Genetic interference by DNA, mRNA or morpholino injection is a widely used approach to study gene function in developmental biology. However, the lack of temporal control over the activity of interfering molecules often hampers investigation of gene function required during later stages of embryogenesis. To elucidate the roles of genes during embryogenesis a precise temporal control of transgene expression levels in the developing organism is on demand.Sleeping Beauty transposon system allows inducible gene expression in an entirely uniform manner without the need to generate transgenic effector lines. Combination of this system with fluorescent protein reporters furthermore facilitates the direct visualization of transgene expressing cells in live embryos.We have generated a transgenic Gal4/Vp16 activator line that is heat-shock inducible, thereby providing a tool to drive the expression of specific effector genes via Gal4/Vp16. Merging the Gal4/Vp16-UAS system with the I-SceI meganuclease and the The combinatorial properties of this expression system provide a powerful tool for the analysis of gene function during embryonic and larval development in fish by ectopic expression of gene products. Oryzias latipes) are the analyses of mutants, miss-expression of wild type genes or their variants by mRNA injection and gene specific translational inhibition by morpholino injections [Drosophila Gal4-UAS approach, by the generation of transgenic lines, has been established successfully in zebrafish [The most widely used strategies to investigate the function of genes in medaka (jections -3. Howevjections ,5. The debrafish ,7. Howevebrafish  can be uebrafish  resultinebrafish . Nonetheebrafish .Sleeping Beauty (SB) transposon system [We have applied the Gal4/Vp16-UAS system for transient transactivation in a heat-shock inducible transgenic Gal4/Vp16 activator line. Generation of transgenic medaka lines, which allow the induction of the Gal4/Vp16 activator to 'physiological' (i.e. non-toxic) levels was achieved by using a 5' truncated version of the zebrafish heat-shock promoter HSP70 . Using an system  yielded in vivo tracing of transgene-expressing cells and observation of effects exerted by the transgene through application of fluorescent markers [DNA injection leading to mosaic expression in G0 allows  markers . However markers , Fig. 1FThe idea is to combine stable heat-shock inducible expression of the Gal4/Vp16 activator with transient expression of effector genes upon microinjection. The effector constructs are uniformly distributed in the entire embryo due to the presence of the SB direct-inverted repeats . We haveIt has been shown that the Gal4/Vp16 activator can interfere with general transcription by titrating the basal transcription machinery [The truncated version of the zfHSP70 promoter fragment used in the activator/reporter construct pCG6.0WCS showed a moderate activation upon heat-shock treatment. This allowed adjusting the induction levels by varying the heat-shock duration. A transgenic medaka line was established (by co-injection of circular vector pCG6.0WCS with MN) in which expression levels directly correlated with the heat-shock duration. Extended heat-shocks resulted in very high expression levels, but also caused retardation phenotypes due to the strong transactivation potential of the Gal4/Vp16 fusion protein. Comparable phenotypes were not observed in heat-shock treated wild type embryos. Depending on the developmental stage at the time of induction, the duration of heat-shock treatment was adjusted to induce Gal4/Vp16 and reporter expression without interfering with embryonic development. Induction periods ranged from one minute of heat-shock at 37°C at early stages (~st16/21hpf) to 10 minutes at later stages (~st22/38hpf). On top of uniform CFP expression in the entire embryo and yolk upon heat-shock, some regions of the embryo showed additional responsiveness of the reporter Fig. .Microinjection experiments and RT-PCR revealed that reporter gene (CFP) expression in transgenic fish is mediated by Gal4/Vp16. Offspring of pCG6.0-WCS/T transgenic fish was injected with Gal4/Vp16 mRNA (3.5 ng/μl) at the one-cell stage without heat-shock treatment. Injected embryos exhibited uniform expression of CFP shortly after the onset of zygotic transcription at the mid-blastula transition , indicatWe applied RT-PCR for the dose/response analysis of activator and reporter mRNA Fig. . TranscrWe tested the Gal4/Vp16 activator line pCG6.0WCS/T as a tool to induce expression of an independent reporter upon injection of plasmid DNA (pCG3.0Y). Transgenic embryos were injected with different concentrations of the reporter pCG3.0Y (5–150 ng/μl). Injected embryos were subjected to heat-shock treatment at different developmental stages for various periods of time, kept at 28°C thereafter and monitored for activator and effector expression during the following days. Due to the SB IR/DRs flanking the expression cassette, the independent reporter was distributed equally in the entire embryo resulting in ubiquitous expression of YFP, entirely co-localizing with the internal reporter (CFP). Additional mosaic clones of cells expressing YFP at higher levels presumably reflect higher plasmid concentrations in these cells . This entire cassette was cloned into pCG1.1 containing the IR/DR sequences of the SB transposable element  resultinA 1.5 kb zebrafish HSP70 promoter fragment  was subcBamHI site resulting in a 7.8 kb plasmid that was verified by sequencing  1–147 and Vp16 transactivation domain: aa 411–491) was designed from Clontech vectors pM  and pM3-VP16 (Vp16) and cloned into pCS2+ .in vitro from pCGGal4/Vp16 using the mMessage mMachine kit (Ambion Inc.).Gal4/Vp16 mRNA was transcribed For microinjections, one-cell stage embryos of the Cab inbred strain were used. Microinjection capillaries were backfilled with the injection solution [DNA (5–150 ng/μl); Yamamoto buffer (1×) or DNA (5 ng/μl); Yamamoto buffer (0.5×); I-SceI buffer (0.5×, New England Biolabs); I-SceI meganuclease (0.35 u/μl, New England Biolabs) with or without Gal4/Vp16 mRNA (3.5–50 ng/μl)]. DNA was prepared using a Qiagen Maxiprep kit (Qiagen, USA) and dialyzed using nitrocellulose filters . DNA was injected through the chorion into the cytoplasm of one-cell stage embryos. Heat-shock treatment was performed in small volumes (100–200 μl) using a waterbath at 37°C. Animals used in the study were kept according to national and international ethical provisions for animal husbandry as implemented at EMBL.Embryos were observed and scored using a MZFLIII dissecting microscope with a 436/20 nm (EF); 480/40 nm (BF) filter set for CFP, a 510/20 nm (EF); 560/40 nm (BF) filter set for YFP and a 360/40 nm (EF); 420 nm (BF) filter set for UV/Brightfield. The stereomicroscope was equipped with a DC500 digital camera for imaging (Leica Microsystems, Germany).Transgenic embryos were heat-shocked and subsequently kept at 28°C to recover for different periods of time. Total RNA was isolated from individual embryos as described . Total RCG designed and performed all experiments and drafted the manuscript. JW conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.


Currently there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes, including functional status. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life.This paper examines the psychometric properties of the AMC Linear Disability Score (ALDS) project item bank using an item response theory model and full information factor analysis. Data were collected from 555 respondents on a total of 160 items.Following the analysis, 79 items remained in the item bank. The remaining 81 items were excluded because of: difficulties in presentation (1 item); low levels of variation in response pattern (28 items); significant differences in measurement characteristics for males and females or for respondents under or over 85 years old (26 items); or lack of model fit to the data at item level (26 items).It is conceivable that the item bank will have different measurement characteristics for other patient or demographic populations. However, these results indicate that the ALDS item bank has sound psychometric properties for respondents in residential care settings and could form a stable base for measuring functional status in a range of situations, including the implementation of computerised adaptive testing of functional status. It is now widely accepted that examining quality of life is an important aspect in the treatment and evaluation of many conditions. Functional status is seen as an important determinant of quality of life. A wide variety of instruments have been developed to quantify functional status . These iThe AMC Linear Disability Score (ALDS) project item bank was developed to quantify functional status ,9. The AThis paper examines these five aspects of the ALDS item bank using the responses given by residents of supported housing schemes, residential care and nursing homes in and around Amsterdam, the Netherlands. This, mainly elderly, population has been chosen because they generally experience some level of functional restriction and consume a large amount of health care services.A and B have half their items in common, as do item sets B and C, item sets C and D and item sets A and D. The items in common between two sets of items are known as 'anchors' and allow all items and patients to be calibrated on the same scale. The patterns of missing data in this type of design are, in statistical terms, ignorable [A), 143 respondents (item set B), 138 respondents (item set C) and 124 respondents (item set D).This paper considers 160 items, which were considered to be applicable in a residential care setting. Each item has two response categories: 'I could carry out the activity' and 'I could not carry out the activity'. If a respondent had never had the opportunity to experience an activity 'not applicable' was recorded. In the analysis, responses in the category 'not applicable' were treated as if the individual items had not been presented to the individual respondents . It was A total of 555 residents of supported housing, residential care and nursing homes were interviewed. The median age was 84 years (range 37 to 101 years), while 444 (80%) were female. Since the respondents were interviewed 'at home', accurate data on medical conditions were not available. All respondents gave informed consent. The study was approved by the medical ethics committee in our hospital.Pik, that patient k responds to item i in the category 'can' is modelled usingIn this paper the data were analysed using the two-parameter logistic item response theory model ,9,17,18.θk denotes the ability of patient k to perform activities of daily life. The discrimination parameter (αi) and difficulty parameter (βi) describe the measurement characteristics of item i. The larger the value of βi, the more difficult item i is. In addition, the larger the value of αi, the better an item is a distinguishing between abilities above and below βi. If the values of αi are constrained to be equal for all items, the model in equation 1 becomes the one-parameter logistic item response theory model [βi for, say males and females, are significantly different. If the values of βi for different groups of respondents are significantly different, then there is evidence of differential item functioning. Full-information factor analysis also uses an extension of the model in equation 1. These approaches are described in mathematical terms in the Appendix. In this paper, estimates of αi and βi were obtained using a marginal maximum likelihood based procedure [θk) follow a Normal distribution and can account for incomplete designs, as described in the Appendix. Expected a posteriori methods were used to estimate θk [where ry model . The modrocedure . This meimate θk .βi) was similar for male and female patients and for patients younger than 85 years and those aged 85 or older. The model is described in depth in the Appendix. Items were excluded from further analysis if the value of the item difficulty parameter was significantly different (1% level) between gender or aged based groups. In this step, the fit of the model to the data from each item was not assessed. In step (c), estimates of the item parameters (αi and βi) were obtained. The fit of the model to the data from each item was assessed using G2 statistics [p-value of less than 0.01, were excluded from the item bank. In addition, the stability of the estimates of the item parameters over different sets of items was examined using the model from step (b). Items were excluded from further analysis if the value of the item difficulty parameter was significantly different (1% level) between item sets A and B, B and C, C and D or A and D. Furthermore, a Kolmogornov-Smirnov test was carried out to examine whether the ability parameters (θk) were Normally distributed. In step (d), the dimensionality of the item bank was examined using item response theory based full information factor analysis [A and B (293 respondents), B and C (281 respondents), C and D (262 respondents) or A and D (274 respondents). A fifth, confirmatory, factor analysis was carried out on the whole data set (555 respondents). In addition, Cronbach's coefficient alpha was calculated for each anchor and the whole data set [χ2 test. The analysis in steps (a), (b), (c) and (e) was carried out in Bilog, version 3.0 [To achieve the objectives of this study, there were five steps in the statistical analysis. In step (a), the amount of variation in the response categories used for each item  was consatistics . Items, analysis ,22,23. Tdata set ,25. In sβi) for for males and females and/or for younger and older respondents. Of these 26 items, 19 had different measurement characteristics for females and for males, 5 items had different measurement characteristics for those aged under 85 and for those aged 85 or over, and 2 items had different measurement characteristics for both males and females and for older and younger respondents. In step (c), 23 items had an item fit statistic p-value of less than 0.01. In addition, 3 items were excluded from further analysis because the value of the item difficulty parameter (βi) was significantly different between two item sets of items. Hence, 79 psychometrically sound items remained in the item bank. A short description of the content of the 79 items in the final version of the calibrated item bank, together with estimates of the dispersion (α) and difficulty (β) parameters and their standard errors, are given in Tables θ do not follow a Normal distribution . In step (d), the full information factor analysis indicated that, for three of the four anchors between the item sets, there was only one latent root of the correlation matrix larger than 1. In the fourth item set, a second latent root was marginally above 1. The percentage of the variance explained by the first factor varied between 67% and 72%. The values of Cronbach's alpha coefficient for the four anchors were between 0.86 and 0.93. The confirmatory factor analysis carried out on the whole data set indicated that 70% of the variance was explained by the first factor. Cronbach's alpha coefficient for the whole data set equalled 0.98. In step (e), the one-parameter logistic item response theory model was fitted to the 79 items remaining after step (c). This model fitted the data significantly less well than the two-parameter model . For 3 items, the item fit statistic had p-value < 0.01. After removal of these items, the two-parameter model was still significantly better than the one-parameter model .Of the 160 items included in the item bank, one was removed because it was worded differently in two different item sets. Of the 159 remaining items, 77 were removed from the item bank. This process is described in Table In this study, the psychometric properties of the item bank have been examined using a sample of 555 respondents and an incomplete calibration design. Each item was presented to between 262 and 293 respondents. These figures are above the minimum, of 200 respondents, regarded as necessary to implement the models used in this paper . It coulθ). This has been examined using item response theory based full-information factor analysis. Part of the full-information factor analysis was performed on sub-sets of the data, as exploratory analyses on incomplete designs may lead to instable results. However, the confirmatory factor analysis was performed on all data. The results, together with the high level of internal consistency, as measured by Cronbach's alpha, and the acceptable fit of the two-parameter logistic item response theory model to the data indicate that the items presented in this paper probably represent a unidimensional construct in a population of respondents requiring residential care.One of the major assumptions underlying the use of the item response theory models described in this paper is that the items reflect a single latent trait (θ) follow a pre-specified, usually Normal, distribution. In this study, there was no evidence that these values did not follow a Normal distribution. This is in contrast to many previously published studies into health and quality of life outcomes, where a strongly skewed distribution was found. The authors feel that there are two reasons for this contrast. Firstly, in this study, the respondents all had some level of restriction in their ability to perform activities of daily life. Secondly, the item bank includes items well above and well below the level of functional status enjoyed by the respondents. This means that the item bank did not have a ceiling or floor effect with respect this this population.Another important assumption when using item response theory models in conjunction with marginal maximum likelihood estimation procedures is that the values of the latent trait (βi) for males and females or for younger and older respondents. This may seem complicated, but is straightforward in the framework of a computerised item bank.In this study, 81 (51%) of 160 items were removed from the item bank because they did not conform to the psychometric standards required of the item bank. This is a much higher level than would be expected in the calibration of an item bank for use in educational measurement. However, when the results are examined more carefully, 28 items were removed because they were too difficult or too easy for the population in this study. In addition, 26 items were removed because they had different item parameters for different groups of respondents. These problems would have been identified much earlier in an educational item bank. Hence, only 26 (25%) of 106 items were removed due to item misfit. The number of items retained in the item bank may have been higher if a more flexible model, based on, for example, non-parametric smoothing techniques had been used [This paper has concentrated on the two-parameter logistic item response theory model. However, the one-parameter logistic item response theory model was also fitted to the 79 items remaining in the item bank. This model fitted the data significantly less well than the two-parameter model, even after 3 items demonstrating misfit at the item level were removed. This confirms the choice of the two-parameter model. This model was chosen because it allows the probability of responding in the category 'can' to be modelled more flexibly than when the one-parameter logistic model is used. This enables a more realistic model for the data to be built than when the more restrictive approach associated with the one-parameter model is chosen .This paper has examined the calibration of the ALDS item bank in a population requiring residential care. It has been shown that the item bank has sound psychometric properties and could form a stable base for a wide range of applications. However, it is possible that the items will have different measurement characteristics for patients requiring treatment for specific chronic conditions or in other countries. Hence, it is important that the ALDS item bank is tested carefully before it is used to assess the functional status in other groups of respondents or in other countries.Now that the measurement properties of the ALDS item bank have been examined carefully, the item bank can be used as a foundation for quantifying functional status. If modern algorithms, such as computerised adaptive testing, are implemented, it will be possible to obtain accurate measurements, whilst keeping the burden of testing on respondents and interviewers to a minimum. Items can be selected for use in further research, for allocation individuals to appropriate care settings and for calculating institutional funding based on the actual care load. It is hoped that the ALDS item bank will play an important part in the implementation of computerised adaptive testing of functional status.βi. This is known as differential item functioning. For instance, if interest is in possible differences in βi between males and females, then the probability, Pik, that patient k responds to item i in the category 'can' is written asThe model in equation 1 can be extended to test whether different groups of respondents to have different values of βiM is the item difficulty for male respondents, βiF-M is the difference between the item difficulty for males and for females and Ik is an indicator variable taking the value 0 if respondent k is male and the value 1 if respondent k is female. The hypothesis H0 : βiF-M = 0 can be tested to examine whether item i has the same measurement characteristics for males and for females.where αi and βi) were estimated using marginal maximum likelihood methods. The likelihood, L, over n items and K (K = 555) respondents can be written asIn this study, the item parameters , can be calculated usingThe value of the standard difficulty parameter, (αim and δi are estimated using marginal maximum likelihood methods.Generally, the parameters ALDS = AMC Linear Disability ScoreNone declared.RH and RL were supported by a grant from the Anton Meelmeijer fonds, a charity supporting innovative research in the Academic Medical Center, Amsterdam, The Netherlands.RL conceived the study and supervised the data collection. RH prepared the first draft and carried out the analyses. RL, MV and RJdH critically reviewed the manuscript. RH prepared the final version.


