Function of the Signal Peptide and N- and C-terminal Propeptides in the Leucine Aminopeptidase from \u3cem\u3eAeromonas proteolytica\u3c/em\u3e

The leucine aminopeptidase from Aeromonas proteolytica (also known as Vibrio proteolyticus) (AAP) is a metalloenzyme with broad substrate specificity. The open reading frame (ORF) for AAP encodes a 54 kDa enzyme, however, the extracellular enzyme has a molecular weight of 43 kDa. This form of AAP is further processed to a mature, thermostable 32 kDa form but the exact nature of this process is unknown. Over-expression of different forms of AAP in Escherichia coli (with AAP\u27s native leader sequence, with and without the N- and/or C-terminal propeptides, and as fusion protein) has allowed a model for the processing of wild-type AAP to be proposed. The role of the A. proteolytica signal peptide in protein secretion as well as comparison to other known signal peptides reveals a close resemblance of the A. proteolytica signal peptide to the outer membrane protein (OmpA) signal peptide. Over-expression of the full 54 kDa AAP enzyme provides an enzyme that is significantly less active, due to a cooperative inhibitory interaction between both propeptides. Over-expression of AAP lacking its C-terminal propeptide provided an enzyme with an identical kcat value to wild-type AAP but exhibited a larger Km value, suggesting competitive inhibition of AAP by the N-terminal propeptide (Ki∼0.13 nM). The recombinant 32 kDa form of AAP was characterized by kinetic and spectroscopic methods and was shown to be identical to mature, wild-type AAP. Therefore, the ease of purification and processing of rAAP along with the fact that large quantities can be obtained now allow new detailed mechanistic studies to be performed on AAP through site-directed mutagenesis

Postoperative Non-steroidal Anti-inflammatory Drugs and Risk of Bleeding in Pediatric Intracapsular Tonsillectomy

Tonsillectomy with or without adenoidectomy is one of the most frequently performed surgeries in the United States, with over 500,000 performed annually. Post-tonsillectomy hemorrhage is one of the most feared complications; thus, medications that could increase the risk of postoperative bleeding traditionally have been avoided. With recent FDA guidelines encouraging a departure from codeine-based medications in pediatric patients undergoing tonsillectomy, we examined the use of ibuprofen for post-tonsillectomy pain control. The records of 449 children who underwent tonsillectomy and received ibuprofen for postoperative pain control were reviewed and compared to a cohort of 1731 children who received codeine for pain postoperatively. Outcomes measured included rates of secondary post-tonsillectomy hemorrhage (PTH), secondary PTH requiring operative control, and emergency room evaluation for dehydration. Use of ibuprofen after pediatric intracapsular tonsillectomy was found to be associated with a statistically significant increase in secondary PTH and secondary PTH requiring operative control; however, ibuprofen was found to provide pain control that is at least equivalent to narcotic. Rates of secondary PTH with postoperative ibuprofen use remain within the national average. We propose that, despite the increased risk of bleeding, the use of ibuprofen is appropriate for use postoperatively in pediatric tonsillectomy patients, given its ability to control pain and lack of respiratory depression effects

Metabolic and Transcriptional Modules Independently Diversify Plasma Cell Lifespan and Function

Plasma cell survival and the consequent duration of immunity vary widely with infection or vaccination. Using fluorescent glucose analog uptake, we defined multiple developmentally independent mouse plasma cell populations with varying life- spans. Long-lived plasma cells imported more fluo- rescent glucose analog, expressed higher surface levels of the amino acid transporter CD98, and had more autophagosome mass than did short-lived cells. Low amino acid concentrations triggered re- ductions in both antibody secretion and mitochon- drial respiration, especially by short-lived plasma cells. To explain these observations, we found that glutamine was used for both mitochondrial respira- tion and anaplerotic reactions, yielding glutamate and aspartate for antibody synthesis. Endoplasmic reticulum (ER) stress responses, which link meta- bolism to transcriptional outcomes, were similar between long- and short-lived subsets. Accordingly, population and single-cell transcriptional compari- sons across mouse and human plasma cell subsets revealed few consistent and conserved dif- ferences. Thus, plasma cell antibody secretion and lifespan are primarily defined by non-transcriptional metabolic traits

