Social and cultural efficacies of medicines: Complications for antiretroviral therapy

Using ethnographic examples of medicine use, prescription, distribution and production, the authors argue that social and cultural effects of pharmaceuticals should be taken into account. Non-medical effects deeply influence the medical outcome of medicine use. Complications around the advent of anti-AIDS medicines in poor countries are taken as a point in case. The authors are medical anthropologists specialised in the social and cultural analysis of pharmaceuticals

Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)

Background Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. Results The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Conclusion Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation

QTLs for oil yield components in an elite oil palm (Elaeis guineensis) cross

Increased modern farming of superior types of the oil palm, Elaeis guineensis Jacq., which has naturally efficient oil biosynthesis, has made it the world’s foremost edible oil crop. Breeding improvement is, however, circumscribed by time and costs associated with the tree’s long reproductive cycle, large size and 10–15 years of field testing. Marker-assisted breeding has considerable potential for improving this crop. Towards this, quantitative trait loci (QTL) linked to oil yield component traits were mapped in a high-yield population. In total, 164 QTLs associated with 21 oil yield component traits were discovered, with cumulative QTL effects increasing in tandem with the number of QTL markers and matching the QT+ alleles for each trait. The QTLs confirmed all traits to be polygenic, with many genes of individual small effects on independent loci, but epistatic interactions are not ruled out. Furthermore, several QTLs maybe pleiotropic as suggested by QTL clustering of inter-related traits on almost all linkage groups. Certain regions of the chromosomes seem richer in the genes affecting a particular yield component trait and likely encompass pleiotropic, epistatic and heterotic effects. A large proportion of the identified additive effects from QTLs may actually arise from genic interactions between loci. Comparisons with previous mapping studies show that most of the QTLs were for similar traits and shared similar marker intervals on the same linkage groups. Practical applications for such QTLs in marker-assisted breeding will require seeking them out in different genetic backgrounds and environments

Model and experiences of initiating collaboration with traditional healers in validation of ethnomedicines for HIV/AIDS in Namibia

Many people with Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) in Namibia have access to antiretroviral drugs but some still use traditional medicines to treat opportunistic infections and offset side-effects from antiretroviral medication. Namibia has a rich biodiversity of indigenous plants that could contain novel anti-HIV agents. However, such medicinal plants have not been identified and properly documented. Various ethnomedicines used to treat HIV/AIDS opportunistic infections have not been scientifically validated for safety and efficacy. These limitations are mostly attributable to the lack of collaboration between biomedical scientists and traditional healers. This paper presents a five-step contextual model for initiating collaboration with Namibian traditional healers in order that candidate plants that may contain novel anti-HIV agents are identified, and traditional medicines used to treat HIV/AIDS opportunistic infections are subjected to scientific validation. The model includes key structures and processes used to initiate collaboration with traditional healers in Namibia; namely, the National Biosciences Forum, a steering committee with the University of Namibia (UNAM) as the focal point, a study tour to Zambia and South Africa where other collaborative frameworks were examined, commemorations of the African Traditional Medicine Day (ATMD), and consultations with stakeholders in north-eastern Namibia. Experiences from these structures and processes are discussed. All traditional healers in north-eastern Namibia were willing to collaborate with UNAM in order that their traditional medicines could be subjected to scientific validation. The current study provides a framework for future collaboration with traditional healers and the selection of candidate anti-HIV medicinal plants and ethnomedicines for scientific testing in Namibia

High density SNP and DArT-based genetic linkage maps of two closely related oil palm populations

Oil palm (Elaeis guineensis Jacq.) is an outbreeding perennial tree crop with long breeding cycles, typically 12 years. Molecular marker technologies can greatly improve the breeding efficiency of oil palm. This study reports the first use of the DArTseq platform to genotype two closely related self-pollinated oil palm populations, namely AA0768 and AA0769 with 48 and 58 progeny respectively. Genetic maps were constructed using the DArT and SNP markers generated in combination with anchor SSR markers. Both maps consisted of 16 major independent linkage groups (2n = 2× = 32) with 1399 and 1466 mapped markers for the AA0768 and AA0769 populations, respectively, including the morphological trait “shell-thickness” (Sh). The map lengths were 1873.7 and 1720.6 cM with an average marker density of 1.34 and 1.17 cM, respectively. The integrated map was 1803.1 cM long with 2066 mapped markers and average marker density of 0.87 cM. A total of 82% of the DArTseq marker sequence tags identified a single site in the published genome sequence, suggesting preferential targeting of gene-rich regions by DArTseq markers. Map integration of higher density focused around the Sh region identified closely linked markers to the Sh, with D.15322 marker 0.24 cM away from the morphological trait and 5071 bp from the transcriptional start of the published SHELL gene. Identification of the Sh marker demonstrates the robustness of using the DArTseq platform to generate high density genetic maps of oil palm with good genome coverage. Both genetic maps and integrated maps will be useful for quantitative trait loci analysis of important yield traits as well as potentially assisting the anchoring of genetic maps to genomic sequences