scholarly journals Leishmania Sexual Reproductive Strategies as Resolved through Computational Methods Designed for Aneuploid Genomes

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 167
Author(s):  
Jahangheer S. Shaik ◽  
Deborah E. Dobson ◽  
David L. Sacks ◽  
Stephen M. Beverley
Keyword(s):  
Computational Methods ◽  
Reproductive Strategies ◽  
Sand Fly ◽  
Genetic Studies ◽  
Sexual Strategies ◽  
Inheritance Patterns ◽  
Sequencing Technologies ◽  
Sexual Recombination ◽  
Natural Isolates ◽  
Informative Approach

A cryptic sexual reproductive cycle in Leishmania has been inferred through population genetic studies revealing the presence of hybrid genotypes in natural isolates, with attempts made to decipher sexual strategies by studying complex chromosomal inheritance patterns. A more informative approach is to study the products of controlled, laboratory-based experiments where known strains or species are crossed in the sand fly vector to generate hybrid progeny. These hybrids can be subsequently studied through high resolution sequencing technologies and software suites such as PAINT that disclose inheritance patterns including ploidies, parental chromosome contributions and recombinations, all of which can inform the sexual strategy. In this work, we discuss the computational methods in PAINT that can be used to interpret the sexual strategies adopted specifically by aneuploid organisms and summarize how PAINT has been applied to the analysis of experimental hybrids to reveal meiosis-like sexual recombination in Leishmania.

scholarly journals Survey of the Bradysia odoriphaga Transcriptome Using PacBio Single-Molecule Long-Read Sequencing

Genes ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 481 ◽  
Author(s):  
Chen ◽  
Lin ◽  
Xie ◽  
Zhong ◽  
Zhang ◽  
...  
Keyword(s):  
Insecticide Resistance ◽  
Single Molecule ◽  
Functional Categories ◽  
Genetic Studies ◽  
Sequencing Technologies ◽  
Clusters Of Orthologous Groups ◽  
Long Read ◽  
Main Gene ◽  
First Time ◽  
Main Factor

The damage caused by Bradysia odoriphaga is the main factor threatening the production of vegetables in the Liliaceae family. However, few genetic studies of B. odoriphaga have been conducted because of a lack of genomic resources. Many long-read sequencing technologies have been developed in the last decade; therefore, in this study, the transcriptome including all development stages of B. odoriphaga was sequenced for the first time by Pacific single-molecule long-read sequencing. Here, 39,129 isoforms were generated, and 35,645 were found to have annotation results when checked against sequences available in different databases. Overall, 18,473 isoforms were distributed in 25 various Clusters of Orthologous Groups, and 11,880 isoforms were categorized into 60 functional groups that belonged to the three main Gene Ontology classifications. Moreover, 30,610 isoforms were assigned into 44 functional categories belonging to six main Kyoto Encyclopedia of Genes and Genomes functional categories. Coding DNA sequence (CDS) prediction showed that 36,419 out of 39,129 isoforms were predicted to have CDS, and 4319 simple sequence repeats were detected in total. Finally, 266 insecticide resistance and metabolism-related isoforms were identified as candidate genes for further investigation of insecticide resistance and metabolism in B. odoriphaga.

scholarly journals Quantitative Seq-LGS – Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

2016 ◽  
Author(s):  
Hussein M. Abkallo ◽  
Axel Martinelli ◽  
Megumi Inoue ◽  
Abhinay Ramaprasad ◽  
Phonepadith Xangsayarath ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Genetic Determinants ◽  
Malaria Parasites ◽  
Apicomplexan Parasites ◽  
Mendelian Genetics ◽  
Sequencing Technologies ◽  
Multiple Phenotypes ◽  
Genome Wide ◽  
Sexual Recombination ◽  
Novel Alleles

ABSTRACTIdentifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.Significance StatementThis paper describes a powerful and rapid approach to the discovery of genes underlying medically important phenotypes in malaria parasites. This is crucial for the design of new drug and vaccine interventions. The approach bypasses the most time-consuming steps required by traditional genetic linkage studies and combines Mendelian genetics, quantitative deep sequencing technologies, genome analysis and mathematical modeling. We demonstrate that the approach can simultaneously identify multigenic drivers of multiple phenotypes, thus allowing complex genotyping studies to be conducted concomitantly. This methodology will be particularly useful for discovering the genetic basis of medically important phenotypes such as drug resistance and virulence in malaria and other apicomplexan parasites, as well as potentially in any organism undergoing sexual recombination.

