68 research outputs found

    The geography of recent genetic ancestry across Europe

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    The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm

    Light emitting diodes (LEDs) applied to microalgal production.

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    Light-emitting diodes (LEDs) will become one of the world's most important light sources and their integration in microalgal production systems (photobioreactors) needs to be considered. LEDs can improve the quality and quantity of microalgal biomass when applied during specific growth phases. However, microalgae need a balanced mix of wavelengths for normal growth, and respond to light differently according to the pigments acquired or lost during their evolutionary history. This review highlights recently published results on the effect of LEDs on microalgal physiology and biochemistry and how this knowledge can be applied in selecting different LEDs with specific technical properties for regulating biomass production by microalgae belonging to diverse taxonomic groups

    Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease

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    Pedigree, linkage and association studies are consistent with heritable variation for complex disease due to the segregation of genetic factors in families and in the population. In contrast, de novo mutations make only minor contributions to heritability estimates for complex traits. Nonetheless, some de novo variants are known to be important in disease etiology. The identification of risk-conferring de novo variants will contribute to the discovery of etiologically relevant genes and pathways and may help in genetic counseling. There is considerable interest in the role of such mutations in complex neuropsychiatric disease, largely driven by new genotyping and sequencing technologies. An important role for large de novo copy number variations has been established. Recently, whole-exome sequencing has been used to extend the investigation of de novo variation to point mutations in protein-coding regions. Here, we consider several challenges for the interpretation of such mutations in the context of their role in neuropsychiatric disease

    A de novo transcriptome of the Asian tiger mosquito, Aedes albopictus, to identify candidate transcripts for diapause preparation

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    <p>Abstract</p> <p>Background</p> <p>Many temperate insects survive the harsh conditions of winter by undergoing photoperiodic diapause, a pre-programmed developmental arrest initiated by short day lengths. Despite the well-established ecological significance of photoperiodic diapause, the molecular basis of this crucial adaptation remains largely unresolved. The Asian tiger mosquito, <it>Aedes albopictus </it>(Skuse), represents an outstanding emerging model to investigate the molecular basis of photoperiodic diapause in a well-defined ecological and evolutionary context. <it>Ae. albopictus </it>is a medically significant vector and is currently considered the most invasive mosquito in the world. Traits related to diapause appear to be important factors contributing to the rapid spread of this mosquito. To generate novel sequence information for this species, as well as to discover transcripts involved in diapause preparation, we sequenced the transcriptome of <it>Ae. albopictus </it>oocytes destined to become diapausing or non-diapausing pharate larvae.</p> <p>Results</p> <p>454 GS-FLX transcriptome sequencing yielded >1.1 million quality-filtered reads, which we assembled into 69,474 contigs (N50 = 1,009 bp). Our contig filtering approach, where we took advantage of strong sequence similarity to the fully sequenced genome of <it>Aedes aegypti</it>, as well as other reference organisms, resulted in 11,561 high-quality, conservative ESTs. Differential expression estimates based on normalized read counts revealed 57 genes with higher expression, and 257 with lower expression under diapause-inducing conditions. Analysis of expression by qPCR for 47 of these genes indicated a high correlation of expression levels between 454 sequence data and qPCR, but congruence of statistically significant differential expression was low. Seven genes identified as differentially expressed based on qPCR have putative functions that are consistent with the insect diapause syndrome; three genes have unknown function and represent novel candidates for the transcriptional basis of diapause.</p> <p>Conclusions</p> <p>Our transcriptome database provides a rich resource for the comparative genomics and functional genetics of <it>Ae. albopictus</it>, an invasive and medically important mosquito. Additionally, the identification of differentially expressed transcripts related to diapause enriches the limited knowledge base for the molecular basis of insect diapause, in particular for the preparatory stage. Finally, our analysis illustrates a useful approach that draws from a closely related reference genome to generate high-confidence ESTs in a non-model organism.</p

    Exome-wide Rare Variant Analysis Identifies TUBA4A Mutations Associated with Familial ALS

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    Exome sequencing is an effective strategy for identifying human disease genes. However, this methodology is difficult in late-onset diseases where limited availability of DNA from informative family members prohibits comprehensive segregation analysis. To overcome this limitation, we performed an exome-wide rare variant burden analysis of 363 index cases with familial ALS (FALS). The results revealed an excess of patient variants within TUBA4A, the gene encoding the Tubulin, Alpha 4A protein. Analysis of a further 272 FALS cases and 5,510 internal controls confirmed the overrepresentation as statistically significant and replicable. Functional analyses revealed that TUBA4A mutants destabilize the microtubule network, diminishing its repolymerization capability. These results further emphasize the role of cytoskeletal defects in ALS and demonstrate the power of gene-based rare variant analyses in situations where causal genes cannot be identified through traditional segregation analysis

    Integration of sequence data from a consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene

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    Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2×10-6). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted. © 2014 Plenge et al

    VariantMetaCaller: automated fusion of variant calling pipelines for quantitative, precision-based filtering

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    BACKGROUND: The low concordance between different variant calling methods still poses a challenge for the wide-spread application of next-generation sequencing in research and clinical practice. A wide range of variant annotations can be used for filtering call sets in order to improve the precision of the variant calls, but the choice of the appropriate filtering thresholds is not straightforward. Variant quality score recalibration provides an alternative solution to hard filtering, but it requires large-scale, genomic data. RESULTS: We evaluated germline variant calling pipelines based on BWA and Bowtie 2 aligners in combination with GATK UnifiedGenotyper, GATK HaplotypeCaller, FreeBayes and SAMtools variant callers, using simulated and real benchmark sequencing data (NA12878 with Illumina Platinum Genomes). We argue that these pipelines are not merely discordant, but they extract complementary useful information. We introduce VariantMetaCaller to test the hypothesis that the automated fusion of measurement related information allows better performance than the recommended hard-filtering settings or recalibration and the fusion of the individual call sets without using annotations. VariantMetaCaller uses Support Vector Machines to combine multiple information sources generated by variant calling pipelines and estimates probabilities of variants. This novel method had significantly higher sensitivity and precision than the individual variant callers in all target region sizes, ranging from a few hundred kilobases to whole exomes. We also demonstrated that VariantMetaCaller supports a quantitative, precision based filtering of variants under wider conditions. Specifically, the computed probabilities of the variants can be used to order the variants, and for a given threshold, probabilities can be used to estimate precision. Precision then can be directly translated to the number of true called variants, or equivalently, to the number of false calls, which allows finding problem-specific balance between sensitivity and precision. CONCLUSIONS: VariantMetaCaller can be applied to small target regions and whole exomes as well, and it can be used in cases of organisms for which highly accurate variant call sets are not yet available, therefore it can be a viable alternative to hard filtering in cases where variant quality score recalibration cannot be used. VariantMetaCaller is freely available at http://bioinformatics.mit.bme.hu/VariantMetaCaller

    A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

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    This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

    Rare and low-frequency coding variants alter human adult height

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    Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways