The Diversity of REcent and Ancient huMan (DREAM): a new microarray for genetic anthropology and genealogy, forensics, and personalized medicine

The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation (CNVs), drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. While many commercial arrays exist for genome-wide single-nucleotide polymorphism (SNP) genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM) - an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its FST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, DREAM's autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent (IBD), and CNV analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies

Enhancing faba bean (Vicia faba L.) genome resources

Grain legume improvement is currently impeded by a lack of genomic resources. The paucity of genome information for faba bean can be attributed to the intrinsic difficulties of assembling/annotating its giant (~13Gb) genome. In order to address this challenge, RNA-seq analysis was performed on faba bean (cv Wizard) leaves. Read alignment to the faba bean reference transcriptome identified 16,300 high quality unigenes. In addition, Illumina paired-end sequencing was used to establish a baseline for genomic information assembly. Genomic reads were assembled de novo into contigs with a size range of 50-5000 bp. Over 85% of sequences did not align to known genes, of which ~10 % could be aligned to known repetitive genetic elements. Over 26,000 of the reference transcriptome unigenes could be aligned to DNA-seq reads with high confidence. Moreover, this comparison identified 56,668 potential splice points in all identified unigenes. Sequence length data was extended at 461 putative loci through alignment of DNA-seq contigs to full length, publically available linkage marker sequences. Reads also yielded coverages of 3466x and 650x for the chloroplast and mitochondrial genomes respectively. Inter- and intra-species organelle genome comparisons established core legume organelle gene sets, and revealed polymorphic regions of faba bean organelle genomes

Transcriptional profiling of degraded RNA in cryopreserved and fixed tissue samples obtained at autopsy

BACKGROUND: Traditional multiplexed gene expression methods require well preserved, intact RNA. Such specimens are difficult to acquire in clinical practice where formalin fixation is the standard procedure for processing tissue. Even when special handling methods are used to obtain frozen tissue, there may be RNA degradation; for example autopsy samples where degradation occurs both pre-mortem and during the interval between death and cryopreservation. Although specimens with partially degraded RNA can be analyzed by qRT-PCR, these analyses can only be done individually or at low levels of multiplexing and are laborious and expensive to run for large numbers of RNA targets. METHODS: We evaluated the ability of the cDNA-mediated Annealing, Selection, extension, and Ligation (DASL) assay to provide highly multiplexed analyses of cryopreserved and formalin fixed, paraffin embedded (FFPE) tissues obtained at autopsy. Each assay provides data on 1536 targets, and can be performed on specimens with RNA fragments as small as 60 bp. RESULTS: The DASL performed accurately and consistently with cryopreserved RNA obtained at autopsy as well as with RNA extracted from formalin-fixed paraffin embedded tissue that had a cryopreserved mirror image specimen with high quality RNA. In FFPE tissue where the cryopreserved mirror image specimen was of low quality the assay performed reproducibly on some but not all specimens. CONCLUSION: The DASL assay provides reproducible results from cryopreserved specimens and many FFPE specimens obtained at autopsy. Gene expression analyses of these specimens may be especially valuable for the study of non-cancer endpoints, where surgical specimens are rarely available

Population Genetics of Vibrio cholerae from Nepal in 2010: Evidence on the Origin of the Haitian Outbreak

Cholera continues to be an important cause of human infections, and outbreaks are often observed after natural disasters, such as the one following the 2010 earthquake in Haiti. Once the cholera outbreak was confirmed, rumors spread that the disease was brought to Haiti by a battalion of Nepalese soldiers serving as United Nations peacekeepers. This possible connection has never been confirmed. We used whole-genome sequence typing (WGST), pulsed-field gel electrophoresis (PFGE), and antimicrobial susceptibility testing to characterize 24 recent Vibrio cholerae isolates from Nepal and evaluate the suggested epidemiological link with the Haitian outbreak. The isolates were obtained from 30 July to 1 November 2010 from five different districts in Nepal. We compared the 24 genomes to 10 previously sequenced V. cholerae isolates, including 3 from the Haitian outbreak (began July 2010). Antimicrobial susceptibility and PFGE patterns were consistent with an epidemiological link between the isolates from Nepal and Haiti. WGST showed that all 24 V. cholerae isolates from Nepal belonged to a single monophyletic group that also contained isolates from Bangladesh and Haiti. The Nepalese isolates were divided into four closely related clusters. One cluster contained three Nepalese isolates and three Haitian isolates that were almost identical, with only 1- or 2-bp differences. Results in this study are consistent with Nepal as the origin of the Haitian outbreak. This highlights how rapidly infectious diseases might be transmitted globally through international travel and how public health officials need advanced molecular tools along with standard epidemiological analyses to quickly determine the sources of outbreaks. IMPORTANCE Cholera is one of the ancient classical diseases and particularly prone to cause major outbreaks following major natural disasters, such as earthquakes and hurricanes, where the normal separation between sewage and drinking water is destroyed. This was the case following the 2010 earthquake in Haiti. Rumors spread that the disease was brought to Haiti by a battalion of Nepalese soldiers serving as United Nations peacekeepers. This possible connection has never been confirmed. Sequencing the genomes of bacteria can give detailed information on whether isolates from different sites share a common origin. We used this technology to sequence isolates of Vibrio cholerae from Nepal, identify single-nucleotide polymorphisms (SNPs), and compare these high-resolution genotypes to the complete genome sequences of isolates from the Haiti outbreak. We provide support for the hypothesis that the isolates were brought to Haiti from Nepal

Persistence of Innate Immune Pathways in Late Stage Human Bacterial and Fungal Keratitis: Results from a Comparative Transcriptome Analysis

Microbial keratitis (MK) is a major cause of blindness worldwide. Despite adequate antimicrobial treatment, tissue damage can ensue. We compared the human corneal transcriptional profile in late stage MK to normal corneal tissue to identify pathways involved in pathogenesis. Total RNA from MK tissue and normal cadaver corneas was used to determine transcriptome profiles with Illumina HumanHT-12 v4 beadchips. We performed differential expression and network analysis of genes in bacterial keratitis (BK) and fungal keratitis (FK) compared with control (C) samples. Results were validated by RTqPCR for 45 genes in an independent series of 183 MK patients. For the microarray transcriptome analysis, 27 samples were used: 12 controls, 7 BK culture positive for Streptococcus pneumoniae (n = 6), Pseudomonas aeruginosa (n = 1), and 8 FK, culture positive for Fusarium sp. (n = 5), Aspergillus sp. (n = 2), or Lasiodiplodia sp. (n = 1). There were 185 unique differentially expressed genes in BK, 50 in FK, and 339 common to both [i.e., genes with fold-change (FC) < −4 or ≥4 and false discovery rate (FDR) adjusted P < 0.05]. MMP9 had the highest FC in BK (91 FC, adj p = 3.64 E-12) and FK (FC 64, adj. p = 6.10 E-11), along with other MMPs (MMP1, MMP7, MMP10, MMP12), pro-inflammatory cytokines (IL1B, TNF), and PRRs (TLR2, TLR4). HIF1A and its induced genes were upregulated uniquely in BK. Immune/defense response and extracellular matrix terms were the most enriched Gene Ontology terms in both BK and FK. In the network analysis, chemokines were prominent for FK, and actin filament reorganization for BK. Microarray and RTqPCR results were highly correlated for the same samples tested with both assays, and with the larger RTqPCR series. In conclusion, we found a great deal of overlap in the gene expression profile of late stage BK and FK, however genes unique to fungal infection highlighted a corneal epithelial wound healing response and for bacterial infection the prominence of HIF1A-induced genes. These sets of genes may provide new targets for future research into therapeutic agents

Genome-Scale Identification of Resistance Functions in Pseudomonas aeruginosa Using Tn-seq

We describe a deep-sequencing procedure for tracking large numbers of transposon mutants of Pseudomonas aeruginosa. The procedure employs a new Tn-seq methodology based on the generation and amplification of single-strand circles carrying transposon junction sequences (the Tn-seq circle method), a method which can be used with virtually any transposon. The procedure reliably identified more than 100,000 transposon insertions in a single experiment, providing near-saturation coverage of the genome. To test the effectiveness of the procedure for mutant identification, we screened for mutations reducing intrinsic resistance to the aminoglycoside antibiotic tobramycin. Intrinsic tobramycin resistance had been previously analyzed at genome scale using mutant-by-mutant screening and thus provided a benchmark for evaluating the new method. The new Tn-seq procedure identified 117 tobramycin resistance genes, the majority of which were then verified with individual mutants. The group of genes with the strongest mutant phenotypes included nearly all (13 of 14) of those with strong mutant phenotypes identified in the previous screening, as well as a nearly equal number of new genes. The results thus show the effectiveness of the Tn-seq method in defining the genetic basis of a complex resistance trait of P. aeruginosa and indicate that it can be used to analyze a variety of growth-related processes

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

<p>Abstract</p> <p>Background</p> <p>High-throughput sequencing technologies, such as the Illumina Genome Analyzer, are powerful new tools for investigating a wide range of biological and medical questions. Statistical and computational methods are key for drawing meaningful and accurate conclusions from the massive and complex datasets generated by the sequencers. We provide a detailed evaluation of statistical methods for normalization and differential expression (DE) analysis of Illumina transcriptome sequencing (mRNA-Seq) data.</p> <p>Results</p> <p>We compare statistical methods for detecting genes that are significantly DE between two types of biological samples and find that there are substantial differences in how the test statistics handle low-count genes. We evaluate how DE results are affected by features of the sequencing platform, such as, varying gene lengths, base-calling calibration method (with and without phi X control lane), and flow-cell/library preparation effects. We investigate the impact of the read count normalization method on DE results and show that the standard approach of scaling by total lane counts (e.g., RPKM) can bias estimates of DE. We propose more general quantile-based normalization procedures and demonstrate an improvement in DE detection.</p> <p>Conclusions</p> <p>Our results have significant practical and methodological implications for the design and analysis of mRNA-Seq experiments. They highlight the importance of appropriate statistical methods for normalization and DE inference, to account for features of the sequencing platform that could impact the accuracy of results. They also reveal the need for further research in the development of statistical and computational methods for mRNA-Seq.</p