varies across seasons. We observed that it takes about 4–5 months after treatment in winter and spring for mite populations to return to the standard economical threshold (3 mites/100 bees). Nevertheless, there is a steeper increase in mite populations (<3 months to exceed the economic threshold) after treating colonies in summer and fall. The level of infestation that leads to colony collapse and the rate of colony decline also varied by season. To our knowledge, this is the first study evaluating seasonal effects on Varroa population growth and the first model of Varroa population growth in Florida, USA. Our results serve as a foundation for Varroa treatment models, aiding beekeepers in the future as a part of a holistic approach to control this devastating honey bee parasite.</p

Table_2_Seasonal differences in Varroa destructor population growth in western honey bee (Apis mellifera) colonies.pdf

Varroa destructor is a major threat for apiculture worldwide. A successful approach to control this parasite must include the application of effective treatments at the correct time. To understand the effect that treatment timing has on Varroa populations at different seasons, we conducted an experiment using a dataset comprising two separate field trials over multiple years, both trials containing four apiary sites composed of 20 honey bee colonies across an area representative of north central Florida environments. Before the start of the season, colonies were treated with two acaricides simultaneously to bring the Varroa populations to ∼0.25 mites/100 bees. Following treatment, we monitored the mite populations monthly via alcohol washes. Our results show that the temporal efficacy of Varroa treatments varies across seasons. We observed that it takes about 4–5 months after treatment in winter and spring for mite populations to return to the standard economical threshold (3 mites/100 bees). Nevertheless, there is a steeper increase in mite populations (<3 months to exceed the economic threshold) after treating colonies in summer and fall. The level of infestation that leads to colony collapse and the rate of colony decline also varied by season. To our knowledge, this is the first study evaluating seasonal effects on Varroa population growth and the first model of Varroa population growth in Florida, USA. Our results serve as a foundation for Varroa treatment models, aiding beekeepers in the future as a part of a holistic approach to control this devastating honey bee parasite.</p

Data from: Insights into the genetic basis of blueberry fruit-related traits using diploid and polyploid models in a GWAS context

Polyploidization is an ancient and recurrent process in plant evolution, impacting the diversification of natural populations and plant breeding strategies. Polyploidization occurs in many important crops; however, its effects on inheritance of many agronomic traits are still poorly understood compared with diploid species. Higher levels of allelic dosage or more complex interactions between alleles could affect the phenotype expression. Hence, the present study aimed to dissect the genetic basis of fruit-related traits in autotetraploid blueberries and identify candidate genes affecting phenotypic variation. We performed a genome-wide association study (GWAS) assuming diploid and tetraploid inheritance, encompassing distinct models of gene action (additive, general, different orders of allelic interaction and the corresponding diploidized models). A total of 1,575 southern highbush blueberry individuals from a breeding population of 117 full-sib families were genotyped using sequence capture and next-generation sequencing, and evaluated for eight fruit-related traits. For the diploid allele calling, 77,496 SNPs were detected; while 80,591 SNPs were obtained in tetraploid, with a high degree of overlap (95%) between them. A linear mixed model that accounted for population and family structure was used for the GWAS analyses. By modeling tetraploid genotypes, we detected 15 SNPs significantly associated with five fruit-related traits. Alternatively, seven significant SNPs were detected for only two traits using diploid genotypes, with two SNPs overlapping with the tetraploid scenario. Our results showed that the importance of tetraploid models varied by trait and that the use of diploid models has hindered the detection of SNP-trait associations and, consequently, the genetic architecture of some commercially important traits in autotetraploid species. Furthermore, 14 SNPs co-localized with candidate genes, five of which lead to non-synonymous amino acid changes. The potential functional significance of these SNPs is discussed

Diploid and Tetraploid data used for GWAS analysis in blueberry

This dataset contains the genotypic and phenotypic information used in the manuscript "Insights into the genetic basis of blueberry fruit-related traits using diploid and polyploid models in a GWAS context". In the original manuscript, a blueberry breeding population was genotyped and phenotyped for eight traits - weight, size, firmness, stem scar diameter, pH, soluble solids content, flower bud density, and yield. Genotypic data (SNPs) are stored in two .csv files (tetraploid and diploid parameterizations, called using the FreeBayes software). Phenotype data for both parameterizations are also stored in two .csv files. For more details, see Ferrão et al., 2018

Research and partnership in studies of sugarcane using molecular markers : a scientometric approach

In this study, we applied scientometric methods and performed a science mapping analysis to investigate and describe the application of molecular markers in genetic studies for sugarcane. We analyzed 344 papers retrieved from Web of Science Thomson Reuters database, considering the time frame from 1974 to 2017, allowing the analysis of the produced scientific knowledge, temporal trends and research partnership in the subject. To our knowledge, a scientometric evaluation of the use of molecular markers for genetic studies in sugarcane has not yet been reported. Our main finding shows that dominant markers are more commonly used than co-dominant markers, and that when co-dominant markers are applied, most of the retrieved information is underexploited, due to lack of knowledge for the use of dosage information. Our results also show that despite the development of high-throughput sequencing technologies, for sugarcane only 13.33% of the studies reported the use of more than 1000 markers. We also found connectivity among researchers and institutions publishing worldwide, but only few authors represented a bridge between different research groups. Thus, the international research partnership is still low. Our findings show dominance in country publication. Six countries (India, Brazil, USA, Australia, China, and France) were responsible for 80% of the published papers and received most citations. We suggest special reinforcement in building international partnership, since collaborations occur mostly within countries. International collaboration can improve research performance and eventually lead to a better exploitation and more development of knowledge for sugarcane1191335355CAPES - Coordenação de Aperfeiçoamento de Pessoal e Nível SuperiorCNPQ - Conselho Nacional de Desenvolvimento Científico e Tecnológico88881.131685/2016-01Não tem2017-09817-0; 2015/23789-4465610/2014-5INCT - Instituto Nacional de Ciência e Tecnologi