The Australian Health Care Agreements for the five years 1 July 2003 to 30 June 2008 were signed in August 2003 after vituperative debate and intransigence from the Commonwealth that vitiated the negotiation process. The new Agreements, which were not as generous as the Agreements they replaced, increase accountability on the States, requiring States to match increases in Commonwealth funding, and de-emphasise the prospects for further reform in Commonwealth-State relations during the course of the Agreements. This paper describes the new Australian Health Care Agreements and the process which led to them. The most significant Australian health policy event for 2003 was the signing of the five-year Australian Health Care Agreements. The Agreements were preceded by an ultimatum to the States and Territories from the Commonwealth indicating that there would be no changes from the offer on the table. This led to bitter political recriminations, but the Agreements were eventually signed.In fact important preparations for Agreement renewal occurred in April 2002 with the Commonwealth and State Ministers, in a display of remarkable amity and accord, endorsing a new approach to the Agreements that:• Commonwealth/State relations in the health arena should focus on the provision of optimal care and health outcomes, regardless of jurisdictional boundaries.• It is in the best interests of all Australians for the Commonwealth, Stats and Territories to work co-operatively to improve the health and wellbeing of the community and the way in which health services are provided;• The 2003–08 Agreements should contain the principles, objectives and proposed health outcomes designed to achieve those objections.The Ministers also agreed to establish nine reference groups to address key issues in health reform which would feed into the Agreement "negotiation" process . The refThe reference groups were co-chaired by senior Government officials and non-Government clinical experts involving participants from the bureaucracies, people who work in health agencies, and consumers. The reference groups created great expectations amongst the neophyte health policy contributors who believed the rhetoric of the Commonwealth about being prepared to consider wide ranging changes to the health sector.Seasoned commentators also called for reform -4. AlthoOn 23 April 2003 the Commonwealth produced a non-negotiable offer with severe penalty clauses if States refused to sign by the Commonwealth's arbitrary deadline of 31 August 2003. An Australian Health Reform Alliance was formed to put pressure on the Commonwealth to respond to the reference group reports and to attempt to ensure that the 2003–2008 Agreements did not waste yet another opportunity to improve the efficiency, equity and quality of the health system. The Alliance's National Health Summit, which met at Old Parliament House, presented its final communiqué to non-Government politicians following a march up the hill to New Parliament House . The ComThe Commonwealth's confrontationalist stance effectively destroyed relationships between the Minister for Health and Ageing, Senator Kay Patterson, and her State colleagues, and she was replaced as Health Minister by Tony Abbott MP in the Ministerial reshuffle of October 2003.There have been five Health Care Agreements since Medicare was introduced in 1984. The emphasis, orientation and priorities of these Agreements have changed over time • funding for palliative care, mental health, and safety and quality initiatives.The most contentious difference between the 1998–2003 and 2003–2008 Agreements related to the indexation provisions : its perception that when the Commonwealth increased expenditure on hospital services, this often had no discernible impact on hospitals as State Governments withdrew funding concomitantly. As Deeble points out, the reality is more complex, but the evidence is that an increased Commonwealth share is associated with growth in spending . The newWhy were the processes so acrimonious and what shaped the Agreement outcome? To some extent the shape of the 2003–08 Agreement negotiations was inevitable. The political context, where all state and territory governments were of the opposite political colour from the Commonwealth, meant that harmonious negotiations were probably never seriously in contemplation. Commonwealth governments of both persuasions have tightened up accountability on states with successive Agreements and so tighter control was also probably inevitable. Two important political choices did exacerbate the tensions and inflamed the processes.First, the 2003–08 framework was more parsimonious than predecessor Agreements. As mentioned above, this represented a saving to the Commonwealth of about $1 billion on the Forward Estimates. A contemporary political issue was the decline in bulk billing. The Commonwealth's response to this involved an injection of around $1 billion. The link between the two policy debates within the Health portfolio is clear. Cabinet probably judged the political costs of finding a $1 billion saving from the states as low, as state premiers complaining about Commonwealth cuts and meanness is a regular part of the political landscape. Further, States would probably have criticised the Commonwealth position regardless of the offer made.The second choice that shaped the process was the Commonwealth's intransigence after the drafts were released. The Commonwealth's position here may have been based on a recognition that, eventually, all the states would have to sign the Agreements as they were politically committed to Medicare and free access at point of admission to hospitals, and that the states could not afford to suffer the cash flow consequences announced by the Commonwealth if the Agreements weren't signed by their deadline. The Prime Minister probably took a strong hand in this decision and left no room for his Health Minister to manoeuvre. The Minister's failure to attend meetings exacerbated an already difficult situation.A positive of the process was the extensive involvement of practitioners in the lead-up to the draft Agreements through the Reference Groups. Commonwealth-state negotiations had hitherto been an arcane process involving bureaucratic insiders. This widening of participation was welcomed by those involved and has set a precedent for future negotiations.The 2003–08 Agreements commit the Commonwealth and states to work towards reform in a number of areas including the interface between hospitals, primary care, and aged care; continuity of care particularly in cancer care and mental health services; and continued work on pharmaceuticals reform. A subtle shift from the predecessor Agreement model is the more sceptical and parsimonious approach to the potential for health care reform. Despite the aspirations implicit in establishing the nine reference groups, the language of the 2003–08 Agreements reflects a much more hard-nosed approach to reform with a strong emphasis on efficiency. This approach is most clearly articulated in Clause 18: "The Commonwealth considers that for its part such reforms can take place within existing funding parameters".Although predecessor Agreements also made provision for reform to Commonwealth/State relations, the progress in designing and implementing reform has not lived up to expectations. The most important shift that occurred during the course of the 1998–2003 Agreements was the rationalisation of hospital provision of outpatient pharmacy services, a long overdue response to a significant frictional issue in Commonwealth/States relations .laissez faire attitude by a federal government to its state politically-allied counterparts. A Commonwealth Labor government would be just as keen as its Liberal predecessor to ensure that states are held accountable for maintaining spending and access.It is unclear whether the dynamic, facilitatory aspects of the 2003–08 Agreements will lead to any reform, especially given the acrimonious exchanges prior to signature of the Agreements. However it is important to note that, with a Federal election due at the end of 2004, there is a possibility that a Labor Government will be administering the remainder of the 2003–08 Australian Health Care Agreement. A new Government may be more committed to reforming and strengthening Medicare. However, despite the fact that a Labor would then hold political office throughout Australia, at all levels, this would not necessarily presage a more The author(s) declare that they have no competing interests.


Grewia flava, a common, fleshy-fruited shrub species in the southern Kalahari. Understanding the population dynamics of Grewia flava is a crucial task, because it is widely involved in the shrub/bush encroachment process, a major concern for rangeland management due to its adverse effect on livestock carrying capacity and biodiversity.In Southern Africa savannas climate change has been proposed to alter rainfall, the most important environmental driver for woody plants. Woody plants are a major component of savanna vegetation determining rangeland condition and biodiversity. In this study we use a spatially explicit, stochastic computer model to assess the impact of climate change on the population dynamics of z of the time-shrub density relationship to quantify the population trend. For each climate change scenario we then compared the departure of z from typical stable population dynamics under current climatic conditions. Based on the simulation experiments we observed a positive population trend for scenario (1) and a negative trend for scenario (2). In terms of the projected rates of precipitation change for scenario (3) and (4) population dynamics were found to be relatively stable. However, for a larger increase in inter-annual variation or in temporal auto-correlation of rainfall population trends were negative, because favorable rainfall years had a limited positive impact due to the limited shrub carrying capacity.For our study we consider four climate change scenarios that have been proposed for the southern Kalahari for the coming decades: (1) an increase in annual precipitation by 30–40%, (2) a decrease by 5–15%, (3) an increase in variation of extreme rainfall years by 10–20%, (4) and increase in temporal auto-correlation, i.e. increasing length and variation of periodic rainfall oscillations related to El Niño/La Niña phenomena. We evaluate the slope We conclude that a possible increase in precipitation will strongly facilitate shrub encroachment threatening savanna rangeland conditions and regional biodiversity. Furthermore, the negative effects found for positive auto-correlated rainfall support current ecological theory stating that periodically fluctuating environments can reduce population viability because species suffer disproportionately from poor environmental conditions. In order to assess biodiversity response under climate change, Hannah et al.  recentlyGrewia flava DC, a common, fleshy-fruited, woody plant species of South African savannas. Understanding the population dynamics of Grewia flava is a crucial task, because it is widely involved in the shrub/bush encroachment process (e.g. [2 (e.g. [2 will have a positive effect on the post-fire regrowth of woody plants resulting in an increase in woody plant cover. Unfortunately, appropriate data verifying this hypothesis are not yet available.In this study we show how climate change may affect the long-term population dynamics of the raisin bush, ss e.g. ,10). Shr. ShrGrewss e.g. -13) and  and Grewss (e.g. ). In the[2 e.g. ,16). For. ForGrewSpatial Grewia Model (SGM)  see ,18), a s, a sSpaty plants . Hence, ear 2050 . Furtherear 2050 ), as welear 2050 . The larGrewia flava population dynamics into the SGM  and (2), negative effects associated with an increase in drought events were more effective than the positive effects related to higher recruitment rates associated with comparable rainfall excess . Considering the negative and positive effects of low and high rainfall years, negative effects, such as drought, outweighed positive effects associated with enforced recruitment in high rainfall years.An increase in inter-annual variation between low and high rainfall years below 100% did not cause any significant departure from stable population dynamics. However, above a threshold value of 100%, corresponding to a reduction of PPL) and intra-cycle variation (ICV) led to negative population trends and a decrease in z-value  yielded a z-value of -0.003, whereas population dynamics were stable for an ICV of 70%. Further thresholds were found above 60% ICV for a PL value of 20 years, 50% for 50 years, 40% for 100 years and 15% for 250 years. In the latter case, a large proportion of the population became extinct below 50% ICV where z was close to its lower limit. It is noteworthy, that we found no significant difference between similar PL scenarios that began with different phase conditions.Despite constant mean and inter-annual variation in precipitation, increasing period length . Howeved Figure . Here, foachment . In thisoachment . An incroachment ,25).Grewia flava population dynamics . Even te scarce .SGM produced no significant departure form stable population dynamics . Rat. Rat28])s Figure . Thus, wnsidered .Grewia flava population trend. Above this threshold frequent droughts kill the offspring and inhibit emergence. Ecological theory generally suggest that population viability decreases with increase in environmental variability or stochasticity [An increase in variability of more than 100% revealed a significant threshold behavior with a negative asticity , becauseasticity . HoweverICV, i.e. intra-cycle variation and PL, i.e. period length to evaluate the impact of climate change related increase in positive auto-correlation of rainfall. In our study region, Kruger [PL value of 22 years between 1955 and 1991. The ICV values used in our simulation experiments refer to an increase in the probability of an extreme rainfall category and are thus difficult to compare with the cyclic variability of actual total rainfall. However, we compared the ICV values from our model with departures of annual rainfall from the inter-annual mean of a typical rainfall oscillation provided by Kruger [ICV value above 60% resembles a realistic rainfall variation between favorable and unfavorable periods of a 22-year oscillation. Although we did not find a negative impact on Grewia flava population dynamics for this scenario, a slight increase in ICV combined with an increasing length of El Niño/La Niña phases might have a significant negative impact on the population viability of Grewia flava  outweigh positive effects in wet years (i.e. increased reproduction). This is noteworthy, as mean annual rainfall and inter-annual variation was kept constant. Until now, this has been primarily shown in solely theoretical studies with under-compensating population dynamics . ,32. 31,3cs (e.g. ) or indics (e.g. ). To ourSGM it is important to discuss the inference of actual precipitation amounts on probability values. Threshold values for extreme rainfall years are based on expert knowledge and may vary depending on the plant species considered. Moreover, percentage changes in extreme rainfall years, as applied in our model, are not necessarily equivalent to percentages changes in mean annual rainfall. For example, an increase in 'high' rainfall years by 10% represents an increase in mean annual rainfall of approximately 10%, depending on actual precipitation amounts in each 'high' rainfall year. Thus, it is important to derive principal population trends from the SGM model results rather than absolute predictions. Another issue regards the temporal dimension: long-term SGM simulation periods deviate from short-term predictions of climate change. However, population trends applied for only a few decades may yield biased results due to the cyclicity of Grewia population dynamics (see [In order to assess the predictive power of ics (see ). Finallics (see ).Grewia flava is relatively long-lived, fire and drought-resistant. Intuitively, this would suggest a low climate change impact on Grewia flava population dynamics. However, we found that despite Grewia flava's capability to survive in a harsh environment, it may be strongly affected when rainfall decreases as predicted, or increases in periodical fluctuations. This may also include possible range shifts in regional distribution which have not been studied here. Based on the model and the climate change scenarios analysed, it would be inappropiate to forecasts changes in the geographical distribution of Grewia flava, because SGM parameters have been estimated and validated for populations in the Kimberley region of the southern Kalahari. Moreover, current geographical distribution suggests that buffer mechanisms may facilitate survival in more arid parts of the southern Kalahari .In this study we have shown that climate change may have severe and sometimes unexpected implications at a regional species level. A woody plant like Grewia flava encroachment in the southern Kalahari. However, increase in rainfall will likely enhance this process. A shift from typical open grassland with solitary trees towards wide spread, homogeneous Grewia flava thickets implies negative cascade effects for other species, resulting in the loss of biodiversity [Decrease in rainfall may reduce the severity of iversity . As a fuSGM and previous results have been presented elsewhere . SGM. SGMSGM Grewia flava typically grows beneath the dominant tree species Acacia erioloba [Grewia flava. Under high cattle grazing a substantial proportion of seeds may be distributed into the open matrix vegetation, since cattle feed on the foliage and fleshy fruits of Grewia flava [Grewia cover, particularly around boreholes . Grewiater fire  and low ter fire . Size clter fire .SGM  (i.e. occupied by Acacia erioloba) or matrix type (M) (i.e. grassland vegetation). However, it switched from T to M status when a tree died after a mean life span of 200 years. The converse occurred where a new tree establishes. Initial tree distribution and spatial recruitment pattern was random with a constant density of 5 trees ha-1 for the entire simulation period. In each time step, SGM simulated important life history stages, environmental conditions and the key ecological processes of Grewia flava, the majority of which are governed by annual rainfall patterns  repr reprSGM ari (see ), an ini-1. Rain falls almost exclusively during summer (November to April) with an inter-annual mean of 417 mm for the period 1940 – 2000 (Kimberley airport, South African Weather Service 2001, unpublished data). For this period we defined a threshold value of 150 mm below and above the long-term mean to classify years into 'low', 'average' and 'high' rainfall years (thresholds of 267 mm yr-1and 567 mm yr-1, respectively) . Similar classifications have been applied in other studies, e.g. in a spatial simulation model of Acacia raddiana in the Negev Desert [Annual rainfall in the southern Kalahari is highly variable, with precipitation ranging between 200 and 700 mm yrly) (see ). Accordv Desert .Grewia size classes and may vary depending on the annual rainfall . Seed dia flava  and reprcal data , the assGrewia flava seeds [M and T. However, depending on annual rainfall conditions, the probability of emergence in the model may vary between 1–2% in average and 2–4% in high rainfall years . As survival of Grewia flava seeds in the soil is very low, seeds that do not emerge are assumed to die.Even though microsite types differ markedly in micro-environmental conditions, they do not differ in emergence rates of va seeds  suggestiSGM, fire was simulated probabilistically for the entire grid and may only occur in high and average rainfall years. Average frequency of 7.9 years in the model is supported by fire intervals reported from similar savannah types [T cells, fire mortality probability is 0% for adults and 75% for seedlings. These model assumptions are realistic, since grass fuel accumulation and fire severity beneath trees is less than in tree inter-spaces . In . In SGM,ption in ). Annualption in  and Schuption in . For seeption in ). All seGrewia flava individuals into categories of small , medium-sized  and large plants  as well as seedlings . We assumed a maximum age for each size class member with MaxAgeS = 5 years for small and MaxAgeM = 25 years for medium-sized shrubs. These estimates are based on annual shoot growth rates and aerial photograph analysis of the study area (see [MaxAge is reached, attain the next size class with Ptransition(S) = 0.2 for small and Ptransition(M) = 0.1 for medium-sized shrubs. No growth occurs in low rainfall years.In the model, each shrub was assigned a size class with an average canopy cover. For definition of shrub size classes we used the canopy volume to group rea (see ). In eacK = 25 m2 as maximum total cell shrub cover. If shrub cover exceeded K, individuals in the cell died. Density-dependent mortality was simulated annually by removing the smallest individuals first, i.e. in descending order of size class, until shrub cover <K . Inter-rix (see ). For thz-value, i.e. the slope of the year – shrub density relationship. This is a reasonable approach for analyzing time-abundance relationships . When pBased on the standard scenario we performed simulation experiments for each of the four different scenarios of climate change with variation in inter-annual mean of precipitation, coefficient of inter-annual variation, and temporal auto-correlation . Probability of low rainfall years is constant whereas frequency of average years is reduced, accordingly.(1) increase in precipitation, i.e. stepwise increase of Plow resulting in a higher probability of low rainfall years (increase in drought events),(2) decrease in precipitation, i.e. stepwise increase of Plow and Phigh resulting in a higher probability of low and high rainfall years at the cost of average years ,(3) increase in inter-annual variation of precipitation, i.e. stepwise increase of P(4) increase in temporal auto-correlation of rainfall with 'good' and 'poor' phases.For the scenario (4) we varied two parameters:PL, i.e. longer phases of favorable and unfavorable rain conditions and,(4a) introduction of rain cycles with increasing period length ICV, i.e. increasing variation between alternating favorable and unfavorable periods within one rain cycle.(4b) increase in intra-cycle variation PL we applied a period length of 10, 20, 50, 100 and 250 years, respectively, with each period subdivided into a similarly long 'good' and 'poor' phase. For example, a 10-year period length was subdivided into a 5-year period of superior and a 5-year period of poor conditions. For an increase in ICV we alternately increased and decreased high and low rainfall probabilities in each period, respectively (see 4a and 4b in Table ICV value of 100% Plow equaled 0.00 and Phigh 0.26 in a 'good' phase, whereas values were 0.30 and 0.00, respectively for a 'poor' phase. Through this procedure inter-annual mean and variation of rainfall probabilities were identical for each scenario and the default set of rainfall probabilities. Combined increase in PL and ICV resulted in an increase of positive auto-correlation. Near-decadal epochs of above- and below-normal rainfall have been identified for the period 1955–1991 [ICV under predicted climate change.For SGM simulation model, conceived the study and drafted the manuscript. FJ supervised the study and the manuscript writing. Both authors read and approved the final manuscript.JT developed the


The major site of hematopoiesis transitions from the fetal liver to the spleen and bone marrow late in fetal development. To date, experiments have not been performed to evaluate functionally the migration and seeding of hematopoietic stem cells (HSCs) during this period in ontogeny. It has been proposed that developmentally timed waves of HSCs enter the bloodstream only during distinct windows to seed the newly forming hematopoietic organs. Using competitive reconstitution assays to measure HSC activity, we determined the localization of HSCs in the mid-to-late gestation fetus. We found that multilineage reconstituting HSCs are present at low numbers in the blood at all timepoints measured. Seeding of fetal bone marrow and spleen occurred over several days, possibly while stem cell niches formed. In addition, using dual-chamber migration assays, we determined that like bone marrow HSCs, fetal liver HSCs migrate in response to stromal cell-derived factor-1α (SDF-1α); however, unlike bone marrow HSCs, the migratory response of fetal liver HSCs to SDF-1α is greatly increased in the presence of Steel factor (SLF), suggesting an important role for SLF in HSC homing to and seeding of the fetal hematopoietic tissues. Together, these data demonstrate that seeding of fetal organs by fetal liver HSCs does not require large fluxes of HSCs entering the fetal bloodstream, and that HSCs constitutively circulate at low levels during the gestational period from 12 to 17 days postconception. Newly forming hematopoietic tissues are seeded gradually by HSCs, suggesting initial seeding is occurring as hematopoietic niches in the spleen and bone marrow form and become capable of supporting HSC self-renewal. We demonstrate that fetal and adult HSCs exhibit specific differences in chemotactic behavior. While both migrate in response to SDF-1α, fetal HSCs also respond significantly to the cytokine SLF. In addition, the combination of SDF-1α and SLF results in substantially enhanced migration of fetal HSCs, leading to migration of nearly all fetal HSCs in this assay. This finding indicates the importance of the combined effects of SLF and SDF-1α in the migration of fetal HSCs, and is, to our knowledge, the first demonstration of a synergistic effect of two chemoattractive agents on HSCs. New results on the migratory behavior of blood cell precursors in the early embryo might be relevant to bone marrow transplants and other clinical therapies During fetal development, the primary anatomical concentration of hematopoietic stem cells (HSCs) changes location several times. The migration of blood-borne progenitors is essential for the establishment of hematopoiesis in subsequent hematopoietic tissues . The speWhile the mechanisms that influence HSC homing and colonization are not completely understood, several experimental models suggest possible regulatory factors. The homing to and colonization of fetal hematopoietic organs by circulating HSCs likely require homing receptor/addressin interactions in the vascular lumen, followed by chemokine/chemokine receptor interactions, integrin/receptor binding, and growth/survival factors. Homing of lymphocytes and leukocytes has been well documented to involve first homing receptor/vascular addressin interactions, resulting in cell tethering and rolling on blood vessel endothelium. The rolling cells respond to a chemoattractant, produced by endothelial or stromal cells within the tissue, by firm adherence to the vessel wall mediated by integrin/receptor interactions. The adhered cells subsequently traverse the vessel wall, migrating toward the increasing gradient of chemoattractant . A simil(Sl), normally expressed in hematopoietic stromal cells, or its receptor gene (W), encoding the c-Kit tyrosine kinase, result in profound but incomplete defects in hematopoiesis (d) activity. Our results indicate that mouse fetal HSCs are found constitutively rather than episodically in fetal circulation and are present at low numbers throughout mid-to-late fetal development. We also measured the seeding of the fetal spleen and fetal bone marrow during this period. The seeding of these organs is a gradual process occurring over several days and does not appear to involve a large influx of HSC. Finally, we found that FL HSCs migrate in response to the chemokine SDF-1α and that this response is substantially enhanced in the presence of SLF. The enhanced chemotactic response of HSCs to the combination of SLF and SDF-1α is a property of FL HSCs, but not adult BM HSCs.+ Thy-1.1lo Sca-1+ Lineage– Mac-1lo , was injected into an adult, lethally irradiated congenic recipient, along with a radioprotective dose of host-type bone marrow. A FE was defined as the amount of blood collected from a single fetus of each age group. The amount of fetal blood transplanted ranged from 4 FE to 0.1 FE. The recipient mice were periodically bled and assayed for donor cells of the B, T, and myeloid lineages.  Mac-1lo  can be d Mac-1lo .+ Thy-1.1lo Sca-1+ Lineage– Mac-1lo  begin to seed the fetal spleen and bone marrow on 14.5–15 dpc and 17.5 dpc, respectively. We propose that fetal HSCs are continuously entering circulation and functionally engraft specialized stem cell niches as they develop  donor and C57BL/Ka-Thy-1.2 (Thy-1.2, Ly-5.1) recipient mouse strains were bred and maintained at the Stanford University Laboratory Animal Facility, Stanford, California, United States. All mice were routinely maintained on acidified water (pH 2.5). Irradiated recipient mice were more than 8 wk old at the time of irradiation. All protocols were approved by the Administrative Panel on Laboratory Animal Care at Stanford University School of Medicine.A20.1  and AL1-4A2 (anti-Ly-5.2, CD45.1, Texas Red conjugate) were used to analyze donor and host cells following reconstitution. Blood analysis included 6B2 (anti-B220), KT31.1 (anti-CD3), GK1.5 (anti-CD4), 53-6.7 (anti-CD8), 8C5 (anti-Gr-1), and M1/70 (anti-Mac-1).The monoclonal antibodies used in immunofluorescence staining for HSC analysis included 2B8 (anti-c-Kit, APC conjugate), 19XE5 (anti-Thy-1.1, FITC conjugate), E13 (anti-Sca-1, Ly6A/E, Texas Red conjugate), and M1/70 (anti-Mac-1, PE conjugate). Lineage marker antibodies included 6B2 (anti-B220), KT31.1 (anti-CD3), GK1.5 (anti-CD4), 53-7.3 (anti-CD5), 53-6.7 (anti-CD8), Ter119 (anti-erythrocyte-specific antigen), 8C5 (anti-Gr-1), and M1/70 (anti-Mac-1). The antibodies were purified and conjugated within our lab. Each antibody was titrated and used at predetermined optimal concentrations .Timed pregnancies of C57BL/Ka-Thy-1.1/Ly-5.2 mice were used to obtain embryos. The day the vaginal plug was observed was designated as 0.5 dpc. The uterus was removed and washed to remove maternal blood. Fetuses were carefully removed to prevent contamination with maternal blood. Fetuses were then decapitated in Hanks' balanced salt solution containing 5 mM EDTA and allowed to bleed out. Fetuses were passaged through several dishes of media until completely pale. Blood was combined and centrifuged. Blood was either prepared for injection by sedimenting RBCs in dextran followed by lysis of erythrocytes in 0.15 M ammonium chloride, 0.01 M potassium bicarbonate solution on ice, or remained unmanipulated and was injected directly into recipients. Results from both preparations were comparable. Spleens were obtained by first removing the spleen and stomach to a dish of Hanks' balanced salt solution containing 2% FBS. The spleens were then peeled from the surface of the stomach and placed in a clean dish of media. Femurs and tibia were removed and cleaned of muscle tissue. Spleens and bone were dissociated using the rubber end of a 1 ml-syringe plunger and filtered through nylon mesh. Blood and tissues were collected from fetuses obtained from at least three pregnant females for each timepoint measured. Fetuses that appeared developmentally advanced or delayed in any age group were discarded.5 CD45 congenic (recipient-type) whole bone marrow cells. Recipient mice were periodically bled to analyze peripheral blood for donor B and T lymphocytes and myeloid cells. Recipients were determined to have LT-MLR if all three of these donor subsets were present for greater than 20 wk. Positive engraftment was determined by comparison to control mice, and in most cases the threshold for positivity was less than 0.1%.Adult recipient mice were lethally irradiated with a split dose of 950 rad as previously described . Recipie6 or 1 × 107 cells/ml) of lineage-depleted cells was placed in the upper chamber. To measure chemokinetic movement, factors were also added to the upper chamber at the same concentration as the lower chamber. Following a 2 h incubation, the upper chamber was removed. A known quantity of fluorescent beads was added to the lower chamber for normalization of migrated HSCs. Migrated cells were removed from the lower chamber and stained with PE-conjugated antirat IgG. After washing, cells were incubated with rat IgG and then labeled with directly conjugated lineage PE, c-Kit APC, Sca-1 Texas Red and Thy-1.1 FITC antibodies. Cells were analyzed by FACS to enumerate migrated HSCs.FL HSCs and adult BM HSCs were prepared as for antibody staining. Cells were stained with a lineage cocktail of the same purified rat IgG monoclonal antibodies used for FACS sorting. The cells were then depleted by magnetic selection using anti-rat IgG beads as per manufacturer's instructions , followed by a 1h incubation in RPMI media  containing 10% FBS in a tissue culture flask at 37°C to remove adherent cells. Dual-chamber chemotaxis assays were performed using 24-well plates with 5-μm pore size inserts (Costar/Corning, Corning, New York, United States), as previously described . SDF-1α-t-test. A p value of <0.05 was considered significant.Results shown in www.ncbi.nlm.nih.gov/LocusLink/) accession numbers of the gene products discussed in this paper are CXCR4 (LocusLink ID 12767), SDF-1α (LocusLink ID 20315), and SLF (LocusLink ID 17311).The LocusLink (


Sorghum bicolor is a close relative of maize and is a staple crop in Africa and much of the developing world because of its superior tolerance of arid growth conditions. We have generated sequence from the hypomethylated portion of the sorghum genome by applying methylation filtration (MF) technology. The evidence suggests that 96% of the genes have been sequence tagged, with an average coverage of 65% across their length. Remarkably, this level of gene discovery was accomplished after generating a raw coverage of less than 300 megabases of the 735-megabase genome. MF preferentially captures exons and introns, promoters, microRNAs, and simple sequence repeats, and minimizes interspersed repeats, thus providing a robust view of the functional parts of the genome. The sorghum MF sequence set is beneficial to research on sorghum and is also a powerful resource for comparative genomics among the grasses and across the entire plant kingdom. Thousands of hypothetical gene predictions in rice and Arabidopsis are supported by the sorghum dataset, and genomic similarities highlight evolutionarily conserved regions that will lead to a better understanding of rice and Arabidopsis. Methylation filtration makes practical the sequencing of large genomes, such as those found in sorghum, by preferentially capturing functionally relevant sequences Sorghum bicolor is a vitally important crop in Africa and much of the developing world. It has a remarkable ability to endure both drought conditions and water-logging and it grows well on marginal lands [al lands . It is tal lands . SorghumCardamine amara to 124,000 Mb for a lily (Fritillaria assyriaca) [Genome sequencing in most plants is difficult because of the size and complexity of the genomes. Plant genomes range in size from 54 megabases (Mb) for syriaca) ,4,5,6. Tsyriaca)  and wholsyriaca) . For exasyriaca) ,10, whicsyriaca) . The lar0t selection (C0t is the product of the DNA concentration [C0] and the reassociation time in seconds [t]), allows the separation of low-copy sequences from those of high copy based on annealing rates [0t selection has been used successfully to sequence the low-copy, genic regions of maize [Evidence has accumulated over the last ten years that many plant genomes are separated into large tracts of methylated repeats and stretches of hypomethylated, low-copy gene–rich space ,13,14,15ng rates ,17. Highof maize  and has of maize . The secof maize ,19,20. IWe have applied MF technology to generate sequence from the hypomethylated portion of the sorghum genome. Successful sequencing of fewer than 550,000 MF reads revealed that approximately 96% of the gene set of sorghum has been sequence-tagged, with an average coverage of 65% across their length. Because MF targets genomic sequence within and around genes, many important components of the genome are represented, including promoters, microRNAs (miRNAs), introns, simple sequence repeats (SSRs), and potentially active transposable elements.Arabidopsis and to identify functional elements conserved across different plant species.The sorghum gene space is a powerful resource for comparative genomics within the grass family and across the plant kingdom. The MF dataset can be used to confirm hypothetical genes in complete genomes such as rice and To calculate the genome space sampled by MF, two independent methods were used, genome sampling and gene-enrichment. Genome sampling is an empirical calculation based on a modification of the Lander-Waterman equations , as usedThe gene enrichment method works on the assumption that genes are enriched in the MF libraries in proportion to the reduction in genome size. For example, if the genome is reduced by 3-fold, then gene discovery should occur 3-fold faster in MF versus whole-genome shotgun libraries. The extent to which this number agrees with the genome sampling method is the extent to which the genes reside in the sampled space. We calculate gene enrichment because it can be estimated very early in a sequencing project, whereas the genome sampling method requires at least 0.1× coverage of the sampled space to get an accurate estimate (unpublished data).S. bicolor range from 735 Mb to 858 Mb [The gene enrichment factor is called filter power (FP); we use FP to derive the sampled genome space by dividing it into the size of the whole genome. We calculated the sorghum FP using a subset of our filtered and unfiltered (UF) sequences compared to a curated database of known genes over a range of BLAST Expect values  . The FP o 858 Mb . If 858 Therefore, completely independent estimates of gene space, namely genome sampling and gene enrichment, agree well and are within measurement error. For the purposes of this manuscript, 247 Mb, which is the average of the two methods, will be used as an approximation of the sampled, hypomethylated genome space . The MF Arabidopsis to assess the expected gene identification rate in a completed plant genome where the level of coverage could be controlled precisely in silico (see Expected Gene Tagging, below). The results of these analyses are summarized in The purpose of a genome reduction method such as MF is to identify genes in a robust and efficient manner. We assessed the efficiency of gene discovery by calculating the percentage of known genes tagged as a function of read number for MF and compared this value to the rate of gene discovery obtained by expressed sequence tags (ESTs) for sorghum . Additiohttp://www.ncbi.nlm.nih.gov/). Because the GenBank annotations were outdated, we reannotated the BACs through a custom annotation pipeline  sequences as a source of gene annotations. At the time of analysis, 14 finished sorghum BACs had been deposited in GenBank , upstream, and downstream genomic regions are covered. The average coverage of the CDS regions of all 137 genes is 65%, thus providing a tag across more than half of the gene on average. This coverage is consistent with the 67% nucleotide coverage predicted at 1.15× raw sequence coverage . AdditioFor comparison, the gene tagging ability of the publicly available sorghum EST sequences was assessed. At the time of analysis, there were 161,766 sorghum ESTs deposited in GenBank. Using criteria of 98% identity over at least 50 bp of the CDS, the sorghum ESTs matched 84/137 (61%) of the annotated BAC genes . NotablyArabidopsis chromosome 1 . Since the simulation is set to replicate Lander-Waterman whole-genome shotgun conditions, these results mean that MF obeys the mathematics of Lander-Waterman, although it is a highly fragmented sampling space. Furthermore, if the BAC gene set is representative of the genome, this implies that nearly all the genes in the genome are accessible to MF and that all genes are currently covered over an average of 65% of their length. Theoretically, 100% nucleotide coverage will be reached at 6× coverage, which would require less than 2.5 million additional MF reads.Arabidopsis simulation, the MF reads, and the sorghum ESTs. Notice that the gene tagging for the sorghum ESTs and MF are more rapid than the Arabidopsis simulation. Rather than reflecting a real difference in ability to tag genes using MF versus whole-genome shotgun, this higher rate likely reflects the larger average gene length for the sorghum CDS annotations (3 kb) versus Arabidopsis (2.3 kb), making gene tagging more rapid in sorghum. Additionally, the sorghum ESTs show the most rapid gene-tagging rate, but begin to level off at 60% gene tagging and are passed by the sorghum MF after 70,000 reads.R/N, where R is the total length of repeats in the genome and N is the size of the genome), the unmethylated fraction of repeats , and the filter power (FP) (N/UM) according to Palmer and others [N/UM), we can calculate the proportion of unmethylated repeats (r/R) as ([r/UM]/[R/N])/(N/UM), or approximately 10%. This is consistent with maize [Candystripe1(Cs1) [Cs1 is known to have a low copy number (less than 10) in sorghum, and the redundancy of coverage across the 23% represented suggests that MF is sampling from a single element (unpublished data).Overall, recognizable repeats constitute 62% of the sorghum genome (d others . Given ath maize , and indpe1(Cs1)  is reprepe1(Cs1) . AdditioThe majority of methylation in plants occurs at the canonical sites CG and CNG (where N is any nucleotide) ,25,26,27Arabidopsis proteins, and are therefore considered genes, were compared to a database of all plant proteins using BLASTX. Sequences with more than one high-scoring segment pair and with an E-value of 1 × 10−20 or less were analyzed for the presence of a frame shift. The rate of potential frame shifts for UF is 103/530 (19.4%) versus 1,599/17,103 (9.35%) for MF, indicating that pseudogenes are recovered at a higher rate in UF (comparable to the rate of retrotransposons) and are therefore most likely methylated.The increased frequency of CG and CNG nucleotides in genic sequences recovered by MF versus UF B suggestteosinte branched2 gene (tb2), which was recovered in our dataset, and the kafirin storage protein gene cluster (tb2 (on BAC AF466204) indicates that it is unmethylated . A 247-bp region was selected for PCR close to the 5′ end because of its near identity across all 11 genes and because of the high CG and CNG content B. The me2.46, or approximately 5.5-fold, less DNA in the HhaI + mcrBC double-digested sample. This suggests that two out of the 11 kafirin genes have some unmethylated HhaI sites.As for CG methylation, the HhaI-digested (orange) sample has the same Ct as the mock-treated control (red); however, the Ct of the HhaI + McrBC double digest (green) is 2.46 cycles greater than the mcrBC alone (dark blue), indicating that some HhaI sites must not be modified. A cycle threshold difference of 2.46 indicates that there is 2To determine which kafirin genes might be unmethylated, we sequenced the kafirin PCR products from mcrBC treated and untreated genomic DNA (gDNA). 130 sequences from mcrBC-treated DNA and 126 sequences from the mock-treated sample were analyzed. The kafirin genes fall into “subfamilies” based on six polymorphisms within this highly conserved genomic region see . Each ofIn order to assess how useful the current low level (approximately 1×) coverage of the gene space is for answering important comparative genomics questions, we chose to analyze genes related to drought resistance. Sorghum's ability to grow in arid conditions makes it an attractive source of genes to enhance drought resistance in other grasses. Part of the drought-responsive pathway in plants involves the activation of dehydration-responsive element binding protein (DREB) transcription factors belonging to the APETALA2 (AP2) family. The overexpression of DREB1-encoding genes can promote drought, freezing, and salinity tolerance in transgenic plants .Arabidopsis, rice, and sorghum DREB1-encoding genes suggests that sorghum has expanded the DREB1 family and that SbDREB1–1 and SbDREB1–2 are the closest orthologs to the Arabidopsis DREB1 family  and contain the genomic sequence of gene predictions, which includes exons and introns. The rice set contains 57,535 genes that we categorized into known (23,115), hypothetical (21,438), and repetitive (12,982), based on the annotation  had a match to sorghum MF, while only 38,462 (67%) matched Arabidopsis. The matches can be further broken down by category, with 22,282 (96%) of known rice genes, 13,262 (62%) of hypothetical rice genes, and 10,906 (84%) rice repeats matched by sorghum MF. In comparison, Arabidopsis annotated 20,827 (90%) known, 7,850 (37%) hypothetical, and 9,785 (75%) repeats. Thus, the 1.15× coverage of the closely related sorghum gene space does a much better job of providing supporting evidence for gene predictions in rice than does Arabidopsis. Interestingly, the number of hypothetical genes matched by sorghum MF is almost 2-fold higher than that annotated by Arabidopsis. This may indicate a higher proportion of grass-specific genes in the hypothetical predictions.The rice sequence was used as the query in searches of sorghum MF and Arabidopsis by sorghum MF to that by rice. Such a comparison provides a good test of annotation capacity without being complicated by different evolutionary distances, since Arabidopsis, being dicotyledonous, is expected to be the same evolutionary distance from both sorghum and rice.To understand how well cross-species gene annotation is accomplished in a low-redundancy MF versus a nearly complete genome, we compared the annotation of Arabidopsis protein was considered supported if it had a BLAST match less than or equal to an E-value of 1 × 10−8 (An 1 × 10−8 . In thisArabidopsis proteins than sorghum, the set is not completely overlapping, and sorghum matches 247 proteins that are not matched by the rice sequences. Since we used rice gene predictions as our database for comparison, it is likely that some of the Arabidopsis proteins are in the genome but are not annotated as genes. To address this possibility, we compared the 247 Arabidopsis proteins to the entire rice genome (Oryza sativa japonica) and found that 59 did indeed match to the bare gDNA versus the annotations, and therefore were not unique to the sorghum-Arabidopsis genomes. That left 188 proteins that may be conserved in sorghum and Arabidopsis, but not in rice. The O. s. japonica genome was sequenced by the BAC-by-BAC method [O. s. indica genome, which was sequenced by whole-genome shotgun [Arabidopsis proteins that are supported by sorghum but either missing from or significantly diverged in the current versions of the O. s. japonica and O. s. indica genomes  assemblies, with 121, 16, and 88 of the rice miRNAs and 52, 10, and 46 of the Arabidopsis miRNAs matching, respectively.We downloaded 122 and 92 known rice and ectively , and usem MF set . For comTo ensure that these were authentic matches and not just due to chance, we performed a test with shuffled miRNA sequences, maintaining the nucleotide composition see . None ofArabidopsis and rice would also be conserved between Arabidopsis and sorghum. Therefore, given that the rice genome is nearly complete, we expect to find the same 52 Arabidopsis miRNAs in sorghum, and we have identified 44 (85%). The eight that are missing may be present in the data but not identified because of sequencing errors; not yet sampled, as we expect only approximately 66% of the nucleotides to be present at this level of coverage; or some of these eight may represent miRNAs conserved in rice but lost in sorghum.We do not know a priori how many of the rice miRNAs would be expected to be conserved in sorghum, but we can assume that most, if not all, of the miRNAs conserved between SSRs are stretches of DNA with simple sequence pattern repetitions, usually in the form of di-, tri-, or tetra-nucleotide expansions such as (CA)n, (CAG)n, or (GATA)n. These stretches of DNA are useful for genetic marker analysis, because they are unstable and often are polymorphic between closely related individuals ,41. OverSaccharum spp.), whose large and variable chromosome content makes genome sequencing impractical. The availability of a large number of sugarcane EST sequences [The sequence of the sorghum gene space provides an excellent tool for comparative genomics . Unlike equences  will enaequences . The seqArabidopsis nearly as well as the completed rice genome and by the ability to identify 95% of the genes from finished sorghum BACs. This was achieved with a minimal sequencing effort, which brings within reach the prospect of sequencing multiple strains of the same species. Such a feat is of critical importance in maize, in which inbred lines differ substantially in gene order and content [The sorghum gene set present in the MF data is very nearly complete, as illustrated by the ability to annotate  content ,49.0t selection, or MF, is that the recovered fragments are not positioned on the genome. Mapping has to be accomplished by either mapping the reads to a physical or genetic map or by combining the gene enrichment with an anchored clone map. MF reads are enriched for SSRs, which make good genetic markers and allow some reads to be placed on a genetic map. If a framework physical map of fingerprinted BAC clones exists, then MF can be easily integrated onto the physical map in three ways: PCR mapping to BAC pools, hybridization to BAC filters, and/or by sequence integration. Sequence integration can be accomplished using either BAC end sequence or shotgun sequence from a representative tiling path of the BAC contigs. While there is no whole genome BAC map of sorghum yet available, a robust map is almost complete in maize [A disadvantage of gene enrichment strategies, whether they are EST sequencing, high Cin maize ,51. It iin maize . BAC seqin maize , which cS. bicolor ATX623, kindly provided by J. Osborne (NC+ Hybrids, Colwich, Kansas, United States), were germinated and grown in soil under growth chamber conditions. Then gDNA was purified from isolated nuclei of 1-mo-old leaves as described [E. coli for generation of MF and UF libraries respectively. Recombinant clones were picked using Genetix Q-bot robot  and stored individually in 384-well microtiter plates.Seeds of escribed , except Two sources of MF sequencing reads were used. Out of 604,641 attempts at Orion Genomics, 532,150 were successful (accession numbers CL147592–CL197752 and CW020594–CW502582), 514,983 of which are considered of nuclear origin based on comparison with chloroplast, mitochondrial, viral, and bacterial databases. Additionally, we have included 36,825 sorghum MF reads previously generated at Cold Spring Harbor Laboratories (Cold Spring Harbor, New York, United States) (accession numbers CC058553–CC059980, BZ329127–BZ342789, BZ342901–BZ352342, BZ365856–BZ368372, BZ369686–BZ370012, BZ421595–BZ424357, BZ625682–BZ629992, and BZ779555–BZ781928). The sorghum UF sequences also came from two sources: Orion Genomics (1,819 reads) (accession numbers CW512190–CW514008) and the University of Oklahoma (15,889 reads) (NCBI TraceDB accession numbers TI566112507–TI566128395). The average read lengths were 600 bp and 550 bp for each class of reads, giving a total, raw nuclear dataset of approximately 330 Mb (MF) and 10.5 Mb (UF). The MF dataset was further collapsed by assembling overlapping read pairs to generate a set of independent sampling events comprising approximately 285 Mb.We have done a first pass definition-line curation of publicly available sequence databases to eliminate obvious transposon sequences that would hamper subsequent analyses by virtue of inflating the true “gene” content of the given database.Arabidopsis protein set, which was used for the gene enrichment calculations and assessment of cross-genome annotation potential, was downloaded from the NCBI . The files were dated 23 May 2003 and contained 28,581 sequences . Repeats were removed from this dataset if the definition line meets both of the following two criteria: (1) Matched the case-insensitive regular expression “/retro|mutator|transpos|reverse transcriptase|polyprotein|\bgag\b|BARE-1|athila/”, and (2) did not match “/\[.*retro.*\]|leucine|WD-repeat|WD repeat|WD40|WD-40| ankyrin|telomere|arm repeat|PPR-repeat|armadillo|tetratricopeptide|TPR-repeat|TPR repeat|Kelch|pentapeptide|C-repeat/”.The This second step was used to replace falsely identified nonrepetitive elements. Removing repeats reduced the database size by 640 sequences to 27,941, which included 4,412 sequences identified as hypothetical by matching the definition line to the case-insensitive regular expression “/hypothetical/.”ftp://ftp.tigr.org/pub/data/Eukaryotic_Projects/o_sativa/annotation_dbs/pseudomolecules/version_2.0/all_chrs/all.seq). The file was dated 30 April 2004 and contained 57,535 sequences . The rice sequence set contains the genomic regions for all predicted rice genes, which includes exons, introns, and untranslated regions where good evidence is provided. No sequences were removed from this database, but they were classified as “repeats,” “hypothetical,” and “known” by the following criteria. (1) Sequences were classified as repeats if the definition line matched a case-insensitive regular expression “/retro|transpos|reverse transcriptase|gag|polyprotein|mutator|maggy|rire|gypsy|copia|bare-1/”; (2) the sequences were classified as hypothetical if the definition line matched a case-insensitive regular expression “/hypothetical/”; and (3) the remaining sequences were classified as known. In total, there were 13,008 repeats, 21,441 hypotheticals, and 25,263 known proteins. The rice chromosomal genomic sequences were used for miRNA identification  and dated 05 September 2003. It contains 12 chromosomes, with sequences comprising 358,546,960 bases.The rice sequence set was downloaded from TIGR . No sequences were removed from this database.Sorghum ESTs were download from the NCBI  of the curated base see . Aside fabulated . For sorThere were 14 finished BAC clones at the time of analysis, with the following accession numbers (and GenInfo identifiers). AC120496.1 (GI:20486389), AF010283.1 (GI:2735839), AF061282.1 (GI:4539654), AF114171.1 (GI:4680196), AF124045.1 (GI:5410347), AF369906.1 (GI:19851516), AF466199.1 (GI:18390096), AF466200.1 (GI:18481699), AF466201.1 (GI:18483227), AF466204.1 (GI:18568251), AF503433.1 (GI:21326110), AF527807.1 (GI:22208458), AF527808.1 (GI:22208471), and AF527809.1 (GI:22208503). The BACs were manually annotated, then reads were mapped to the BACs by BLAST to determine the locations of hits relative to the genes.ftp://ftp.tigr.org/pub/data/TIGR_Plant_Repeats/) and contained 11,043 repeat entries. RepeatMasker was run with the following parameters: “-s; -w; -no_is; -nolow; -lib cereal_repbase.lib”. RepeatMasker parameters also included “-xsmall” to mask in lowercase and “-w” to use the MaskerAid [N=–1; Q=3; R=3; kap; E=1e-10; hspmax=0. To look for potentially novel genes, we used Fgenesh (http://www.softberry.com/berry.phtml) with monocot parameters, Genscan [Arabidopsis parameters, and SNAP [Arabidopsis parameters.We analyzed the BACs with several computational tools in addition to manual editing. Repetitive elements were identified using RepeatMasker  with theaskerAid  enhancemaskerAid ,56 usingaskerAid . The fir Genscan  with Araand SNAP  with Arahttp://www.acedb.org) and edited gene structures by hand. One of the challenges was how to determine when the tools had identified pseudogenes. These are often marked by adjacent repeats, BLASTX alignments containing stop codons, or gene predictions with tiny introns to compensate for frame-shifts. Another challenge was how to use cross-species alignments. Alignments that are nearly identical to genomic sequence are useful for delimiting exon boundaries, but inexact matches pose problems because alignments may terminate because of real exon boundaries or differences between the sequences. Since most of the alignments were from plants other than S. bicolor, we did not employ any programs that align a protein or transcript directly to a genome. Instead, we assigned the position of the splice sites in part by consulting exon predictions, since gene finding algorithms contain probabilistic models of splice sites. We did not report any raw gene predictions. However, some genes do contain exons with no overlapping evidence and are included in the gene structure because they complete an otherwise incomplete gene structure and in some cases are necessary to maintain the reading frame. The BAC annotations are available in GFF format with the supplemental online data.In order to annotate the locations of genes in each BAC, we loaded all the computational results into the ACEDB viewer . A sequence was considered mapped to a BAC if the match was over 90% of the read with 98% identity or higher. A single read was mapped to only one location. A gene was considered tagged if one or more MF sequence(s) overlapped the CDS region by 50 bases or more. The set of Arabidopsis chromosome 1 was compared to the empirical gene tagging results in sorghum. The sequence and annotation of Arabidopsis chromosome 1 was downloaded from TIGR  on 20 February 2004. The chromosome is approximately 30 Mb long with 7,520 genes annotated. The median gene size is 1,960 bp.A computational simulation of shotgun sequencing Computationally generated “reads” of 700 bp in length were created from the chromosome for different levels of raw coverage from 0.5× up to 3.5×. The reads were then mapped back to the chromosome annotation to determine the percentage of the 7,520 genes that were tagged at each level of raw coverage .The lleagues . This daU-BLASTN  search oArabidopsis miRNAs. The shuffling maintains the nucleotide composition of each while scrambling the order [In order to test the specificity of these miRNA matches, we generated shuffled sequences for the 122 rice and 92 he order . The shu−8, which corresponds to a bit score of approximately 61. The rice hits were then counted and categorized.The rice sequences were compared to the sorghum MF using NCBI-BLASTN with the rice sequences as the query and the sorghum MF reads as the database . We counted a rice gene as hit if the E-value was less than or equal to 1 × 10Arabidopsis protein set using NCBI-BLASTX . We counted a rice gene as hit if the E-value was less than or equal to 1 × 10−8, which corresponds to a bit score of approximately 51. The rice genes hit were counted and categorized.To assess how well rice is annotated by a dicot, the rice sequences were also searched against the Arabidopsis protein set was compared the sorghum MF dataset using NCBI-TBLASTN . We counted an Arabidopsis protein as hit if the E-value was less than or equal to 1 × 10−8, which corresponded to a bit score of approximately 57. The Arabidopsis hits were then counted and categorized as shown in The Arabidopsis protein set was also compared to the rice gene sequence dataset using NCBI-TBLASTN . We counted an Arabidopsis protein as hit if the E-value was less than or equal to 1 × 10−8, which corresponded to a bit score of at least 57. The Arabidopsis hits were then counted and categorized as shown in The Arabidopsis proteins that were annotated by sorghum MF but not rice sequence. These 247 proteins were then compared to the entire rice genome using NCBI-TBLASTN . From that set of 247 we removed any Arabidopsis proteins if the E-value was less than or equal to 1 × 10−8, which corresponded to a bit score of at least 59. The remaining 188 proteins were then compared to the entire genome from the O. s. indica cultivar of rice [Arabidopsis proteins if the E-value was less than or equal to 1 × 10−8, which corresponded to a bit score of approximately 60. The resulting set contained 127 Arabidopsis proteins that were supported by sorghum MF but not found in the rice genomes.There were 247  of rice  using NCMethylation was assessed using MethylScreen analysis, which is a real-time PCR technique that reports DNA methylation occupancy information for genomic markers through enzymatic interrogation. MethylScreen analysis compares the cycle thresholds (Cts) of gDNA that has been subjected to various treatments and infers 5′ methylated cytosine (5 mC) occupancy through the changes in Ct mediated by the treatments. The Ct of any locus is a function of the number of copies present within the assay tube. MethylScreen analysis relies upon the simple formula that total gene copies = number of methylated copies + number of unmethylated copies in every sample. Typical sample assays utilize four sample subportions, the first portion of a sample is mock-digested, reporting total copies present. A second  portion is treated with a methylation-sensitive restriction enzyme (MSRE), reporting the number of gene copies that are methylated. The third portion is digested with a methylation-dependent restriction enzyme (MDRE) such as mcrBC, reporting the number of copies that are unmethylated. The fourth reaction is doubly-digested with both the MSRE and MDRE. When working with relatively pure samples, methylated loci have a Ct from MSRE that is the same as the untreated control, and the Ct obtained from the MDRE is greater. Conversely, unmethylated loci have a MDRE Ct that is identical to untreated and a greater Ct in the MSRE reaction.tb2 targeted a 263 bp region from the 5′ end of the gene for the assay. There are four HhaI restriction sites and more than 25 possible mcrBC half-sites (5′-RC-3′) in this region .The gene s region A. We devtb2 gene. Cycling parameters were 95 °C for 3 min, followed by 50 cycles of two-step PCR: 95 °C for 30 s and 56 °C for 30 s. We utilized both a low-temperature (70 °C) and a high-temperature (82 °C) plate read. The input of gDNA was cut to 10 ng per reaction. All amplifications were performed in quadruplicate. Three replicate analyses were performed (digestions and cycling). The threshold was set using a template dilution standard control. For the kafirin genes, the average difference in Ct between the mcrBC single and the HhaI + McrBC double-digests is 2.46 cycles (22.08 ± 0.34 HhaI + McrBC - 19.62 ± 0.19 McrBC).Each of the 11 genes was broken into approximately 1.5-kb pieces, which were aligned to create a consensus kafirin assembly B. The coPCR products from the kafirin cycling reactions were cloned using the topoisomerase-assisted method . Libraries of insert-bearing clones were generated using standard techniques. From each library, 200 lacZ-negative clones were selected for characterization. The clones were sequenced with a single read using the M13 priming site on the pCR2.1 plasmid (Invitrogen). All seven subfamilies were discovered from both the treated and untreated genomic samples (unpublished data), indicating that all 11 genes were amplified and recoverable, even in the mcrBC-digested fractions.Arabidopsis DREB genes DREB1A, DREB1B, DREB1C, DREB2A, and DREB2B were used in a TBLASTN search of an assembly the sorghum dataset using WU-BLAST . Matches to the sorghum assembly with an E-value of 1 × 10−8 or less were analyzed with FGENESH (monocot) to select assemblies with a full-length protein. Out of 67 full length proteins identified in this manner, five sorghum proteins were identified as DREB1 genes based on conservation of the AP2 domain and a conserved C-terminal motif, LWSY [The five if, LWSY .Table S1Arabidopsis proteins that have matches to the sorghum MF set at a TBLASTN E-value less than or equal to 1 × 10−8, but are not found in the O. s. japonica or O. s. indica genomes at the same cutoff.Shown is a list of 127 (120 KB DOC).Click here for additional data file.http://www.ncbi.nlm.nih.gov/). On 6 January 2004, Orion deposited 50,161 of the sequences under accession numbers CL147592–CL197752. The 36,825 Cold Spring Harbor Laboratories MF sequences were previously deposited in GenBank under the accession numbers CC058553–CC059980, BZ329127–BZ342789, BZ342901–BZ352342, BZ365856–BZ368372, BZ369686–BZ370012, BZ421595–BZ424357, BZ625682–BZ629992, and BZ779555–BZ78192. The remaining 481,989 MF sequences from Orion Genomics are deposited in GenBank under accession numbers CL147592–CL197752 and CW020594–CW502582. The Orion UF sequences are deposited in GenBank's Genome Survey Sequence under accession numbers CW512190–CW514008. The University of Oklahoma UF sequences are deposited in the NCBI trace archive under accession numbers TI566112507–TI566128395. GenBank accession numbers for other genes discussed in this paper are sorghum Cs1 (AF206660); Arabidopsis DREB genes DREB1A (Q9M0L0), DREB1B (P93835), DREB1C (Q9SYS6), DREB2A (O82132), and DREB2B (O82133). Genbank accession numbers for BAC clones (with GenInfo identifiers) are AC120496.1 (GI:20486389), AF010283.1 (GI:2735839), AF061282.1 (GI:4539654), AF114171.1 (GI:4680196), AF124045.1 (GI:5410347), AF369906.1 (GI:19851516), AF466199.1 (GI:18390096), AF466200.1 (GI:18481699), AF466201.1 (GI:18483227), AF466204.1 (GI:18568251), AF503433.1 (GI:21326110), AF527807.1 (GI:22208458), AF527808.1 (GI:22208471), and AF527809.1 (GI:22208503). The GenBank accession number for the protein CAPRICE is NP_182164. Accession numbers for genes used in phylogenetic analysis of sorghum DREB are as follows. Rice genes are OsDREB1A (AF300970), OsDREB1B (AF300972), OsDREB1C (AP001168, nucleotides 142337–142981), and OsDREB1D (AB023482, nucleotides1489–2250); AP2 domains from other Arabidopsis proteins are also included: APETALA2 (R2 domain, accession number P47927), AtERF-1 (BAA32418), LEAFY PETIOLE (AAF32292), and TINY (Q39127).The sorghum MF sequence set is deposited in the Genome Survey Sequence division of GenBank (