Top PDF Caracterização de amostras de mel por next generation sequencing

Caracterização de amostras de mel por next generation sequencing

Caracterização de amostras de mel por next generation sequencing

Relativamente à temperatura de incubação das amostras de mel, os fragmentos de DNA visualizados no gel de agarose cuja incubação foi de 40 C apresentam algum tipo de degradação do DNA. É possível inferir que esta temperatura não é suficiente para remover totalmente açúcares, polifenóis e outros contaminantes na totalidade, dificultando, consequentemente, a lise dos grãos de pólen. Este resultado reforçou os resultados obtidos anteriormente, e permitiu definir a temperatura de incubação (65 C). Em relação ao tipo de lise, a lise mecânica e química mostrou ser mais eficaz do que a lise mecânica. Os fragmentos de DNA das amostras submetidas à lise mecânica e química apresentaram uma maior eficiência de amplificação. Este resultado permite afirmar que a quantidade e qualidade dos fragmentos de DNA obtidos é mais elevada quando se aplica este tipo de lise. Para além disso, também se observou que houve amplificação de todas as amostras lisadas mecânica e quimicamente enquanto que, em alguns casos, não houve qualquer tipo de amplificação com a lise mecânica.
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Development of a new pharmacogenomics system for lung cancer based in next generation sequencing

Development of a new pharmacogenomics system for lung cancer based in next generation sequencing

tumoral para diagnóstico recorre à obtenção de um pedaço do tumor, normalmente retirado por cirurgia. Este é designado por biópsia sólida e apresenta várias desvantagens na aplicação da medicina de precisão. A deteção de conteúdo genético tumoral a partir do sangue (biopsia líquida) permite que sejam recolhidas amostras ao longo do tratamento de uma forma menos in- vasiva e dispendiosa. O recurso a cirurgia para obter ADN tumoral não só não pode ser aplicado a todos os doentes, como normalmente é executado apenas uma vez e o que é recolhido é primeiro submetido a análises de anatomia patológica. Estas análises envolvem a utilização de formalina e parafinização da amostra o que degrada o ADN contido nesta. A introdução de amostras de sangue no chip LungCARD permite a captura de células tumorais libertadas pelo tumor (cir- culantes), e o seu conteúdo genético é extraído. As regiões de interesse do ADN tumoral são amplificadas por PCR e preparadas para sequenciação. Os dados obtidos serão então analisados através da metodologia definida neste projeto, de forma a que no fim as variantes detetadas nas amostras e que se encontrem associadas a este tipo de cancro sejam apresentadas num relatório final. Este terá por sua vez o objetivo de oferecer os resultados da análise dos dados de um doente específico, de forma a facilitar a decisão relativa à terapia direcionada a aplicar.
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A trial of karyotypic microdissection as an enrichment pathway for next-generation sequencing

A trial of karyotypic microdissection as an enrichment pathway for next-generation sequencing

Para esse efeito, uma primeira assemblagem foi realizada com o software Newbler. Contudo, a detec¸ c˜ ao de uma contamina¸c˜ ao bacteriana nos dados sequenciados, que levaria ` a exclus˜ ao de mais de metade dos fragmentos sequenciados, motivou o desenvolvimento de uma aplica¸ c˜ ao inform´ atica capaz de incluir todos os passos que constituem a assemblagem - desde o processamento inicial dos fragmentos at´ e ` a produ¸ c˜ ao final de contigs - maximizando, assim, o n´ umero de fragmentos usados. Os objectivos passariam por evitar a exclus˜ ao desnecess´ aria de fragmentos, possivelmente relevantes para na assemblagem do cromossoma W de E. velox, mas tamb´ em para a obten¸ c˜ ao de uma maior profundidade e amplitude de cobertura do cromossoma, a fim de produzir um maior n´ umero de contigs com elevado grau de confian¸ ca. Por outro lado, a n˜ ao exclus˜ ao de fragmentos de origem bacteriana, permitiria usar a assemblagem destes como um controlo interno da validade da mesma. Com o intuito de validar tanto a assemblagem efectuada pelo Newbler, assim como aquela efectuada posteriormente com a aplica¸ c˜ ao desenvolvida, procedeu-se ` a compara¸ c˜ ao in silico dos resultados atrav´ es da an´ alise do seu mapeamento contra o genoma da bact´ eria apontada como a principal fonte de contamina¸ c˜ ao. Adicionalmente, para efeitos da valida¸ c˜ ao experimental dos resultados obtidos, alguns contigs produzidos pela aplica¸ c˜ ao desenvolvida foram selecionados e usados como modelo para desenho de primers com o intuito de amplificar e sequenciar as amostras de ADN pertencentes ao lacert´ıdeo, pelo m´ etodo de Sanger. Embora os contigs produzidos pelas assemblagens parecessem ser candidatos promissores, o conjunto de testes preliminares com um pequeno conjunto de loci n˜ ao resultou em qualquer amplifica¸ c˜ ao das amostras de lacert´ıdeo.
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Diversity and specificity of the marine sponge microbiome as inspected by next generation sequencing

