Enhancing capacity for next generation sequencing (NGS ......Diagnostic mutation detection using...

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Enhancing capacity for next generation sequencing (NGS) and genomics in health, agricultural, ecological and environmental applications in Kazakhstan A Newton-Al-Farabi Partnership Programme Researcher links workshop September 20 th -23 rd 2016 Hotel Grand Voyage, Almaty, Kazakhstan Organised by School of Biology, Univeristy of Leeds, UK & Institute of Microbiology & Virology, Almaty, Kazakhstan

Transcript of Enhancing capacity for next generation sequencing (NGS ......Diagnostic mutation detection using...

Page 1: Enhancing capacity for next generation sequencing (NGS ......Diagnostic mutation detection using Next Generation Sequencing for healthcare in the UK 12.20-12.50 Ms Morag Taylor (St

Enhancing capacity for next generation

sequencing (NGS) and genomics in health,

agricultural, ecological and environmental

applications in Kazakhstan

A Newton-Al-Farabi Partnership Programme Researcher links

workshop

September 20th-23rd 2016

Hotel Grand Voyage, Almaty, Kazakhstan

Organised by School of Biology, Univeristy of Leeds, UK &

Institute of Microbiology & Virology, Almaty, Kazakhstan

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Workshop Overview

Next generation sequencing and genomics are technologies that have developed at an

astonishing rate in recent years. They have become fundamental to health research and

diagnostics, including genetic disease and cancer, infectious disease, bacterial drug resistance

and personalised drug treatments for patients. It is also central to many areas of agricultural,

ecological and environmental research and diagnostics. This workshop will bring together UK

researchers using NGS and genomics in different fields, with Kazakh scientists with the aim of

fostering links that will help enhance their capability to apply this new technology in their own

work, to identify new opportunities for collaborative research projects between the UK and

Kazakhstan and to promote career development of young scientists. Overall we hope this will

promote the ability of Kazakh scientists to apply cutting edge NGS/genomics techniques in

health care, agricultural and environmental endeavours and support new biotechnology

enterprises.

https://goodmanlab.org/research/workshops-meetings/next-generation-sequencing-

researcher-links-workshop-almaty-kazakhstan-september-18th-24th-2016/

Workshop #tag: #AlmatyNGS2016

Dr Simon Goodman School of Biology University of Leeds Woodhouse Lane Leeds LS2 9JT UK

Dr Kobey Karamendin Institute of Microbiology and Virology 103 Bogenbai batyr str. Almaty, 050010 Kazakhstan

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Programme

Mon 19th September

Registration from 17.00 to 19.00

Tues 20th September

09.00-10.00 Registration

10.00-10.10 Opening remarks

10.10-11.00 Plenary Dr Aynur Akilzhanova (Nazarbayev University) Genomic research in Kazakhstan: Challenges and opportunities for clinical applications

11.00-11.30 Coffee break

11.30-12.20 Plenary Dr Ian Carr (St James’s Hospital, University of Leeds) Diagnostic mutation detection using Next Generation Sequencing for healthcare in the UK

12.20-12.50 Ms Morag Taylor (St James’s Hospital, University of Leeds) The Role of Next Generation Sequencing in colorectal cancer research

12.50-14.00 Lunch

14.00-14.20 Dr Saule Rakhimova (Nazarbayev University) Transcriptome profiling of oesophageal cancer: from sampling to sequencing on HiSeq2000

14.20-14.40 Dr Ulykbek Kairov (Nazarbayev University) Meta-analysis of cancer transcriptome profiles using an independent components method

14.40-15.00 Dr Ulykbek Kairov (Nazarbayev University) Analysis of human whole-transcriptome sequencing data from Illumina HiSeq2000 platform

15.00-15.20 Dr Niamh Forde (Faculty of Medicine, University of Leeds) Using β€˜Omics’ to understand successful early pregnancy events in cattle: The perspective of a reproductive biologist

15.20-16.00 Coffee break

16.00-17.00 Vladislav Govorkovskiy (Illumina, CIS) Application of Illumina NGS-technologies in healthcare, research and agriculture

Overview of NGS technologies and panel discussion on NGS equipment/sequencing platforms Chaired by Ian Carr (St James’s Hospital, University of Leeds)

17.30-19.00 Poster session and speed networking

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Weds 21st September

09.30-10.20 Plenary Dr Mary O’Connell (School of Biology, University of Leeds) Comparative genomics and Mechanisms of protein evolution

10.20-10.40 Dr Antonia Ford (School of Biological Sciences, University of Bangor) Genomic characterisation of wild tilapia populations

10.40-11.00 Ms Jennifer Stockdale (School of Biosciences, University of Cardiff) Hungry for more: Utilising Next Generation Sequencing to determine the dietary range of different species

11.00-11.30 Coffee break

11.30-11.50 Dr Elizabeth Duncan (School of Biology, University of Leeds) Understanding the molecular mechanisms of gene-environment interactions in insects

11.50-12.10 Dr Helen Hipperson (NERC Biomolecular Analysis Facility, University of Sheffield) Identifying genes affecting both adaptive divergence and reproductive isolation in Howea palms from Lord Howe Island using RNA-Seq

12.10-12.30 Dr Askhat Molkenov (Nazarbayev University) Peculiarities of bioinformatics processing and data conversion from Illumina HiSeq2000

12.30-12.50 Dr Deborah Dawson (NERC Biomolecular Analysis Facility, University of Sheffield) Support for biomolecular studies of the natural environment in the UK

12.50-14.00 Lunch

14.00-15.30 Discussion panel – designing and troubleshooting NGS projects Chaired by Morag Taylor (St James’s Hospital, University of Leeds)

15.30-16.00 Coffee break

16.00-17.00 Discussion panel – designing and troubleshooting NGS projects continued

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Thurs 22nd September

09.30-10.20 Plenary Dr Chris Knight (Faculty of Life Sciences, University of Manchester) Testing evolutionary mechanisms: mutation in microbes and more

10.20-10.40 Dr Saule Daugalieva (Institute of Microbiology and Virology) NGS 16S sequencing for microbial identification

10.40-11.00 Raushan Nugmanova (National Center for Biotechnology) Study of mutation clusters in bacteria using Ion Torrent sequencing

11.00-11.30 Coffee break

11.30-11.50 Dr Jenny Dunn (Royal Society for Protection of Birds) Using next-generation sequencing to examine co-infection and environmental parasite transmission

11.50-12.10 Dr Alexander Shevtsov (National Center for Biotechnology) NGS sequencing of veterinary pathogens

12.10-12.30 Dr Aizhan Turmagambetova (Institute of Microbiology and Virology) NGS for ecological research applications: macrophages profiling in Kazakhstan lakes

12.30-12.50 Dr Kobey Karamendin (Institute of Microbiology and Virology) NGS 16S sequencing of necropsy material from Saiga antelope after a mass die-off in Spring 2015

12.50-14.00 Lunch

14.00-15.30 NGS bioinformatics & data analysis resources and pipelines: Overview, demonstrations and panel discussion Chaired by Helen Hipperson (NERC Biomolecular Analysis Facility, University of Sheffield)

15.30-16.00 Coffee break

16.00-17.00 Bioinformatics discussion continued

19.00-23.00 Conference dinner

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Fri 23rd September

09.30-10.00 Rowan Kennedy (Newton-Al Farabi Partnership Programme) UK-Kazakhstan research funding opportunities

10.00-10.30 Dr Simon Goodman (School of Biology, University of Leeds) Overview of research structure, funding and career development in the UK

10.30-11.00 Coffee break

11.00-12.00 Break out groups - Identification of research priorities and collaboration opportunities for UK-Kazakh researchers

12.00-12.30 Report of break out groups and closing remarks

12.30-14.00 Lunch

Departures

Posters

Author Title

Ulan Kozhamkulov Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan

Whole genome sequencing of clinical isolates of M.tuberculosis with a different drug sensitivity profile on the Roche 454 GS FLX + platform

Ainur Akhmetova Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan

Creating a HaloPlex cardiogenetic panel and preparation of DNA libraries for the targeted sequencing of patients with arrhythmias

Nurlan Torokeldiev Medical School of the International Ala-Too University in Bishkek

Pattern of genetic variation, fine-scale genetic structure and footprints of natural selection in populations of Juglans regia L. in the southern Kyrgyz Republic

Vladislav Govorkovskiy Illumina representative, Belarus

Poster about NGS technology

Vladislav Govorkovskiy Illumina representative, Belarus

Poster about production

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Abstracts

Dr Ian M. Carr, St James’s University Hospital, University of Leeds, UK

Diagnostic mutation detection using Next Generation Sequencing

Next generation sequencing (NGS) is a relatively new technology that can quickly and cheaply

generate huge amounts of sequence data. Consequently, it has rapidly found a wide range of

applications in both basic and translational research. These application range from de novo genome

assembly of large eukaryotic genomes to amplicon sequencing of huge cohorts. NGS also promises to

revolutionise diagnostic testing where it may prove cheaper than current testing methodologies, allow

the testing of low quality samples or allow the development of completely novel diagnostic tests.

In the UK, NGS technologies are seen as the future of many DNA based testing methodologies. The

Yorkshire Regional DNA Laboratory, in Leeds, was one of the first to offer NGS based diagnoses' and

has reported on over 6,000 cases. Currently, the Yorkshire Regional DNA Laboratory uses a range of

methodologies to identify mutations ranging from single base substitutions to large structural

rearrangements. I will discuss these advances in light of the population demographics in the Yorkshire

region and how the new tests are implemented alongside current best practises that it may either

replace or augment.

Dr Deborah Dawson, NERC NBAF Centre, University of Sheffield, UK

Support for biomolecular studies of the natural environment in the UK

In the UK, support is provided for molecular studies of the natural environment by the NERC

Biomolecular Analysis Facility. The Facility provides access to high-level genomics, metabolomics and

bioinformatics through its four nodes at Sheffield, Edinburgh, Liverpool and Birmingham.

The Facility offers the very latest, class-leading technologies, including next-generation sequencing

(Illumina and Pacific Biosciences), SNP genotyping, and high resolution MS and NMR metabolomic

platforms. Applications include de novo sequencing, metagenomics, epigenetics, sequence-capture,

sequencing-based genotyping and expression profiling (RNAseq, oligoarrays and NanoString). The

Facility also supports metabolomics, medium-scale genotyping, bioinformatics and advanced data

analysis techniques (genome and transcriptome assembly and annotation, expression analysis, etc.).

Each node takes the lead in providing support in one area. At Sheffield, access is provided to laboratory

facilities, equipment, training and expertise. The main call is for the development and application of

genetic markers for use in population genetics and behavioural ecology. We also support various other

techniques, including metabarcoding for genetic studies of diet. The service at Sheffield is based on a

well-proven arrangement, in which researchers visit the laboratory to complete their own analyses

under the supervision of someone experienced in the required technology. In most cases, the majority

of the bench work will be carried out by visitors to the Facility under the supervision of Facility staff.

Training is provided, as appropriate.

The Facility has supported over 200 projects and 150 PhD students. Our users have published over

300 publications from Facility-supported studies, including large numbers in high-ranking journals

such as Nature and Science.

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Dr Elizabeth J. Duncan, School of Biology, Faculty of Biological Sciences, University of Leeds, UK

Understanding the molecular mechanisms of gene-environment interactions in insects.

The phenotype of a plant or animal is dependent on interactions between their genes and the

environment. Some plants and animals are even able to generate markedly different phenotypes in

response to a change in the environment, a phenomenon known as phenotypic plasticity.

Using the honeybee (Apis mellifera) and the pea aphid (Acyrthosiphon pisum) we have a developed

an analysis pipeline to begin to understand the molecular basis of how these gene-environment

interactions occur.

The honeybee and pea aphid both change the way they reproduce in response to changes in the

environment. In the honeybee hive only one female, the queen, usually reproduces. If the queen and

her pheromone are lost from the hive this triggers the normally sterile worker bees to become

reproductively active. Using a combination of techniques including RNA-seq to measure gene

expression and immunohistochemistry to determine which cell types in the ovary are affected we

have isolated a conserved signalling pathway as key to this process, Notch signalling. Among other

roles, Notch signalling has a key function in forming and maintaining stem cell niches and I propose

that these niches are key to gene-environment responses.

Epigenetic mechanisms, such as DNA methylation and histone modifications, also play a role in altering

the way animals respond to their environment and may also regulate stem-cell niches. To investigate

the role of epigenetic mechanisms in regulating the gene-environment interactions seen in the

honeybee I have used chromatin immunoprecipitation-sequencing (to investigate a particular histone

modification) and whole genome bisulphite sequencing to determine methylation patterns across the

genome.

Ultimately I aim to determine if there are conserved signalling pathways or regulatory networks that

control plasticity amongst diverse animals. Using these relatively simple and tractable systems to

understand the mechanisms of plasticity will allow us to understand, at a whole-organism level, how

animals are responding to their environment.

Jenny C. Dunn1, Rebecca C. Thomas2, Helen Hipperson3, Keith C. Hamer2 & Simon J. Goodman2

1 RSPB Centre for Conservation Science, Royal Society for the Protection of Birds, The Lodge, Potton

Road, Sandy, Bedfordshire, SG19 2DL, UK

2 School of Biology, Irene Manton Building, University of Leeds, Leeds. LS2 9JT, UK

3 NERC Biomolecular Analysis Facility, Department of Animal and Plant Sciences, University of

Sheffield, Western Bank, Sheffield, S10 2TN, UK

Using next-generation sequencing to examine co-infection and environmental parasite transmission

Co-infection with different parasites or multiple strains of the same parasite species is common in

natural systems and has implications for disease ecology and epidemiology. Traditional methods using

PCR either detect the dominant strain or return convoluted results from Sanger sequencing. Next-

generation sequencing (NGS) provides the opportunity to detect multiple strains of parasite

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simultaneously from single samples, either from individuals or the environment. Here, I will describe

the application of NGS for parasite strain identification in a declining species of migratory bird, the

European Turtle Dove Streptopelia turtur. We screened blood samples and oral swabs for

haemoparasites and Trichomonas gallinae respectively, examining a single gene region (cytochrome

b) for haemoparasites, and two gene regions (ITS and FeDH) for Trichomonas gallinae. I will discuss

the laboratory methods and the bioinformatics analysis used, and discuss the applications of the

results in the context of ecology and conservation.

Dr Antonia G P Ford, School of Biological Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW,

UK

Genomic characterisation of wild tilapia populations

Tilapia cichlid fish, and particularly the genus Oreochromis, are a mainstay of tropical aquaculture.

While most focus has been on strains of Nile tilapia (Oreochromis niloticus), several aquaculture

populations make use of hybrid lines and the ready hybridization of Oreochromis species. Future strain

enhancement may further benefit from the availability of additional wild genetic resources, which

have previously been used to enhance growth, environmental tolerance, control sex ratios, and

introduce genetic resistance to disease. However, existing native wild populations are frequently

poorly characterised and threatened by invasive tilapia species. Here, I will discuss an ongoing project

aiming to characterise wild populations of Oreochromis tilapia across a region of high cichlid

biodiversity, Tanzania, East Africa. Several introduced aquaculture tilapia species are found in wild

populations throughout Tanzania, where they are thought to compete with and hybridise with native

species. The project uses next generation sequencing (Illumina HiSeq) and SNP genotyping (Agena) to

survey wild populations to examine the extent and nature of introgression.

Dr Niamh Forde, Division of Reproduction and Early Development, Leeds Institute of Cardiovascular

and Metabolic Medicine, School of Medicine, University of Leeds, UK

Using β€˜Omics’ to understand successful early pregnancy events in cattle: The perspective of a

reproductive biologist.

In most mammalian species studied, the majority of pregnancy loss occurs in the first three weeks of

pregnancy. A large proportion of this loss can be attributed to asynchrony between the embryo and

the endometrium and or dysregulation of the uterine environment. A number of key events are

required to support successful early pregnancy in cattle. Specifically, an adequate post-ovulatory rise

in the hormone progesterone (P4) in circulation which to alter the endometrial transcriptome, an

appropriate uterine environment with the secretions required to drive embryo development as well

as appropriate pregnancy recognition signalling by the conceptus to the endometrium to maintain P4

concentrations in circulation and to establish uterine receptivity to implantation. The focus of my talk

will be on how we utelised β€˜omic’ technologies to understand how the hormone progesterone alters

the ability of the uterus to support successful early pregnancy. In addition, I will demonstrate how

using RNA sequencing technologies helped us to identify an earlier pregnancy recognition response to

an embryo in the endometrium and proposed some biomarkers of early pregnancy in cattle. I will also

demonstrate how we have used RNA sequencing to look at how the metabolic environment of the

mother can have an impact on the transcriptome of lots of different reproductive tissues. Finally, I will

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sum up the limitations and the pitfalls of using these types of technologies to address your biological

question.

Helen Hipperson, LT Dunning, WJ Baker, RK Butlin, C Devaux, I Hutton, J Igea, AST Papadopulos, X Quan, CM Smadja, CGN Turnbull, TC Wilson, VS Savolainen

NERC NBAF Centre, University of Sheffield, UK

Identifying genes affecting both adaptive divergence and reproductive isolation in Howea palms from Lord Howe Island using RNA-Seq

Howea belmoreana and Howea forsteriana are sister species of palm, both endemic to Lord Howe Island (LHI; located in the Tasman Sea between Australia and New Zealand) where they have diverged in sympatry. Originally composed solely of volcanic substrate, the deposition of calcareous soil on LHI is thought to have led to ecological speciation. Currently, H. belmoreana adults are restricted to volcanic soils whilst H. forsteriana is also found on the younger calcarenite soil. There are several ecological differences between these habitats; the calcareous soils are dryer, have higher pH, and have increased salinity compared to volcanic soil. The species are largely reproductively isolated with a five week difference in peak flowering time between them, both in the wild and when cultivated in a common garden. Differences in the peak flowering times are also maintained regardless of the soil type that H. forsteriana occurs on. Genes that have a dual role in controlling ecological adaptation and flowering time may have played a direct role in Howea speciation. To characterise such pleiotropic genes we first used RNA-Seq to identify differentially expressed genes between the Howea species using three tissue types (floral, leaf and root) sampled from 36 trees distributed across LHI. We also examined loci with divergent coding sequences. From both analyses we identified 16 candidate genes that were associated with ecological differences between the species and/or flowering time divergence, and examined the effect that eight of these genes have on flowering time in Arabidopsis knockout mutants. Finally, we put forward six plausible ecological speciation loci, providing support for the hypothesis that pleiotropy could help to overcome the antagonism between selection and recombination during speciation with gene flow.

Dr Mary O’Connell, School of Biology, Faculty of Biological Sciences, University of Leeds, UK

Comparative genomics and Mechanisms of protein evolution

The relationship between sequence and function has proven difficult to fully elucidate but it is key to

understanding what makes a species unique. Here I will describe how we can help to bridge the gaps

in our understanding of the relationships (i) between species and (ii) between genotype and

phenotype, by adequately modelling major patterns in genomic sequence data. I will present results

from a small selection of large-scale comparative genomics studies and I will describe our approach

for identifying the evolution of species-specific proteins/protein functions using genome-scale data

and computational evolutionary models. Taking an applied evolutionary approach to modelling may

provide us with an increased understanding of species-specific response to disease/drugs at the

molecular level.

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Dr Chris Knight, Faculty of Life Sciences, University of Manchester

Testing evolutionary mechanisms: mutation in microbes and more

Tackling major global challenges, such as the rise in antimicrobial resistance, requires a focus on the

fundamental evolutionary processes that underlie them. We are experimentally testing the

spontaneous evolution of antibiotic resistance in different microbes. Mutation rates have been

measured using phenotypic markers, including antibiotic resistances, for over 70 years. We find

patterns in this data suggesting that dense populations may evolve resistance at a lower rate than

sparse populations. Manipulating population densities in the laboratory, in either bacteria or yeast,

we can modify the mutation rate to several different antibiotic resistances by over an order of

magnitude. We find that this β€˜density associated mutation rate plasticity’ (DAMP) requires an

evolutionarily ancient mutation avoidance mechanism, but is modified or mediated in particular

lineages, including by cell-cell interactions with the surrounding community. The next level is

therefore to consider the evolution of mixed microbial communities. We are considering both

experimental (mouse gut) and broader microbial meta-genetic data (soil communities), where we are

using novel approaches to distinguish the biologically interesting signals from a range of technical

confounders. Through a combination of modelling approaches and next generation sequence data we

are gaining a closer connection between our understandings of genotypic change, phenotype and

ecology. This will contribute to addressing major issues, including antimicrobial resistance, but at the

same time help shed new, molecular, light on classically understood evolutionary processes.

Jennifer Stockdale1, Jenny Dunn1,2, Joanna Redihough1, Helen Hipperson3, William Symondson1

1Cardiff University School of Biosciences, Sir Martin Evans Building, Museum Avenue, Cardiff, CF10

3AX.

2RSPB Centre for Conservation Science, The Lodge, Sandy, Bedfordshire. SG19 2DL

3 NERC Biomolecular Analysis Facility, Department of Animal and Plant Sciences, University of

Sheffield, Western Bank, Sheffield, S10 2TN, UK

Hungry for more: Utilising next generation sequencing to determine the dietary range of different

species.

Next generation sequencing (NGS) is increasingly being used to look at the complete dietary range of

species. To date, there have been ecological analyses using molecular scatology to study the diets of

killer whales and leopards at one end of the spectrum, with specialist termite-eating spiders at the

other. Molecular analyses consequently tend to be replacing more traditional techniques of

morphological analysis of faecal samples, stomach flushing, nest cameras and direct observation to

identify dietary components. At Cardiff University we are using NGS to determine the dietary ranges

of invertebrates and vertebrates in both temperature and tropical habitats. I will discuss three

ongoing projects examining diets of the Common Crane (which eats invertebrates and plants),

thrushes in farmland (which eat invertebrates), and the European Turtle Dove (which eats plant

seeds). Work on the recently reintroduced Common Crane to the Somerset levels will provide new

insight into Eurasian Crane diet, which may aid any potential future reintroductions and will help to

sustain these birds in Britain. NGS is also being used to monitor the diets of thrushes in farmland

landscapes of different complexity enabling us to link the prey found in their faeces with the use of

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landscape elements (arable field, woodland etc.). Finally, we have been able to determine implications

of diet for Turtle Dove body condition, consider changes in diet over time and usage of bespoke habitat

management options with implications for conservation management.

Morag Taylor, Susan Richman, Tim Palmer, Henry Wood, Caroline Young, Phil Quirke

St James’s University Hospital, University of Leeds, UK

The Role of Next Generation Sequencing in Colorectal Cancer Research

In the United Kingdom (UK), colorectal cancer (CRC) is the fourth most common cancer, and the

second most common cause of cancer related deaths. It’s important to understand both the

prognostic and predictive markers of CRC to improve these statistics. The advent of next generation

sequencing (NGS) is allowing us to explore tumour profiling and mutation screening in new ways,

advancing the role of molecular pathology.

We are part of several multicentre clinical trials investigating CRC biomarkers to determine patient

treatment. Until now, we have favoured the lower cost sequencing alternatives, but with the

continuing reduction in sequencing costs, and the need to adapt assays quickly whilst keeping

technical time down, we are developing a pipeline to move our clinical trials to NGS.

We have investigated genomic heterogeneity in CRC. Using copy number variation data from NGS, we

have analysed the primary tumours and all distant metastases from eight patients who died of

advanced CRC. We generated phylogenetic trees for each patient to follow the evolution of the

disease.

The human microbiome has been studied for many years, but NGS has made this study area more

accessible. It has allowed for the identification of bacteria that were previously un-culturable. Studies

have shown the gut microbiome plays a role in CRC, but as yet, this isn’t fully understood. In order to

investigate this, we are developing a pipeline to study the human microbiome isolated from guaiac

faecal occult blood test cards, used worldwide to screen for CRC. We will follow this by doing a UK

study to investigate if the microbiome can be used as a future tool to predict CRC using 16s rRNA

sequencing on an Illumina MiSeq.

Ainur Akilzhanova

Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan

Genomic research in Kazakhstan: challenges and opportunities for clinical applications

Technological advancements are rapidly propelling the field of genome research forward. Advances in genetics and genomics such as the sequence of the human genome, the human haplotype map, open access databases, cheaper genotyping and chemical genomics have already transformed basic and translational biomedical research. At the National Laboratory Astana (NLA), Center for Life Sciences, Nazarbayev University several projects in the field of genomic and personalized medicine are conducting. The prioritized areas of research include genomics of multifactorial diseases, cancer genomics, bioinformatics, genetics of infectious diseases and population genomics. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer

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diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine.

Kazakhstan is a unique country located in the middle of Central Asia, laying on the ancient Great Silk road. Kazakh populations have been strongly influenced by the nomadic lifestyle, and a long history of migration has led to admixture of western and Asian populations, which has molded the genetic architecture. Thus it is crucial to understand the genetic background of ethnic Kazakhs to properly investigate the genetic basis of common diseases or traits in Kazakh populations. To develop a personalized medicine program for Kazakhstan, we first need acquire personal genomic data for Kazakhs. To do so, we need a core of scientists who can: (1) design proper studies; (2) diagnose accurately; (3) sequence efficiently (using multiomic technologies); (4) analyze and maintain massive sequence data; (5) analyze the relations between genetic variants and phenotypes (i.e., disease status or biomarkers.

To further develop genomic and biomedical projects at NLA and in Kazakhstan the development of bioinformatics research and infrastructure is essential, as well as establishment of new collaborations in this field.

Widespread use of genetic tools will allow the identification of diseases before the onset of clinical symptoms, the individualization of drug treatment, and could induce individual behavioral changes on the basis of calculated disease risk. However, many challenges remain for the successful translation of genomic knowledge and technologies into health advances, such as medicines and diagnostics.

It is important to integrate research and education in the fields of genomics, personalized medicine and bioinformatics which will be possible with opening of new Medical Faculty in Nazarbayev University. Educating both those in practice and those in training about key concepts of genomics and, importantly, engaging them in the design of how this knowledge will be applied most effectively will rapidly bring the era of genomic medicine to patient care, resulting in improved health. And all of this must be based on good research and scientific platform which requires development of well-equipped modern laboratories, bioinformatics, qualified trained physicians and laboratory staff and understanding policy among population of the country.

Π“Π΅Π½ΠΎΠΌΠ½Ρ‹Π΅ исслСдования Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅: ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΡ‹ ΠΈ возмоТности для клиничСских ΠΏΡ€ΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ

ВСхнологичСскиС достиТСния послСдних дСсятилСтий ΠΏΡ€ΠΎΠ΄Π²ΠΈΠ½ΡƒΠ»ΠΈ ΠΎΠ±Π»Π°ΡΡ‚ΡŒ Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΎΠΌΠ½Ρ‹Ρ… исслСдований Π²ΠΏΠ΅Ρ€Π΅Π΄. ДостиТСния Π² области Π³Π΅Π½Π΅Ρ‚ΠΈΠΊΠΈ ΠΈ Π³Π΅Π½ΠΎΠΌΠΈΠΊΠΈ, Ρ‚Π°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ Π³Π΅Π½ΠΎΠΌΠ° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°, ΠΊΠ°Ρ€Ρ‚Ρ‹ Π³Π°ΠΏΠ»ΠΎΡ‚ΠΈΠΏΠΎΠ² Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°, Π±Π°Π·Ρ‹ Π΄Π°Π½Π½Ρ‹Ρ… ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚ΠΎΠ³ΠΎ доступа, ΡƒΠ΄Π΅ΡˆΠ΅Π²Π»Π΅Π½ΠΈΠ΅ гСнотипирования ΠΈ химичСской Π³Π΅Π½ΠΎΠΌΠΈΠΊΠΈ ΡƒΠΆΠ΅ трансформировали Ρ„ΡƒΠ½Π΄Π°ΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Π΅ ΠΈ трансляционныС биомСдицинскиС исслСдования. Π’ National Laboratory Astana (NLA), Π¦Π΅Π½Ρ‚Ρ€Π΅ Π½Π°ΡƒΠΊ ΠΎ ΠΆΠΈΠ·Π½ΠΈ НазарбаСв УнивСрситСта Ρ€Π΅Π°Π»ΠΈΠ·ΡƒΡŽΡ‚ΡΡ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Ρ‹ Π² области Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠΉ ΠΈ пСрсонализированной ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹. ΠŸΡ€ΠΈΠΎΡ€ΠΈΡ‚Π΅Ρ‚Π½Ρ‹Π΅ направлСния исслСдований: Π³Π΅Π½ΠΎΠΌΠΈΠΊΠ° ΠΌΠ½ΠΎΠ³ΠΎΡ„Π°ΠΊΡ‚ΠΎΡ€Π½Ρ‹Ρ… Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ, Ρ€Π°ΠΊΠ°, Π±ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠ° ΠΈ Π²Ρ‹Ρ‡ΠΈΡΠ»ΠΈΡ‚Π΅Π»ΡŒΠ½Π°Ρ систСмная биология, Π³Π΅Π½Π΅Ρ‚ΠΈΠΊΠ° ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ ΠΈ популяционная Π³Π΅Π½ΠΎΠΌΠΈΠΊΠ°, ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΎΠΌΠ½Ρ‹Π΅ исслСдования, Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ° ΠΈ Π²Π½Π΅Π΄Ρ€Π΅Π½ΠΈΠ΅ NGS ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π² ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΡƒ. Π’ настоящСС врСмя ΠΎΡ†Π΅Π½ΠΊΠ° риска ΠΎΠ±Ρ‰ΠΈΡ… слоТных Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ Π½Π° основС изучСния Π”ΠΠš, ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ молСкулярных сигнатур для диагностики ΠΈ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π° Ρ€Π°ΠΊΠ°, Π³Π΅Π½ΠΎΠΌ ассоциированной Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ ΠΈ ΠΏΠΎΠ΄Π±ΠΎΡ€Π΅ Π΄ΠΎΠ·Ρ‹ тСрапСвтичСских ΠΏΡ€Π΅ΠΏΠ°Ρ€Π°Ρ‚ΠΎΠ² ΡΠ²Π»ΡΡŽΡ‚ΡΡ Π²Π°ΠΆΠ½Ρ‹ΠΌΠΈ вопросами пСрсонализированной ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹.

Page 14: Enhancing capacity for next generation sequencing (NGS ......Diagnostic mutation detection using Next Generation Sequencing for healthcare in the UK 12.20-12.50 Ms Morag Taylor (St

ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½ являСтся ΡƒΠ½ΠΈΠΊΠ°Π»ΡŒΠ½ΠΎΠΉ страной, располоТСнной Π² Ρ†Π΅Π½Ρ‚Ρ€Π΅ Π¦Π΅Π½Ρ‚Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ Азии, Π»Π΅ΠΆΠΈΡ‚ Π½Π° Π΄Ρ€Π΅Π²Π½Π΅ΠΌ Π’Π΅Π»ΠΈΠΊΠΎΠΌ шСлковом ΠΏΡƒΡ‚ΠΈ. ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½ΡΠΊΠΎΠ΅ насСлСниС Π±Ρ‹Π»ΠΎ ΠΏΠΎΠ΄ ΡΠΈΠ»ΡŒΠ½Ρ‹ΠΌ влияниСм ΠΊΠΎΡ‡Π΅Π²ΠΎΠ³ΠΎ ΠΎΠ±Ρ€Π°Π·Π° ΠΆΠΈΠ·Π½ΠΈ, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΈΠΌΠ΅Π΅Ρ‚ Π΄ΠΎΠ»Π³ΡƒΡŽ ΠΈΡΡ‚ΠΎΡ€ΠΈΡŽ ΠΌΠΈΠ³Ρ€Π°Ρ†ΠΈΠΈ, Ρ‡Ρ‚ΠΎ ΠΏΡ€ΠΈΠ²Π΅Π»ΠΎ ΠΊ смСси Π·Π°ΠΏΠ°Π΄Π½Ρ‹Ρ… ΠΈ азиатских популяций, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ сформировали Π³Π΅Π½Π΅Ρ‚ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ Π°Ρ€Ρ…ΠΈΡ‚Π΅ΠΊΡ‚ΡƒΡ€Ρƒ Π½Π°Ρ€ΠΎΠ΄Π°. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ, ΠΊΡ€Π°ΠΉΠ½Π΅ Π²Π°ΠΆΠ½ΠΎ, Ρ‡Ρ‚ΠΎΠ±Ρ‹ ΠΏΠΎΠ½ΡΡ‚ΡŒ гСнСтичСский Ρ„ΠΎΠ½ этничСских ΠΊΠ°Π·Π°Ρ…ΠΎΠ², Ρ‡Ρ‚ΠΎΠ±Ρ‹ Π΄ΠΎΠ»ΠΆΠ½Ρ‹ΠΌ ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚ΡŒ Π³Π΅Π½Π΅Ρ‚ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ основу ΠΎΠ±Ρ‰ΠΈΡ… Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ ΠΈΠ»ΠΈ ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² Ρƒ казахского насСлСния. Для Ρ‚ΠΎΠ³ΠΎ, Ρ‡Ρ‚ΠΎΠ±Ρ‹ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Ρ‚ΡŒ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½ΡƒΡŽ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡƒ ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹ для ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π°, ΠΌΡ‹ Π² ΠΏΠ΅Ρ€Π²ΡƒΡŽ ΠΎΡ‡Π΅Ρ€Π΅Π΄ΡŒ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎ ΠΏΠΎΠ»ΡƒΡ‡ΠΈΡ‚ΡŒ Π»ΠΈΡ‡Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ Π³Π΅Π½ΠΎΠΌΠΎΠ² казахстанцСв. Для этого Π½ΡƒΠΆΠ΅Π½ ΠΏΡƒΠ» ΡƒΡ‡Π΅Π½Ρ‹Ρ…, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚: (1) Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Ρ‚ΡŒ ΠΈ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΡ‚ΡŒ Π½Π°Π΄Π»Π΅ΠΆΠ°Ρ‰ΠΈΠ΅ исслСдования; (2) Ρ‚ΠΎΡ‡Π½ΠΎ Π΄ΠΈΠ°Π³Π½ΠΎΡΡ‚ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ; (3) эффСктивно ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡΡ‚ΡŒ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ с использованиСм ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΎΠΌΠΈΠΊΡΠ½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ; (4) Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ΠΈ ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΈΠ²Π°Ρ‚ΡŒ большиС массивы Π΄Π°Π½Π½Ρ‹Ρ… ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ; (5) Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρƒ гСнСтичСскими Π²Π°Ρ€ΠΈΠ°Π½Ρ‚Π°ΠΌΠΈ ΠΈ Ρ„Π΅Π½ΠΎΡ‚ΠΈΠΏΠ°ΠΌΠΈ (Ρ‚.Π΅. статусом заболСвания ΠΈΠ»ΠΈ Π±ΠΈΠΎΠΌΠ°Ρ€ΠΊΠ΅Ρ€Π°ΠΌΠΈ) ΠΈ др…

Π’ цСлях дальнСйшСго развития Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… ΠΈ биомСдицинских исслСдований Π² NLA ΠΈ Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅ ΠΈΠΌΠ΅Π΅Ρ‚ Π²Π°ΠΆΠ½ΠΎΠ΅ Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ инфраструктуры ΠΈ Π±ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π½Π°Π»Π°ΠΆΠΈΠ²Π°Π½ΠΈΠ΅ сотрудничСства с ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹ΠΌΠΈ лабораториями ΠΈ консорциумами Π² этой области, с ΠΊΠ»ΠΈΠ½ΠΈΠΊΠ°ΠΌΠΈ ΠΈ Π²ΡƒΠ·Π°ΠΌΠΈ ΠΈ Π½Π°ΡƒΡ‡Π½Ρ‹ΠΌΠΈ ΠΊΠΎΠ»Π»Π΅ΠΊΡ‚ΠΈΠ²Π°ΠΌΠΈ.

Π¨ΠΈΡ€ΠΎΠΊΠΎΠ΅ использованиС гСнСтичСских инструмСнтов ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ‚ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ заболСвания Π΄ΠΎ появлСния клиничСских симптомов, ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ лСкарствСнной Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ, ΠΈ ΠΌΠΎΠΆΠ΅Ρ‚ Π²Ρ‹Π·Π²Π°Ρ‚ΡŒ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½Ρ‹Π΅ повСдСнчСскиС измСнСния Π½Π° основС

расчСтного риска заболСвания. Π’Π΅ΠΌ Π½Π΅ ΠΌΠ΅Π½Π΅Π΅, ΠΌΠ½ΠΎΠ³ΠΈΠ΅ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΡ‹ ΠΎΡΡ‚Π°ΡŽΡ‚ΡΡ Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½Ρ‹ΠΌΠΈ для ΡƒΡΠΏΠ΅ΡˆΠ½ΠΎΠ³ΠΎ ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ΄Π° Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… Π·Π½Π°Π½ΠΈΠΉ, Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ ΠΈ достиТСний Π² ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΡƒ Π² области здравоохранСния.

Π’Π°ΠΆΠ½ΠΎ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΡ‚ΡŒ ΠΈΠ½Ρ‚Π΅Π³Ρ€Π°Ρ†ΠΈΡŽ Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… исслСдований ΠΈ образования Π² области Π³Π΅Π½ΠΎΠΌΠΈΠΊΠΈ, пСрсонализированной ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹ ΠΈ Π±ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ становится Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹ΠΌ с ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚ΠΈΠ΅ΠΌ Π½ΠΎΠ²ΠΎΠ³ΠΎ мСдицинского Ρ„Π°ΠΊΡƒΠ»ΡŒΡ‚Π΅Ρ‚Π° Π² НазарбаСв УнивСрситСтС. ΠžΠ±ΡƒΡ‡Π΅Π½ΠΈΠ΅ ΠΊΠ°ΠΊ Π½Π° ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΠ΅, Ρ‚Π°ΠΊ ΠΈ Π² ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠΌ процСссС ΠΊΠ»ΡŽΡ‡Π΅Π²Ρ‹ΠΌ концСпциям Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠΉ ΠΈ пСрсонализированной ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹ ΠΈ, Ρ‡Ρ‚ΠΎ Π½Π΅ΠΌΠ°Π»ΠΎΠ²Π°ΠΆΠ½ΠΎ, Π²ΠΎΠ²Π»Π΅Ρ‡Π΅Π½ΠΈΠ΅ Π² Π΄ΠΈΠ·Π°ΠΉΠ½, ΠΊΠ°ΠΊ это Π·Π½Π°Π½ΠΈΠ΅ Π±ΡƒΠ΄Π΅Ρ‚ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ эффСктивно ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΡ‚ΡŒΡΡ Π² клиничСской ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΠ΅, ΠΌΠΎΠ³ΡƒΡ‚ ΡΠΏΠΎΡΠΎΠ±ΡΡ‚Π²ΠΎΠ²Π°Ρ‚ΡŒ Π±ΠΎΠ»Π΅Π΅ быстрому Π²Π½Π΅Π΄Ρ€Π΅Π½ΠΈΡŽ эры Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠΉ ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹ Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅, Ρ‡Ρ‚ΠΎ ΠΌΠΎΠΆΠ΅Ρ‚ привСсти ΠΊ ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½ΠΈΡŽ Π·Π΄ΠΎΡ€ΠΎΠ²ΡŒΡ Π½Π°Ρ€ΠΎΠ΄Π°. И всС это Π΄ΠΎΠ»ΠΆΠ½ΠΎ Π±Ρ‹Ρ‚ΡŒ основано Π½Π° Ρ…ΠΎΡ€ΠΎΡˆΠ΅ΠΉ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΡΠΊΠΎΠΉ ΠΈ Π½Π°ΡƒΡ‡Π½ΠΎΠΉ ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠ΅, которая Ρ‚Ρ€Π΅Π±ΡƒΠ΅Ρ‚ Ρ…ΠΎΡ€ΠΎΡˆΠΎ ΠΎΠ±ΠΎΡ€ΡƒΠ΄ΠΎΠ²Π°Π½Π½Ρ‹Ρ… соврСмСнных Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΉ, развития Π±ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, наличия ΠΊΠ²Π°Π»ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²Π»Π΅Π½Π½Ρ‹Ρ… Π²Ρ€Π°Ρ‡Π΅ΠΉ ΠΈ пСрсонала Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΈ, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²Π»Π΅Π½Π½ΠΎΠ³ΠΎ насСлСния страны.

Ulykbek Kairov

Laboratory of Bioinformatics and Computational Systems Biology, Center for Life Sciences,

National Laboratory Astana, Nazarbayev University

Analysis of human whole-transcriptome sequencing data from Illumina HiSeq2000 platform

The high-throughput genomic technologies and particularly Illumina HiSeq2000 next-generation

sequencing platform have a major impact on studying cancer. Illumina HiSeq2000 NGS platform

generating up to 600 GB of sequencing data per run. Huge amount of sequencing data requires

application of reproducible bioinformatics methods, mathematical and statistical approaches for

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analysis. Transcriptomic profiling of cancer specimens with Illumina HiSeq2000 NGS platform has

provided a comprehensive opportunity for in-depth investigation of gene expression and affected

molecular pathways. In our study we aimed to perform comprehensive analysis of sequencing data

from HiSeq2000 platform to identify affected molecular pathways and extract meaningful molecular

signals from oesophageal cancer specimens of Kazakhstani patients.

Анализ Π΄Π°Π½Π½Ρ‹Ρ… ΠΏΠΎΠ»Π½Ρ‹Ρ… транскриптомов с ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹ сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния

Illumina HiSeq2000.

Π’Ρ‹ΡΠΎΠΊΠΎΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Π΅ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, Π² частности, ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠ° сСквСнирования

Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния Illumina HiSeq2000, ΡΠ²Π»ΡΡŽΡ‚ΡΡ Π·Π½Π°Ρ‡ΠΈΠΌΡ‹ΠΌΠΈ Π² соврСмСнном ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠΈ

онкологичСских Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ. ΠŸΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠ° сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния Illumina HiSeq2000

Π³Π΅Π½Π΅Ρ€ΠΈΡ€ΡƒΠ΅Ρ‚ Π΄ΠΎ 600 Π“Π± Π΄Π°Π½Π½Ρ‹Ρ… Π·Π° ΠΎΠ΄ΠΈΠ½ запуск. Π“Π΅Π½Π΅Ρ€ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Π΅ ΠΎΠ³Ρ€ΠΎΠΌΠ½Ρ‹Π΅ массивы Π΄Π°Π½Π½Ρ‹Ρ… Ρ‚Ρ€Π΅Π±ΡƒΡŽΡ‚

примСнСния воспроизводимых биоинформатичСских ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² ΠΈ нСстандартных

матСматичСских ΠΈ статистичСских ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² Π°Π½Π°Π»ΠΈΠ·Π°. ВранскриптомноС ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅

ΠΎΠΏΡƒΡ…ΠΎΠ»Π΅Π²Ρ‹Ρ… ΠΎΠ±Ρ€Π°Π·Ρ†ΠΎΠ² с ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹ Illumina HiSeq2000 NGS ΠΎΡ‚ΠΊΡ€Ρ‹Π²Π°Π΅Ρ‚ Π½ΠΎΠ²Ρ‹Π΅

возмоТности ΠΌΠ°ΡΡˆΡ‚Π°Π±Π½ΠΎΠ³ΠΎ исслСдования гСнСтичСской экспрСссии ΠΈ поиска ΠΊΠ»ΡŽΡ‡Π΅Π²Ρ‹Ρ…

молСкулярных сСтСй. НашС исслСдованиС Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½ΠΎ Π½Π° ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ всСстороннСго Π°Π½Π°Π»ΠΈΠ·Π°

гСнСтичСской экспрСссии для поиска молСкулярных сигналов Π² транскриптомных профилях

казахстанских ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с Π΄ΠΈΠ°Π³Π½ΠΎΠ·ΠΎΠΌ Ρ€Π°ΠΊ ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π°.

Ulykbek Kairov

Laboratory of Bioinformatics and Computational Systems Biology, Center for Life Sciences, National

Laboratory Astana, Nazarbayev University

Meta-analysis of cancer transcriptome profiles using Independent Component Analysis

The high-throughput genomic technologies such a microarray technology and next-generation

sequencing have a major impact on studying cancer. Huge amount of genomic data requires

application of reproducible analytical approaches. In our study we demonstrated application of

Independent Component Analysis method to do meta-analysis of breast cancer gene expression data.

We identified from 7 to 8 reproducible components in all four breast cancer datasets and developed

graph-based approach to meta-analysis and interpretation of these independent components such

that each of them was associated with a small gene network. Using analysis of these networks, we

provided a tentative interpretation of stably reproducible components. Thus, we found that various

factors such as proliferation, immune response, contamination of tumor cells by lymphocytes and

normal tissues affect gene expression in breast cancer.

ΠœΠ΅Ρ‚Π°-Π°Π½Π°Π»ΠΈΠ· Ρ€Π°ΠΊΠΎΠ²Ρ‹Ρ… транскриптомов с ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ ΠœΠ΅Ρ‚ΠΎΠ΄Π° НСзависимых ΠšΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚.

Π’Ρ‹ΡΠΎΠΊΠΎΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Π΅ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, Ρ‚Π°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ высокоплотных

ΠΌΠΈΠΊΡ€ΠΎΡ‡ΠΈΠΏΠΎΠ² ΠΈ сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния Illumina HiSeq2000, вносят Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ

Π²ΠΊΠ»Π°Π΄ Π² соврСмСнноС ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ онкологичСских Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ. ΠžΠ³Ρ€ΠΎΠΌΠ½Ρ‹Π΅ массивы Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ…

Π΄Π°Π½Π½Ρ‹Ρ… Ρ‚Ρ€Π΅Π±ΡƒΡŽΡ‚ примСнСния воспроизводимых аналитичСских ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ². Π’ нашСм исслСдовании

ΠΌΡ‹ продСмонстрировали способо примСнСния ΠœΠ΅Ρ‚ΠΎΠ΄Π° НСзависимых ΠšΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚ для ΠΌΠ΅Ρ‚Π°-

Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°Π±ΠΎΡ€ΠΎΠ² Π΄Π°Π½Π½Ρ‹Ρ… с Ρ€Π°ΠΊΠΎΠΌ ΠΌΠΎΠ»ΠΎΡ‡Π½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ‹. Π‘Ρ‹Π»ΠΎ ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½ΠΎ ΠΎΡ‚ 7 Π΄ΠΎ 8

воспроизводимых ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚ Π²ΠΎ всСх Π½Π°Π±ΠΎΡ€Π°Ρ… Ρ€Π°ΠΊΠ° ΠΌΠΎΠ»ΠΎΡ‡Π½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ‹ ΠΈ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π»ΠΈ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ с

ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ Ρ‚Π΅ΠΎΡ€ΠΈΠΈ Π³Ρ€Π°Ρ„ΠΎΠ² для провСдСния ΠΌΠ΅Ρ‚Π°-Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚Π°Ρ†ΠΈΠΈ нСзависимых

ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚.

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Saule Rakhimova

National Laboratory Astana, Nazarbayev University)

Transcriptome profiling of oesophageal cancer: from biomaterial sampling to sequencing on

HiSeq2000.

The report presents the study of transcriptome profile of esophageal squamous cell carcinoma using

NGS technology. Description of work includes the following steps: sampling of biological material,

nucleic acids isolation, library preparation, library validation methods used in the laboratory.

Esophageal cancer is the sixth common cancer in Kazakhstan, and usually not detected until it has

progressed to an advanced incurable stage. More than 80% of the cancer cases and deaths occur in

developing countries and Central and East Asia. Aim of study: to identify genetic basis of esophageal

cancer by performing whole human transcriptome sequencing study in Kazakhstan.

Patient recruitment was carried out on the Thoracic surgery department, Oncology Center, Astana.

We include only patient with confirmed informed consent and confirmed diagnosis of esophageal

squamous cell carcinoma, to whom was performed radical surgery (Ivor Lewis esophagectomy), and

was available blood analysis, biochemical data, CT, X-ray, histopathological data.

Materials: pairs of freshly frozen (after RNA later solution) esophageal cancer tissue specimen and

normal tissue specimen.

Methods: RNA isolation, Library preparation, Library validation, Hybridization on flow cell, Sequencing

on HiSeq 2000.

For RNA isolation and purification was used Qiagen kits, for library preparation was used Tru Seq RNA

sample preparation kit, all procedures were performed according to Illumina protocols.

Π‘Π°ΡƒΠ»Π΅ Π Π°Ρ…ΠΈΠΌΠΎΠ²Π° (Π§Π£ Β«National Laboratory AstanaΒ», НазарбаСв УнивСрситСт) – Вранскриптомный

ΠΏΡ€ΠΎΡ„ΠΈΠ»ΡŒ Ρ€Π°ΠΊΠ° ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π°: ΠΎΡ‚ Π·Π°Π±ΠΎΡ€Π° ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Π° Π΄ΠΎ сСквСнирования Π½Π° HiSeq2000.

Π’ Π΄ΠΎΠΊΠ»Π°Π΄Π΅ прСдставлСно использованиС NGS Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ Π½Π°ΡƒΡ‡Π½ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π° ΠΏΠΎ

ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΡŽ транскриптомного профиля плоскоклСточного Ρ€Π°ΠΊΠ° ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π°. ОписаниС Ρ€Π°Π±ΠΎΡ‚Ρ‹

Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅ этапы: Π·Π°Π±ΠΎΡ€ Π±ΠΈΠΎΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Π°, Π²Ρ‹Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π½ΡƒΠΊΠ»Π΅ΠΈΠ½ΠΎΠ²Ρ‹Ρ… кислот, ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΡƒ

Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ, ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ Π²Π°Π»ΠΈΠ΄Π°Ρ†ΠΈΠΈ Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Π½Ρ‹Π΅ Π½Π° Π±Π°Π·Π΅ Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΈ.

Π Π°ΠΊ ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π° Π·Π°Π½ΠΈΠΌΠ°Π΅Ρ‚ ΡˆΠ΅ΡΡ‚ΠΎΠ΅ мСсто Π² структурС ΠΎΠ½ΠΊΠΎΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅, ΠΈ, ΠΊΠ°ΠΊ ΠΏΡ€Π°Π²ΠΈΠ»ΠΎ,

Π½Π΅ обнаруТиваСтся, ΠΏΠΎΠΊΠ° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠ΅ Π½Π΅ прогрСссируСт Π΄ΠΎ Π·Π°ΠΏΡƒΡ‰Π΅Π½Ρ‹Ρ… стадий. Π‘ΠΎΠ»Π΅Π΅ 80%

случаСв заболСваСмости ΠΈ смСртности приходится Π½Π° Ρ€Π°Π·Π²ΠΈΠ²Π°ΡŽΡ‰ΠΈΠ΅ΡΡ страны ΠΈ страны

Π¦Π΅Π½Ρ‚Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ ΠΈ Восточной Азии. ЦСль исслСдования: выявлСниС гСнСтичСских основ Ρ€Π°ΠΊΠ°

ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π° Π½Π° основС исслСдования ΠΏΠΎΠ»Π½ΠΎΠ³ΠΎ транскриптома Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅.

Π Π΅ΠΊΡ€ΡƒΡ‚ΠΈΠ½Π³ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ Π½Π° Π±Π°Π·Π΅ отдСлСния Ρ‚ΠΎΡ€Π°ΠΊΠ°Π»ΡŒΠ½ΠΎΠΉ Ρ…ΠΈΡ€ΡƒΡ€Π³ΠΈΠΈ, онкологичСского

Ρ†Π΅Π½Ρ‚Ρ€Π°, Π³. Астана. Π’ исслСдованиС Π±Ρ‹Π»ΠΈ Π²ΠΊΠ»ΡŽΡ‡Π΅Π½Ρ‹ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Ρ‹ с: подписанными Ρ„ΠΎΡ€ΠΌΠ°ΠΌΠΈ

ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ согласия, ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€ΠΆΠ΄Π΅Π½Π½Ρ‹ΠΌ клиничСским Π΄ΠΈΠ°Π³Π½ΠΎΠ·ΠΎΠΌ - плоскоклСточного

Ρ€Π°ΠΊΠ° ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π°, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΌ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»Π°ΡΡŒ Ρ€Π°Π΄ΠΈΠΊΠ°Π»ΡŒΠ½Π°Ρ опСрация (Ivor Lewis Esophagectomy), с

Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΊΡ€ΠΎΠ²ΠΈ, биохимичСских Π΄Π°Π½Π½Ρ‹Ρ…, КВ, Ρ€Π΅Π½Ρ‚Π³Π΅Π½-обслСдования,

гистологичСским Π·Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅ΠΌ.

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ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹: ΠΏΠ°Ρ€Π° свСТСзамороТСнной (Π»ΠΈΠ±ΠΎ ΠΎΠ±Ρ€Π°Π·Ρ†Π° Ρ‚ΠΊΠ°Π½Π΅ΠΉ Π² РНК ΡΡ‚Π°Π±ΠΈΠ»ΠΈΠ·ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΌ растворС)

Ρ‚ΠΊΠ°Π½ΠΈ ΠΏΠΈΡ‰Π΅Π²ΠΎΠ΄Π° с Π½ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ участка ΠΈ Ρ†Π΅Π½Ρ‚Ρ€Π° ΠΎΠΏΡƒΡ…ΠΎΠ»ΠΈ.

Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ использованлись ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ выдСлСния ΠΈ очистки РНК, ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ, Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Π΅

ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ Π²Π°Π»ΠΈΠ΄Π°Ρ†ΠΈΠΈ Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ, гибридизация Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ Π½Π° ΠΏΡ€ΠΎΡ‚ΠΎΡ‡Π½ΡƒΡŽ ячСйку, сСквСнированиС

Π½Π° HiSeq 2000

Для выдСлСния ΠΈ очистки РНК использовали Π½Π°Π±ΠΎΡ€Ρ‹ Qiagen, для ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠΈ Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊΠΈ

использовали Tru Seq RNA sample preparation kit, всС ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈΡΡŒ Π² соотвСтствии с

ΠΏΡ€ΠΎΡ‚ΠΎΠΊΠΎΠ»Π°ΠΌΠΈ Illumina.

Vladislav Govorovskiy

Illumina representative, Belarus

Application of Illumina NGS-technologies in healthcare, research and agriculture

Next-generation sequencing (NGS) technologies transform biological and medical research.

Researchers around the world use next-generation sequencing systems to drive genetic analysis at

higher rate.

Ongoing development of Sequence By Synthesis (SBS) technology provides possibilities to drive

various researches in spheres of interest: science, healthcare, agriculture, forensic, reproductive

medicine. Development of modern devices, such as MiniSeq, HiSeq 4000, HiSeq X, has provided

customers with new possibilities in the NGS sphere. Computational power of those machines coupled

with ongoing designing of kits and panels it has opened great prospects for modern research.

Illumina platform also allow using alternative methods of sample preparation that extends the

potential use of the system. Variety of discussed methods and their potential combinations provide

considerable scope expansion for modern science and medicine.

Π‘Π΅ΠΊΠ²Π΅Π½ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния ΠΏΡ€Π΅ΠΎΠ±Ρ€Π°Π·ΠΈΠ»ΠΎ исслСдования Π² сфСрС Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹.

Π˜ΡΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΠΈ ΠΏΠΎ всСму ΠΌΠΈΡ€Ρƒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡŽΡ‚ систСмы NGS для продвиТСния гСнСтичСских

Π°Π½Π°Π»ΠΈΠ·ΠΎΠ² Π΄ΠΎ Ρ€Π°Π½Π΅Π΅ нСдостиТимого уровня.

ΠŸΠΎΡΡ‚ΠΎΡΠ½Π½ΠΎΠ΅ ΡΠΎΠ²Π΅Ρ€ΡˆΠ΅Π½ΡΡ‚Π²ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Sequence By Synthesis (SBS) ΠΎΡ‚ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ Illumina

Π΄Π°Ρ‘Ρ‚ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΡ‚ΡŒ всё Π±ΠΎΠ»Π΅Π΅ разносторонниС исслСдования Π² Ρ€Π°Π·Π½ΠΎΠΎΠ±Ρ€Π°Π·Π½Ρ‹Ρ… сфСрах

Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… исслСдований, здравоохранСния, сСльского хозяйства, криминалистики,

Ρ€Π΅ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΈΠ²Π½ΠΎΠΉ ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹.

ПоявлСниС соврСмСнного оборудования, Ρ‚Π°ΠΊΠΎΠ³ΠΎ ΠΊΠ°ΠΊ MiniSeq, HiSeq 4000, HiSeq X, Π΄Π°Π»ΠΎ

ΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚Π΅Π»ΡΠΌ Π½ΠΎΠ²Ρ‹Π΅ возмоТности Π² сфСрС NGS, Π° вмСстС с постоянно ΡΠΎΠ²Π΅Ρ€ΡˆΠ΅Π½ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠΌΠΈΡΡ

Π½Π°Π±ΠΎΡ€Π°ΠΌΠΈ ΠΈ панСлями, это ΠΎΡ‚ΠΊΡ€Ρ‹Π»ΠΎ ΠΎΠ³Ρ€ΠΎΠΌΠ½Ρ‹Π΅ пСрспСктивы для соврСмСнных исслСдований.

ΠŸΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠ° Illumina Ρ‚Π°ΠΊΠΆΠ΅ Π΄Π°Π΅Ρ‚ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ Π°Π»ΡŒΡ‚Π΅Ρ€Π½Π°Ρ‚ΠΈΠ²Π½Ρ‹Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ

ΠΏΡ€ΠΎΠ±ΠΎΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠΈ, Ρ‡Ρ‚ΠΎ Ρ€Π°ΡΡˆΠΈΡ€ΡΠ΅Ρ‚ ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π» использования Π΄Π°Π½Π½ΠΎΠΉ систСмы.

Π Π°Π·Π½ΠΎΠΎΠ±Ρ€Π°Π·ΠΈΠ΅ ΠΈ комбинация Π΄Π°Π½Π½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² ΠΈ ΠΈΡ… ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Π΅ ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Ρ†ΠΈΠΈ ΠΏΡ€Π΅Π΄ΠΎΡΡ‚Π°Π²Π»ΡΡŽΡ‚

Π·Π½Π°Ρ‡ΠΈΠΌΠΎΠ΅ Ρ€Π°ΡΡˆΠΈΡ€Π΅Π½ΠΈΠ΅ Π³Ρ€Π°Π½ΠΈΡ† для соврСмСнной Π½Π°ΡƒΠΊΠΈ ΠΈ ΠΌΠ΅Π΄ΠΈΡ†ΠΈΠ½Ρ‹.

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Askhat Molkenov

Nazarbayev University, Kazakhstan

Peculiarities of Bioinformatics Processing and Data Conversion from Illumina HiSeq2000

High throughput next generation sequencing platforms provided new opportunities to scientists in

genomic research field. Nowadays there are carried out large-scale genomic studies of different

organisms, including humans, animals, plants and bacteria with the usage of next generation

sequencing technologies. Modern bioinformatics is a synthesis of biological, information and technical

disciplines aimed to solve scientific problems. In this report, I will present some methods and examples

used in the daily analytical protocols on the base of Laboratory of Bioinformatics and Computational

Systems Biology for the analysis of genomic data from Illumina HiSeq 2000.

ΠžΡΠΎΠ±Π΅Π½Π½ΠΎΡΡ‚ΠΈ биоинформатичСской ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ ΠΈ прСобразования Π΄Π°Π½Π½Ρ‹Ρ… с ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹ HiSeq

2000.

Π’Ρ‹ΡΠΎΠΊΠΎΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹ сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния ΠΎΡ‚ΠΊΡ€Ρ‹Π»ΠΈ ΠΏΠ΅Ρ€Π΅Π΄

ΡƒΡ‡Π΅Π½Ρ‹ΠΌΠΈ Π½ΠΎΠ²Ρ‹Π΅ возмоТности для Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… исслСдований. Π’ настоящСС врСмя проводятся

ΠΌΠ°ΡΡˆΡ‚Π°Π±Π½Ρ‹Π΅ Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Π΅ исслСдования Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… ΠΎΡ€Π³Π°Π½ΠΈΠ·ΠΌΠΎΠ², Π² Ρ‚ΠΎΠΌ числС людСй, ΠΆΠΈΠ²ΠΎΡ‚Π½Ρ‹Ρ…,

растСний ΠΈ Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ с ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния.

БоврСмСнная Π±ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠ° прСдставляСт собой синтСз биологичСских, ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ

тСхничСских дисциплин, Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Π½Ρ‹Ρ… Π½Π° Ρ€Π΅ΡˆΠ΅Π½ΠΈΠ΅ Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… Π·Π°Π΄Π°Ρ‡. Π’ своСм Π΄ΠΎΠΊΠ»Π°Π΄Π΅ я

ΠΏΡ€Π΅Π΄ΡΡ‚Π°Π²Π»ΡŽ Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ ΠΈ ΠΏΡ€ΠΈΠΌΠ΅Ρ€Ρ‹, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅ΠΌΡ‹Π΅ Π² Π΅ΠΆΠ΅Π΄Π½Π΅Π²Π½Ρ‹Ρ… аналитичСских

ΠΏΡ€ΠΎΡ‚ΠΎΠΊΠΎΠ»Π°Ρ… Π½Π° Π±Π°Π·Π΅ Π›Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΈ Π‘ΠΈΠΎΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠΈ ΠΈ Π²Ρ‹Ρ‡ΠΈΡΠ»ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ систСмной Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ для

Π°Π½Π°Π»ΠΈΠ·Π° Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… Π΄Π°Π½Π½Ρ‹Ρ… с Illumina HiSeq2000.

Saule Daugalieva

Institute of Microbiology and Virology, Kazakhstan

NGS 16S sequencing for microbial identification

Laboratory shared of Institute Microbiology and Virology was established in 2014. In the laboratory,

performed the molecular genetic studies on research projects carried out in our institute. The

laboratory is equipped with modern equipment and everything necessary for the research to date. In

the laboratory there are: an Eppendorf PCR cycler, real-time PCR Applied Biosystems 7500, 8-capillary

sequencer Applied Biosystems 3500, next generation sequencer MiSeq Illumina. In addition, there are

accessories: spectrophotometer Quibit, Ajilent Bioanalyzer 2100 gel documentation system Vilber

Lourmat ECX- F15.M, and chromatography mass spectrometer Shimadzu LCMS-860.

Department of Microbiology of our Institute conducted Molecular following types studies of

microorganisms: oil degraded, cellulose degraded, nitrogen-fixing, lactic acid, plant pathogens,

bacteria, fungi and yeast. The main areas of research are the identification of microorganisms by PCR

analysis and sequencing, full genome analysis, and identification of specific genes. In the near future

we plan to hold the soil and water metagenomic analysis from different regions of Kazakhstan and of

the environment.

In 2014, we performed full genome analysis of 14 species of bacteria on the NGS-sequencer MiSeq

Illumina. At this sequencer we performed 16S metagenomic analysis of 120 strains of bacterial

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cultures. Following the acquisition of capillary sequencer, we have conducted with the help of the

identification of 12 species of fungi, and 8 species of yeast, as well as 110 species of bacteria.

When conducting full genome analysis on MiSeq instrument we used a set of sample preparation and

Nextera XT kit for sequencing MiSeq Kit v2.

16S metagenomic analysis for libraries prepared using indexes Nextera XT Index Kit (24 Indexes, 96

Samples) Illumina using KAPA HIFI HOTSTART READY MIX. Purification was carried out using reagent

Ampure XP beads on the magnetic stand. Quantity and quality of the libraries was determined with a

spectrophotometer Quibit 2.0, and 2100 Bioanalyzer Ajilent 2100 and by horizontal gel

electrophoresis. These libraries were normalized and pooled. As a control, was added Phix Control v.3.

Sequencing was performed using a set MiSeq Kit v.2 (500 cycles) and MiSeq Kit v.3 (600 cycles). The

processing of the results was performed using MiSeq Reporter program and 16S metagenomic

program on Illumina website.

Лаборатория ΠΊΠΎΠ»Π»Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ пользования института ΠΌΠΈΠΊΡ€ΠΎΠ±ΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ вирусологии создана Π²

2014 Π³ΠΎΠ΄Ρƒ. Π’ Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΈ Π²Ρ‹ΠΏΠΎΠ»Π½ΡΡŽΡ‚ΡΡ молСкулярно-гСнСтичСскиС исслСдования ΠΏΠΎ Π½Π°ΡƒΡ‡Π½Ρ‹ΠΌ

ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π°ΠΌ, ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠΌΡ‹ΠΌ Π² нашСм институтС. Лаборатория оснащСна соврСмСнным

ΠΎΠ±ΠΎΡ€ΡƒΠ΄ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΈ всСм Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΡ‹ΠΌ для провСдСния Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… исслСдований Π½Π° соврСмСнном

ΡƒΡ€ΠΎΠ²Π½Π΅. Π’ Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€ΠΈΠΈ ΠΈΠΌΠ΅ΡŽΡ‚ΡΡ: ПЦР-Π°ΠΌΠΏΠ»ΠΈΡ„ΠΈΠΊΠ°Ρ‚ΠΎΡ€ Eppendorf, ПЦР Ρ€Π΅Π°Π»-Ρ‚Π°ΠΉΠΌ Applied

Biosystems 7500, 8-капиллярный сСквСнатор Applied Biosystems 3500, сСквСнатор Π½ΠΎΠ²ΠΎΠ³ΠΎ

поколСния MiSeq Illumina. ΠšΡ€ΠΎΠΌΠ΅ Ρ‚ΠΎΠ³ΠΎ, имССтся Π²ΡΠΏΠΎΠΌΠΎΠ³Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠ΅ ΠΎΠ±ΠΎΡ€ΡƒΠ΄ΠΎΠ²Π°Π½ΠΈΠ΅:

спСктрофотомСтр Quibit, Π±ΠΈΠΎΠ°Π½Π°Π»ΠΈΠ·Π°Ρ‚ΠΎΡ€ Ajilent 2100, систСма докумСнтирования Π³Π΅Π»Π΅ΠΉ Vilber

Lourmat ECX- F15.M, Π° Ρ‚Π°ΠΊΠΆΠ΅ систСма хроматомасспСктромСтрии Shimadzu LCMS-860.

ΠžΡ‚Π΄Π΅Π»ΠΎΠΌ ΠΌΠΈΠΊΡ€ΠΎΠ±ΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ института проводятся молСкулярныС исслСдования ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΡ… Π²ΠΈΠ΄ΠΎΠ²

ΠΌΠΈΠΊΡ€ΠΎΠΎΡ€Π³Π°Π½ΠΈΠ·ΠΌΠΎΠ²: Π½Π΅Ρ„Ρ‚Π΅ΠΎΠΊΠΈΡΠ»ΡΡŽΡ‰ΠΈΡ…, Ρ†Π΅Π»Π»ΡŽΠ»ΠΎΠ·ΠΎΠ»ΠΈΡ‚Π΅Ρ‡Π΅ΡΠΊΠΈΡ…, Π°Π·ΠΎΡ‚Ρ„ΠΈΠΊΡΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ…,

молочнокислых, Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ-Ρ„ΠΈΡ‚ΠΎΠΏΠ°Ρ‚ΠΎΠ³Π΅Π½ΠΎΠ², Π³Ρ€ΠΈΠ±ΠΎΠ² ΠΈ Π΄Ρ€ΠΎΠΆΠΆΠ΅ΠΉ. ΠžΡΠ½ΠΎΠ²Π½Ρ‹ΠΌΠΈ направлСниями

исслСдований ΡΠ²Π»ΡΡŽΡ‚ΡΡ идСнтификация ΡˆΡ‚Π°ΠΌΠΌΠΎΠ² ΠΌΠΈΠΊΡ€ΠΎΠΎΡ€Π³Π°Π½ΠΈΠ·ΠΌΠΎΠ² ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌΠΈ ПЦР-Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ

сСквСнирования, ΠΏΠΎΠ»Π½ΠΎΠ³Π΅Π½ΠΎΠΌΠ½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ·, Π° Ρ‚Π°ΠΊΠΆΠ΅ идСнтификация ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Π½Ρ‹Ρ… Π³Π΅Π½ΠΎΠ². Π’

блиТайшСС врСмя ΠΌΡ‹ ΠΏΠ»Π°Π½ΠΈΡ€ΡƒΠ΅ΠΌ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΌΠ΅Ρ‚Π°Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠΎΡ‡Π²Ρ‹, Π²ΠΎΠ΄Ρ‹ Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ…

Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π° ΠΈ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ² ΠΎΠΊΡ€ΡƒΠΆΠ°ΡŽΡ‰Π΅ΠΉ срСды.

Π’ 2014 Π³ΠΎΠ΄Ρƒ Π½Π°ΠΌΠΈ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ ΠΏΠΎΠ»Π½ΠΎΠ³Π΅Π½ΠΎΠΌΠ½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· 14 Π²ΠΈΠ΄ΠΎΠ² Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ Π½Π° NGS-сСквСнаторС

MiSeq Illumina. На Π΄Π°Π½Π½ΠΎΠΌ сСквСнаторС Π½Π°ΠΌΠΈ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ 16S ΠΌΠ΅Ρ‚Π°Π³Π΅Π½ΠΎΠΌΠ½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΎΠΊΠΎΠ»ΠΎ 120

ΡˆΡ‚Π°ΠΌΠΌΠΎΠ² Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΊΡƒΠ»ΡŒΡ‚ΡƒΡ€. ПослС приобрСтСния капиллярного сСквСнатора, ΠΌΡ‹ ΠΏΡ€ΠΎΠ²Π΅Π»ΠΈ

с Π΅Π³ΠΎ ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ 12 Π²ΠΈΠ΄ΠΎΠ² Π³Ρ€ΠΈΠ±ΠΎΠ² ΠΈ 8 Π²ΠΈΠ΄ΠΎΠ² Π΄Ρ€ΠΎΠΆΠΆΠ΅ΠΉ, Π° Ρ‚Π°ΠΊΠΆΠ΅ 110 Π²ΠΈΠ΄ΠΎΠ²

Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ.

ΠŸΡ€ΠΈ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΏΠΎΠ»Π½ΠΎΠ³Π΅Π½ΠΎΠΌΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π½Π° ΠΏΡ€ΠΈΠ±ΠΎΡ€Π΅ MiSeq ΠΌΡ‹ использовали Π½Π°Π±ΠΎΡ€ для

ΠΏΡ€ΠΎΠ±ΠΎΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠΈ Nextera XT ΠΈ Π½Π°Π±ΠΎΡ€ для сСквСнирования MiSeq Kit v2.

Π‘ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊΠΈ для 16S ΠΌΠ΅Ρ‚Π°Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π³ΠΎΡ‚ΠΎΠ²ΠΈΠ»ΠΈ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ индСксов Nextera XT Index Kit

(24 Indexes, 96 Samples) Illumina с ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ KAPA HIFI HOTSTART READY MIX. ΠžΡ‡ΠΈΡΡ‚ΠΊΡƒ

ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ Ρ€Π΅Π°Π³Π΅Π½Ρ‚Π° Ampure XP beads Π½Π° ΠΌΠ°Π³Π½ΠΈΡ‚Π½ΠΎΠΌ ΡˆΡ‚Π°Ρ‚ΠΈΠ²Π΅. ΠšΠΎΠ»ΠΈΡ‡Π΅ΡΡ‚Π²ΠΎ ΠΈ качСство

Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊ опрСдСляли Π½Π° спСктрофотомСтрС Quibit 2.0, Π±ΠΈΠΎΠ°Π½Π°Π»ΠΈΠ·Π°Ρ‚ΠΎΡ€Π΅ Ajilent 2100 ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ

Π³ΠΎΡ€ΠΈΠ·ΠΎΠ½Ρ‚Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ гСль-элСктрофорСза. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊΠΈ Π½ΠΎΡ€ΠΌΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π»ΠΈ ΠΈ объСдиняли.

Π’ качСствС контроля добавляли Phix Control v.3. Π‘Π΅ΠΊΠ²Π΅Π½ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ Π½Π°Π±ΠΎΡ€Π°

MiSeq Kit v.2 (500 Ρ†ΠΈΠΊΠ»ΠΎΠ²) ΠΈ MiSeq Kit v.3 (600 Ρ†ΠΈΠΊΠ»ΠΎΠ²). ΠžΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΡƒ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ²

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ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ MiSeq Reporter ΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ 16S metagenomic Π½Π° сайтС

Illumina.

Raushan Nugmanova

National Center for Biotechnology, Kazakhstan

Study of mutation clusters using Ion Torrent

Phenomenon of nonuniform pattern of mutations in the genome has been observed for many years.

Recent studies have shown presence of certain mutation clusters in cancer genomes, yeast cells, Big

Blue mice, retroelements as well as in bacteria under the pressure of the DNA damaging agents. Such

clusters were detected in the particular regions of the genome, accumulating within a number of

generations. Deep understanding of mutagenesis effect became possible with the development of

next generation sequencing, emergence of which provides deep and sensitive analysis of broad range

of mutations at high speed, generating high quality data. Therefore such approach is widely used in

genome-wide studies. The study of mutagenesis in bacteria is crucial as it might work as a potential

anti-bacterial treatment or may show new aspects of bacterial genome organization. As the previously

conducted study revealed presence of mutation clusters in the several E.coli genomes after the

mutagenesis by ethyl methanesulphonate (EMS), it is important to see whether this phenomenon is

unique only for Gram-negative E.coli, or also might be found in Gram-positive bacteria species as

B.subtilis after the EMS treatment. The use of Ion-Torrent Next-Generation Sequencing technology

allows analyzing several bacterial genomes in one run. The results of the current study showed

presence of mutation clusters in the genome of B.subtilis. In addition, further work is required to

understand molecular basics of mutation clusters in Ξ”Ada and Ξ”MutS E.coli strains.

Π€Π΅Π½ΠΎΠΌΠ΅Π½ Π½Π΅Ρ€Π°Π²Π½ΠΎΠΌΠ΅Ρ€Π½ΠΎΠ³ΠΎ рспрСдСлСния ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΉ Π² Π³Π΅Π½ΠΎΠΌΠ΅ Π½Π°Π±Π»ΡŽΠ΄Π°Π΅Ρ‚ΡΡ Π½Π° протяТСнии ΠΌΠ½ΠΎΠ³ΠΈΡ…

Π»Π΅Ρ‚. НСдавниС исслСдования ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Π½Ρ‹Ρ… кластСров ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΉ Π² Π³Π΅Π½ΠΎΠΌΠ°Ρ…

Ρ€Π°ΠΊΠ°, Π΄Ρ€ΠΎΠΆΠΆΠ°Ρ…, Big Blue mouse, рСтроэлСмСнтах, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π² бактСриях ΠΏΠΎΠ΄ дСйствиСм Π”ΠΠš-

ΠΏΠΎΠ²Ρ€Π΅ΠΆΠ΄Π°ΡŽΡ‰ΠΈΡ… Π°Π³Π΅Π½Ρ‚ΠΎΠ². ΠŸΠΎΠ΄ΠΎΠ±Π½Ρ‹Π΅ кластСры Π±Ρ‹Π»ΠΈ ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½Ρ‹ Π² ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Π½Ρ‹Ρ… Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ…

Π³Π΅Π½ΠΎΠΌΠ°, накопливаясь Π² Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ Π½Π΅ΡΠΊΠΎΠ»ΡŒΠΊΠΈΡ… ΠΏΠΎΠΊΠΎΠ»Π΅Π½ΠΈΠΉ. Π“Π»ΡƒΠ±ΠΎΠΊΠΎΠ΅ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ эффСкта

ΠΌΡƒΡ‚Π°Π³Π΅Π½Π΅Π·Π° стало Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹ΠΌ с Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ΠΌ сСквСнирования Π½ΠΎΠ²ΠΎΠ³ΠΎ поколСния, появлСниС

ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ³ΠΎ обСспСчиваСт Π΄Π΅Ρ‚Π°Π»ΡŒΠ½Ρ‹ΠΉ ΠΈ Ρ‚ΠΎΡ‡Π½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· ΡˆΠΈΡ€ΠΎΠΊΠΎΠ³ΠΎ спСктра ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΉ Π½Π° высокой

скорости, гСнСрируя высококачСствСнныС Π΄Π°Π½Π½Ρ‹Π΅. ΠŸΠΎΡΡ‚ΠΎΠΌΡƒ ΠΏΠΎΠ΄ΠΎΠ±Π½Ρ‹ΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ ΡˆΠΈΡ€ΠΎΠΊΠΎ

распространСн Π² Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… исслСдованиях. Π˜Π·ΡƒΡ‡Π΅Π½ΠΈΠ΅ ΠΌΡƒΡ‚Π°Π³Π΅Π½Π΅Π·Π° Π² бактСриях Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎ, Ρ‚Π°ΠΊ

ΠΊΠ°ΠΊ это ΠΌΠΎΠΆΠ΅Ρ‚ ΡΡ‚Π°Ρ‚ΡŒ ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΡŒΠ½Ρ‹ΠΌ Π°Π½Ρ‚ΠΈΠ±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ°Π»ΡŒΠ½Ρ‹ΠΌ Π»Π΅Ρ‡Π΅Π½ΠΈΠ΅ΠΌ ΠΈΠ»ΠΈ ΠΌΠΎΠΆΠ΅Ρ‚ ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚ΡŒ Π½ΠΎΠ²Ρ‹Π΅

аспСкты ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ Π³Π΅Π½ΠΎΠΌΠ° Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ. Π’Π°ΠΊ ΠΊΠ°ΠΊ ΠΏΡ€Π΅Π΄Ρ‹Π΄ΡƒΡ‰Π΅Π΅ исслСдованиС ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅

кластСров Π² Π³Π΅Π½ΠΎΠΌΠ΅ ΠΊΠΈΡˆΠ΅Ρ‡Π½ΠΎΠΉ ΠΏΠ°Π»ΠΎΡ‡ΠΊΠΈ послС ΠΌΡƒΡ‚Π°Π³Π΅Π½Π΅Π·Π° ΡΡ‚ΠΈΠ»ΠΌΠ΅Ρ‚Π°Π½ΠΎΡΡƒΠ»ΡŒΡ„ΠΎΠ½Π°Ρ‚ΠΎΠΌ, Π²Π°ΠΆΠ½ΠΎ

ΠΏΡ€ΠΎΡΠ»Π΅Π΄ΠΈΡ‚ΡŒ являСтся Π»ΠΈ Π΄Π°Π½Π½Ρ‹ΠΉ Ρ„Π΅Π½ΠΎΠΌΠ΅Π½ ΡƒΠ½ΠΈΠΊΠ°Π»ΡŒΠ½Ρ‹ΠΌ Ρ‚ΠΎΠ»ΡŒΠΊΠΎ для Π³Ρ€Π°ΠΌΠΎΡ‚Ρ€ΠΈΡ†Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠΉΠΎΠΉ E.coli

ΠΈΠ»ΠΈ ΠΆΠ΅ Ρ‚Π°ΠΊΠΆΠ΅ присутствуСт Π² Π³Ρ€Π°ΠΌΠΎΠΏΠΎΠ»ΠΎΠΆΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΌ B.subtilis. ИспользованиС Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Ion-

Torrent Next-Generation Sequencing позволяСт ΠΏΡ€ΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ нСсколько Π³Π΅Π½ΠΎΠΌΠΎΠ² Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΉ

Π·Π° ΠΎΠ΄ΠΈΠ½ ΠΏΡ€ΠΎΠ±Π΅Π³. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ Π΄Π°Π½Π½ΠΎΠ³ΠΎ исслСдования ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… кластСров Π²

Π³Π΅Π½ΠΎΠΌΠ΅ B.subtilis. К Ρ‚ΠΎΠΌΡƒ ΠΆΠ΅ трСбуСтся дальнСйшая Ρ€Π°Π±ΠΎΡ‚Π°, Ρ‡Ρ‚ΠΎΠ±Ρ‹ ΠΏΠΎΠ½ΡΡ‚ΡŒ молСкулярныС основы

кластСров ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΉ Π² ΡˆΡ‚Π°ΠΌΠΌΠ°Ρ… Ξ”Ada ΠΈ Ξ”MutS E.coli.

