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• Small_molecule_inhibitors_in_melanoma___Kenski___Kong___WES

  Small-molecule inhibitors targeting the most commonly activated pathway in melanoma, MAPK pathway (either alone or in combination) are already given to melanoma patients for few years, and initially reduce tumour burden dramatically, eventually melanomas become resistant and tumours progress while on treatment. Resistance to this treatment occurs by acquisition of additional mutations or other alterations that affect the mitogen-activated protein kinase (MAPK) pathway by either direct or indirect signalling. Many resistance mechanisms somehow lead to reactivation of extracellular signal-regulated kinase (ERK), thereby restoring signalling of the oncogenic BRAF/MEK/ERK pathway. In addition, PI3K pathway activation contributes to resistance to BRAF inhibition. Less frequent but equally important to the phenomenon of targeted drug resistance is the observation that B15–20% of BRAF mutant melanoma patients fail to respond to BRAF inhibition already early on treatment, owing to intrinsic resistance. These patients have little therapeutic options, unless immunotherapy can be given. To better understand the resistance mechanisms in MAPK inhibitor-treated melanoma patients and melanoma biology, our lab generated a big panel of MAPK inhibitor resistant melanoma cell lines by continuous drug exposure. The understanding of the genetic landscape and gene expression as well as cross resistance to other treatment regimens, and other aspects of melanoma biology such as phenotype switch, will allow us to better exploit new therapeutic strategies for melanoma patients.

  Study EGAS00001002863

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__head___neck

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005450

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947

• cfDNA dataset from extracelular vesicles and paired non-fractionated samples

  Liquid biopsies contain multiple analytes that can be mined to improve the detection and management of cancer. Beyond cell-free DNA (cfDNA), mutations have been detected in DNA associated with extracellular vesicles (EV-DNA). The genome-wide composition and structure of EV-DNA remains poorly characterized, and whether circulating EVs are enriched in tumor signal compared to unfractionated cfDNA is still unclear. Here, using whole genome sequencing from selected lung cancer patients with a relatively high cfDNA tumor content >5%, we determined that the tumor fraction and heterogeneity are comparable between DNA associated with small (<200 nm) EVs and matched plasma cfDNA. DNA in EV fractions, obtained with standardized size-exclusion chromatography, are comprised of short ~150-180 bp fragments and long >1000 bp fragments that are poor in tumor signal. Other fractions only exhibit short fragments with similar tumor DNA content. The composition in bases at the end of EV-DNA fragments, as well as their fragmentation patterns are similar to total plasma cfDNA. Mitochondrial DNA however is relatively enriched in EV fractions. Our results suggests that cfDNA in plasma may be of dual nature, either bound to proteins (including the nucleosome) but also associated to EVs. cfDNA associated to small EV (including exosomes) is however not preferentially enriched in tumor signal.

  Study EGAS00001006848

• Genome wide variation in the Angolan Namib desert reveals unique Pre-Bantu ancestry

  The populations of the Angolan Namib Desert have been largely neglected in previous surveys of the genomic landscape of southern Africa. Although at present, the Namib is culturally dominated by Southwest Bantu-speaking cattle-herders, the region exhibits an extraordinary ethnographic diversity which includes an array of semi-nomadic peoples whose subsistence strategies fall outside the traditional division between foraging and food production and can thus be referred to as “peripatetic”. Among these small-scale populations are the last speakers of the Kwadi branch of the Khoe-Kwadi language family associated with the introduction of pastoralism into southern Africa (Kwepe), as well as a range of groups whose origins remain enigmatic (Kwisi, Twa and Tjimba). Using genome-wide data from 208 individuals belonging to nine ethnically diverse groups from the Angolan Namib and adjacent areas (Kwepe, Kwisi, Twa, Tjimba, !Xun, Kuvale, Himba, Nyaneka, Ovimbundu) in combination with published data from other regions of Africa, we reconstruct in detail the histories of contact emerging from pre-historic migrations to southern Africa and show that peripatetic groups from southwestern Angola stand out for exhibiting elevated levels of an unique, regionally-specific and highly divergent Pre-Bantu ancestry. These findings highlight the importance of the Namib for understanding the deep genetic structure of Africa.

  Study EGAS00001007011

• ATAC-Seq of CD4 T cell subsets

  Blood samples were taken from 4 age-matched healthy volunteers (two males and two females), and naïve CD4 T cells were isolated using the naïve CD4+ T Cell Isolation Kit II, human (Miltenyi Biotec). Two hundred thousand cells were plated in a 96-well plate, activated with Dynabeads Human T-activator CD3/CD28 (bead-to-cell ratio of 1:1, as recommended by the manufacturer) (ThermoFisher Scientific) and polarized towards CD4 T cell subtypes (Teff, Th1, Th2, rTh17, pTh17, and Treg cells) with specific cocktails of recombinant cytokines and neutralizing antibodies (see details in the material and methods) for each subset. At day 4 post-stimulation, forty thousand cells were used to perform ATAC-Seq on CD4 T cell subtypes. Again, crude nuclei of live CD4+ T cell subsets were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007345

• MutWP1__CRUK_Grand_Challenge__normal_kidney_Nanoseq

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005451

• MutWP1__CRUK_Grand_Challenge__matched_blood_Nanoseq

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001006774

• RRBS data (cfSort study) from noncancer tissue DNA

  The RRBS libraries of the genomic DNA from the 521 tissue samples were constructed following the standard RRBS protocol. 100-200 ng of intact genomic DNA in the volume of 21.5 µl was used as input material. Restriction digestion was done with 2.5 µl 10xCutSmart buffer and 1 µl MspI (NEB) for 18 h at 37 oC and 20 min at 65 oC. 0.5 µl 10xCutSmart buffer, 0.3 µl dACGTP mixture (100 mM dATP, 10 mM dCTP, 10 mM dGTP), 1 µl Klenow (exo-, 5U/µl, NEB) and 2.6 µl RT-PCR water, 0.6 µl 50 mM DTT (ThermoFisher) was added to the mixture for end repair and A-overhang addition with the program 30 oC for 20 min, 37 oC for 1 h and 75 oC for 20 min. Adapter ligation was then performed with 1 µl 10xThermoFisher HC T4 ligase buffer, 0.4 µl 100 mM ATP (ThermoFisher), 0.2 µl 50 mM DTT, 1 µl ThermoFisher HC T4 DNA ligase (30 Weiss Unit/µl), 30 ng home-made duplex UMI adapter with all the cytosines methylated (protocol adopted from Kennedy et al.) at 16 oC for 20 h and 65 oC for 20 min. Bisulfite conversion of the adapter-ligated product was carried out with QIAGEN EpiTect plus DNA bisulfite kit following their protocol for two rounds of conversion. The converted product was purified with Qiagen MinElute spin column and eluted with 20 µl RT-PCR water. PCR amplification was done using the NEBNext Multiplex Oligos for Illumina (2.5 µl of universal and index primer each) and 25 µl KAPA HiFi HotStart Uracil+ ReadyMix (Roche) with the following cycling conditions: 98 oC for 45 s, 9 cycles of 98 oC for 15 s, 60 oC for 30 s and 72 oC for 30 s, followed by a final extension at 72 oC for 5 min. The PCR product was purified with 1x AmpureXP beads and eluted with 30 µl EB buffer. DNA concentration was measured by Qubit 1xdsDNA HS assay. 5% TBE-UREA PAGE and bioanalyzer assay was performed as quality control on each library before sequencing.

  Dataset EGAD00001010880