Comparison and integration of computational methods for deleterious synonymous mutation prediction

2019 ◽  
Vol 21 (3) ◽  
pp. 970-981 ◽  
Author(s):  
Na Cheng ◽  
Menglu Li ◽  
Le Zhao ◽  
Bo Zhang ◽  
Yuhua Yang ◽  
...  
Keyword(s):  
Computational Methods ◽  
Computational Models ◽  
Predictive Performance ◽  
Specific Method ◽  
Ensemble Model ◽  
Synonymous Mutation ◽  
Synonymous Mutations ◽  
Sequencing Technologies ◽  
Nucleotide Mutation ◽  
Mutation Prediction

Abstract Synonymous mutations do not change the encoded amino acids but may alter the structure or function of an mRNA in ways that impact gene function. Advances in next generation sequencing technologies have detected numerous synonymous mutations in the human genome. Several computational models have been proposed to predict deleterious synonymous mutations, which have greatly facilitated the development of this important field. Consequently, there is an urgent need to assess the state-of-the-art computational methods for deleterious synonymous mutation prediction to further advance the existing methodologies and to improve performance. In this regard, we systematically compared a total of 10 computational methods (including specific method for deleterious synonymous mutation and general method for single nucleotide mutation) in terms of the algorithms used, calculated features, performance evaluation and software usability. In addition, we constructed two carefully curated independent test datasets and accordingly assessed the robustness and scalability of these different computational methods for the identification of deleterious synonymous mutations. In an effort to improve predictive performance, we established an ensemble model, named Prediction of Deleterious Synonymous Mutation (PrDSM), which averages the ratings generated by the three most accurate predictors. Our benchmark tests demonstrated that the ensemble model PrDSM outperformed the reviewed tools for the prediction of deleterious synonymous mutations. Using the ensemble model, we developed an accessible online predictor, PrDSM, available at http://bioinfo.ahu.edu.cn:8080/PrDSM/. We hope that this comprehensive survey and the proposed strategy for building more accurate models can serve as a useful guide for inspiring future developments of computational methods for deleterious synonymous mutation prediction.

scholarly journals Population genetics of lichen-forming fungi – a review

2010 ◽  
Vol 42 (5) ◽  
pp. 499-519 ◽  
Author(s):  
Silke WERTH
Keyword(s):  
Population Genetics ◽  
Population Genetic ◽  
Reproductive Strategies ◽  
Natural Populations ◽  
Future Research ◽  
Molecular Tools ◽  
Genetic Studies ◽  
Green Algal ◽  
Fungal Genetic ◽  
Genetic Structures

AbstractPopulation genetics investigates the distribution of genetic variation in natural populations and the genetic differentiation among populations. Lichen-forming fungi are exciting subjects for population genetic studies due to their obligate symbiosis with a green-algal and/or cyanobacterial photobiont, and because their different reproductive strategies could influence fungal genetic structures in various ways. In this review, first, I briefly summarize the results from studies of chemotype variation in populations of lichen-forming fungi. Second, I compare and evaluate the DNA-based molecular tools available for population genetics of lichen-forming fungi. Third, I review the literature available on the genetic structure of lichen fungi to show general trends. I discuss some fascinating examples, and point out directions for future research.

Attachment and sexual strategies

2009 ◽  
Vol 32 (1) ◽  
pp. 43-44
Author(s):  
Lane E. Volpe ◽  
Robert A. Barton
Keyword(s):  
Mate Choice ◽  
Sexual Behaviour ◽  
Reproductive Strategies ◽  
Life Histories ◽  
Sexual Strategies ◽  
Intervening Variables

AbstractSexual behaviour and mate choice are key intervening variables between attachment and life histories. We propose a set of predictions relating attachment, reproductive strategies, and mate choice criteria.

scholarly journals Computational methods for chromosome-scale haplotype reconstruction

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shilpa Garg
Keyword(s):  
Genetic Variation ◽  
Computational Methods ◽  
Whole Genome ◽  
Haplotype Reconstruction ◽  
High Quality ◽  
Short Read ◽  
Short Read Sequencing ◽  
Sequencing Technologies ◽  
Long Read ◽  
Haplotype Information

AbstractHigh-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.

scholarly journals Host–microbial dialogues in atopic dermatitis

2019 ◽  
Vol 31 (7) ◽  
pp. 449-456 ◽  
Author(s):  
Tetsuro Kobayashi ◽  
Keisuke Nagao
Keyword(s):  
Atopic Dermatitis ◽  
Clinical Manifestations ◽  
Skin Surface ◽  
Skin Microbiota ◽  
Genetic Studies ◽  
Monogenic Disorders ◽  
Sequencing Technologies ◽  
Functional Immunity ◽  
Eczematous Dermatitis ◽  
Novel Therapeutic Strategies

AbstractRecent advances in sequencing technologies have revealed the diversity of microbes that reside on the skin surface which has enhanced our understanding on skin as an ecosystem, wherein the epidermis, immune cells and the microbiota engage in active dialogues that maintain barrier integrity and functional immunity. This mutual dialogue is altered in atopic dermatitis (AD), in which an impaired epidermal barrier, the skin microbial flora and aberrant immunity can form a vicious cycle that leads to clinical manifestations as eczematous dermatitis. Microbiome studies have revealed an altered microbial landscape in AD and genetic studies have identified genes that underlie barrier impairment and immune dysregulation. Shifting from the long-standing notion that AD was mediated by conventional allergic responses, emerging data suggest that it is a disorder of an altered host–microbial relationship with sophisticated pathophysiology. In this review, we will discuss recent advancements that suggest the roles of the skin microbiota in AD pathophysiology, genetic factors that mediate barrier impairment, dysbiosis and inflammation. Studies in mice, classic AD and monogenic disorders that manifest as AD collectively facilitate our understanding of AD pathophysiology and provide a foundation for novel therapeutic strategies.

