Genomic and transcriptomic analysis of the streptomycin-dependent Mycobacterium tuberculosis strain 18b.

The ability of Mycobacterium tuberculosis to establish a latent infection (LTBI) in humans confounds the treatment of tuberculosis. Consequently, there is a need to discover new therapeutic agents that can kill M. tuberculosis both during active disease and LTBI. The streptomycin-dependent strain of M. tuberculosis, 18b, provides a useful tool for this purpose since upon removal of streptomycin (STR) it enters a non-replicating state that mimics latency both in vitro and in animal models. The 4.41 Mb genome sequence of M. tuberculosis 18b was determined and this revealed the strain to belong to clade 3 of the ancient ancestral lineage of the Beijing family. STR-dependence was attributable to insertion of a single cytosine in the 530 loop of the 16S rRNA and to a single amino acid insertion in the N-terminal domain of initiation factor 3. RNA-seq was used to understand the genetic programme activated upon STR-withdrawal and hence to gain insight into LTBI. This revealed reconfiguration of gene expression and metabolic pathways showing strong similarities between non-replicating 18b and M. tuberculosis residing within macrophages, and with the core stationary phase and microaerophilic responses. The findings of this investigation confirm the validity of 18b as a model for LTBI, and provide insight into both the evolution of tubercle bacilli and the functioning of the ribosome.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Effect of single nucleotide polymorphisms in cytochrome P450 isoenzyme and N-acetyltransferase 2 genes on the metabolism of artemisinin-based combination therapies in malaria patients from Cambodia and Tanzania.

The pharmacogenetics of antimalarial agents are poorly known, although the application of pharmacogenetics might be critical in optimizing treatment. This population pharmacokinetic-pharmacogenetic study aimed at assessing the effects of single nucleotide polymorphisms (SNPs) in cytochrome P450 isoenzyme genes (CYP, namely, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5) and the N-acetyltransferase 2 gene (NAT2) on the pharmacokinetics of artemisinin-based combination therapies in 150 Tanzanian patients treated with artemether-lumefantrine, 64 Cambodian patients treated with artesunate-mefloquine, and 61 Cambodian patients treated with dihydroartemisinin-piperaquine. The frequency of SNPs varied with the enzyme and the population. Higher frequencies of mutant alleles were found in Cambodians than Tanzanians for CYP2C9*3, CYP2D6*10 (100C → T), CYP3A5*3, NAT2*6, and NAT2*7. In contrast, higher frequencies of mutant alleles were found in Tanzanians for CYP2D6*17 (1023C → T and 2850C → T), CYP3A4*1B, NAT2*5, and NAT2*14. For 8 SNPs, no significant differences in frequencies were observed. In the genetic-based population pharmacokinetic analyses, none of the SNPs improved model fit. This suggests that pharmacogenetic data need not be included in appropriate first-line treatments with the current artemisinin derivatives and quinolines for uncomplicated malaria in specific populations. However, it cannot be ruled out that our results represent isolated findings, and therefore more studies in different populations, ideally with the same artemisinin-based combination therapies, are needed to evaluate the influence of pharmacogenetic factors on the clearance of antimalarials.

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

Clinical and genetic investigation of a large Tunisian family with complete achromatopsia: identification of a new nonsense mutation in GNAT2 gene.

Complete achromatopsia is a rare autosomal recessive disease associated with CNGA3, CNGB3, GNAT2 and PDE6C mutations. This retinal disorder is characterized by complete loss of color discrimination due to the absence or alteration of the cones function. The purpose of the present study was the clinical and the genetic characterization of achromatopsia in a large consanguineous Tunisian family. Ophthalmic evaluation included a full clinical examination, color vision testing and electroretinography. Linkage analysis using microsatellite markers flanking CNGA3, CNGB3, GNAT2 and PDE6C genes was performed. Mutations were screened by direct sequencing. A total of 12 individuals were diagnosed with congenital complete achromatopsia. They are members of six nuclear consanguineous families belonging to the same large consanguineous family. Linkage analysis revealed linkage to GNAT2. Mutational screening of GNAT2 revealed three intronic variations c.119-69G>C, c.161+66A>T and c.875-31G>C that co-segregated with a novel mutation p.R313X. An identical GNAT2 haplotype segregating with this mutation was identified, indicating a founder mutation. All patients were homozygous for the p.R313X mutation. This is the first report of the clinical and genetic investigation of complete achromatopsia in North Africa and the largest family with recessive achromatopsia involving GNAT2; thus, providing a unique opportunity for genotype-phenotype correlation for this extremely rare condition.

Mutation screening of the glutamate cysteine ligase modifier (GCLM) gene in patients with schizophrenia.

BACKGROUND: Experimental evidences show that glutathione and its rate-limiting synthesizing enzyme, the glutamate-cysteine ligase (GCL), are involved in the pathogenesis of schizophrenia. Furthermore, genetic association has been previously reported between two single nucleotide polymorphisms lying in noncoding regions of glutamate cysteine ligase modifier (GCLM) gene, which specifies for the modifier subunit of GCL and schizophrenia. OBJECTIVE: We wanted to investigate the presence of GCLM true functional mutations, likely in linkage disequilibrium with the previously identified single nucleotide polymorphism alleles, in the same set of cases that allowed the detection of the original association signal. METHODS: We screened all the coding regions of GCLM and their intronic flanking vicinities in 353 patients with schizophrenia by direct DNA sequencing. RESULTS: Ten sequence variations were identified, five of which were not previously described. None of these DNA changes was within the GCLM coding sequence and in-silico analysis failed to indicate functional impairment induced by these variations. Furthermore, screening of normal controls and downstream statistical analyses revealed no significant relationship of any of these DNA variants with schizophrenia. CONCLUSION: It is unlikely that functional mutations in the GCLM gene could play a major role in genetic predisposition to schizophrenia and further studies will be required to assess its etiological function in the disease.

High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

LINGO1 and LINGO2 variants are associated with essential tremor and Parkinson disease.

Genetic variation in the leucine-rich repeat and Ig domain containing 1 gene (LINGO1) was recently associated with an increased risk of developing essential tremor (ET) and Parkinson disease (PD). Herein, we performed a comprehensive study of LINGO1 and its paralog LINGO2 in ET and PD by sequencing both genes in patients (ET, n=95; PD, n=96) and by examining haplotype-tagging single-nucleotide polymorphisms (tSNPs) in a multicenter North American series of patients (ET, n=1,247; PD, n= 633) and controls (n=642). The sequencing study identified six novel coding variants in LINGO1 (p.S4C, p.V107M, p.A277T, p.R423R, p.G537A, p.D610D) and three in LINGO2 (p.D135D, p.P217P, p.V565V), however segregation analysis did not support pathogenicity. The association study employed 16 tSNPs at the LINGO1 locus and 21 at the LINGO2 locus. One variant in LINGO1 (rs9652490) displayed evidence of an association with ET (odds ratio (OR) =0.63; P=0.026) and PD (OR=0.54; P=0.016). Additionally, four other tSNPs in LINGO1 and one in LINGO2 were associated with ET and one tSNP in LINGO2 associated with PD (P<0.05). Further analysis identified one tSNP in LINGO1 and two in LINGO2 which influenced age at onset of ET and two tSNPs in LINGO1 which altered age at onset of PD (P<0.05). Our results support a role for LINGO1 and LINGO2 in determining risk for and perhaps age at onset of ET and PD. Further studies are warranted to confirm these findings and to determine the pathogenic mechanisms involved.

Exome sequencing identifies INPPL1 mutations as a cause of opsismodysplasia.

Opsismodysplasia (OPS) is a severe autosomal-recessive chondrodysplasia characterized by pre- and postnatal micromelia with extremely short hands and feet. The main radiological features are severe platyspondyly, squared metacarpals, delayed skeletal ossification, and metaphyseal cupping. In order to identify mutations causing OPS, a total of 16 cases (7 terminated pregnancies and 9 postnatal cases) from 10 unrelated families were included in this study. We performed exome sequencing in three cases from three unrelated families and only one gene was found to harbor mutations in all three cases: inositol polyphosphate phosphatase-like 1 (INPPL1). Screening INPPL1 in the remaining cases identified a total of 12 distinct INPPL1 mutations in the 10 families, present at the homozygote state in 7 consanguinous families and at the compound heterozygote state in the 3 remaining families. Most mutations (6/12) resulted in premature stop codons, 2/12 were splice site, and 4/12 were missense mutations located in the catalytic domain, 5-phosphatase. INPPL1 belongs to the inositol-1,4,5-trisphosphate 5-phosphatase family, a family of signal-modulating enzymes that govern a plethora of cellular functions by regulating the levels of specific phosphoinositides. Our finding of INPPL1 mutations in OPS, a severe spondylodysplastic dysplasia with major growth plate disorganization, supports a key and specific role of this enzyme in endochondral ossification.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.