Sex, Genes and Diplomonads: The Evolution of Sex-related Genes in Hexamita inflata – Begüm Serra Büyüktarakçı

Presenter

Begüm Serra Büyütarakçı

After I completed BSc at Boğaziçi University, Molecular Biology and Genetics department, I moved to Sweden for MSc and studied Evolutionary Biology at Uppsala University. Meanwhile, I got interested in bioinformatics and focused on phylogenetic analysis in the thesis of my master’s degree. I am currently working as a research assistant in Molecular Evolution group of Jan Andersson at Biomedical Centre (BMC), Uppsala University.

Abstract

Sexual reproduction is widespread among eukaryotes however it is not very wellknown outside of the animals, land plants and fungi kingdoms. Metamonada, a phylum of single-celled eukaryotes, comprises diverse lineages including diplomonads. Some members of diplomonads have been assumed to be asexual, though the presence of putative meiotic genes were reported in recent studies. I applied a comparative phylogenomic approach to clarify the occurrence of sexual life cycle in diplomonads. Here, I surveyed the sets of sex-related genes in the ongoing Hexamita inflata genome project. The inventory of sex-related genes was compiled based on the major sexual processes: cell fusion (plasmogamy), nuclear fusion (karyogamy) and meiosis. My analysis showed that H. inflata encodes karyogamy protein, Gex1 but not the plasmogamy protein, Hap2. Putatively meiosis specific genes: Spo11, Dmc1, Hop2 and Mnd1 were identified in H. inflata genome. Based on my findings, H. inflata possesses Mer3/Hfm1 gene which is required during meiotic crossover formation and postmeiotic genes (Mlh2/Pms1 and Mad2). I hypothesize that H. inflata is capable of some sex-related processes such as nuclear fusion and meiotic inter-homolog recombination. My results indicate that the sex machinery varies among diplomonads and other Metamonada based on the wide distribution of sex-related genes.

Date: September 30th, 2020 – 4:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:

https://www.bigmarker.com/bioinfonet/Sex-Genes-and-Diplomonads-The-Evolution-of-Sex-related-Genes-in-Hexamita-inflata

Density based clustering and error correction of metabarcodes in Nanopore sequencing using the novel bioinformatics algorithm ASHURE – Bilgenur Baloğlu

Presenter

Bilgenur Baloğlu

Bilgenur Baloglu earned her B.S. in molecular biology and genetics at Istanbul Technical University. She then earned her Ph.D. in Biological Sciences from National University of Singapore in 2018. Her thesis focused on the biological assessment of aquatic habitats using DNA sequencing technologies, which contributed to solving an ecological outbreak caused by aquatic insects as well as led to the discovery of nearly 350 insect species in a tropical swamp forest. Throughout her Ph.D., she provided consulting services to the National Water Agency of Singapore government. Dr. Baloglu worked as/is as postdoctoral researcher at the Centre for Biodiversity Genomics, University of Guelph in Canada, where she focused on developing new methods for DNA sequencing, Nanopore sequencing, and phylogenetics of sub-arctic insects. She is also coordinating a US EPA funded project on the Great Lakes DNA barcoding along with four collaborating universities in the USA.

Abstract

Metabarcoding (identification of the plant, animal, and fungal taxa present in an environmental sample) rapidly gains importance in ecology, food safety, pest identification, and disease surveillance. It has a compelling advantage over traditional approaches for obtaining data on species distributions, however, it is often difficult to detect all the species present in a bulk sample using High-throughput Sequencing (HTS). This can – in parts – be attributed to the shorter read lengths most HTS instruments generate. Moreover, most HTS platforms are not portable, making in situ field-based sequencing not feasible. Oxford Nanopore sequencing platforms such as the MinION represent an exception to that and they are also known to provide longer reads albeit limited by rather high error rates (~12-15%). We used a freshwater mock community of 50 Operational Taxonomic Units (OTU) to test the capacity of the Oxford Nanopore MinION coupled with a rolling circle amplification protocol to provide long read metabarcoding results. We also propose a new Python pipeline that explores error profiles of nanopore consensus sequences, mapping accuracy, and overall community representation within a complex bulk sample. Using our molecular and bioinformatics workflow, we were able to estimate the diversity of the tested freshwater mock community with an average sequence accuracy of >99% for 1D2 sequencing on the nanopore platform. We also showed that the high error rates associated with long-read single-molecule sequencing can be mitigated by using a rolling circle amplification protocol. Future bioassessment programs will tremendously benefit from such portable, highly accurate, species-level metabarcoding and it appears that we reached a point were cost-effective field-based DNA metabarcoding is possible.

Date: August 28th, 2020 – 3:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:

https://www.bigmarker.com/bioinfonet/Density-based-clustering-and-error-correction-of-metabarcodes-in-Nanopore-sequencing-using-ASHURE

The Impact of Protein Structure on Sequence Evolution – Julien Y. Dutheil

Presenter

Julien Y. Dutheil

My research aims at understanding the mechanisms of biological evolution at the molecular level. I am in particular interested in the study of stochastic processes and the role of organisational levels (a.k.a. “systems”). Research in my group combines computational with experimental approaches, applied to population genomics, structural bioinformatics and statistical analysis of “omics” data.

Abstract

The fate of mutations in populations depends on their impact on the fitness of the individual that carries them. This fitness effect depends, in turn, on the location of the mutation in the genome: a mutation occurring in a non-coding region generates a new allele that will evolve neutrally, while a mutation located within a functional region can have deleterious or advantageous effects, effects that will furthermore depend on the function of the underlying gene. Yet within a given gene, mutations can have very distinct effects. For genes encoding a macromolecule, RNA or protein, an important determinant of these effects is the structure of the encoded molecule. I will here present some insights that we gained regarding the impact of protein structure on the evolution of sequences, with a focus on protein-encoding sequences. In particular, we ask the following questions: (1) what is the distribution of adaptive mutations along 3D protein structures and (2) to which extent does protein structure generate coevolution between positions? To leverage information about the distribution of fitness effects, we relied on comparative genome analyses. I will present two statistical approaches: an extension of the McDonald-Kreitman approach that allows inferring the rate of adaptive non-synonymous substitutions by modeling the distribution of fitness effects of mutations, and a substitution mapping procedure used for inferring coevolving positions.

Date: September 4th, 2020 – 6:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:

https://www.bigmarker.com/bioinfonet/The-Impact-of-Protein-Structure-on-Sequence-Evolution

Projecting the Course of COVID-19 in Turkey: A Probabilistic Modeling Approach – Hüseyin Cahit Burduroğlu

Presenter

Hüseyin Cahit Burduroğlu

He graduated from the Molecular Biology and Genetics department of Yildiz Technical University. After working in the area of structural bioinformatics for 3 years in two different projects that are focused on the stability of metalloproteins and peptides to be used on drug-delivery, he joined the Bioinformatics Master Program in METU Informatics Institute in 2019 where he currently works as a research assistant.

Abstract

The COVID-19 Pandemic originated in Wuhan, China, in December 2019 and became one of the worst global health crises ever. The first confirmed cases were announced early in March and since then, serious containment measures have taken place in Turkey. Here, we present a different approach, a Bayesian negative binomial multilevel model with mixed effects, for the projection of the COVID-19 pandemic and apply this model to the Turkish case. We predicted confirmed daily cases and cumulative numbers for June 6th to June 26th with 80%, 95%, and 99% prediction intervals (PI). Our projections showed that if we continued to comply with measures and no drastic changes are seen in diagnosis or management protocols, the epidemic curve would tend to decrease in this time interval. Also, the predictive validity analysis suggests that proposed model projections should be in the 95% PI band for the first 12 days of the projections.

Date: August 21th, 2020 – 2:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:

https://www.bigmarker.com/bioinfonet/Projecting-the-Course-of-COVID-19-in-Turkey-A-Probabilistic-Modeling-Approach

Lewontin Paradoksu ve Düşündürdükleri – Ergi Deniz Özsoy

Presenter

Ergi Deniz Özsoy

Ergi Deniz Özsoy, 1967 yılında Hannover’da doğdu. 1993 yılında Hacettepe Üniversitesi Fen Fakültesi Biyoloji Bölümü’nü bitiren Özsoy, 1996 yılında yine aynı bölümde yüksek lisans tezini vererek bilim uzmanı oldu. 2002 yılında Hacettepe Üniversitesi Biyoloji Bölümü ‘nde doktorasını tamamladı. Doktora deneylerini Groningen Üniversitesi Genetik Bölümü Popülasyon Genetiği biriminde aldığı TÜBİTAK bursuyla tamamladı. 2000 ve 2002 yıllarında Kuzey Karolina Üniversitesi’nde istatistiksel genetik üzerine eğitim aldı. 2004 yılından itibaren çeşitli sürelerle aynı üniversitede Trudy Mackay’ın laboratuvarında kantitatif genetik ve genomik çalıştı. 2010 yılında Fullbright bursiyeri olarak Kaliforniya Üniversitesi San Diego’da Ekoloji ve Evrimsel Biyoloji Bölümü’nde araştırmalarda bulundu. Şu an Hacettepe Üniversitesi Biyoloji Bölümü’nde genotip-fenotip ilişkisinin karmaşık genetiği ve genomiği üzerine evrimsel genetik perspektif kullanarak Drosophila modelleri çerçevesinde çalışmaktadır. Ek olarak egzersiz genetiği ve genomiği, gelişim genetiği ve çeşitli genetik temelli hastalıkları genomdaki genetik varyasyonla ilişkisinin araştırılması gibi çalışmalarda yürütmektedir. Evrimsel biyoloji, genetik, genomik ve kantitatif genetik Özsoy’un çalışma alanlarıdır. Özsoy, evrimsel biyolojinin tarihi ve evrim felsefesi ve biyoloji felsefesi konularıyla da ilgilenmektedir. Bu konularda yurt içinde ve yurt dışında yayınlanmış makaleleri bulunmaktadır.

Özet

Bir türün sahip olduğu genetik çeşitlilik miktarının genellikle, nötral (seçilimsel olarak birbirine eş) mutasyonların birikmesiyle oluştuğu düşünülür. Nötral evrim kuramına göre, nötral mutasyonların genetik sürüklenme ile birikmesi sonucunda oluşan heterozigotluk (genetik çeşitlilik) ile populasyonların etkin (efektif) büyüklüğü arasında doğrusal bir ilişki olmalıdır: popülasyon büyüklüğü arttıkça nötral mutasyonların birikme ihtimali de artar ve genomik heterozigotluk düzeyiyle, dolayısıyla, popülasyon büyüklüğü doğru orantılıdır. Bununla birlikte, ilk defa tüm açıklığıyla çağımızın büyük evrimsel genetikçisi Richard Lewontin’in analizinin işaret ettiği gibi, bu ilişki bir yanılsamaya dayalı olabilir ve yapılan pek çok çalışma büyük popülasyon-düşük genetik varyasyon ya da düşük genetik varyasyon büyük popülasyon büyüklüğüne sahip pek çok türe ve tür-içi (popülasyonlar arası) farka işaret etmektedir. Popülasyon büyüklüğü ile nötral genetik çeşitlilik arasındaki bu çelişki- evrimsel biyoloji literatüründe Lewontin Paradoksu olarak anılmaktadır ve evrimsel biyolojinin zorlu problemlerinden biri olarak aktif araştırma konusudur. Bu konuşmada, Lewontin paradoksunun çözümüne işaret eden modern çalışmalar ve yaklaşımlar, klasik Hill-Robertson etkisinin genişletilmiş bağlamında, “bağlantılı seçilim (linked selection)” sürecine vurgu yapılarak özetlenecektir.

Tarih: 8 Ağustos 2020 – 18:00 (GMT+3)

Dil: Türkçe

Aşağıdaki linkten webinara kayıt olabilirsiniz:

https://www.bigmarker.com/bioinfonet/Lewontin-Paradoksu-ve-Dusundurdukleri

Drivers of Genetic Diversity in Regions of Low Recombination – Kimberly Gilbert

Presenter

Kimberly Gilbert

Dr. Gilbert obtained her PhD from the University of British Columbia in 2016, studying theoretical population genetics and the impact of demography on evolutionary processes and inferences. Her research broadly includes both theoretical and empirical data analysis in topics of evolutionary biology, including population structure, effective population size, local adaptation, and mutation load. She is currently a postdoctoral fellow at the University of Lausanne, Switzerland. More information is available on her website: http://kjgilbert.github.io/