Diversity and specificity of the marine sponge microbiome as inspected by next generation sequencing

Atualmente, estas tecnologias são amplamente aplicadas e com grande êxito na exploração molecular das simbioses que ocorrem entre micróbios e esponjas. Ademais, por via destas, tem sido possível desvendar o nível de ‘intimidade’ molecular a que vivem estes organismos. Sabe-se hoje em dia que as comunidades microbianas simbiontes de esponjas marinhas contribuem imensamente para o ‘bem-estar’ do seu hospedeiro por via da produção de moléculas antimicrobianas, por exemplo. Por outro lado, por meio do hospedeiro são ‘providenciados’ abrigo, produtos finais metabólicos como amónia, e produtos orgânicos que derivam da predação por filtração de plâncton unicelular. Todos os anteriores fatores contribuem de forma ainda não verdadeiramente quantificada para o estabelecimento e estruturação do microbioma destes metazoários. Neste estudo, foi abordado o procarioma (isto é, o consórcio de todas as bactérias e arqueias -procariotas- presentes num dado ambiente) de quatro esponjas marinhas. Estas foram amostradas ao largo da costa do Algarve e a baixa profundidade em 2012. No total, 26 espécimes pertencentes às espécies Phorbas fictitius (n=12), Dysidea fragilis (n=3), Cliona viridis (n=4) and C. celata (n=7) foram recolhidos. Todas as amostras foram processadas no sentido de isolar o endossoma de cada indivíduo, isto é, o seu interior, coberto pelo ectossoma. Todas as amostras (indivíduos) foram ademais sujeitas à extração de ADN segundo protocolos padronizados pelo ‘Earth Microbiome Project’.
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Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples.

Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples.

So why not just sequence DNA? There are certainly advantages to sequencing DNA, including its greater stability and the ability to retrieve genetic material from archived samples. Nevertheless, there are also advantages to sequencing RNA for some applications. There is an abundance of publicly available RNA-seq datasets that are potentially useful for future pathogen studies. Another advantage is relevant to the study of human biopsies in which the microbial material is a minor component of the sample. The bacterial-to-human tran- scriptome size ratio is typically greater than the bacterial-to-human genome size ratio because of the abundance of extra human DNA that is poorly or not expressed. In these cases, it is more cost effective to assess the microbial component through RNA sequencing. An added benefit of RNA-seq for clinical diagnosis is the ability to simultaneously obtain information on ex- pressed pathogenic and resistance markers that can inform treatment options.
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Dissecting Genomic Aberrations in Myeloproliferative Neoplasms by Multiplex-PCR and Next Generation Sequencing.

Dissecting Genomic Aberrations in Myeloproliferative Neoplasms by Multiplex-PCR and Next Generation Sequencing.

Myeloproliferative neoplasms (MPN) are a heterogeneous group of hematopoietic disorders which arise from genetically altered myeloid stem or progenitor cells. MPN are characterized by an overproduction of mature myeloid cells, which is due to deregulated cell-autonomous proliferation and which may result in splenomegaly and constitutive symptoms. In addition to the affected hematopoietic lineage (granulocytes, eosinophils, mast cells etc.), molecular mark- ers are used to classify MPN subtypes. Since the first description of the Bcr-Abl oncogene, mo- lecular genetic tools have become instrumental in diagnosis and treatment monitoring of MPN. In addition to the development of highly sensitive quantitative polymerase chain reac- tion (PCR) for RNA expression analysis, fundamental improvements have been made in the field of automated sequencing. Sanger sequencing, having dominated the field for decades, is now complemented by “next generation sequencing” (NGS). These methods allow for a fast, sensitive, and cost-efficient high-throughput screening of genomic aberrations and their appli- cation has already fundamentally improved our understanding of how genetic alterations affect health and disease. For classical Philadelphia chromosome-negative (Ph - ) MPN, which com- prise Essential Thrombocythemia (ET), Polycythemia Vera (PV) and Primary Myelofibrosis (PMF), the clonal nature is reflected by a gain-of-function mutation in the JAK2 gene, which was identified using a functional approach [1]. The JAK2V617F mutation is specific for mye- loid neoplasms and is present in approximately 95% of patients with PV and in 50–60% of pa- tients with ET and PMF, respectively [2]. Moreover, JAK2 exon 12 mutations are present in rare cases of JAK2V617F-negative PV as well as MPL mutations in JAK2V617F-negative ET and PMF. In addition, using a whole genome sequencing approach, Klampfl et al. and Nagalia et al identified calreticulin (CALR) mutations in the majority of ET and PMF patients that are negative for JAK2 or MPL alterations [3,4]. Furthermore, somatic mutations in other genes, such as TET2, DNMT3A, ASXL1, EZH2, IDH1/2, U2AF1, SF3B1, SRSF2, CBL, NF-E2, SH2B3 (LNK), CHEK2 [3], and SOCS 1, 2 and 3, IKZF, SETBP1, among others, have been found in all stages of MPN [5–9]. Furthermore, frequent CSF3R mutations were found in chronic neutro- philic leukemia and atypical CML [10]. Additionally, in eosinophilic MPN, fusion proteins with constitutive tyrosine kinase activity involving PDGFRα, PDGFRβ, and FGFR1 have been described. In systemic mastocytosis (SM), a gain-of-function mutation in the tyrosine kinase receptor (KIT D816V) contributes to cell-autonomous proliferation of atypical mast cells.
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Comparison of Sample Preparation Methods Used for the Next-Generation Sequencing of Mycobacterium tuberculosis.

Comparison of Sample Preparation Methods Used for the Next-Generation Sequencing of Mycobacterium tuberculosis.

The advent and widespread application of next-generation sequencing (NGS) technologies to the study of microbial genomes has led to a substantial increase in the number of studies in which whole genome sequencing (WGS) is applied to the analysis of microbial genomic epidemiology. However, microorganisms such as Mycobacterium tuberculosis (MTB) pres- ent unique problems for sequencing and downstream analysis based on their unique physi- ology and the composition of their genomes. In this study, we compare the quality of sequence data generated using the Nextera and TruSeq isolate preparation kits for library construction prior to Illumina sequencing-by-synthesis. Our results confirm that MTB NGS data quality is highly dependent on the purity of the DNA sample submitted for sequencing and its guanine-cytosine content (or GC-content). Our data additionally demonstrate that the choice of library preparation method plays an important role in mitigating downstream sequencing quality issues. Importantly for MTB, the Illumina TruSeq library preparation kit produces more uniform data quality than the Nextera XT method, regardless of the quality of the input DNA. Furthermore, specific genomic sequence motifs are commonly missed by the Nextera XT method, as are regions of especially high GC-content relative to the rest of the MTB genome. As coverage bias is highly undesirable, this study illustrates the impor- tance of appropriate protocol selection when performing NGS studies in order to ensure that sound inferences can be made regarding mycobacterial genomes.
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Read length and repeat resolution: exploring prokaryote genomes using next-generation sequencing technologies.

Read length and repeat resolution: exploring prokaryote genomes using next-generation sequencing technologies.

It was thought that the presence of multi-copy repeat families would cause a relative abundance of repeats of a particular length [25]. Extending the reads beyond this threshold length would cause a sudden improvement in the assembly and introduce a step- wise character to the curves in Figure 5. This does not appear to be the case for the bacterial genomes examined here. The most probable explanation is that the algorithm only identifies exact repeats. Members of a repeat family which have diverged would be detected as a series of small exact repeats rather than a single, large, degenerate repeat. As such, there would be no accumulation of repeats at a specific length that would be required to produce a ‘‘step’’ in the curves. Given the demonstrated accuracy of the algorithm, the coverage depths achievable with next-generation sequencers, and the underlying characteristics of short read assemblers, the assumption that only exact repeats are problematic is probably justified. Thus, it is unlikely that significant length thresholds would be observed in true assemblies.
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Development of a low bias method for characterizing viral populations using next generation sequencing technology.

Development of a low bias method for characterizing viral populations using next generation sequencing technology.

Having confirmed that our experimental method worked, we then focused on the data obtained from sequencing the ‘‘clinical sample,’’ which yielded over 14 million reads (Table 1). Unlike the NL4-3 sample, no known HIV genome was associated with the patient enrolled in the clinical trial. As a result, only a low number of these reads mapped to a single reference genome. To address this issue, we devised a novel methodology that would allow us to reconstruct a ‘‘consensus sequence’’ consisting of the most abundant sequence present for each region of the HIV genome for this specific patient. In particular, to fully utilize the amount of data obtained from our Illumina sequencing run as well as the sequence data present in the Los Alamos National Labs HIV Database, we developed an iterative strategy for enhanced mapping that utilized larger amounts of known sequence data for building HIV sequences (Figure 2). In this process, the reads were aligned against 414 known subtype B HIV-1 genomes from the Los Alamos National Laboratories using the iterative mapping method described in the Methods section, and the master reference sequence for this sample was constructed by combining regions of consensus where the Illumina reads mapped to each of these genomes. By taking the different regions of consensus that mapped to each of the 414 genomes, we were then able to generate our consensus sequence that could then be used as our reference sequence for mapping our Illumina reads. Our consensus sequence for this specific sample is given in Supplemental File S2.
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Sandra González-de la Fuente, Esther Camacho, Ramón Peiró-Pastor, Alberto Rastrojo, Fernando Carrasco-Ramiro, Begoña Aguado, Jose M Requena

Sandra González-de la Fuente, Esther Camacho, Ramón Peiró-Pastor, Alberto Rastrojo, Fernando Carrasco-Ramiro, Begoña Aguado, Jose M Requena

At this point, a detailed sequence checking was per- formed using PacBio-utilities (v.1; https://github.com/ douglasgscofield/PacBio-utilities), designed to cor- rect deletions and insertions introduced with some fre- quency, mainly in homopolymer strings, by the PacBio sequencing. Corrections were dictated by the sequence derived from Illumina reads, which have higher accu- racy than the PacBio ones. Sequence insertions/deletions were corrected when they were supported by more than ten Illumina reads and the indel was present in 80% (or above) of the reads mapping the concerned position. Ad- ditionally, a second correction step was carried out using an in-house Python script, which uses the output gener- ated by the Pilon tool (v.1.2.2, using option: --diploid).
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Detection and removal of biases in the analysis of next-generation sequencing reads.

Detection and removal of biases in the analysis of next-generation sequencing reads.

Failure to eliminate the mappability bias will lead to increased read densities within regions with higher mappability. This can lead to spurious results, since subsequent analysis revealed that mappability was correlated with certain biological features. We began by examining mappability as a function of transcript length. We divided all exons into five bins based on the length of the transcripts comprising them and examined mappability across the region surrounding the exon/intron junctions within each bin. We found a positive correlation between transcript length and mappability (Fig. 2C). This association was highly significant (Kruskal-Wallis rank sum test, P ,5.7e-227, see Materials and Methods). We next divided all exons into five bins based on evolutionary conservation levels of the exons among 18 placental mammals (see Materials and Methods). We observed a positive correlation between mappability and conservation with ,10% differences in mappability between the most conserved and least conserved exons (Kruskal-Wallis rank sum test, P,0) (Fig. 2D). Finally, we divided all exons into five bins based on transcript expression levels in lung fibroblasts obtained from [27] (this particular tissue was chosen as it was relevant for subsequent analyses). We again observed a clear, albeit more complex, relationship between the expression level and mappability, with the highest differential between exons and introns found in exons from highly expressed genes (Kruskal-Wallis rank sum test, P,5.8e-19) (Fig. 2E). Thus, without proper normalization of mappability, even if reads are uniformly and randomly simulated from the genome, exonic regions from long transcripts will have the highest read densities, more conserved exons would have greater densities, and exons from highly expressed genes would have the greatest differential between exon and introns in terms of read densities. These correlations with biological feature can be highly misleading, as they will lead to skewed results suggestive of representing biological phenomena. We highlight that these biases are only dependent on read length, but not on sequencing platform or type of experiment.
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Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes.

Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes.

To compare a large number of whole genome shotgun sequencing libraries processed at different sequencing centers by a standardized protocol and not expected to contain etiologic microbes or be complicated by issues of handling of pathology samples, we used the Leif Microbiome Analyzer to identify non- aligning reads from 57 Illumina HiSeq 2000 runs performed by various sequencing centers on 1000 Genomes Project samples. The results are shown in Figure 1. Known contaminant sequences (defined here as read pairs in a human sample which match specifically with NCBI BLAST sequences other than primate, EBV, and phage) were present in all runs, varying from 0.000007% to 0.015% of total read pairs with a median of 0.0003%. Low homology sequences (defined here as read pairs which did not match with sequences in the NCBI BLAST databases, usually due to either a high number of sequencing errors or to the presence of novel contaminant strains/species in the run) are listed in a separate column and are not counted as known contaminant sequences–although some may well originate from novel contaminants. Eukaryotic DNA contamination was common, typically aligning to the genus Bos, which may be originating from fetal calf serum used in cell culture media. Bradyrhizobium contamination was found in 25 out of 57 runs. This particular contaminant varied from center to center (Figure 1). The highest levels of Bradyrhizobium were found in runs from center BCM, where 19 runs out of 30 were contaminated, reaching levels as high as 0.003% of reads (Figure 1). Some runs from centers SC, BI, and MPIMG contained a few reads which matched specifically with Bradyrhizobium sp. DFCI-1 (Figure 1 and Text S5, S6 and S7). No Bradyrhizobium read pairs were found in two runs submitted by Illumina or four runs submitted by WUGSC. However, runs from these centers did show contamination from other organisms. Other species commonly encountered included genera Rhizobium/ Agrobacterium, Sphingomonas, Burkholderia, Ralstonia, Pseudomonas, Stenotrophomonas, Flavobacterium (reported together in column ‘‘Ul- trapure water system contaminants – Other’’ of Figure 1); sequence alignments to all species are reported in Spreadsheet S1. These 57 sequencing runs indicate that contamination is widespread and Bradyrhizobium sp. DFCI-1 is a prominent contaminant, but contamination levels are highly variable between runs–even runs from the same sequencing center.
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Leukemia gene atlas--a public platform for integrative exploration of genome-wide molecular data.

Leukemia gene atlas--a public platform for integrative exploration of genome-wide molecular data.

To our knowledge, the LGA is the first repository custom- tailored to the requirements of the leukemia research community in the field of molecular and clinical data. It provides extensive access to published leukemia data and thus helps to interpret newly measured data. It comprises several types of molecular data and supports integration of data types. The corresponding samples are annotated extensively. The user can choose between eight different analysis and visualization tools. Further data sets and data types, e.g. based on ChIP-chip or reduced representation bisulfite sequencing experiments, are continuously added.
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Deep annotation of Populus trichocarpa microRNAs from diverse tissue sets.

Deep annotation of Populus trichocarpa microRNAs from diverse tissue sets.