RTOG/NRG 1115 Quality of Life of Phase III Dose Escalated Radiation Therapy (RT) and Standard Androgen Deprivation Therapy (ADT) with GnRH Agonist vs. Dose Escalated RT and ADT with GnRH Agonist and Orteronel (TAK-700) for Men with High-Risk Prostate

Purpose/Objective(s): Quality of life (QOL) was assessed with the hypothesis that QOL and fatigue scores would not differ significantly between the ADT + RT (Arm A) and the experimental group receiving ADT + RT + oreteronel (Arm B). Materials/Methods: In both arms, ADT with GnRH agonist was given for 24 mos, and dose escalated RT started 8-10 wks after initiation of ADT. In Arm B, oreteronel was given BID for 24 mos. QOL was measured with Expanded Prostate Cancer Index Composite (EPIC) and EQ-5D global QOL assessment. EPIC has 4 domains: bowel, urinary, sexual, and hormonal. EQ-5D index score was calculated using health states obtained from 5 dimensions, and a visual analog score (VAS). For EPIC, EQ-5D index and VAS, higher scores indicate better QOL. Fatigue was measured by the 7-item Patient-Reported Outcome Measurement Information System (PROMIS) short form. Total score is standardized into a T-score with mean of 50 and standard deviation of 10 with higher score representing more fatigue. Change scores, calculated as follow-up minus baseline, were compared between arms. Longitudinal analysis using repeated measures mixed effects models was conducted (prior to ADT [baseline], one wk prior to starting RT, last wk of RT, and 1 and 2.5 yrs after initiation of therapy). Results: Of 231 eligible patients, 196 consented to QOL, 102 on Arm A and 94 on Arm B. Compliance prior to start of RT and end of RT was 83%. At 1 and 2.5 yrs, 80% and 62% of pts, respectively, completed the EPIC. There were no differences between any EPIC domain between arms from the start of RT through the end of follow-up. Men on oreteronel had a significantly greater decline in bowel score prior to starting RT then control patients (-6.12, 95% confidence interval [CI]: -9.24, -3.01 vs. -1.93, 95% CI: -4.48, 0.63, respectively, p=0.038). Arm B patients also had a statistically significant and clinically meaningful worse change in urinary score vs control from baseline to pre-RT (-2.33, 95% CI: -5.02, 0.36 vs. 1.38, 95% CI: -1.07, 3.83, respectively, p=0.043). No other timepoints were significant. The only sig. between arm difference in EPIC sexual and hormonal scores was also at pre-RT in favor of Arm A over Arm B; p=0.024 and p=0.0024 respectively). Fatigue was also greater in the oreteronel patients prior to starting RT (3.81, 95% CI: 1.88, 5.74 vs. 1.18, 95% CI: -0.23, 2.60, p=0.028). Conclusion: The addition of oreteronel to RT and ADT resulted in greater declines in QOL prior to the start of RT but did not result in significant differences at any other time points. Although oreteronel development has been halted, the QOL results are encouraging for other drugs in this class that remain under investigation. In ongoing prospective trials, QOL impacts should be measured in conjunction with changes in clinical outcome and survival. This project was supported by grants UG1CA189867, U10CA180868, U10CA180822 from the National Cancer Institute and Takeda Pharmaceutical

EPR and X-ray Crystallographic Characterization of the Product-Bound Form of the Mn\u3csup\u3eII\u3c/sup\u3e-Loaded Methionyl Aminopeptidase from \u3cem\u3ePyrococcus furiosus\u3c/em\u3e

