A universal test to determine the integrity of RNA, and its suitability for reverse transcription, in animal tissue laboratory specimens

Degradation of RNA in diagnostic specimens can cause false-negative test results and potential misdiagnosis when tests rely on the detection of specific RNA sequence. Current molecular methods of checking RNA integrity tend to be host species or group specific, necessitating libraries of primers and reaction conditions. The objective here was to develop a universal (multi-species) quality assurance tool for determining the integrity of RNA in animal tissues submitted to a laboratory for analyses. Ribosomal RNA (16S rRNA) transcribed from the mitochondrial 16S rDNA was used as template material for reverse transcription to cDNA and was amplified using polymerase chain reaction (PCR). As mitochondrial DNA has a high level of conservation, the primers used were shown to reverse transcribe and amplify RNA from every animal species tested. Deliberate degradation of rRNA template through temperature abuse of samples resulted in no reverse transcription and amplification. Samples spiked with viruses showed that single-stranded viral RNA and rRNA in the same sample degraded at similar rates, hence reverse transcription and PCR amplification of 16S rRNA could be used as a test of sample integrity and suitability for analysis that required the sample's RNA, including viral RNA. This test will be an invaluable quality assurance tool for determination of RNA integrity from tissue samples, thus avoiding erroneous test results that might occur if degraded target RNA is used unknowingly as template material for reverse transcription and subsequent PCR amplification.

Are high-impact species predictable? An analysis of naturalised grasses in northern Australia

Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.

A universal equation to predict methane production of forage-fed cattle in Australia

The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.