In order to understand the similarity and differences between the new sRNA sequencing runs, we created a venn diagram comparing presence-absence of miRNAs across the four datasets (Figure 2A). We annotated 164 miRNAs from the pooled dataset, 173 from leaves, 169 from xylem, and 158 from mechanically treated xylem. miRNAs specific to P. trichocarpa were identified by looking for a matching miRNA (within 4 mismatches) anywhere in green plants in miRBASE. It is important to note that in this context, P. trichocarpa specificity is based on failure to annotate a specific miRNA from other genomes, which does not necessarily imply absence from other plant genomes. A total of 110 P. trichocarpa specific miRNAs were identified. These include 36, 53, 51, and 37 P. trichocarpa specific miRNAs identified from pooled, leaf, xylem, and mechanically treated xylem, respectively.
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Differential expression in “rogue” paramutation in peas (Pisum sativum L.): - from mRNA to siRNA

Differential expression in “rogue” paramutation in peas (Pisum sativum L.): - from mRNA to siRNA

The “rogue” phenotype in peas (Pisum sativum L.) was the first reported case of paramutation, however, since this finding, most of the studies focussed on some cases of paramutation in maize. The main aim of this work was the identification of differentially expressed tags in the pea cv. Onward vs. its paramutated rogue line JI2723. One hundred-nine combinations of 4 RAPD primers were used in multi-RAPD differential display analysis, but no expression polymorphisms were identified between the two epigenomes. However, the RT-qPCR analysis of 24 out of the over 120 putatively differentially expressed sequences identified via next generation sequencing of suppression subtractive hybridization (SSH) libraries, allowed the identification of 11 differently expressed sequences. Among these sequences, 8 exhibited very significant differences in their expression in the two epigenomes. A procedure for pre-selection of putatively differently expressed sequences before more accurate confirmation by RT- qPCR analysis was developed and is expected to increase the efficiency of the analytical procedure. Recent studies performed in the Laboratory proved the existence of differences in the DNA methylation between the two epigenomes. Partial sequences of the genes related with DNA methylation and chromatin remodelling, ddm1,drm2 and mop1 were retrieved from the pea genome permitting the expression of these genes to
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Next Generation Semiconductor Based Sequencing of the Donkey (Equus asinus) Genome Provided Comparative Sequence Data against the Horse Genome and a Few Millions of Single Nucleotide Polymorphisms.

Next Generation Semiconductor Based Sequencing of the Donkey (Equus asinus) Genome Provided Comparative Sequence Data against the Horse Genome and a Few Millions of Single Nucleotide Polymorphisms.

For each of the sequenced and aligned dataset described above the combination of the mpileup and bcftools functions of Samtools [50] was used for calling variants (SNPs) without any pre- set filter. Variants were called following these criteria: i) only nucleotide substitutions were considered, neglecting indels as Ion Torrent and Illumina sequencers poorly obtain concordant results for this variability [43]; ii) variation that obtained a mapping quality score 20 and a coverage 4X at the mutation point; iii), variation that were in homopolymeric regions, char- acterized by the presence of 4 or more contiguous identical nucleotides, were discarded. The latter filtering step was not applied to Illumina data because this technology is less prone to errors in short homopolymeric stretches [52]. All these analyses were done using Bash and Python scripts. Samtools options and Python scripts were also used to obtain information about Ion Proton reads aligned to the donkey Y chromosome scaffolds [36], avoiding potential homologous X chromosome regions. Single nucleotide polymorphism density was calculated in 1-Mbp windows across the EcuCab2.0 autosomes and chromosome X. A box plot represen- tation was obtained as mentioned above. Analysis of every predicted variation was performed using the Variant Effect Predictor perl script and web interface [53] with the horse genome (EquCab2.0) as reference genome. To obtain a first evaluation of the SNP calling data 20 primer pairs were designed to target 20 randomly selected SNPs (included in putatively anno- tated donkey genome regions as deduced using information obtained from the EcuCab2.0 genome) and used to amplify and sequence amplicons obtained from a DNA pool obtained merging equimolar quantity of DNA extracted from Peppe and Pippo (S1 Table). Sequencing was carried out using the Sanger technology as previously described [45,46]. Obtained electro- pherograms were analysed using CodonCode Aligner (CodonCode Corporation, Dedham, MA, USA) and checked visually inspecting SNP positions.
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Comparative genome-wide polymorphic microsatellite markers in Antarctic penguins through next generation sequencing

Comparative genome-wide polymorphic microsatellite markers in Antarctic penguins through next generation sequencing