Methionine aminopeptidases (MetAPs) are ubiquitous metallohydrolases that remove the N-terminal methionine from nascent polypeptide chains. Although various crystal structures of MetAP in the presence of inhibitors have been solved, the structural aspects of the product-bound step has received little attention. Both perpendicular- and parallel-mode electron paramagnetic resonance (EPR) spectra were recorded for the MnII-loaded forms of the type-I (Escherichia coli) and type-II (Pyrococcus furiosus) MetAPs in the presence of the reaction product l-methionine (l-Met). In general, similar EPR features were observed for both [MnMn(EcMetAP-I)]−l-Met and [MnMn(PfMetAP-II)]−l-Met. The observed perpendicular-mode EPR spectra consisted of a six-line hyperfine pattern at g = 2.03 (A = 8.8 mT) with less intense signals with eleven-line splitting at g = 2.4 and 1.7 (A = 4.4 mT). The former feature results from mononuclear, magnetically isolated MnII ions and this signal are 3-fold more intense in the [MnMn(PfMetAP-II)]−l-Met EPR spectrum than in the [MnMn(EcMetAP-I)]−l-Met spectrum. Inspection of the EPR spectra of both [MnMn(EcMetAP-I)]−l-Met and [MnMn(PfMetAP-II)]−l-Met at 40 K in the parallel mode reveals that the [Mn(EcMetAP-I)]−l-Met spectrum exhibits a well-resolved hyperfine split pattern at g = 7.6 with a hyperfine splitting constant of A = 4.4 mT. These data suggest the presence of a magnetically coupled dinuclear MnII center. On the other hand, a similar feature was not observed for the [MnMn(PfMetAP-II)]−l-Met complex. Therefore, the EPR data suggest that l-Met binds to [MnMn(EcMetAP-I)] differently than [MnMn(PfMetAP-II)]. To confirm these data, the X-ray crystal structure of [MnMn(PfMetAP-II)]−l-Met was solved to 2.3 Å resolution. Both Mn1 and Mn2 reside in a distorted trigonal bipyramidal geometry, but the bridging water molecule, observed in the [CoCo(PfMetAP-II)] structure, is absent. Therefore, l-Met binding displaces this water molecule, but the carboxylate oxygen atom of l-Met does not bridge between the two MnII ions. Instead, a single carboxylate oxygen atom of l-Met interacts with only Mn1, while the N-terminal amine nitrogen atom binds to M2. This l-Met binding mode is different from that observed for l-Met binding [CoCo(EcMetAP-I)]. Therefore, the catalytic mechanisms of type-I MetAPs may differ somewhat from type-II enzymes when a dinuclear metalloactive site is present

Autotaxin-LPA Signaling Contributes to Obesity-Induced Insulin Resistance in Muscle and Impairs Mitochondrial Metabolism

Autotaxin (ATX) is an adipokine that generates the bioactive lipid, lysophosphatidic acid (LPA). ATX-LPA signaling has been implicated in diet-induced obesity and systemic insulin resistance. However, it remains unclear whether the ATX-LPA pathway influences insulin function and energy metabolism in target tissues, particularly skeletal muscle, the major site of insulin-stimulated glucose disposal. The objective of this study was to test whether the ATX-LPA pathway impacts tissue insulin signaling and mitochondrial metabolism in skeletal muscle during obesity. Male mice with heterozygous ATX deficiency (ATX+/−) were protected from obesity, systemic insulin resistance, and cardiomyocyte dysfunction following high-fat high-sucrose (HFHS) feeding. HFHS-fed ATX+/− mice also had improved insulin-stimulated AKT phosphorylation in white adipose tissue, liver, heart, and skeletal muscle. Preserved insulin-stimulated glucose transport in muscle from HFHS-fed ATX+/− mice was associated with improved mitochondrial pyruvate oxidation in the absence of changes in fat oxidation and ectopic lipid accumulation. Similarly, incubation with LPA decreased insulin-stimulated AKT phosphorylation and mitochondrial energy metabolism in C2C12 myotubes at baseline and following palmitate-induced insulin resistance. Taken together, our results suggest that the ATX-LPA pathway contributes to obesity-induced insulin resistance in metabolically relevant tissues. Our data also suggest that LPA directly impairs skeletal muscle insulin signaling and mitochondrial function

RGS14 is a mitotic spindle protein essential from the first division of the mammalian zygote.

Heterotrimeric G protein alpha subunits, RGS proteins, and GoLoco motif proteins have been recently implicated in the control of mitotic spindle dynamics in C. elegans and D. melanogaster. Here we show that regulator of G protein signaling-14 (RGS14) is expressed by the mouse embryonic genome immediately prior to the first mitosis, where it colocalizes with the anastral mitotic apparatus of the mouse zygote. Loss of Rgs14 expression in the mouse zygote results in cytofragmentation and failure to progress to the 2-cell stage. RGS14 is found in all tissues and segregates to the nucleus in interphase and to the mitotic spindle and centrioles during mitosis. Alteration of RGS14 levels in exponentially proliferating cells leads to cell growth arrest. Our results indicate that RGS14 is one of the earliest essential product of the mammalian embryonic genome yet described and has a general role in mitosis

Risk factors for late bowel and bladder toxicities in NRG Oncology prostate cancer trials of high-risk patients: A meta-analysis of physician-rated toxicities

Purpose: A meta-analysis of sociodemographic variables and their association with late (\u3e180 days from start of radiation therapy[RT]) bowel, bladder, and clustered bowel and bladder toxicities was conducted in patients with high-risk (clinical stages T2c-T4b or Gleason score 8-10 or prostate-specific antigen level \u3e20) prostate cancer. Methods and materials: Three NRG trials (RTOG 9202, RTOG 9413, and RTOG 9406) that accrued from 1992 to 2000 were used. Late toxicities were measured with the Radiation Therapy Oncology Group Late Radiation Morbidity Scale. After controlling for study, age, Karnofsky Performance Status, and year of accrual, sociodemographic variables were added to the model for each outcome variable of interest in a stepwise fashion using the Fine-Gray regression models with an entry criterion of 0.05. Results: A total of 2432 patients were analyzed of whom most were Caucasian (76%), had a KPS score of 90 to 100 (92%), and received whole-pelvic RT+HT (67%). Of these patients, 13 % and 16% experienced late grade ≥2 bowel and bladder toxicities, respectively, and 2% and 3% experienced late grade ≥3 bowel and bladder toxicities, respectively. Late grade ≥2 clustered bowel and bladder toxicities were seen in approximately 1% of patients and late grade ≥3 clustered toxicities were seen in 2 patients ( Conclusions: Patients with high-risk prostate cancer who receive whole-pelvic RT+LT HT are more likely to have a grade ≥2 bowel toxicity than those who receive prostate-only RT. LT bowel and bladder toxicities were infrequent. Future studies will need to confirm these findings utilizing current radiation technology and patient-reported outcomes

Crop Updates 2006 - Lupins and Pulses

This session covers sixty six papers from different authors: 2005 LUPIN AND PULSE INDUSTRY HIGHLIGHTS 1. Lupin Peter White, Department of Agriculture 2. Pulses Mark Seymour, Department of Agriculture 3. Monthly rainfall at experimental sites in 2005 4. Acknowledgements Amelia McLarty EDITOR 5. Contributors 6. Background Peter White, Department of Agriculture 2005 REGIONAL ROUNDUP 7. Northern agricultural region Wayne Parker, Department of Agriculture 8. Central agricultural region Ian Pritchard and Bob French, Department of Agriculture 9. Great southern and lakes Rodger Beermier, Department of Agriculture 10. South east region Mark Seymour, Department of Agriculture LUPIN AND PULSE PRODUCTION AGRONOMY AND GENETIC IMPROVEMENT 11. Lupin Peter White, Department of Agriculture 12. Narrow-leafed lupin breeding Bevan Buirchell, Department of Agriculture 13. Progress in the development of pearl lupin (Lupinus mutabilis) for Australian agriculture, Mark Sweetingham1,2, Jon Clements1, Geoff Thomas2, Roger Jones1, Sofia Sipsas1, John Quealy2, Leigh Smith1 and Gordon Francis1 1CLIMA, The University of Western Australia 2Department of Agriculture 14. Molecular genetic markers and lupin breeding, Huaan Yang, Jeffrey Boersma, Bevan Buirchell, Department of Agriculture 15. Construction of a genetic linkage map using MFLP, and identification of molecular markers linked to domestication genes in narrow-leafed lupin (Lupinus augustiflolius L) Jeffrey Boersma1,2, Margaret Pallotta3, Bevan Buirchell1, Chengdao Li1, Krishnapillai Sivasithamparam2 and Huaan Yang1 1Department of Agriculture, 2The University of Western Australia, 3Australian Centre for Plant Functional Genomics, South Australia 16. The first gene-based map of narrow-leafed lupin – location of domestication genes and conserved synteny with Medicago truncatula, M. Nelson1, H. Phan2, S. Ellwood2, P. Moolhuijzen3, M. Bellgard3, J. Hane2, A. Williams2, J. Fos‑Nyarko4, B. Wolko5, M. Książkiewicz5, M. Cakir4, M. Jones4, M. Scobie4, C. O’Lone1, S.J. Barker1, R. Oliver2, and W. Cowling1 1School of Plant Biology, The University of Western Australia, 2Australian Centre for Necrotrophic Fungal Pathogens, Murdoch University, 3Centre for Bioinformatics and Biological Computing, Murdoch University, 4School of Biological Sciences and Biotechnology, SABC, Murdoch University,5Institute of Plant Genetics, Polish Academy of Sciences, Poznań, Poland 17. How does lupin optimum density change row spacing? Bob French and Laurie Maiolo, Department of Agriculture 18. Wide row spacing and seeding rate of lupins with conventional and precision seeding machines Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 19. Influence of row spacing and plant density on lupin competition with annual ryegrass, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 20. Effect of timing and speed of inter-row cultivation on lupins, Martin Harries, Jo Walker and Steve Cosh, Department of Agriculture 21. The interaction of atrazine herbicide rate and row spacing on lupin seedling survival, Martin Harries and Jo Walker Department of Agriculture 22. The banding of herbicides on lupin row crops, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 23. Large plot testing of herbicide tolerance of new lupin lines, Wayne Parker, Department of Agriculture 24. Effect of seed source and simazine rate of seedling emergence and growth, Peter White and Greg Shea, Department of Agriculture 25. The effect of lupin row spacing and seeding rate on a following wheat crop, Martin Harries, Jo Walker and Dirranie Kirby, Department of Agriculture 26. Response of crop lupin species to row spacing, Leigh Smith1, Kedar Adhikari1, Jon Clements2 and Patrizia Guantini3, 1Department of Agriculture, 2CLIMA, The University of Western Australia, 3University of Florence, Italy 27. Response of Lupinus mutabilis to lime application and over watering, Peter White, Leigh Smith and Mark Sweetingham, Department of Agriculture 28. Impact of anthracnose on yield of Andromeda lupins, Geoff Thomas, Kedar Adhikari and Katie Bell, Department of Agriculture 29. Survey of lupin root health (in major production areas), Geoff Thomas, Ken Adcock, Katie Bell, Ciara Beard and Anne Smith, Department of Agriculture 30. Development of a generic forecasting and decision support system for diseases in the Western Australian wheatbelt, Tim Maling1, Art Diggle1,2, Debbie Thackray1, Kadambot Siddique1 and Roger Jones1,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 31.Tanjil mutants highly tolerant to metribuzin, Ping Si1, Mark Sweetingham1,2, Bevan Buirchell1,2 and Huaan Yang l,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 32. Precipitation pH vs. yield and functional properties of lupin protein isolate, Vijay Jayasena1, Hui Jun Chih1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 33. Lupin protein isolation with the use of salts, Vijay Jayasena1, Florence Kartawinata1,Ranil Coorey1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 34. Field pea, Mark Seymour, Department of Agriculture 35. Breeding highlights Kerry Regan1,2, Tanveer Khan1,2, Stuart Morgan1 and Phillip Chambers1 1Department of Agriculture, 2CLIMA, The University of Western Australia 36. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge1 and Rod Hunter1 1Department of Agriculture, 2CLIMA, The University of Western Australia 37. Days to flowering of field pea varieties throughout WA Mark Seymour1, Ian Pritchard1, Rodger Beermier1, Pam Burgess1 and Dr Eric Armstrong2 Department of Agriculture, 2NSW Department of Primary Industries, Wagga Wagga 38. Semi-leafless field peas yield more, with less ryegrass seed set, in narrow rows, Glen Riethmuller, Department of Agriculture 39. Swathing, stripping and other innovative ways to harvest field peas, Mark Seymour, Ian Pritchard, Rodger Beermier and Pam Burgess, Department of Agriculture 40. Pulse demonstrations, Ian Pritchard, Wayne Parker, Greg Shea, Department of Agriculture 41. Field pea extension – focus on field peas 2005, Ian Pritchard, Department of Agriculture 42. Field pea blackspot disease in 2005: Prediction versus reality, Moin Salam, Jean Galloway, Pip Payne, Bill MacLeod and Art Diggle, Department of Agriculture 43. Pea seed-borne mosaic virus in pulses: Screening for seed quality defects and virus resistance, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 44. Yield losses from sowing field peas infected with pea seed-borne mosaic virus, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 45. Desi chickpea, Wayne Parker, Department of Agriculture 46. Breeding highlights, Tanveer Khan 1,2, Pooran Gaur3, Kadambot Siddique2, Heather Clarke2, Stuart Morgan1and Alan Harris1, 1Department of Agriculture2CLIMA, The University of Western Australia, 3International Crop Research Institute for Semi Arid Tropics (ICRISAT), India 47. National chickpea improvement program, Kerry Regan1, Ted Knights2 and Kristy Hobson3,1Department of Agriculture, 2Agriculture New South Wales 3Department of Primary Industries, Victoria 48. Chickpea breeding lines in CVT exhibit excellent ascochyta blight resistance, Tanveer Khan1,2, Alan Harris1, Stuart Morgan1 and Kerry Regan1,2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 49. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge2 and Rod Hunter2, 1CLIMA, The University of Western Australia 2Department of Agriculture 50. Desi chickpeas for the wheatbelt, Wayne Parker and Ian Pritchard, Department of Agriculture 51. Large scale demonstration of new chickpea varieties, Wayne Parker, MurrayBlyth, Steve Cosh, Dirranie Kirby and Chris Matthews, Department of Agriculture 52. Ascochyta management with new chickpeas, Martin Harries, Bill MacLeod, Murray Blyth and Jo Walker, Department of Agriculture 53. Management of ascochyta blight in improved chickpea varieties, Bill MacLeod1, Colin Hanbury2, Pip Payne1, Martin Harries1, Murray Blyth1, Tanveer Khan1,2, Kadambot Siddique2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 54. Botrytis grey mould of chickpea, Bill MacLeod, Department of Agriculture 55. Kabuli chickpea, Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 56. New ascochyta blight resistant, high quality kabuli chickpea varieties, Kerry Regan1,2, Kadambot Siddique2, Tim Pope2 and Mike Baker1, 1Department of Agriculture, 2CLIMA, The University of Western Australia 57. Crop production and disease management of Almaz and Nafice, Kerry Regan and Bill MacLeod, Department of Agriculture, and CLIMA, The University of Western Australia 58. Faba bean,Mark Seymour, Department of Agriculture 59. Germplasm evaluation – faba bean, Mark Seymour1, Tim Pope2, Peter White1, Martin Harries1, Murray Blyth1, Rodger Beermier1, Pam Burgess1 and Leanne Young1,1Department of Agriculture, 2CLIMA, The University of Western Australia 60. Factors affecting seed coat colour of faba bean during storage, Syed Muhammad Nasar-Abbas1, Julie Plummer1, Kadambot Siddique2, Peter White 3, D. Harris4 and Ken Dods4.1The University of Western Australia, 2CLIMA, The University of Western Australia, 3Department of Agriculture, 4Chemistry Centre 61. Lentil,Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 62. Variety and germplasm evaluation, Kerry Regan1,2, Tim Pope2, Leanne Young1, Phill Chambers1, Alan Harris1, Wayne Parker1 and Michael Materne3, 1Department of Agriculture 2CLIMA, The University of Western Australia, 3Department of Primary Industries, Victoria Pulse species 63. Land suitability for production of different crop species in Western Australia, Peter White, Dennis van Gool, and Mike Baker, Department of Agriculture 64. Genomic synteny in legumes: Application to crop breeding, Huyen Phan1, Simon Ellwood1, J. Hane1, Angela Williams1, R. Ford2, S. Thomas3 and Richard Oliver1,1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University 2BioMarka, School of Agriculture and Food Systems, ILFR, University of Melbourne 3NSW Department of Primary Industries 65. ALOSCA – Development of a dry flow legume seed inoculant, Rory Coffey and Chris Poole, ALOSCA Technologies Pty Ltd 66. Genetic dissection of resistance to fungal necrotrophs in Medicago truncatula, Simon Ellwood1, Theo Pfaff1, Judith Lichtenzveig12, Lars Kamphuis1, Nola D\u27Souza1, Angela Williams1, Emma Groves1, Karam Singh2 and Richard Oliver1 1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University, 2CSIRO Plant Industry APPENDIX I: LIST OF COMMON ACRONYM

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead