Biology subjects

Jordan, D.

Publications and source records attributed to Jordan, D..

4 recordsLinked to original sources

bioRxiv2018

Identification of functional long non-coding RNAs in C. elegans

BackgroundFunctional characterisation of the compact genome of the model organism Caenorhabditis elegans remains incomplete despite its sequencing twenty years ago. The last decade of research has seen a tremendous increase in the number of non-coding RNAs identified in various organisms. While we have mechanistic understandings of small non-coding RNA pathways, long non-coding RNAs represent a diverse class of active transcripts whose function remains less well characterised.\n\nResultsBy analysing hundreds of published transcriptome datasets, we annotated 3,397 potential lncRNAs including 146 multi-exonic loci that showed increased nucleotide conservation and GC content relative to other non-coding regions. Using CRISPR / Cas9 genome editing we generated deletion mutants for ten long non-coding RNA loci. Using automated microscopy for in-depth phenotyping, we show that six of the long non-coding RNA loci are required for normal development and fertility. Using RNA interference mediated gene knock-down, we provide evidence that for two of the long non-coding RNA loci, the observed phenotypes are dependent on the corresponding RNA transcripts.\n\nConclusionsOur results highlight that a large section of the non-coding regions of the C. elegans genome remain unexplored. Based on our in vivo analysis of a selection of high-confidence lncRNA loci, we expect that a significant proportion of these high-confidence regions is likely to have biological function at either the genomic or the transcript level.

genetics↗

bioRxiv2018

Examination of Australian Streptococcus suis Isolates From Clinically Affected Pigs in a Global Context and the Genomic Characterisation of ST1 as a Predictor of Virulence

Streptococcus suis is a major zoonotic pathogen that causes severe disease in both humans and pigs. In this study, we investigated S. suis from 148 cases of clinical disease in pigs from 46 pig herds over a period of seven years. These isolates underwent whole genome sequencing, genome analysis and antimicrobial susceptibility testing. Genome sequence data of Australian isolates was compared at the core genome level to clinical isolates from overseas. Results demonstrated eight predominant multi-locus sequence types and two major cps gene types (cps2 and 3). At the core genome level Australian isolates clustered predominantly within one large clade consisting of isolates from the UK, Canada and North America. In particular, serotype 2 MLST25 strains were very closely associated with Canadian and North American strains. A very small proportion of Australian swine isolates (5%) were phylogenetically associated with south-east Asian and UK isolates, many of which were classified as causing systemic disease, and derived from cases of human and swine disease. In addition, we show that ST1 clones carry a constellation of putative virulence genes not present in other Australian STs, and that this is mirrored in overseas ST1 clones. Based on this dataset we provide a comprehensive outline of the current S. suis clones associated with disease in Australian pigs and their global context, and discuss the implications this has on antimicrobial therapy, potential vaccine candidates and public health.\n\nImportanceIn this study, we examine in detail, the genomic characteristics of 148 Streptococcus suis isolates from clinically diseased Australian pigs. We report the antimicrobial susceptibility profiles, virulence gene analysis and relationship to isolates from other regions of the world. We also demonstrate that ST1 clones, regardless of serotype, carry a large array of putative virulence genes while maintaining a small total gene content. This compilation of data has major ramifications for vaccine development, and refines the understanding of the distribution of various strains of this potentially-fatal zoonotic agent in the global pig industry

microbiology↗

bioRxiv2018

A domestication history of dynamic adaptation and genomic deterioration in sorghum

The evolution of domesticated cereals was a complex interaction of shifting selection pressures and repeated introgressions. Genomes of archaeological crops have the potential to reveal these dynamics without being obscured by recent breeding or introgression. We report a temporal series of archaeogenomes of the crop sorghum (Sorghum bicolor) from a single locality in Egyptian Nubia. These data indicate no evidence for the effects of a domestication bottleneck but instead suggest a steady decline in genetic diversity over time coupled with an accumulating mutation load. Dynamic selection pressures acted sequentially on architectural and nutritional domestication traits, and adaptation to the local environment. Later introgression between sorghum races allowed exchange of adaptive traits and achieved mutual genomic rescue through an ameliorated mutation load. These results reveal a model of domestication in which genomic adaptation and deterioration was not focused on the initial stages of domestication but occurred throughout the history of cultivation.

evolutionary biology↗

bioRxiv2017

Quantification of frequency-dependent genetic architectures and action of negative selection in 25 UK Biobank traits

Understanding the role of rare variants is important in elucidating the genetic basis of human diseases and complex traits. It is widely believed that negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1-p)], where p is the MAF and negative values of imply larger effect sizes for rare variants. We estimate by maximizing its profile likelihood in a linear mixed model framework using imputed genotypes, including rare variants (MAF >0.07%). We applied this method to 25 UK Biobank diseases and complex traits (N = 113,851). All traits produced negative estimates with 20 significantly negative, implying larger rare variant effect sizes. The inferred best-fit distribution of true values across traits had mean -0.38 (s.e. 0.02) and standard deviation 0.08 (s.e. 0.03), with statistically significant heterogeneity across traits (P = 0.0014). Despite larger rare variant effect sizes, we show that for most traits analyzed, rare variants (MAF <1%) explain less than 10% of total SNP-heritability. Using evolutionary modeling and forward simulations, we validated the model of MAF-dependent trait effects and estimated the level of coupling between fitness effects and trait effects. Based on this analysis an average genome-wide negative selection coefficient on the order of 10-4 or stronger is necessary to explain the values that we inferred.

genetics↗