Combinatorial pooled sequencing: experiment design and decoding

A comprehensive framework for the delimitation of species within the Bemisia tabaci cryptic complex, a global pest-species group

Identifying cryptic species poses a substantial challenge to both biologists and naturalists due to morphological similarities. Bemisia tabaci is a cryptic species complex containing more than 44 putative species; several of which are currently among the world's most destructive crop pests. Interpreting and delimiting the evolution of this species complex has proved problematic. To develop a comprehensive framework for species delimitation and identification, we evaluated the performance of distinct data sources both individually and in combination among numerous samples of the B. tabaci species complex acquired worldwide. Distinct datasets include full mitogenomes, single-copy nuclear genes, restriction site-associated DNA sequencing, geographic range, host speciation, and reproductive compatibility datasets. Phylogenetically, our well-supported topologies generated from three dense molecular markers highlighted the evolutionary divergence of species of the B. tabaci complex and suggested that the nuclear markers serve as a more accurate representation of B. tabaci species diversity. Reproductive compatibility datasets facilitated the identification of at least 17 different cryptic species within our samples. Native geographic range information provides a complementary assessment of species recognition, while the host range datasets provide low rate of delimiting resolution. We further summarized different data performances in species classification when compared with reproductive compatibility, indicating that combination of mtCOI divergence, nuclear markers, geographic range provide a complementary assessment of species recognition. Finally, we represent a model for understanding and untangling the cryptic species complexes based on the evidence from this study and previously published articles.

DNA-pools targeted-sequencing as a robust cost-effective method to detect rare variants: Application to dilated cardiomyopathy genetic diagnosis

Dilated cardiomyopathy (DCM) is a heart disease characterized by left ventricular dilatation and systolic dysfunction. In 30% of cases, pathogenic variants, essentially private to each patient, are identified in at least one of almost 50 reported genes. Thus, while costly, exons capture-based Next Generation Sequencing (NGS) of a targeted gene panel appears as the best strategy to genetically diagnose DCM. Here, we report a NGS strategy applied to pools of 8 DNAs from DCM patients and validate its robustness for rare variants detection at 4-fold reduced cost. Our pipeline uses Freebayes to detect variants with the expected 1/16 allele frequency. From the whole set of detected rare variants in 96 pools we set the variants quality parameters optimizing true positives calling. When compared to simplex DNA sequencing in a shared subset of 50 DNAs, 96% of SNVs/InsDel were accurately identified in pools. Extended to the 384 DNAs included in the study, we detected 100 variants (ACMG class 4 and 5), mostly in well-known morbid gene causing DCM such as TTN, MYH7, FLNC, and TNNT2. To conclude, we report an original pool-sequencing NGS method accurately detecting rare variants. This innovative approach is cost-effective for genetic diagnostic in rare diseases.

Identifying chromatin features that regulate gene expression distribution

Gene expression variability, differences in the number of mRNA per cell across a population of cells, is ubiquitous across diverse organisms with broad impacts on cellular phenotypes. The role of chromatin in regulating average gene expression has been extensively studied. However, what aspects of the chromatin contribute to gene expression variability is still underexplored. Here we addressed this problem by leveraging chromatin diversity and using a systematic investigation of randomly integrated expression reporters to identify what aspects of chromatin microenvironment contribute to gene expression variability. Using DNA barcoding and split-pool decoding, we created a large library of isogenic reporter clones and identified reporter integration sites in a massive and parallel manner. By mapping our measurements of reporter expression at different genomic loci with multiple epigenetic profiles including the enrichment of transcription factors and the distance to different chromatin states, we identified new factors that impact the regulation of gene expression distributions.

Loci specific epigenetic drug sensitivity

Therapeutic targeting of epigenetic modulators offers a novel approach to the treatment of multiple diseases. The cellular consequences of chemical compounds that target epigenetic regulators (epi-drugs) are complex. Epi-drugs affect global cellular phenotypes and cause local changes to gene expression due to alteration of a gene chromatin environment. Despite increasing use in the clinic, the mechanisms responsible for cellular changes are unclear. Specifically, to what degree the effects are a result of cell-wide changes or disease related locus specific effects is unknown. Here we developed a platform to systematically and simultaneously investigate the sensitivity of epi-drugs at hundreds of genomic locations by combining DNA barcoding, unique split-pool encoding, and single cell expression measurements. Internal controls are used to isolate locus specific effects separately from any global consequences these drugs have. Using this platform we discovered wide-spread loci specific sensitivities to epi-drugs for three distinct epi-drugs that target histone deacetylase, DNA methylation and bromodomain proteins. By leveraging ENCODE data on chromatin modification, we identified features of chromatin environments that are most likely to be affected by epi-drugs. The measurements of loci specific epi-drugs sensitivities will pave the way to the development of targeted therapy for personalized medicine.

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

A newly recorded Rickettsia of the Torix group is a recent intruder and an endosymbiont in the whitefly Bemisia tabaci

The bacterium Rickettsia is found widely in phytophagous insects and often exerts profound effects on the phenotype and fitness of its hosts. Here, we decrypt a new, independent, phylogenetically ancient Torix Rickettsia endosymbiont found constantly in a laboratory line of an economically important insect Asia II 7, a putative species of the Bemisia tabaci whitefly complex (Hemiptera: Aleyrodidae), and occasionally in field whitefly populations. This new Rickettsia distributes throughout the body of its whitefly host. Genetically, compared to Rickettsia_bellii_MEAM1 found earlier in whiteflies, the new Rickettsia species has more gene families and pathways, which may be important factors in shaping specific symbiotic relationships. We propose the name 'Candidatus Rickettsia_Torix_Bemisia_tabaci (RiTBt)' for this new endosymbiont associated with whiteflies. Comparative genomic analyses indicate that RiTBi may be a relatively recent intruder in whiteflies given its low abundance in the field and relatively larger genome compared to Rickettsia_bellii_MEAM1.

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article available online.

Efficient identification of SNPs in pooled DNA samples using a dual mononucleotide addition-based sequencing method

Identifying single nucleotide polymorphism (SNPs) from pooled samples is critical for many studies and applications. SNPs determined by next-generation sequencing results may suffer from errors in both base calling and read mapping. Taking advantage of dual mononucleotide addition-based pyrosequencing, we present Epds, a method to efficiently identify SNPs from pooled DNA samples. On the basis of only five patterns of non-synchronistic extensions between the wild and mutant sequences using dual mononucleotide addition-based pyrosequencing, we employed an enumerative algorithm to infer the mutant locus and estimate the proportion of mutant sequence. According to the profiles resulting from three runs with distinct dual mononucleotide additions, Epds could recover the mutant bases. Results showed that our method had a false-positive rate of less than 3%. Series of simulations revealed that Epds outperformed the current method (PSM) in many situations. Finally, experiments based on profiles produced by real sequencing proved that our method could be successfully applied for the identification of mutants from pooled samples. The software for implementing this method and the experimental data are available at http://bioinfo.seu.edu.cn/Epds.