Estimation of genetic and demographic parameters of extensively raised chicken populations using genome-wide single nucleotides polymorphism (SNP) data.

M. Sc. University of KwaZulu-Natal, Pietermaritzburg 2015.Village chicken populations are raised under a farming system that faces a number of challenges such as small flock size, lack of animal performance and pedigree records, lack of proper husbandry and poorly defined and structured mating systems all of which can negatively influence the genetic structure of the populations. Understanding of the evolutionary history, demographic structure, inbreeding levels and risk of a population to extinction is important in facilitating genetic improvement programs while maintaining biodiversity of extensively raised chicken populations. Linkage disequilibrium (LD) is an important source of information about historical events of recombination in a population and together with an understanding of the haplotype structure can provide valuable guidelines for breed improvement. This study was undertaken to investigate the existing LD level, inbreeding levels, effective population size and haplotype structure of extensively raised chicken populations from Southern Africa. A total of 312 village chickens from Malawi (n = 30, from one ecotype), South Africa, (n = 146, from three different ecotypes) and Zimbabwe (n = 135, from three different ecotypes) were genotyped using the Illumina chicken iSelect SNP60K bead chip. LD was calculated for each population from a total of 43,175 SNP after pruning for minor allele frequency (MAF) <0.05, genotyping call rate of <0.95, and deviation from Hardy Weinberg Equilibrium (HWE) p <0.001 and missing genotypes of more than 5%. Linkage disequilibrium averaged 0.41±0.006 and was observed to extend up to a marker distance of 100 kb. From the LD, effective population size was estimated that indicated reduced size of the breeding population over the past 40 generations to less than 20 individuals. Haplo-block structure analysis resulted in a total of 649, 2104 and 2442 blocks from Malawi, South Africa and Zimbabwe, respectively. Most of the observed blocks were less than 20 kb with a few that were more than 500 kb. Haplo-block genome coverage was 39 Mbp, 64.4 Mbp and 54.5 Mbp for Malawi, South Africa, and Zimbabwe, respectively. Large haplo-blocks on chromosome 8 spanned QTL regions associated mostly with body composition traits. The LD pattern was consistent with low effective population sizes and loss of heterozygosity in the village chicken populations. Potentially useful haplo-blocks spanning regions of known QTLs should be targeted for further analysis and identification of genes conferring optimal production performance of village chickens under harsh and marginalized production systems. Overall, the study provides baseline information on the utility of genome wide SNP data in studying extensively raised village chicken populations

Impact of pretreatment low-abundance HIV-1 drug-resistant variants on virological failure among HIV-1/TB-co-infected individuals.

OBJECTIVES: To determine the impact of pretreatment low-abundance HIV-1 drug-resistant variants (LA-DRVs) on virological failure (VF) among HIV-1/TB-co-infected individuals treated with NNRTI first-line ART. METHODS: We conducted a case-control study of 170 adults with HIV-1/TB co-infection. Cases had at least one viral load (VL) ≥1000 RNA copies/mL after ≥6 months on NNRTI-based ART, and controls had sustained VLs <1000 copies/mL. We sequenced plasma viruses by Sanger and MiSeq next-generation sequencing (NGS). We assessed drug resistance mutations (DRMs) using the Stanford drug resistance database, and analysed NGS data for DRMs at ≥20%, 10%, 5% and 2% thresholds. We assessed the effect of pretreatment drug resistance (PDR) on VF. RESULTS: We analysed sequences from 45 cases and 125 controls. Overall prevalence of PDR detected at a ≥20% threshold was 4.7% (8/170) and was higher in cases than in controls (8.9% versus 3.2%), P = 0.210. Participants with PDR at ≥20% had almost 4-fold higher odds of VF (adjusted OR 3.7, 95% CI 0.8-18.3) compared with those without, P = 0.104. PDR prevalence increased to 18.2% (31/170) when LA-DRVs at ≥2% were included. Participants with pretreatment LA-DRVs only had 1.6-fold higher odds of VF (adjusted OR 1.6, 95% CI 0.6-4.3) compared with those without, P = 0.398. CONCLUSIONS: Pretreatment DRMs and LA-DRVs increased the odds of developing VF on NNRTI-based ART, although without statistical significance. NGS increased detection of DRMs but provided no additional benefit in identifying participants at risk of VF at lower thresholds. More studies assessing mutation thresholds predictive of VF are required to inform use of NGS in treatment decisions

A 16S Next Generation Sequencing Based Molecular and Bioinformatics Pipeline to Identify Processed Meat Products Contamination and Mislabelling

Processed meat is a target in meat adulteration for economic gain. This study demonstrates a molecular and bioinformatics diagnostic pipeline, utilizing the mitochondrial 16S ribosomal RNA (rRNA) gene, to determine processed meat product mislabeling through Next-Generation Sequencing. Nine pure meat samples were collected and artificially mixed at different ratios to verify the specificity and sensitivity of the pipeline. Processed meat products (n = 155), namely, minced meat, biltong, burger patties, and sausages, were collected across South Africa. Sequencing was performed using the Illumina MiSeq sequencing platform. Each sample had paired-end reads with a length of &plusmn;300 bp. Quality control and filtering was performed using BBDuk (version 37.90a). Each sample had an average of 134,000 reads aligned to the mitochondrial genomes using BBMap v37.90. All species in the artificial DNA mixtures were detected. Processed meat samples had reads that mapped to the Bos (90% and above) genus, with traces of reads mapping to Sus and Ovis (2&ndash;5%) genus. Sausage samples showed the highest level of contamination with 46% of the samples having mixtures of beef, pork, or mutton in one sample. This method can be used to authenticate meat products, investigate, and manage any form of mislabeling

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation during a Pandemic

The COVID-19 pandemic has spread very fast around the world. A few days after the first detected case in South Africa, an infection started in a large hospital outbreak in Durban, KwaZulu-Natal (KZN). Phylogenetic analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. This manuscript outlines the obstacles encountered in order to genotype SARS-CoV-2 in near-real time during an urgent outbreak investigation. This included problems with the length of the original genotyping protocol, unavailability of reagents, and sample degradation and storage. Despite this, three different library preparation methods for Illumina sequencing were set up, and the hands-on library preparation time was decreased from twelve to three hours, which enabled the outbreak investigation to be completed in just a few weeks. Furthermore, the new protocols increased the success rate of sequencing whole viral genomes. A simple bioinformatics workflow for the assembly of high-quality genomes in near-real time was also fine-tuned. In order to allow other laboratories to learn from our experience, all of the library preparation and bioinformatics protocols are publicly available at protocols.io and distributed to other laboratories of the Network for Genomics Surveillance in South Africa (NGS-SA) consortium