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Genetic Status of Golden Lion Tamarin (GLT)

Golden Lion Tamarin (GLT)
In assessing the genetic status of GLT, the information given about the pedigree shows that firstly, all the individuals within the population have very low mean kinship (MK) hence it shows that the animals are genetically important. Secondly, the observed heterozygosity Ho among the individuals is high which shows that there is a lot of genetic variability in the population. Thirdly, the sex ratio of males to females in the population is 35 : 30 respectively, this suggest that mating among the population follows a monogamous pattern of one male to one female, except for one case in the pedigree where one female (3025) mated with two males (3429 and 2457). Overall, I think that the population is well managed however, there are some factors like missing information for some Sire and Dam in the early generations and a breeding status of false for most of the population which suggests some work need to be done to keep data management in check
The five breeding pairs I would give priority to include:
Pair 3 (3358, 3713): not related, female have no offspring, male have one offspring and low MK (0.035, 0.026)
Pair 4 (3875, 3493): not related, both have no offspring and low MK (0.035, 0.03)
Pair 5 (3954, 3560): not related, both have no offspring and low MK (0.033, 0.026)
Pair 12 (3799, 3729): not related, both have no offspring, rare allele present in female and low MK (0.033, 0.023)
Pair 13 (3946, 3759): both have no offspring, rare alleles and low Mean Kinship (0.028, 0.021)
The selection of the pairs were based on evidence provided in the pedigree data that the individuals are not related and they share a few alleles identical by decent with the rest of the population (low mean kinship). Therefore, they have the highest genetic value due to the presence of those unique alleles. Mean kinship however doesn’t always optimize genetic diversity, it is dependent on the population structure
Often times, increasing offspring production and reducing the loss of population genetic variation can be seen as separate and competing goals(Fiumera, Porter et al. 2004). Preserving genetic variations and avoiding inbreeding in order to maximize the long-term viability of captive populations is the primary goal of genetic management (National Research Council Institute for Laboratory Animal 2003). I recommend when planning breeding, inbreeding avoidance by ensuring that the relatives don’t mate should be a priority. Also, individuals with low mean kinship and high heterozygosity and who carry rare alleles should be selected. A reduction in the rate of loss of rare alleles helps to maximize the effective population size and this in turn helps to maintain genetic variability(Kimura and Ohta 1969).
In terms of genetic variance, the populations from the four different zoos are assessed below:
Zoo one (focal) have a low MK (0.031), high effective allelic diversity Ae (5.01), high average observed heterozygosity (0.63) and high FIS (0.131) which demonstrates that the population somewhat genetically healthy because even though it has a low MK, the high inbreeding coefficient suggests that inbreeding occurs within the population which means that they are not well managed. The presence of only one unique allele also suggest that the population is endangered.
Zoo two (pop_2) have a low Mean Kinship (0.020) among individuals, high effective allelic diversity Ae (5.47), two unique allele, high average observed heterozygosity (0.83), low FIS (0.027) and a P-value (0.345) which demonstrates that the population is genetically healthy and well managed.
Zoo three (pop_3) shows a high MK (0.103) among individuals, a really low allelic diversity Ae (3.19), low observed heterozygosity (0.56) and very high FIS (0.327) and a P-value (0.004) which demonstrates a genetically unhealthy population. These characteristics suggests that inbreeding is high, p-value also indicates a statistically differentiated population showing that they are not well managed.
Zoo four (pop_4) have the characteristics of a population that is genetically healthy. This include a very low MK (0.007), a high effective allelic diversity Ae (6.71), high average observed heterozygosity (0.87) and five unique alleles which demonstrates that the population is well managed compared to the other populations.
The genetic divergence among populations in the four zoos shows that there is a great genetic differentiation 0.15-0.25 between population 3 and 4 as well as a statistical significance between population 3 and 4. For the rest of the populations, there is a moderate genetic differentiation 0.05-0.15 and no statistical significance between them. Furthermore, Frankham et al. (2010), states that FST >0.15 shows a biologically significant differentiation thus, the FST between population 3 and 4 is 0.21 which means that there is a biologically significant differentiation among the populations. Similarly, the p value is 0.0133 which is <0.05 that means that there is a statistical significance among the population therefore we reject the null hypothesis since we have statistical support that allele frequencies are differentiated among the two population.
My recommendations for future management of gene flow among the populations are;
Dobson and May (1986), stated that gene flow by exchanging animals or potential gametes and embryos among subdivided populations is advantageous for protection against diseases and catastrophes. Hedrick (1995) has also shown that 20% of gene flow from source population shouldn’t be exceeded when augmenting translocation into a recipient population in order to reduce detrimental genetic load without uniquely adapted alleles. I would therefore recommend moving 95% of the standing genetic variations within the source population because they have the least number of unique alleles.

References
Fiumera, A. C., B. A. Porter, et al. (2004). “Maximizing offspring production while maintaining genetic diversity in supplemental breeding programs of highly fecund managed species.” Conservation Biology 18(1): 94-101.
Kimura, M. and T. Ohta (1969). “The average number of generations until fixation of a mutant gene in a finite population.” Genetics 61(3): 763.
National Research Council Institute for Laboratory Animal, R. (2003). Genetic Considerations in the Management of Captive Nonhuman Primates. International Perspectives: The Future of Nonhuman Primate Resources, National Academies Press (US).
Frankham, R., 2010. Challenges and opportunities of genetic approaches to biological conservation. Biological conservation, 143(9), pp.1919-1927.
May, R.M. and Dobson, A.P., 1986. Population dynamics and the rate of evolution of pesticide resistance. Pesticide resistance: strategies and tactics for management, pp.170-193.
Hedrick, P.W., 1995. Gene flow and genetic restoration: the Florida panther as a case study. Conservation Biology, 9(5), pp.996-1007.

Detecting Microbes in Food

Detecting Microbes in Food
Abstract
In this experiment, the purpose was to detect the number of microbes in different food samples from the final dilution for each. The hypothesis was that the growth of many microbes will be determined with this experiment using the Plate Count Agar. Using the Plate Count Agar there will be two highest amounts of microbes and there will be more microbes in milk than frozen food. The instructional materials that were used in this experiment were consisted of sterile water blanks, Petri dishes, pipettes, your choice of food sample, bottles of molten Plate Count Agar, and a blender to blend the different food samples. The results of this experiment showed that Raisins had the most amount of microbes and the Grapes had fewer microbes. In conclusion, This experiment actually applies to everyday life because microbes are everywhere and this experiment shows how much microbes can be on one food sample

Introduction

Food Microbiology is the scientific study of organisms in contaminated food. This covers the major areas of concern like food spoilage, foodborne illness, and food production. That may cause diseases if food is uncooked, these foods are used to produce fermented foods. Fermented foods are some of the oldest consumed, Fermentation may provide characteristics to foods like yogurt, bread, cheese, and beer. Traditional fermented foods play a major role in the diet of many communities worldwide(Diaz, A. 2014). However, the foodborne illness also known as food poisoning is a major foodborne illness that have affected thousands of people over time like Salmonella. Salmonella causes approximately 155,000 deaths each year (Tadesse, G. 2014). As stated above, this report will detect the number of microbes in a food sample from the final dilution from each with the test materials of sterile water, a Petri dish, pipettes, different food samples, bottles of molten Plate Count Agar, and Blender. As stated above, the hypothesis determined that there will be more microbes in milk than frozen food and there might be two highest amounts of microbes. Milk is made up of proteins, fats, carbohydrates, vitamins, and minerals, providing an ideal environment in the growth of organisms. Raw milk is usually complex microbial community containing diverse organisms (Li, N.2018). Milk should have the highest amount of microbes because of food spoilage and being left out for so long.
Material and Methods

In this experiment, 20 grams of food types were added in the blender mixed with 180mL of sterile water for 5 minutes. Each blended mixtures was distributed to their own petri dish. The first blended mixtures were distributed to 0.1mL into the petri dish labeled 1:100. Some of the blended mixtures were transferred to 1.0mL into 99mL of sterile water to create the 1:1000 dilation. The rest of the blended mixture was distributed to 1.0mL and 0.1mL from a 99ml bottle into a petri dish label 1:1000 and 1:10,000. Secondly, a bottle of media was collected to pour the media on the bottom of each dish. Allow media to solidify. Lastly, the dishes were placed into the incubator for 24 hours. The dishes were later collected from the incubator.

Results

During this experiment, observations were made in regard to the final dilution in different food types using media. Based on the number of Colonies forming units in the different food types the Raisins showed the highest amount of microbes in it and the Grapes showed the lowest amount of microbes. Due to the raisins being kept for a long time and the grapes were fresh also the raisins are high in sugar probably had an effect on the results. This plate count would not be used to access the safety of fermented food because the test result does not show any harmful bacteria. The hypothesis was incorrect. Below in figure 1.
Figure 1
Food Type
CFU per plate
Final Dilution
CFU per 20 grams of the food
Frozen Broc.
55
10,000
550,000
Fresh blueberries
58
1,000
58,000
Frozen blueberries
81
1:1,000
81,000
Fresh Broc.
81
1:1,000
81,000
Milk
52
1,000
52,000
Raisins
38
100,000
380,000
Grapes
28
1,000
28,000
In this chart, are the different food sample that was experimented using the Plate Count Agar.

Discussion
The main objective of this experiment was to detect which food type would have the most amount of microbes in it. The hypothesis that was tested was using the Plate Count Agar there will be two highest amounts of bacteria in the food samples. Throughout the data in this experiment, the hypothesis was found to be incorrect and it was actually only one highest amount of microbes and the lowest amount of bacteria. and milk actually had the second-lowest amount of microbes. Based on the chart, Raisins were showed as the highest and Grapes were showed as the lowest amount of microbes when compared to other food types. This may be due to the Raisins being high in sugar and the been kept for and long time and the Grapes were fresh. In this experiment, it was necessary to serial dilution in order to be able to count the number of microbes on the food samples. A possible improvement to the experiment to help reduce the number of errors would be to carefully read the methods and listen to your professor. Another improvement is to make sure you are putting the right amount of chemicals in your experiment. This experiment actually applies to everyday life because bacteria are everywhere and this experiment shows how much bacteria can be on one food sample.

Literature Cited

Brown, A. (2007) Benson’s Microbiological Applications: Laboratory Manual in General Microbiology (9th ed.) New York, NY: McGraw-Hill.
Diaz, A (2019) Comparison of the microbial composition of African fermented foods using amplicon sequencing. Nature.com
Li, N. (2018) Variation in Raw Milk Microbiota Throughout 12 Months and the Impact of Weather Conditions Nature.com
Tadesse, G. (2014) A meta-analysis of the prevalence of Salmonella in food animals in Ethiopia biomedcentral.com

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