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Lin, B.

Publications and source records attributed to Lin, B..

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Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short read whole genome sequencing. However, standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the advantages of short reads. Starting from only [~]1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as Linked-Reads. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes (Weisenfeld et al. 2017). In this manuscript, we show the advantages of Linked-Reads over standard short read approaches for reference based analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

genomics

Relating C-reactive Protein to Psychopathology after Cardiac Surgery and Intensive Care Unit Admission: A Mendelian Randomization Study

Patients admitted to an intensive care unit (ICU) are subjected to a high burden of stress, rendering them prone to develop stress-related psychopathology. Dysregulation of inflammation and, more specifically, upregulation of inflammatory markers such as C-reactive protein (CRP) is potentially key in development of post-ICU psychopathology.\n\nTo investigate the effects of state-independent CRP on symptoms of post-traumatic stress disorder (PTSD) and depression after ICU admission, we analysed the three leading single nucleotide polymorphisms (SNPs) of loci most strongly associated with blood CRP levels (i.e. rs2794520, rs4420638, and rs1183910) in an ICU survivor cohort. Genetic association was estimated by linear and logistical regression models of individual SNPs and genetic risk score (GRS) profiling. Mendelian Randomization (MR) was used to investigate potential causal relationships.\n\nSingle-SNP analyses were non-significant for both quantitative and binary trait analyses after correction for multiple testing. In addition, GRS results were non-significant and explained little variance in psychopathology. Moreover, MR analysis did not reveal any causality and MR-Egger regression showed no evidence of pleiotropic effects (p-pleiotropy >0.05). Furthermore, estimation of causality between these loci and other psychiatric disorders was similarly non-significant.\n\nIn conclusion, by applying a range of statistical models we demonstrate that the strongest plasma CRP-influencing genetic loci are not associated with post-ICU PTSD and depressive symptoms. Our findings add to an expanding body of literature on the absence of associations between trait CRP and neuropsychiatric phenotypes.

genetics