Assessing the contribution of road transport emission to air pollution and greenhouse gases in Africa: A disaggregate study in Kenya

Air pollution and greenhouse gas emissions affect health, climate and agriculture. In sub-Saharan Africa (SSA) air quality monitoring is underdeveloped which leads to uncertainty in the understanding of air pollution concentrations. However, studies that have been conducted in SSA show that ambient air pollution generally exceeds World Health Organization (WHO) guidelines. These studies show particularly high concentrations in urban areas such as Nairobi, Kenya. One of the key reasons is due to emissions from transport. Therefore, the main objective of this thesis is to quantify transport related emissions, set within the context of emissions from other sectors, using Nairobi, Kenya as a case study. Thus, this thesis has developed a methodology and framework at different scales (individual vehicle, city and national) to improve our understanding of transport-related emissions of air pollutants and greenhouse gas (GHG) to help guide policy making on future mitigation plans. Road transport emissions were investigated at multiple scales; at the finest scale, particulate matter (PM) emissions from the tailpipe were measured for a few vehicles using a novel multiplexed portable measurement system. At the urban scale, a model for fuel economy was constructed for a fleet from data collected in the field. Finally, at the national scale, available data gathered on fuel economy, vehicle activity and emissions were integrated to provide a country-level assessment of air pollution and GHG emissions from road transport, including evaluation of transport policies to reduce air pollution and GHGs

Soil data collection using wireless sensor networks and offsite visualization: case study of the innovative solutions for digital agriculture project in Kenya

A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Masters of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyThe applications of Wireless Sensor Networks (WSN) and Internet of Everything (IoE) has changed how we obtain and consume information. Traditional farming has come a long way in accepting scientific methods to improve production. Smart Agriculture is one of the ways technology has greatly contributed to maximized crop production. Centrally placed labs and mobile soil labs have played a key role in this improved way of farming. Soil samples are collected from farms and analyzed to provide data to farmers, extension workers, and policymakers. This process takes time and is costly to implement. In addition, the definition of trends is difficult as replication of sampling requires more funding. This study proposes to connect end devices in an IoE system bringing in real-time data and at low-cost and also providing local data at local stations. The system is built incrementally to have a minimum viable product (MVP) using a combination of Agile and Waterfall methods of development. The system presents a pilot remote sensor module in a WSN using a Raspberry Pi minicomputer as an end node and three sensors collecting information on soil humidity and temperature, air humidity and temperature and soil pH values in real-time. A cloud-based data analysis and visualization are used. The system supports the ongoing work by soil labs by collecting information that is close to real-time. The study brings on board real-time data relaying of farm parameters that make it easier for small scale farm owners, extension officers, soil labs and other stakeholders to make instant informed decisions

A computational framework for transcriptome assembly and annotation in non-model organisms: the case of venturia inaequalis

Philosophiae Doctor - PhDIn this dissertation three computational approaches are presented that enable optimization of reference-free transcriptome reconstruction. The first addresses the selection of bona fide reconstructed transcribed fragments (transfrags) from de novo transcriptome assemblies and annotation with a multiple domain co-occurrence framework. We showed that selected transfrags are functionally relevant and represented over 94% of the information derived from annotation by transference. The second approach relates to quality score based RNA-seq sub-sampling and the description of a novel sequence similarity-derived metric for quality assessment of de novo transcriptome assemblies. A detail systematic analysis of the side effects induced by quality score based trimming and or filtering on artefact removal and transcriptome quality is describe. Aggressive trimming produced incomplete reconstructed and missing transfrags. This approach was applied in generating an optimal transcriptome assembly for a South African isolate of V. inaequalis. The third approach deals with the computational partitioning of transfrags assembled from RNA-Seq of mixed host and pathogen reads. We used this strategy to correct a publicly available transcriptome assembly for V. inaequalis (Indian isolate). We binned 50% of the latter to Apple transfrags and identified putative immunity transcript models. Comparative transcriptomic analysis between fungi transfrags from the Indian and South African isolates reveal effectors or transcripts that may be expressed in planta upon morphogenic differentiation. These studies have successfully identified V. inaequalis specific transfrags that can facilitate gene discovery. The unique access to an in-house draft genome assembly allowed us to provide preliminary description of genes that are implicated in pathogenesis. Gene prediction with bona fide transfrags produced 11,692 protein-coding genes. We identified two hydrophobin-like genes and six accessory genes of the melanin biosynthetic pathway that are implicated in the invasive action of the appressorium. The cazyome reveals an impressive repertoire of carbohydrate degrading enzymes and carbohydrate-binding modules amongst which are six polysaccharide lyases, and the largest number of carbohydrate esterases (twenty-eight) known in any fungus sequenced to dat

Inferring bona fide transfrags in RNA-Seq derived-transcriptome assemblies of non-model organisms

Background: De novo transcriptome assembly of short transcribed fragments (transfrags) produced from sequencing-by-synthesis technologies often results in redundant datasets with differing levels of unassembled, partially assembled or mis-assembled transcripts. Post-assembly processing intended to reduce redundancy typically involves reassembly or clustering of assembled sequences. However, these approaches are mostly based on common word heuristics and often create clusters of biologically unrelated sequences, resulting in loss of unique transfrags annotations and propagation of mis-assemblies. Results: Here, we propose a structured framework that consists of a few steps in pipeline architecture for Inferring Functionally Relevant Assembly-derived Transcripts (IFRAT). IFRAT combines 1) removal of identical subsequences, 2) error tolerant CDS prediction, 3) identification of coding potential, and 4) complements BLAST with a multiple domain architecture annotation that reduces non-specific domain annotation. We demonstrate that independent of the assembler, IFRAT selects bona fide transfrags (with CDS and coding potential) from the transcriptome assembly of a model organism without relying on post-assembly clustering or reassembly. The robustness of IFRAT is inferred on RNA-Seq data of Neurospora crassa assembled using de Bruijn graph-based assemblers, in single (Trinity and Oases-25) and multiple (Oases-Merge and additive or pooled) k-mer modes. Single k-mer assemblies contained fewer transfrags compared to the multiple k-mer assemblies. However, Trinity identified a comparable number of predicted coding sequence and gene loci to Oases pooled assembly. IFRAT selects bona fide transfrags representing over 94% of cumulative BLAST-derived functional annotations of the unfiltered assemblies. Between 4-6% are lost when orphan transfrags are excluded and this represents only a tiny fraction of annotation derived from functional transference by sequence similarity. The median length of bona fide transfrags ranged from 1.5kb (Trinity) to 2kb (Oases), which is consistent with the average coding sequence length in fungi. The fraction of transfrags that could be associated with gene ontology terms ranged from 33-50%, which is also high for domain based annotation. We showed that unselected transfrags were mostly truncated and represent sequences from intronic, untranslated (5′ and 3′) regions and non-coding gene loci. Conclusions: IFRAT simplifies post-assembly processing providing a reference transcriptome enriched with functionally relevant assembly-derived transcripts for non-model organism.Department of Science and Technology National Research Foundation South African Research Chair initiativeWeb of Scienc

A glance at quality score: implication for de novo transcriptome reconstruction of Illumina reads

Downstream analyses of short-reads from next-generation sequencing platforms are often preceded by a pre-processing step that removes uncalled and wrongly called bases. Standard approaches rely on their associated base quality scores to retain the read or a portion of it when the score is above a predefined threshold. It is difficult to differentiate sequencing error from biological variation without a reference using a quality score. The effects of quality score based trimming have not been systematically studied in de novo transcriptome assembly. Using RNA-Seq data produced from Illumina,we teased out the effects of quality score based filtering or trimming on de novo transcriptome reconstruction. We showed that assemblies produced from reads subjected to different quality score thresholds contain truncated and missing transfrags when compared to those from untrimmed reads. Our data supports the fact that de novo assembling of untrimmed data is challenging for de Bruijn graph assemblers. However, our results indicates that comparing the assemblies from untrimmed and trimmed read subsets can suggest appropriate filtering parameters and enables election of the optimum de novo transcriptome assembly in non-model organisms.South African Research Chair Initiative National Research Foundation of South Afric

Chromosomal-level assembly of the Asian seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species’ native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics.Web of Scienc

Typology of Kimbeere Relative Clauses in Kimbeere

In this paper we explore the typology of Kimbeere- a Kenya Bantu language. The paper demonstrates that like in other languages, Kimbere has different types of relative clauses namely restrictive, non-restrictive, direct, indirect, appositive, headless among other. Kimbere also has a type of relative clause called ingi relative. The paper is descriptive and contributes typological data which is crucial for drawing principles and parameters in natural language. Key Words: Relative clause, direct, indirect, headless, restrictive, typology DOI: 10.7176/JLLL/62-09 Publication date: November 30th 201

Poly(ADP-ribose) polymerase 9 mediates early protection against Mycobacterium tuberculosis infection by regulating type I IFN production

The ADP ribosyltransferases (PARPs 1-17) regulate diverse cellular processes, including DNA damage repair. PARPs are classified on the basis of their ability to catalyze poly-ADP-ribosylation (PARylation) or mono-ADP-ribosylation (MARylation). Although PARP9 mRNA expression is significantly increased in progressive tuberculosis (TB) in humans, its participation in host immunity to TB is unknown. Here, we show that PARP9 mRNA encoding the MARylating PARP9 enzyme was upregulated during TB in humans and mice and provide evidence of a critical modulatory role for PARP9 in DNA damage, cyclic GMP-AMP synthase (cGAS) expression, and type I IFN production during TB. Thus, Parp9-deficient mice were susceptible to Mycobacterium tuberculosis infection and exhibited increased TB disease, cGAS and 2\u273\u27-cyclic GMP-AMP (cGAMP) expression, and type I IFN production, along with upregulation of complement and coagulation pathways. Enhanced M. tuberculosis susceptibility is type I IFN dependent, as blockade of IFN α receptor (IFNAR) signaling reversed the enhanced susceptibility of Parp9-/- mice. Thus, in sharp contrast to PARP9 enhancement of type I IFN production in viral infections, this member of the MAR family plays a protective role by limiting type I IFN responses during TB