Recent Next Generation Sequencing (NGS) technol- ogies make it feasible to obtain a large number of markers (e.g. microsatellites, SNPs) and have thus revolutionized molecular studies in non-model organisms, permitting rapid characterization of gene structure and expression (Ellegren, 2008). Studies using neutral microsatellites can provide information to understand aspects of species’ ecol- ogy and population genetic structure (Freer et al., 2015; Vianna et al., 2017). Moreover, behavioral differences be- tween males and females are frequently interpreted com- paring population genetic patterns obtained from different markers such as mtDNA (maternal lineage) and micro- satellite loci (biparental lineage; Freer et al., 2015; Vianna et al., 2017). An increasing number of genomes have re- cently become available, including those of several bird species (Jarvis et al., 2014; Zhang et al., 2014), with two species of penguins among them (Li et al., 2014). Those studies focus on genome description and structure, phylog- eny, adaptation, and comparative analyses. Although a large number of microsatellite loci are becoming available for new genomes, they are seldom evaluated with regard to their level of polymorphism in related species.
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Identification and characterization of microRNAs in normal equine tissues by Next Generation Sequencing.

Identification and characterization of microRNAs in normal equine tissues by Next Generation Sequencing.

The role of microRNAs (miRNAs) as a post-transcriptional gene regulator has been elucidated in a broad range of organisms including domestic animals. Characterization of miRNAs in normal tissues is an important step to investigate the functions of miRNAs in various physiological and pathological conditions. Using Illumina Next Generation Sequencing (NGS) technology, we identified a total of 292 known and 329 novel miRNAs in normal horse tissues including skeletal muscle, colon and liver. Distinct sets of miRNAs were differentially expressed in a tissue-specific manner. The miRNA genes were distributed across all the chromosomes except chromosomes 29 and 31 in the horse reference genome. In some chromosomes, multiple miRNAs were clustered and considered to be polycistronic transcript. A base composition analysis showed that equine miRNAs had a higher frequency of A+U than G+C. Furthermore, U tended to be more frequent at the 59 end of miRNA sequences. This is the first experimental study that identifies and characterizes the global miRNA expression profile in normal horse tissues. The present study enriches the horse miRNA database and provides useful information for further research dissecting biological functions of miRNAs in horse.
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An alternative storage method for characterization of the intestinal microbiota through next generation sequencing

An alternative storage method for characterization of the intestinal microbiota through next generation sequencing

Gut microbiota has been the subject of various molecular studies mainly due to its importance and wide-ranging relationships with human hosts. However, the storage of fecal samples prior to DNA extraction is critical when characterizing the composition of intestinal microbiota. Therefore, we aimed to understand the effects of different fecal storage methods to characterize intestinal microbiota using Next Generation Sequencing (NGS) as well as to establish an alternative conservation method of bacterial genetic material in these samples using guanidine. Stool samples from 10 healthy volunteers were collected. Each sample was divided into five aliquots: one aliquot was extracted immediately after collection (fresh) and two aliquots were subjected to freezing at -20 °C or -80 °C and extracted after 48 h. The other two aliquots were stored in guanidine at room temperature or 4 °C and extracted after 48 h. The V4 hypervariable regions of the bacterial and archeal 16S rRNA gene were amplified by PCR and sequenced using an Ion Torrent PGM platform for NGS. The data were analyzed using QIIME software. Statistical significance was determined using a non- parametric Kruskal-Wallis test. A total of 11,494,688 reads with acceptable quality were obtained. Unweighted principal coordinate analysis (PCoA) revealed that the samples were clustered based on the host rather than by the storage group. At the phylum and genus levels, we observed statistically significant differences between two genera, Proteobacteria (p=0.013) and Suterella (p=0.004), comparing frozen samples with guanidine-stored samples. Our data suggest that the use of guanidine can preserve bacterial genetic materials as well as freezing, providing additional conveniences.
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Evolution for the Next Generation.

Evolution for the Next Generation.

Although the key forces driving evolution are usually thought of as mutation, genetic drift, natural selection, and divergence, the developmental pathways from genes to phenotypes, [r]

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