Tales of Human Migration, Admixture, and Selection in Africa

2018 ◽  
Vol 19 (1) ◽  
pp. 405-428 ◽  
Author(s):  
Carina M. Schlebusch ◽  
Mattias Jakobsson
Keyword(s):  
Human Migration ◽  
Population History ◽  
Population Divergence ◽  
Before Present ◽  
Hunter Gatherers ◽  
Genetic Studies ◽  
Sequencing Technologies ◽  
Anatomically Modern Humans ◽  
History Of ◽  
Divergence Dates

In the last three decades, genetic studies have played an increasingly important role in exploring human history. They have helped to conclusively establish that anatomically modern humans first appeared in Africa roughly 250,000–350,000 years before present and subsequently migrated to other parts of the world. The history of humans in Africa is complex and includes demographic events that influenced patterns of genetic variation across the continent. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter–gatherers, as the world's deepest population divergences occur among these groups, and that the deepest population divergence dates to 300,000 years before present. However, the spread of pastoralism and agriculture in the last few thousand years has shaped the geographic distribution of present-day Africans and their genetic diversity. With today's sequencing technologies, we can obtain full genome sequences from diverse sets of extant and prehistoric Africans. The coming years will contribute exciting new insights toward deciphering human evolutionary history in Africa.

scholarly journals The First Genetic Linkages among Expressed Regions of the Garlic Genome

2005 ◽  
Vol 130 (4) ◽  
pp. 569-574 ◽  
Author(s):  
Yayeh Zewdie ◽  
Michael J. Havey ◽  
James P. Prince ◽  
Maria M. Jenderek
Keyword(s):  
Average Distance ◽  
Plant Introduction ◽  
Nucleotide Polymorphisms ◽  
Single Male ◽  
Single Nucleotide ◽  
Genetic Studies ◽  
Asexual Propagation ◽  
Sexual Recombination ◽  
Genetic Linkages ◽  
Heterozygous Plant

Garlic (Allium sativum L.) has been cultivated by asexual propagation since time immemorial. The discovery of male-fertile garlic accessions has opened a venue for genetic studies and improvement through sexual recombination. An S1 family of 84 plants was generated from a single male-fertile heterozygous plant from the U.S. Dept. of Agriculture Plant Introduction 540316 and used to identify the first genetic linkages in garlic based on single nucleotide polymorphisms, simple sequence repeats, and randomly amplified polymorphic DNAs. Thirty-seven markers formed nine linkage groups covering 415 centimorgans (cM) with average distance of 15 cM between loci; other 16 loci remained unlinked. A male fertility locus was placed on the map. This first genetic map of garlic is a seminal step toward the genetic improvement of garlic and eventual marker-assisted breeding.

scholarly journals Computational enhancement of single-cell sequences for inferring tumor evolution

2018 ◽  
Author(s):  
Sayaka Miura ◽  
Louise A Huuki ◽  
Tiffany Buturla ◽  
Tracy Vu ◽  
Karen Gomez ◽  
...  
Keyword(s):  
Single Cell ◽  
Computational Methods ◽  
False Negative ◽  
Evolutionary Information ◽  
Tumor Evolution ◽  
Single Cell Sequencing ◽  
Sequencing Technologies ◽  
Molecular Phylogenetic ◽  
Phylogenetic Framework

AbstractMotivation: Tumor sequencing has entered an exciting phase with the advent of single-cell techniques that are revolutionizing the assessment of single nucleotide variation (SNV) at the highest cellular resolution. However, state-of-the-art single-cell sequencing technologies produce data with many missing bases (MBs) and incorrect base designations that lead to false-positive (FP) and false-negative (FN) detection of somatic mutations. While computational methods are available to make biological inferences in the presence of these errors, the accuracy of the imputed MBs and corrected FPs and FNs remains unknown.Results: Using computer simulated datasets, we assessed the robustness performance of four existing methods (OncoNEM, SCG, SCITE, and SiFit) and one new method (BEAM). BEAM is a Bayesian evolution-aware method that improves the quality of single-cell sequences by using the intrinsic evolutionary information in the single-cell data in a molecular phylogenetic framework. Overall, BEAM and SCITE performed the best. Most of the methods imputed MBs with high accuracy, but effective detection and correction of FPs and FNs require sampling a large number of SNVs. Analysis of an empirical dataset shows that computational methods can improve both the quality of tumor single-cell sequences and their utility for biological inference.Conclusions: Tumor cells descend from pre-existing cells, which creates evolutionary continuity in single-cell sequencing datasets. This information enables BEAM and other methods to correctly impute missing data and incorrect base assignments, but correction of FPs and FNs remains challenging when the number of SNVs sampled is small relative to the number of cells sequenced.Availability: BEAM is available on the web at https://github.com/SayakaMiura/BEAM.Contact:[email protected]

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