Abstract

Linked selection is a major driver of genetic diversity. Selection against deleterious mutations removes linked neutral diversity (background selection [BGS]), creating a positive correlation between recombination rates and genetic diversity. Purifying selection against recessive variants, however, can also lead to associative overdominance (AOD), due to an apparent heterozygote advantage at linked neutral loci that opposes the loss of neutral diversity by BGS. Zhao and Charlesworth (2016) identified the conditions under which AOD should dominate over BGS in a single-locus model and suggested that the effect of AOD could become stronger if multiple linked deleterious variants co-segregate. We present a model describing how and under which conditions multi-locus dynamics can amplify the effects of AOD. We derive the conditions for a transition from BGS to AOD due to pseudo-overdominance, i.e., a form of balancing selection that maintains complementary deleterious haplotypes that mask the effect of recessive deleterious mutations. Simulations confirm these findings and show that multi-locus AOD can increase diversity in low-recombination regions much more strongly than previously appreciated. While BGS is known to drive genome-wide diversity in humans, the observation of a resurgence of genetic diversity in regions of very low recombination is indicative of AOD. We identify 22 such regions in the human genome consistent with multi-locus AOD. Our results demonstrate that AOD may play an important role in the evolution of low-recombination regions of many species.

Date: July 16th, 2020 – 6:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:

https://www.bigmarker.com/bioinfonet/Drivers-of-Genetic-Diversity-in-Regions-of-Low-Recombination

INSaFLU ve galaxyproject ile SARS-CoV-2 varyantlarının karşılaştırılması – RSG-Türkiye Aktif Üyeleri

Çalışmayı Yapanlar

  • Nazlı S. Kara, İstinye Üniversitesi
  • Meltem Kutnu, ODTÜ
  • Yasemin Utkueri, Sabancı Üniversitesi
  • Funda Yılmaz, Radbound University
  • Elif Bozlak, University of Veterinary Medicine Vienna; Vienna Graduate School of Population Genetics
  • Evrim Fer, University of Arizona

Özet

2020 BioHackathon’u, var olan varyant tespit etme iş akışlarının COVID-19 için geliştirilmesi veya üretilen büyük miktardaki verinin analiz edilebilmesi için yeni iş akışları oluşturulmasına ev sahipliği yapmıştır. Bunlardan bazıları Galaxy Project, INSaFLU ve nf-core’dur. Bu iş akışları yeni nesil dizileme teknolojisi ile dizilenen genom verisini analiz eder ve anotasyonu yapılmış tek nükleotid polimorfizm (SNP) ve kısa ekle-sil (indel) varyantlarını çıktı olarak verir. Kullandıkları algoritmalara göre farklı avantaj ve dezavantajları vardır. Bu çalışmada Galaxy Project tarafından yayımlanmış SARS-CoV-2 genom varyantlarını INSaFLU iş akışıyla belirlenen varyantlarla karşılaştırmayı, böylece bu iki iş akışının performanslarını değerlendirebilmeyi amaçladık. Sonuç olarak iki iş akışı tarafından ortak olarak bulunan 600’e yakın varyant bulduk. Bu varyantların neredeyse yarısının replikaz poliprotein 1ab’de olduğunu tespit ettik. Ortak olarak bulunan varyantlarda non-synonymous varyantların synonymous varyantlardan fazla olduğu gördük. Çalışmada tespit edilen ortak ve özgün varyantlar ileriki araştırmalarda daha detaylı incelenebilir.

Tarih: 21 Haziran 2020 – 20:00 (GMT+3)

Dil: Türkçe

Aşağıdaki linkten webinara kayıt olabilirsiniz:

https://www.bigmarker.com/bioinfonet/INSaFLU-ve-galaxyproject-ile-SARSCoV2-varyantlarinin-karsilastirilmasi

Phylogenetic Analysis of SARS-CoV-2 Genomes in Turkey – Aylin Bircan

Presenter

Aylin Bircan

Aylin Bircan received my BSc degree in Chemistry from Koc University in 2012. She worked in Quality Control and Assurance departments of several pharmaceutical companies. In 2018 she received my MSc degree in Computational Biology and Bioinformatics from Kadir Has University. Since 2018 September, she has been a Ph.D. student in Molecular Biology, Genetics and Bioengineering program at Sabanci University. she has been working on phylogenetic analysis of Class C GPCRs under the supervision of Dr. Ogün Adebali.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged in Wuhan, and spread across the continents, and caused the COVID-19 pandemic. In this talk, I will talk about our recent study which focuses on comprehensive genomic analysis of the virus isolates in Turkey. We built a phylogenetic tree with globally obtained 15,277 severe SARS-CoV-2 genomes, and clustered the virus isolates based on the phylogenetic tree and previously annotated classification methods. We performed a phylogenetic analysis of the first thirty SARS-CoV-2 genomes isolated and sequenced in Turkey to identify specific groups circulating in the country. Our results suggest that the first introduction of the virus to the country is earlier than the first reported case of infection. Virus genomes isolated from Turkey are scattered among most types in the phylogenetic tree. Two of the seventeen sub-clusters were found enriched with the isolates of Turkey, which possibly have spread expansively in the country. Finally, we traced virus genomes based on heir phylogenetic placements. This analysis suggested multiple independent international introductions of the virus and revealed a hub for the inland transmission.

Date: June 17th, 2020 – 2:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:
https://www.bigmarker.com/bioinfonet/Phylogenetic-Analysis-of-SARS-CoV-2-Genomes-in-Turkey

Accessing Multi-omics Data for the Purposes of Tumour Profiling – Aashil A. Batavia

Presenter

Aashil A. Batavia

Aashil Batavia received his undergraduate degree from the University of Manchester obtaining a B.Sc. in Biomedical Sciences in 2014. During his dissertation, he implemented in silico experimental evolution to gain insights into the relationship between mutation rate plasticity, evolvability and robustness; exposing him to computational approaches for biomedical research for the first time. In 2015, he elected to return to the University of Manchester where he obtained an M.Sc in Bioinformatics and Systems Biology. Here he completed two research projects, one of which assessed the impact of human variants on the structure and function of Prpf8; mutations in which have been shown to cause retinitis pigmentosa. This work paved the way for his move to Switzerland in 2017 where he would begin his PhD at the Institute of Pathology and Molecular Pathology, USZ and the Department of Biosystems Science and Engineering, ETH Zurich. With a foot in both the computational and experimental worlds, his current work is focused on the multi-omics assessment of a rare form of renal cell carcinoma termed wild-type von Hippel-Lindau (wtVHL) clear cell renal cell carcinoma.

Abstract

Cancers are a very complex and heterogeneous set of diseases and therefore, cancer research is by no means trivial. The greater our understanding of the molecular landscape of a particular tumour type the better equipped we will become to combat its growth and spread. Publicly available multi-omic datasets provide a valuable resource to further this understanding. These data sets are commonly used for the identification of novel areas of study, the validation of results and the benchmarking/assessment of novel statistical methods. The Cancer Genome Atlas (TCGA) provides one such dataset with its repository consisting of 11,000 patients across 33 cancer types. This rich resource assists research on both a tumour specific and pan-cancer setting. In this webinar, I will introduce the various ways of accessing The Cancer Genome Atlas repository, navigating the multiple data types available and the tools I use for the multi-omics assessment (single and integrated) of my tumours of interest; renal cell carcinomas.

Date: May 5th, 2020 – 3:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:
https://www.bigmarker.com/bioinfonet/Accessing-Multi-omics-Data-for-the-Purposes-of-Tumour-Profiling

Molecular Simulations as an in silico Experiment – Seyit Kale

Presenter

Seyit Kale

Seyit Kale received his Bachelor of Science in Physics from İhsan Doğramacı Bilkent University in 2006, and his Ph.D. in Biophysics and Structural Biology from Brandeis University in 2012. He continued his postdoctoral studies at the University of Chicago, developing methods for computational chemistry. Later in 2015, he became a visiting fellow at the National Institutes of Health in Bethesda, Maryland, where he developed and pursued an interest in the physics of chromatin and epigenetics. He joined Izmir Biomedicine and Genome Center in late 2019 as a research group leader where he is currently running a lab in computational biophysics.

Abstract

Structural studies in biology provide invaluable insights into how molecular machines inside our cells look like, yet the stories are often far from over. The set of atomic coordinates of a macromolecule is like a picture: it’s worth a thousand words. Then again, a picture lacks the temporal information which underlies the dynamic personalities of the molecule. Over the last several decades, exponential growth in computing power drew increasingly more physical scientists toward questions of life sciences. Faster algorithms and more accurate interaction potentials have been developed to propagate the Newtonian equations of motion in length- and timescales relatable to biological phenomena. In this lecture, I will discuss an often frowned upon analogy, i.e., how a molecular simulation can be thought of as an in silico experiment, by providing a historical and physical perspective.

Date: March 5th, 2020 – 5:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:
https://www.bigmarker.com/bioinfonet/Molecular-Simulations-as-an-in-silico-Experiment

RSG-Turkey is a member of The International Society for Computational Biology (ISCB) Student Council (SC) Regional Student Groups (RSG). We are a non-profit community composed of early career researchers interested in computational biology and bioinformatics.

Contact: turkey.rsg@gmail.com

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