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Alexander Shevtsov

National Center for Biotechnology, Kazakhstan

NGS sequencing of veterinary pathogens

The previous two decades have led to a reduction in saiga populations by 95%, which connected with

the uncontrolled providence in the period 1994-2003. Various measures helped to reverse the

situation, and in 2013 in Kazakhstan, the number of saiga population has increased 5 times and

amounted to 110 thousand. However, despite the growth of the saiga population in Kazakhstan, they

are still in danger of extinction from infectious diseases. The main cause of the mass death of saiga in

Kazakhstan was recognized as pasteurellosis, a zoonotic disease of vertebrate animals, which is the

etiological agent of P. multocida. Despite the high ecological damage done by pasteurellosis there is a

little information about the genetic factors of the high pathogenesis of causative agent selected from

the saiga. In this research there was carried out whole genome sequencing of three strains of P.

multocida. The strain of P. multocida Z-1 was isolated from the Ural population fallen during the

outbreak in 2010 which killed a third of the population (11,920 individuals). Strains of P. multocida Z-

3 and P. multocida K-1 isolated from Betpakdalasaiga populations during outbreaks of 2012 and 2013.

Whole genome sequencing with the using IonTorrent allowed to get 2,184,434 readings for strain P.

multocida Z-1, 2,212,653 readings for strain P. multocida Z-3, 1,893,014 readings for strain P.

multocida K-1, with an average length of about 160 bp reads . The collected genomes were as follows:

2288383, 2336270 and 2303903 bp respectively. Despite the fact that two saiga populations do not

cross in the wild, strains of P. multocida isolated from them have a large set of identical genes (2025),

which is comprised of 92.6%-95,8% of the predicted proteins, which exceeds the numerical value of

the major genes previously analyzed Pasteurella spp. Meanwhile the strains from bekpakdalasaiga

populations have the largest pool of common genes compared with the Ural population. A

comparative analysis of the genomes of strains isolated from Saiga 11 with the genomes of strains

isolated from mammals and 3 genomes of birds revealed the unique genes of strain Z1 (24 genes), Z3

(35 genes) and K1 (21 genes). Most of these genes are identical bacteriophages or were small

predicted proteins of unknown function (s1). 40 genes have been characterized for all three analyzed

strains.

ΠŸΡ€Π΅Π΄ΡˆΠ΅ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ Π΄Π²Π° дСсятилСтия ΠΏΡ€ΠΈΠ²Π΅Π»ΠΈ ΠΊ ΡΠΎΠΊΡ€Π°Ρ‰Π΅Π½ΠΈΡŽ популяций сайги Π½Π° 95%, Ρ‡Ρ‚ΠΎ связано

с Π½Π΅ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΠΈΡ€ΡƒΠ΅ΠΌΡ‹ΠΌ промыслом Π² ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ 1994-2003 Π³ΠΎΠ΄ΠΎΠ². Π Π°Π·Π»ΠΈΡ‡Π½Ρ‹Π΅ ΠΌΠ΅Ρ€Ρ‹ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ

ΠΏΠ΅Ρ€Π΅Π»ΠΎΠΌΠΈΡ‚ΡŒ ΡΠΈΡ‚ΡƒΠ°Ρ†ΠΈΡŽ, ΠΈ ΡƒΠΆΠ΅ Π² 2013 Π³ΠΎΠ΄Ρƒ Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅ Ρ‡ΠΈΡΠ»Π΅Π½Π½ΠΎΡΡ‚ΡŒ популяции сайгаков

ΡƒΠ²Π΅Π»ΠΈΡ‡ΠΈΠ»Π°ΡΡŒ Π² 5 Ρ€Π°Π· ΠΈ составила 110 тыс. Однако, нСсмотря Π½Π° рост популяций сайги Π²

ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅, ΠΈΠΌ Π΄ΠΎ настоящСго Π²Ρ€Π΅ΠΌΠ΅Π½ΠΈ ΡƒΠ³Ρ€ΠΎΠΆΠ°Π΅Ρ‚ ΠΎΠΏΠ°ΡΠ½ΠΎΡΡ‚ΡŒ исчСзновСния ΠΎΡ‚ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½Ρ‹Ρ…

Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ. Основной ΠΏΡ€ΠΈΡ‡ΠΈΠ½ΠΎΠΉ массовой Π³ΠΈΠ±Π΅Π»ΠΈ сайгаков Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅ Π±Ρ‹Π» ΠΏΡ€ΠΈΠ·Π½Π°Π½

пастСрСллСз, зоонозная болСзнь ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡ‡Π½Ρ‹Ρ… ΠΆΠΈΠ²ΠΎΡ‚Π½Ρ‹Ρ…, этиологичСским Π°Π³Π΅Π½Ρ‚ΠΎΠΌ ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ

являСтся P.multocida. НСсмотря Π½Π° высокий экологичСский ΡƒΡ€ΠΎΠ½ ΠΎΡ‚ Π΄Π°Π½Π½ΠΎΠ³ΠΎ заболСвания ΠΌΠ°Π»ΠΎ

ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΎ гСнСтичСских Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² высокого ΠΏΠ°Ρ‚ΠΎΠ³Π΅Π½Π΅Π·Π° возбудитСля Π²Ρ‹Π΄Π΅Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΡ‚ сайги.

Π’ Π΄Π°Π½Π½ΠΎΠΌ исслСдовании Π±Ρ‹Π»ΠΎ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΏΠΎΠ»Π½ΠΎΠ³Π΅Π½ΠΎΠΌΠ½ΠΎΠ΅ сСквСнированиС Ρ‚Ρ€Π΅Ρ… ΡˆΡ‚Π°ΠΌΠΌΠΎΠ² P.

multocida. Π¨Ρ‚Π°ΠΌΠΌ P. multocida Z-1 Π±Ρ‹Π» ΠΈΠ·ΠΎΠ»ΠΈΡ€ΠΎΠ²Π°Π½ ΠΎΡ‚ сайгака ΡƒΡ€Π°Π»ΡŒΡΠΊΠΎΠΉ популяции павшСго Π²

ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ Π²ΡΠΏΡ‹ΡˆΠΊΠΈ 2010 Π³. ΡƒΠ½Π΅ΡΡˆΠ΅ΠΉ Ρ‚Ρ€Π΅Ρ‚ΡŒ популяции (11920 особСй). Π¨Ρ‚Π°ΠΌΠΌΡ‹ P. multocida Z-3 ΠΈ P.

multocida К-1 ΠΈΠ·ΠΎΠ»ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ ΠΎΡ‚ сайгаков бСтпакдалинской популяции Π² ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ Π²ΡΠΏΡ‹ΡˆΠ΅ΠΊ 2012 ΠΈ

2013 Π³ΠΎΠ΄ΠΎΠ².

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ПолногСномноС сСквСнированиС с использованиСм IonTorrent, ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΏΠΎΠ»ΡƒΡ‡ΠΈΡ‚ΡŒ 2,184,434

ΠΏΡ€ΠΎΡ‡Ρ‚Π΅Π½ΠΈΠΉ для ΡˆΡ‚Π°ΠΌΠΌΠ° P. multocida Z-1, 2,212,653 ΠΏΡ€ΠΎΡ‡Ρ‚Π΅Π½ΠΈΠΉ для ΡˆΡ‚Π°ΠΌΠΌΠ° P. multocida Z-3 ΠΈ

1,893,014 ΠΏΡ€ΠΎΡ‡Ρ‚Π΅Π½ΠΈΠΉ для ΡˆΡ‚Π°ΠΌΠΌΠ° P. multocida K-1, со срСднСй Π΄Π»ΠΈΠ½ΠΎΠΉ ΠΏΡ€ΠΎΡ‡Ρ‚Π΅Π½ΠΈΠΉ ΠΎΠΊΠΎΠ»ΠΎ 160 ΠΏ.Π½.

Π‘ΠΎΠ±Ρ€Π°Π½Π½Ρ‹Π΅ Π³Π΅Π½ΠΎΠΌΡ‹ составили: 2288383, 2336270 ΠΈ 2303903 ΠΏ.Π½.

соотвСтствСнно. НСсмотря Π½Π° Ρ‚ΠΎ Ρ‡Ρ‚ΠΎ Π΄Π²Π΅ популяции сайги Π² СстСствСнных условиях Π½Π΅

ΠΏΠ΅Ρ€Π΅ΡΠ΅ΠΊΠ°ΡŽΡ‚ΡΡ, ΡˆΡ‚Π°ΠΌΠΌΡ‹ P. multocida Π²Ρ‹Π΄Π΅Π»Π΅Π½Π½Ρ‹Π΅ ΠΎΡ‚ Π½ΠΈΡ… ΠΈΠΌΠ΅ΡŽΡ‚ большой Π½Π°Π±ΠΎΡ€ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ‡Π½Ρ‹Ρ…

Π³Π΅Π½ΠΎΠ² (2025), ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ составил 92,6%-95,8% прСдсказанных Π±Π΅Π»ΠΊΠΎΠ², Ρ‡Ρ‚ΠΎ ΠΏΡ€Π΅Π²Ρ‹ΡˆΠ°Π΅Ρ‚ числСнноС

Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ основных Π³Π΅Π½ΠΎΠ² Ρ€Π°Π½Π΅Π΅ Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… пастСрСлл. ΠŸΡ€ΠΈ этом ΡˆΡ‚Π°ΠΌΠΌΡ‹ ΠΎΡ‚ сайгаков

бСкпактдалинской популяции ΠΈΠΌΠ΅ΡŽΡ‚ наибольший ΠΏΡƒΠ» ΠΎΠ±Ρ‰ΠΈΡ… Π³Π΅Π½ΠΎΠ², Π² сравнСнии с ΡƒΡ€Π°Π»ΡŒΡΠΊΠΎΠΉ

популяциСй. Π‘Ρ€Π°Π²Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· Π³Π΅Π½ΠΎΠΌΠΎΠ² ΡˆΡ‚Π°ΠΌΠΌΠΎΠ² Π²Ρ‹Π΄Π΅Π»Π΅Π½Π½Ρ‹Ρ… ΠΎΡ‚ сайги 11 с Π³Π΅Π½ΠΎΠΌΠ°ΠΌΠΈ

ΡˆΡ‚Π°ΠΌΠΌΠΎΠ² Π²Ρ‹Π΄Π΅Π»Π΅Π½Π½Ρ‹Ρ… ΠΎΡ‚ ΠΌΠ»Π΅ΠΊΠΎΠΏΠΈΡ‚Π°ΡŽΡ‰ΠΈΡ… ΠΈ 3 Π³Π΅Π½ΠΎΠΌΠ°ΠΌΠΈ ΠΏΡ‚ΠΈΡ† ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ» Π²Ρ‹ΡΠ²ΠΈΡ‚ΡŒ ΡƒΠ½ΠΈΠΊΠ°Π»ΡŒΠ½Ρ‹Π΅

Π³Π΅Π½Ρ‹ для ΡˆΡ‚Π°ΠΌΠΌΠ° Z1 (24 Π³Π΅Π½Π°), Z3 (35 Π³Π΅Π½ΠΎΠ²) ΠΈ K1 (21 Π³Π΅Π½). Π‘ΠΎΠ»ΡŒΡˆΠΈΠ½ΡΡ‚Π²ΠΎ ΠΈΠ· этих Π³Π΅Π½ΠΎΠ² ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ‡Π½Ρ‹

Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΎΡ„Π°Π³Π°ΠΌ ΠΈΠ»ΠΈ ΠΊΠΎΡ€ΠΎΡ‚ΠΊΠΈΠΌΠΈ Π±Π΅Π»ΠΊΠ°ΠΌΠΈ с нСизвСстной Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠ΅ΠΉ. Π‘ΠΎΡ€ΠΎΠΊ Π³Π΅Π½ΠΎΠ² Π±Ρ‹Π»ΠΈ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π½Ρ‹

для всСх Ρ‚Ρ€Π΅Ρ… Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… ΡˆΡ‚Π°ΠΌΠΌΠΎΠ².

Aizhan Turmagambetova

Institute of Microbiology and Virology, Kazakhstan

Detection of viruses in environmental samples using NGS

Diagnostics of viral infections is on the verge of creating of new theories, hypotheses and discoveries

with the advent of NGS. This is due to several reasons, the most important of which are a multiple

increase of data about the availability of viruses in the environment, including soil, water, feces, air,

etc., as well as the ability to analyze of viruses without their cultivation.

In our research, we studied the biodiversity of viruses in the water reservoirs of Almaty region.

Sequencing was carried out by a double-barrel shotgun method. In this case the useful information

could be obtained by paired-end sequencing of DNA fragment. These two sequences are oriented in

opposite directions and along of the length of the fragment can be separated from each other, and

also can be used for genome assembling using different software. In our research was used the HiSeq

sequencing system and Edena software. Total contigs were 447,000 with a length of 200 to 80,000 bp.

The Metavir2 program selected the 184,431 contigs and the 249,780 of which was identified as viral

gene sequences, and 157,000 of which are previously unknown viral sequences.

Bacteriophages, algae viruses and viruses of the protozoa were the 97% of total viruses of this water

sample. Other 3% included the viruses capable of causing of the disease of animals, higher plants and

humans. Among them: 2 families of retro-transcribing viruses (Retroviridae, Caulimoviridae), 2

families of single-stranded RNA viruses (ssRNA viruses), family of single-stranded DNA virus (ssDNA

viruses - Inoviridae), family of double-stranded RNA virus (dsRNA viruses - Endornaviridae) and 20

families of double-stranded DNA viruses (dsDNA viruses, among them Herpesviridae, etc) were

detected.

Thus, the NGS is opening a new era in the development of monitoring of viral infections that allows

take a different look at the ecology of viruses.

Диагностика виусов Π² ΠΎΠ±Ρ€Π°Π·Ρ†Π°Ρ… ΠΎΠΊΡƒΡ€ΡƒΠΆΠ°ΡŽΡ‰Π΅ΠΉ срСды с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ массивного ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ

сСквСнирования

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Π‘ появлСниСм массивного ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ сСквСнирования (NGS – next generation sequencing)

диагностика вирусных ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΉ стоит Π½Π° ΠΏΠΎΡ€ΠΎΠ³Π΅ создания Π½ΠΎΠ²Ρ‹Ρ… Ρ‚Π΅ΠΎΡ€ΠΈΠΉ, Π³ΠΈΠΏΠΎΡ‚Π΅Π· ΠΈ получСния

Π½ΠΎΠ²Ρ‹Ρ… ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚ΠΈΠΉ. Π­Ρ‚ΠΎ обусловлСно рядом ΠΏΡ€ΠΈΡ‡ΠΈΠ½ основными ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΡΠ²Π»ΡΡŽΡ‚ΡΡ ΠΌΠ½ΠΎΠ³ΠΎΠΊΡ€Π°Ρ‚Π½ΠΎΠ΅

ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΠ΅ Π΄Π°Π½Π½Ρ‹Ρ… ΠΎ Π½Π°Π»ΠΈΡ‡ΠΈΠΈ вирусов Π² ΠΎΠΊΡ€ΡƒΠΆΠ°ΡŽΡ‰Π΅ΠΉ срСдС, Π²ΠΊΠ»ΡŽΡ‡Π°Ρ ΠΏΠΎΡ‡Π²Ρƒ, Π²ΠΎΠ΄Ρƒ, экскрСмСнты,

Π²ΠΎΠ·Π΄ΡƒΡ… ΠΈ Ρ‚.Π΄., Π° Ρ‚Π°ΠΊΠΆΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡ‚ΡŒ Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ вирусов Π±Π΅Π· ΠΈΡ… ΠΏΡ€Π΅Π΄Π²Π°Ρ€ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ

ΠΊΡƒΠ»ΡŒΡ‚ΠΈΠ²ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡ.

Π’ Π½Π°ΡˆΠΈΡ… исслСдованиях ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ биоразнообразия вирусов Π² Π²ΠΎΠ΄ΠΎΠ΅ΠΌΠ°Ρ…

Алматинской области. Π‘Π΅ΠΊΠ²Π΅Π½ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ Π΄Π²ΡƒΡΡ‚Π²ΠΎΠ»ΡŒΠ½ΠΎΠ³ΠΎ Π΄Ρ€ΠΎΠ±ΠΎΠ²ΠΈΠΊΠ°. Π’ этом

случаС полСзная информация ΠΌΠΎΠΆΠ΅Ρ‚ Π±Ρ‹Ρ‚ΡŒ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π° ΠΏΡ€ΠΈ сСквСнировании ΠΏΠ°Ρ€Π½Ρ‹Ρ… ΠΊΠΎΠ½Ρ†ΠΎΠ²

Ρ„Ρ€Π°Π³ΠΌΠ΅Π½Ρ‚Π° Π”ΠΠš. Π­Ρ‚ΠΈ Π΄Π²Π΅ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ Π² ΠΏΡ€ΠΎΡ‚ΠΈΠ²ΠΎΠΏΠΎΠ»ΠΎΠΆΠ½Ρ‹Ρ… направлСниях

ΠΈ ΠΏΠΎ Π΄Π»ΠΈΠ½Π΅ Ρ„Ρ€Π°Π³ΠΌΠ΅Π½Ρ‚Π° ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹ Π΄Ρ€ΡƒΠ³ ΠΎΡ‚ Π΄Ρ€ΡƒΠ³Π°, Π½ΠΎ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ для

сборки Π³Π΅Π½ΠΎΠΌΠΎΠ² с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ Ρ€Π°Π·Π»ΠΈΡ‡Π½ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎΠ³ΠΎ обСспСчСния. Π’ Π½Π°ΡˆΠΈΡ… исслСдованиях

Π±Ρ‹Π» использован сСквСнатор HiSeq ΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ° Edena.

Π‘Ρ‹Π»ΠΎ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½ΠΎ 447000 ΠΊΠΎΠ½Ρ‚ΠΈΠ³ΠΎΠ² с Π΄Π»ΠΈΠ½ΠΎΠΉ ΠΎΡ‚ 200 Π΄ΠΎ 80000 ΠΏΠ°Ρ€ оснований, ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ°

Metavir2 ΠΎΡ‚ΠΎΠ±Ρ€Π°Π»Π° 184431, Π² ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π»Π° ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ 249780 вирусных

Π³Π΅Π½Π°, ΠΏΡ€ΠΈ этом 157000 ΠΈΠ· Π½ΠΈΡ…, это Ρ€Π°Π½Π΅Π΅ нСизвСстныС вирусныС ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ.

97% вирусов Π΄Π°Π½Π½ΠΎΠ³ΠΎ Π²ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΎΠ±Ρ€Π°Π·Ρ†Π° составляли Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΎΡ„Π°Π³ΠΈ (5 сСмСйств), вирусы

водорослСй (1 сСмСйство) ΠΈ ΠΏΡ€ΠΎΡΡ‚Π΅ΠΉΡˆΠΈΡ… (1 сСмСйство). ΠžΡΡ‚Π°Π»ΡŒΠ½Ρ‹Π΅ 3% ΠΏΡ€ΠΈΡˆΠ»ΠΈΡΡŒ Π½Π° вирусы

способныС Π²Ρ‹Π·Ρ‹Π²Π°Ρ‚ΡŒ заболСвания ΠΆΠΈΠ²ΠΎΡ‚Π½Ρ‹Ρ…, Π²Ρ‹ΡΡˆΠΈΡ… растСний ΠΈ Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°. ΠžΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½ΠΎ 2

сСмСйства Ρ€Π΅Ρ‚Ρ€ΠΎ транскрибируСмых вирусов (Retroviridae, Caulimoviridae), 2 сСмСйства вирусов

с ΠΎΠ΄Π½ΠΎΡ†Π΅ΠΏΠΎΡ‡Π΅Ρ‡Π½ΠΎΠΉ РНК (ssRNA viruses), 1 сСмСйство вирусов с ΠΎΠ΄Π½ΠΎΡ†Π΅ΠΏΠΎΡ‡Π΅Ρ‡Π½ΠΎΠΉ Π”ΠΠš (ssDNA

viruses - Inoviridae), 1 сСмСйство вирусов с Π΄Π²ΡƒΡ†Π΅ΠΏΠΎΡ‡Π΅Ρ‡Π½ΠΎΠΉ РНК (dsRNA viruses - Endornaviridae) ΠΈ

20 сСмСйств вирусов с Π΄Π²ΡƒΡ†Π΅ΠΏΠΎΡ‡Π΅Ρ‡Π½ΠΎΠΉ Π”ΠΠš (dsDNA viruses, срСди ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Ρ‚Π°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ Herpesviridae

ΠΈ Ρ‚.Π΄.).

Π’Π°ΠΊΠΈΠΌ ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ, NGS ΠΎΡ‚ΠΊΡ€Ρ‹Π»ΠΎ Π½ΠΎΠ²Ρ‹ΠΉ этап Π² Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠΈ ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° вирусных ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΉ,

ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰ΠΈΠΉ ΠΏΠΎ-Π΄Ρ€ΡƒΠ³ΠΎΠΌΡƒ Π²Π·Π³Π»ΡΠ½ΡƒΡ‚ΡŒ Π½Π° экологию вирусов.

Kobey Karamendin

Institute of Microbiology and Virology, Kazakhstan

NGS 16S sequencing of necropsy material from Saiga antelope after a mass die-off in Spring 2015

During metagenomic studies using MiSeq sequencer to identify bacterial infections pathogens in Saiga

it was determined that 89.05% of all short reads were of bacteria of the genus Pasteurella, among

which the Pasteurella multocida species reached 48.32%. Other species were: Pasteurella eae - 10.75

%, Pasteurella pneumotropica - 4.06 %, Unclassified at Species level - 34.91 %.

ΠŸΡ€ΠΈ ΠΌΠ΅Ρ‚Π°Π³Π΅Π½ΠΎΠΌΠ½Ρ‹Ρ… исслСдованиях Π½Π° сСквСнаторС MiSeq для выявлСния Π²ΠΎΠ·Π±ΡƒΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ всСх

Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΉ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΎ, Ρ‡Ρ‚ΠΎ 89.05 % всСх ΠΊΠΎΡ€ΠΎΡ‚ΠΊΠΈΡ… ΠΏΡ€ΠΎΡ‡Ρ‚Π΅Π½ΠΈΠΉ составляли

Π±Π°ΠΊΡ‚Π΅Ρ€ΠΈΠΈ Ρ€ΠΎΠ΄Π° Pasteurella, срСди ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΏΡ€Π΅ΠΎΠ±Π»Π°Π΄Π°Π» Π²ΠΈΠ΄ Pasteurella multocida ΠΈ составил 48,32

%. Из Π΄Ρ€ΡƒΠ³ΠΈΡ… Π²ΠΈΠ΄ΠΎΠ² ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½Ρ‹: Pasteurella eae - 10.75 %, Pasteurella pneumotropica - 4.06 %,

Π½Π΅ΠΎΠΏΠΎΠ·Π½Π°Π½Π½Ρ‹Π΅ Π²ΠΈΠ΄Ρ‹ - 34.91 %.

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Participants

Name Area of research Country Institute

Abdikerim, Saltanat Molecular genetics KZ IGGC

Akhmetova, Ainur Genetics of Human Diseases KZ NU

Akilzhanova, Ainur Genomic and Personalized medicine KZ NU

Alexyuk, Madina antiviral protection research, metagenomics KZ IMV

Amirbekov, Aday Immunogenetic aspects of cancer screening KZ MU

Amirgazin, Asylulan Bacterial genomics KZ NCB

Bogoyavlenskiy, Andrey antiviral protection research, metagenomics

KZ IMV

Daugaliyeva, Saule Microbiology, metagenomics KZ IMV

Jantayeva, Kira Population genetics KZ MU

Jarmukhanov, Zharkyn Human genetics KZ NCB

Kachieva, Zulfiya Human diseases KZ MU

Kahbatkyzy, Nurzhibek Population genetics KZ IGGC

Kairov, Ulykbek Bioinformatics & KZ NU

Kamalova, Dinara Bacterial genomics KZ NCB

Karamendin, Kobey Viral ecology, evolution KZ IMV

Kozhamkulov, Ulan Microbiology, molecular epidemiology KZ NU

Kulnazarov, Batyr Microbiology, metagenomics KZ IMV

Kuzovleva, Elena Population genetics KZ IGGC

Kydyrmanov, Aidyn Viral ecology, evolution KZ IMV

Moldakozhayev, Alibek Viral ecology, evolution KZ IMV

Nugmanova, Raushan Bacterial genomics KZ NCB

Nurmoldin, Shalkar Thyroid cancer research KZ MU

Perfilyeva, Anastasiya Molecular genetics KZ IGGC

Rakhimova, Saule Genetic studies of multifactorial diseases KZ NU

Shevtsov, Alexandr Bacterial genomics KZ NCB

Turmagambetova, Aizhan antiviral protection research, metagenomics

KZ IMV

Zholdybayeva, Elena Viral genetics KZ NCB

Zhunussova, Gulnur Molecular genetics KZ IGGC

Torokeldiev, Nurlan Population genetics KRG IAUB

Zhanibek Egizbayev Illumina representative KZ ILLM

Govorovskiy, Vladislav Illumina representative BLR ILLM

Carr, Ian Bioinformatics & health UK UoL

Dawson, Deborah Population & ecological genetics UK UoSh

Duncan, Elizabeth Genomics & evolutionary biology UK UoL

Dunn, Jennifer Disease ecology, conservation UK RSPB

Ford, Antonia Population & ecological genetics, genomics UK UoB

Forde, Niamh Reproductive biology UK UoL

Goodman, Simon Population genetics, disease ecology, conservation UK UoL

Hipperson, Helen Bioinformatics & population genetics UK UoSh

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Knight, Christopher Microbial systems biology UK UoM

O'Connell, Mary Computational biology UK UoL

Stockdale, Jennifer Disease ecology, conservation UK UoC

Taylor, Morag Cancer genetics UK UoL

KZ – Kazakhstan

UK – United kingdom

KRG – Kyrgyzstan

BLR - Belarus

UoL - University of Leeds

UoM - University of Manchester

UoSh - University of Sheffield

UoC - University of Cardiff

UoB - University of Bangor

RSPB - Royal Society for Protection of Birds

ILLM – Illumina Corp. IMV - Institute of Microbiology and Virology

MU – Medical University

NCB - National Center for Biotechnology

IGGC – Institute of General Genetics and Cytology

NU - Nazarbayev University

IAUB - International Ala-Too University in Bishkek