Detecting quantitative trait loci affecting beef tenderness on bovine chromosome 7 near calpastatin and lysyl oxidase

From a study of 3 large half-sib families of cattle, we describe linkage between DNA polymorphisms on bovine chromosome 7 and meat tenderness. Quantitative trait loci (QTL) for Longissimus lumborum peak force (LLPF) and Semitendonosis adhesion (STADH) were located to this map of DNA markers, which includes the calpastatin ( CAST) and lysyl oxidase (LOX) genes. The LLPF QTL has a maximum lodscore of 4.9 and allele substitution of approximately 0.80 of a phenotypic standard deviation, and the peak is located over the CAST gene. The STADH QTL has a maximum lodscore of 3.5 and an allele substitution of approximately 0.37 of a phenotypic standard deviation, and the peak is located over the LOX gene. This suggests 2 separate likelihood peaks on the chromosome. Further analyses of meat tenderness measures in the Longissimus lumborum, LLPF and LL compression (LLC), in which outlier individuals or kill groups are removed, demonstrate large shifts in the location of LLPF QTL, as well as confirming that there are indeed 2 QTL on bovine chromosome 7. We found that both QTL are reflected in both LLPF and LLC measurements, suggesting that both these components of tenderness, myofibrillar and connective tissue, are detected by both measurements in this muscle.

Isolation, characterization and mapping of temperature-sensitive mutants of mycobacteriophage I3

Eighteen temperature-sensitive mutants of mycobacteriophage I3 have been isolated and partially characterized. All the mutants were defective in vegetative replication. Based on temperature shift experiments with the temperature sensitive mutants, the thermosensitive phase of the phage development period has been characterized for each mutant. The genes have been mapped by recombination analysis. The early, continuous and middle genes seem to cluster on the genetic map

Liquefaction Hazard Mapping of Bangalore, South India

his paper presents identification and mapping of vulnerable and safe zones for liquefaction hazard. About 850 bore logs data collected from geotechnical investigation reports have been used to estimate the liquefaction factor of safety for Bangalore Mahanagara palike (BMP) area of about 220 km(2). Liquefaction factor of safety is arrived based on surface level peak ground acceleration presented by Anbazhagan and Sitharam(5) and liquefaction resistance, using corrected standard penetration test (SPT) N values. The estimated factor of safety against liquefaction is used to estimate liquefaction potential index and liquefaction severity index. These values are mapped using Geographical information system (GIS) to identify the vulnerable and safe zones in Bangalore. This study shows that more than 95% of the BMP area is safe against liquefaction potential. However the western part of the BMP is not safe against liquefaction, as it may be subjected to liquefaction with probability of 35 to 65%. Three approaches used in this study show that 1) mapping least factor of safety irrespective of depth may be used to find liquefiable area for worst case. 2) mapping liquefaction potential index can be used to assess the liquefaction severity of the area by considering layer thickness and factor of safety and 3) mapping of liquefaction severity index can be used to access the probability of liquefaction of area.

Identification of quantitative trait loci for resistance to two species of root-lesion nematode (Pratylenchus thornei and P. neglectus) in wheat

Pratylenchus thornei and P. neglectus are two species of root-lesion nematode that cause substantial yield losses in wheat. No commercially available wheat variety has resistance to both species. A doubled-haploid population developed from a cross between the synthetic hexaploid wheat line CPI133872 and the bread wheat Janz was used to locate and tag quantitative trait loci (QTLs) associated with resistance to both P. thornei and P. neglectus. Wheat plants were inoculated with both species of nematode in independent replicated glasshouse trials repeated over 2 years. Known locations of wheat microsatellite markers were used to construct a framework map. After an initial single-marker analysis to detect marker-trait linkages, chromosome regions associated with putative QTLs were targetted with microsatellite markers to increase map density in the chromosome regions of interest. In total, 148 wheat microsatellite markers and 21 amplified fragment length polymorphism markers were mapped. The codominant microsatellite marker Xbarc183 on the distal end of chromosome 6DS was allelic for resistance to both P. thornei and P. neglectus. The QTL were designated QRlnt.lrc-6D.1 and QRlnn.lrc-6D.1, for the 2 traits, respectively. The allele inherited from CPI133872 explained 22.0-24.2% of the phenotypic variation for P. thornei resistance, and the allele inherited from Janz accounted for 11.3-14.0% of the phenotypic variation for P. neglectus resistance. Composite interval mapping identified markers that flank a second major QTL on chromosome 6DL (QRlnt.lrc-6D.2) that explained 8.3-13.4% of the phenotypic variation for P. thornei resistance. An additional major QTL associated with P. neglectus resistance was detected on chromosome 4DS (QRlnn.lrc-4D.1) and explained a further 10.3-15.4% of the phenotypic variation. The identification and tagging of nematode resistance genes with molecular markers will allow appropriate allele combinations to be selected, which will aid the successful breeding of wheat with dual nematode resistance.

Mapping of adult plant resistance to net form of net blotch in three Australian barley populations

Net form of net blotch (NFNB), caused by Pyrenophora teres Drechs. f. teres Smedeg., is a serious disease problem for the barley industry in Australia and other parts of the world. Three doubled haploid barley populations, Alexis/Sloop, WI2875-1/Alexis, and Arapiles/Franklin, were used to identify genes conferring adult plant resistance to NFNB in field trials. Quantitative trait loci (QTLs) identified were specific for adult plant resistance because seedlings of the parental lines were susceptible to the NFNB isolates used in this study. QTLs were identified on chromosomes 2H, 3H, 4H, and 7H in both the Alexis/Sloop and WI2875-1/Alexis populations and on chromosomes 1H, 2H, and 7H in the Arapiles/Franklin population. Using QTLNetwork, epistatic interactions were identified between loci on chromosomes 3H and 6H in the Alexis/Sloop population, between 2H and 4H in the WI2875-1/Alexis population, and between 5H and 7H in the Arapiles/Franklin population. Comparisons with earlier studies of NFNB resistance indicate the pathotype-dependent nature of many resistance QTLs and the importance of establishing an international system of pathotype nomenclature and differential testing.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

A method for mapping the distribution and density of rabbits and other vertebrate pests in Australia

The European wild rabbit has been considered Australia’s worst vertebrate pest and yet little effort appears to have gone into producing maps of rabbit distribution and density. Mapping the distribution and density of pests is an important step in effective management. A map is essential for estimating the extent of damage caused and for efficiently planning and monitoring the success of pest control operations. This paper describes the use of soil type and point data to prepare a map showing the distribution and density of rabbits in Australia. The potential for the method to be used for mapping other vertebrate pests is explored. The approach used to prepare the map is based on that used for rabbits in Queensland (Berman et al. 1998). An index of rabbit density was determined using the number of Spanish rabbit fleas released per square kilometre for each Soil Map Unit (Atlas of Australian Soils). Spanish rabbit fleas were released into active rabbit warrens at 1606 sites in the early 1990s as an additional vector for myxoma virus and the locations of the releases were recorded using a Global Positioning System (GPS). Releases were predominantly in arid areas but some fleas were released in south east Queensland and the New England Tablelands of New South Wales. The map produced appears to reflect well the distribution and density of rabbits, at least in the areas where Spanish fleas were released. Rabbit pellet counts conducted in 2007 at 54 sites across an area of south east South Australia, south eastern Queensland, and parts of New South Wales (New England Tablelands and south west) in soil Map Units where Spanish fleas were released, provided a preliminary means to ground truth the map. There was a good relationship between mean pellet count score and the index of abundance for soil Map Units. Rabbit pellet counts may allow extension of the map into other parts of Australia where there were no Spanish rabbit fleas released and where there may be no other consistent information on rabbit location and density. The recent Equine Influenza outbreak provided a further test of the value of this mapping method. The distribution and density of domestic horses were mapped to provide estimates of the number of horses in various regions. These estimates were close to the actual numbers of horses subsequently determined from vaccination records and registrations. The soil Map Units are not simply soil types they contain information on landuse and vegetation and the soil classification is relatively localised. These properties make this mapping method useful, not only for rabbits, but also for other species that are not so dependent on soil type for survival.

A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

DNase I Site Mapping and Micrococcal Nuclease Digestion of Pachytene Chromatin Reveal Novel Structural Features

A comparison of the DNase I digestion products of the 32P-5’-end-labeled pachytene nucleosome core particles (containing histones H2A, TH2A, X2, H2B, THPB, H3a, nd H4) and liver nucleosome core particles (containing somatic histones H2A, H2B, H3, and H4) revealed that the cleavage sites that are 30, 40, and 110 nucleotidesa way from the 5’-enda re significantly more accessiblei n the pachytene core particles than in the liver core particles. These cleavage sites correspond to the region wherein H2B interacts with the nucleosome core DNA. These results, therefore, suggest that the histone-DNA interactiona t these sites in the pachytene core particles is weaker, possibly because of the presence of the histone variant THBB interacting at similar topological positions in the nucleosome core as that of its somatic counterpart H2B. Such a loosened structumrea y also be maintainede ven in the native pachytene chromatin since micrococcal nuclease digestion of pachytene nuclei resulted in a higher ratio of subnucleosomes (SN4 + SN?) to mononucleosomes than that observed liinv er chromatin

Queensland Coastal Wetlands Resources Mapping Data

1:100,000 coastal wetland vegetation mapping for Queensland including mangrove communities, saltpans and saline grasslands. Mapping taken from Landsat TM images with ground truthing. Additional metadata is available for details of techniques and accuracy for each section of coastline. Data Currency for each section of coast: NT border to Flinders River - 1995 SE Gulf of Carpentaria - 1987, 1988, 1991, 1992 Cape York Peninsula - 1986-88, 1991 Cape Trib to Bowling Green Bay - 1997-99 The Burdekin Region - 1991 The Bowen Region - 1994-95 The Whitsunday Region - 1997 Repulse Bay - 1989 Central Qld - 1995, 1997 The Curtis Coast Region - 1997 Round Hill Head to Tin Can Inlet - 1997 Moreton Region - 1995. Article Links: 1/ #1662. Queensland Coastal Wetland Resources: the Northern Territory Border to Flinders River. Project Report. Information Series QI00099. 2/ #1663. Queensland Coastal Wetland Resources: Sand Bay to Keppel Bay. Project Report. Information Series QI00100. 3/ #1664. Queensland Coastal Wetland Resources: Cape Tribulation to Bowling Green Bay. Project Report. Information Series QI01064. 4/ #1666. Coastal Wetlands Resources Investigation of the Burdekin Delta for declaration as fisheries reserves. Report to Ocean Rescue 2000. Project Report. 5/ #1667. Queensland Coastal Wetland Resource Investigation of the Bowen Region: Cape Upstart to Gloucester Island. Project Report. 6/ #1784. Resource Assessment of the Tidal Wetland Vegetation of Western Cape York Peninsula, North Queensland, Report to Ocean Rescue 2000. Project Report. 7/ #1785. Marine Vegetation of Cape York Peninsula. Cape York Peninsula Land Use Strategy. Project Report. 8/ #3544. Queensland Coastal Wetland Resources: The Whitsunday Region. Project Report.Information Series QI01065. 9/ #3545. Queensland Coastal Wetland Resources: Round Hill Head to Tin Can Inlet. Project Report. Information Series QI99081.

Genome-wide mapping of cystitis due to Streptococcus agalactiae and Escherichia coli in mice identifies a unique bladder transcriptome that signifies pathogen-specific antimicrobial defense against urinary tract infection

The most common causes of urinary tract infections (UTIs) are Gram-negative pathogens such as Escherichia coli; however, Gram-positive organisms including Streptococcus agalactiae, or group B streptococcus (GBS), also cause UTI. In GBS infection, UTI progresses to cystitis once the bacteria colonize bladder, but the host responses triggered in the bladder immediately following infection are largely unknown. Here, we used genome-wide expression profiling to map the bladder transcriptome of GBS UTI in mice infected transurethrally with uropathogenic GBS that was cultured from a 35 year-old women with cystitis. RNA from bladders was applied to Affymetrix Gene-1.0ST microarrays; qRT-PCR was used to analyze selected gene responses identified in array datasets. A surprisingly small significant gene list of 172 genes was identified at 24h; this compared to 2507 genes identified in a side-by-side comparison with uropathogenic E. coli (UPEC). No genes exhibited significantly altered expression at 2h in GBS-infected mice according to arrays despite high bladder bacterial loads at this early time point. The absence of a marked early host response to GBS juxtaposed with broad-based bladder responses activated by UPEC at 2h. Bioinformatics analyses including integrative systems-level network mapping revealed multiple activated biological pathways in the GBS cystitis transcriptome that regulate leukocyte activation, inflammation, apoptosis, and cytokine-chemokine biosynthesis. These findings define a novel, minimalistic type of bladder host response triggered by GBS UTI, which comprises collective antimicrobial pathways that differ dramatically from those activated by UPEC. Overall, this study emphasizes the unique nature of bladder immune activation mechanisms triggered by distinct uropathogens.

Mapping the integrity of differential obligations within the United Nations framework convention on climate change

This chapter unpacks public institutional integrity concepts through an examination of differential obligations within the global climate regime.

CYP19A1 fine-mapping and Mendelian randomization: Estradiol is causal for endometrial cancer

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8x10(-11)). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4x10(-8)). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11-1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03-1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.

Mapping compositional parameters of cocoa to sensory profiles

This project will establish an innovative quantitative analytical technique which will assist the development of Queensland's cocoa industry through a better understanding of those components that can produce unique sensory and flavour profiles of cocoa products.

Functional evaluation of genetic variants associated with endometriosis near GREB1

STUDY QUESTION: Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER: We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN: Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION: Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE: Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. LIMITATIONS, REASONS FOR CAUTION: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. WIDER IMPLICATIONS OF THE FINDINGS: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. STUDY FUNDING/COMPETING INTERESTS: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests.