Rapid flow-sorting to simultaneously resolve multiplex massively parallel sequencing products

Sample preparation for Roche/454, ABI/SOLiD and Life Technologies/Ion Torrent sequencing are based on amplification of library fragments on the surface of beads prior to sequencing. Commonly, libraries are barcoded and pooled, to maximise the sequence output of each sequence run. Here, we describe a novel approach for normalization of multiplex next generation sequencing libraries after emulsion PCR. Briefly, amplified libraries carrying unique barcodes are prepared by fluorescent tagging of complementary sequences and then resolved by high-speed flow cytometric sorting of labeled emulsion PCR beads. The protocol is simple and provides an even sequence distribution of multiplex libraries when sequencing the flow-sorted beads. Moreover, since many empty and mixed emulsion PCR beads are removed, the approach gives rise to a substantial increase in sequence quality and mean read length, as compared to that obtained by standard enrichment protocols

Scalable Transcriptome Preparation for Massive Parallel Sequencing

Background: The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity. Methodology: In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation. Conclusion/Significance: The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods

Separate Origins of Group I Introns in Two Mitochondrial Genes of the Katablepharid Leucocryptos marina

Mitochondria are descendants of the endosymbiotic α-proteobacterium most likely engulfed by the ancestral eukaryotic cells, and the proto-mitochondrial genome should have been severely streamlined in terms of both genome size and gene repertoire. In addition, mitochondrial (mt) sequence data indicated that frequent intron gain/loss events contributed to shaping the modern mt genome organizations, resulting in the homologous introns being shared between two distantly related mt genomes. Unfortunately, the bulk of mt sequence data currently available are of phylogenetically restricted lineages, i.e., metazoans, fungi, and land plants, and are insufficient to elucidate the entire picture of intron evolution in mt genomes. In this work, we sequenced a 12 kbp-fragment of the mt genome of the katablepharid Leucocryptos marina. Among nine protein-coding genes included in the mt genome fragment, the genes encoding cytochrome b and cytochrome c oxidase subunit I (cob and cox1) were interrupted by group I introns. We further identified that the cob and cox1 introns host open reading frames for homing endonucleases (HEs) belonging to distantly related superfamilies. Phylogenetic analyses recovered an affinity between the HE in the Leucocryptos cob intron and two green algal HEs, and that between the HE in the Leucocryptos cox1 intron and a fungal HE, suggesting that the Leucocryptos cob and cox1 introns possess distinct evolutionary origins. Although the current intron (and intronic HE) data are insufficient to infer how the homologous introns were distributed to distantly related mt genomes, the results presented here successfully expanded the evolutionary dynamism of group I introns in mt genomes

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Early blood glucose profile and neurodevelopmental outcome at two years in neonatal hypoxic-ischaemic encephalopathy

Background: To examine the blood glucose profile and the relationship between blood glucose levels and neurodevelopmental outcome in term infants with hypoxic-ischaemic encephalopathy. Methods: Blood glucose values within 72 hours of birth were collected from 52 term infants with hypoxic-ischaemic encephalopathy. Hypoglycaemia [ 150 mg/dL (8.3 mmol/L)] were correlated to neurodevelopmental outcome at 24 months of age. Results: Four fifths of the 468 blood samples were in the normoglycaemic range (392/468:83.8%). Of the remaining 76 samples, 51.3% were in the hypoglycaemic range and (48.7%) were hyperglycaemic. A quarter of the hypoglycaemic samples (28.2%:11/39) and a third of the hyperglycaemic samples (32.4%:12/37) were recorded within the first 30 minutes of life. Mean (SD) blood glucose values did not differ between infants with normal and abnormal outcomes [4.89(2.28) mmol/L and 5.02(2.35) mmol/L, p value = 0.15] respectively. In term infants with hypoxic-ischaemic encephalopathy, early hypoglycaemia (between 0-6 hours of life) was associated with adverse outcome at 24 months of age [OR = 5.8, CI = 1.04-32)]. On multivariate analysis to adjust for grade of HIE this association was not statistically significant. Late hypoglycaemia (6-72 hours of life) was not associated with abnormal outcome [OR = 0.22, CI (0.04-1.14)]. The occurrence of hyperglycaemia was not associated with adverse outcome. Conclusion: During the first 72 hours of life, blood glucose profile in infants with hypoxic-ischaemic encephalopathy varies widely despite a management protocol. Early hypoglycaemia (0-6 hours of life) was associated with severe HIE, and thereby; adverse outcome

Assigning a function to a conserved archaeal metallo-β-lactamase from Haloferax volcanii

The metallo-β-lactamase family of enzymes comprises a large group of proteins with diverse functions in the metabolism of the cell. Among others, this superfamily contains proteins which are involved in DNA and RNA metabolism, acting as nucleases in e.g. repair and maturation. Many proteins have been annotated in prokaryotic genomes as being potential metallo-β-lactamases, but very often the function has not been proven. The protein HVO_2763 from Haloferax volcanii is such a potential metallo-β-lactamase. HVO_2763 has sequence similarity to the metallo-β-lactamase tRNase Z, a tRNA 3′ processing endonuclease. Here, we report the characterisation of this metallo-β-lactamase HVO_2763 in the halophilic archaeon Haloferax volcanii. Using different in vitro assays with the recombinant HVO_2763, we could show that the protein does not have tRNA 3′ processing or exonuclease activity. According to transcriptome analyses of the HVO_2763 deletion strain, expression of proteins involved in membrane transport is downregulated in the mutant. Therefore, HVO_2763 might be involved directly or indirectly in membrane transport

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge