Recent orders

Larger Mammalian Body Size Leads to Lower Retroviral Activity

Biology

Students Name

Institution of Affiliation

Course Title

Date

Larger Mammalian Body Size Leads to Lower Retroviral Activity

The retroviruses have affected mammals affected mammals for more than 100 years, leaving the descendants of the hosts in the host genomes to which are referred to as the endogenous retrovirus. The amount of the endogenous retrovirus is to some extent determined by the retrovirus’ mode of replication, but also a suggestion that the host’s life history traits have the possibilities of suppressing or enhancing the retrovirus activity. According to the research results, body size limits the ability of the endogenous retrovirus to replicate due to their adverse effects impacted on the host.

The endogenous retrovirus is favored by lower body size and higher horizontal transmission rates because the retroviral integration is tumorigenic and the negative correlation between body size and the endogenous retrovirus arise from the need to reduce the risk of cancer having the assumptions that the risk scales positively with the body size. It is however contrasted by the research model that indicates that the lifetime risk of cancer tend to be relatively invariant among the mammals regardless of their body size best regarded as the Peto’s Paradox, to which indicates that the larger bodies mammals have as well evolved the mechanisms of limiting the endogenous retrovirus activity.

The fixation of a new endogenous retrovirus insertion is influenced by the fitness consequences of the host. A smaller number of the endogenous retrovirus have been exapted and possess beneficial actions to the host, although the integration of the retrovirus into the host’s genes have a highly deleterious impact, as the consequent alteration of the gene expression has the possibilities of leading to malignant transformations. Also, the illegitimate recombination between the endogenous retrovirus at different loci may also have the deleterious effect, and therefore the uncontrolled proliferation of the endogenous retrovirus would be extremely detrimental to the host. The process of reproduction could only be limited either through cessation replication or by the host-mediated suppression. The vertebrates’ genomes have evolved a variety of responses that tend to act at various stages of their viral life cycle to limit the retroviral replication along with the associated tumorigenic potential.

The mice and the humans are the two mammalian species are among the first to get their genomes sequenced, indicating variations in the in the patterns of the endogenous retrovirus activity. The human endogenous retroviruses are inactive, with a noticeable deceleration in activity over the last 25 million years which is in contrast to that of the mice genome showing no signs of deceleration in the endogenous retrovirus activity having active and unfixed numbers. The number of mates, as well as the type of placenta, have the possibility of influencing the abundance of the endogenous retrovirus through an increased risk of the horizontal or the vertical retroviral transmission. A possible cofounder includes the effective population size of the host; the species with a higher effective population size are expected to be more efficient at purging slightly deleterious mutations such as those incurred by the endogenous retrovirus proliferation. Being a researcher, the next experiment that I could do is based on the Human Tripartite Motif 5α Domains.

Reference

Katzourakis, Aris, et al. “Larger mammalian body size leads to lower retroviral activity.” PLoS pathogens 10.7 (2014): e1004214.

REVIEW OF MENDEL’S LAW OF INHERITANCE, HARDY-WEINBERG EQUILIBRIUM, AND DNA FORENSICS

Biology 332 BIOINFORMATICS

EXERCISE 6. STR, AND DNA FORENSICS (CODIS)

NAME: __________________

REVIEW OF MENDEL’S LAW OF INHERITANCE, HARDY-WEINBERG EQUILIBRIUM, AND DNA FORENSICS

DNA forensics has become an important tool to solve social problems in modern times. Part of the power of this technology lies in providing robust statistical values to refute or support statements of guilt, paternity, ancestry, and identity. To fully understand the technology, it is imperative to understand the ideas and principles that form the biological basis of its power. The first two ideas came from Gregor Mendel (1865): the law of segregation and the law of independent assortment. It describes how you inherit your genes and how genetic diversity is generated. The second idea is the Hardy –Weinberg Equilibrium which describes how genetic materials as genotypes and alleles are structured in a population. Your instructor will give a brief discussion on these ideas.

To determine whether evolution has occurred, the Hardy-Weinberg Equilibrium is utilized by population geneticist. This formula is based on Mendel’s Laws of Inheritance and could allow us to track the pattern of allelic and genotypic frequency changes over time. This is also the theoretical foundation of modern DNA forensic analysis. A short lecture by the instuctor will allow to understand how this is done.

Any changes in the gene frequencies in the population over time can be detected. The law states that if no evolution is occurring, then an equilibrium of allele frequencies will remain in effect in each succeeding generation of sexually reproducing individuals. In order for equilibrium to remain in effect (i.e. that no evolution is occurring) then the following five conditions must be met:

No mutations must occur so that new alleles do not enter the population.

No gene flow can occur (i.e. no migration of individuals into, or out of, the population).

Random mating must occur (i.e. individuals must pair by chance)

The population must be large so that no genetic drift (random chance) can cause the allele frequencies to change.

No selection can occur so that certain alleles are not selected for, or against.

Obviously, the Hardy-Weinberg equilibrium cannot exist in real life. Some or all of these types of forces all act on living populations at various times and evolution at some level occurs in all living organisms. The Hardy-Weinberg formulas allow us to detect some allele frequencies that change from generation to generation, thus allowing a simplified method of determining that evolution is occurring. There are two formulas that must be memorized:

p2 + 2pq + q2 = 1 and p + q = 1

p = frequency of the dominant allele in the population
q = frequency of the recessive allele in the population

p2 = percentage of homozygous dominant individuals
q2 = percentage of homozygous recessive individuals
2pq = percentage of heterozygous individuals

For a multiple allele system, or a gene with three (3) alleles in a Hardy-Weinberg equilibrium., the allelic frequency is

P + q + r =1

And the genotypic frequency equation would be:

P2 + 2pq + q2 + 2pr + 2qr + r2 = 1.0

INTRODUCTION TO STR

DNA is present in nearly every cell of our bodies, and we leave cells behind everywhere we go without even realizing it. Flakes of skin, drops of blood, hair, and saliva all contain DNA that can be used to identify us. In fact, the study of forensics, commonly used by police departments and prosecutors around the world, frequently relies upon these small bits of shed DNA to link criminals to the crimes they commit. This fascinating science is often portrayed on popular television shows as a simple, exact, and infallible method of finding a perpetrator and bringing him or her to justice. In truth, however, teasing out a DNA fingerprint and determining the likelihood of a match between a suspect and a crime scene is a complicated process that relies upon probability to a greater extent than most people realize. Government-administered DNA databases, such as the Combined DNA Index System (CODIS), do help speed the process, but they also bring to light complex ethical issues involving the rights of victims and suspects alike. Thus, understanding the ways in which DNA evidence is obtained and analyzed, what this evidence can tell investigators, and how this evidence is used within the legal system is critical to appreciating the true ethical and legal impact of forensic genetics.

How Does DNA Identification Work?

Although the overwhelming majority of the human genome is identical across all individuals, there are regions of variation. This variation can occur anywhere in the genome, including areas that are not known to code for proteins. Investigation into these noncoding regions reveals repeated units of DNA that vary in length among individuals. Scientists have found that one particular type of repeat, known as a short tandem repeat (STR), is relatively easily measured and compared between different individuals. In fact, the Federal Bureau of Investigation (FBI) has identified 13 core STR loci that are now routinely used in the identification of individuals in the United States, and Interpol has identified 10 standard loci for the United Kingdom and Europe. Nine STR loci have also been identified for Indian populations.

As its name implies, an STR contains repeating units of a short (typically three- to four-nucleotide) DNA sequence. The number of repeats within an STR is referred to as an allele. For instance, the STR known as D7S820, found on chromosome 7, contains between 5 and 16 repeats of GATA. Therefore, there are 12 different alleles possible for the D7S820 STR. An individual with D7S820 alleles 10 and 15, for example, would have inherited a copy of D7S820 with 10 GATA repeats from one parent, and a copy of D7S820 with 15 GATA repeats from his or her other parent. Because there 12 different alleles for this STR, there are therefore 78 different possible genotypes, or pairs of alleles. Specifically, there are 12 homozygotes, in which the same allele is received from each parent, as well as 66 heterozygotes, in which the two alleles are different.

The Statistical Strength of a 13-STR Profile

Within the U.S., the 13-STR profile is a widely used means of identification, and this technology is now routinely employed to identify human remains, to establish or exclude paternity, or to match a suspect to a crime scene sample.

In order to utilize STR information as a means of human identification, the FBI established the frequency with which each allele of each of the 13 core STRs naturally occurs in people of different ethnic backgrounds. To this end, the FBI analyzed DNA samples from hundreds of unrelated Caucasian, African American, Hispanic, and Asian individuals. Assuming that all 13 STRs follow the principle of independent assortment (and they should, as they are scattered widely across the genome) and that the population randomly mates, a statistical calculation based upon the FBI-determined STR allele frequencies reveals that the probability of two unrelated Caucasians having identical STR profiles, or so-called “DNA fingerprints,” is approximately 1 in 575 trillion (Reilly, 2001).

This very small number needs to be put into perspective. Note that this figure refers to pairs of people, and there are many pairs of people in the world. Indeed, for the 100 million Caucasians in the world, there are 5,000 trillion pairs of people, so roughly eight or nine pairs would be expected to match at the 13 STR loci. This predicted matching does not specify which profile is shared by two people, and the chance that anyone matches the particular profile associated with a crime is still very small. The distinction between two people sharing a profile and one person having a particular profile is an example of the so-called “birthday problem.” Here, the probability that a person has a particular birthday is 1 in 365, ignoring February 29, but there is a 50% chance that two people in a random group of 23 people have the same unspecified birthday (Weir, 2007).

Location of the 13 STR sequences on human chromosomes. DNA sequence of one of the STRs used by CODIS

The number of repeats determines the allele identity. This STR has 12 repeats of the sequence AGAT and is named allele 12. The allele for this STR having 13 repeats is named allele 13.

Does the DNA Databank System Help Solve Crimes?

The current DNA database maintained by the FBI, known as the Combined DNA Index System (CODIS), contains case samples (DNA samples from crime scenes or “rape kits”) and individuals’ samples (collected from convicted felons or arrestees) that are compared automatically by the system’s software as new samples are entered. As of February 2007, CODIS had produced over 45,400 “hits,” which assisted in more than 46,300 investigations (Federal Bureau of Investigation, n.d.). However, contrary to how DNA analysis is portrayed on popular television shows, DNA samples are not analyzed within the course of an hour. Rather, the U.S. currently has an enormous backlog of samples waiting to be typed and entered into the database. Some of these samples are from cases that have outlasted their statutes of limitation, so even if these samples could help solve a crime, the crime can no longer be tried.

This delay brings up the dilemma of the validity of statutes of limitation. These statutes were established at a time when large quantities of physical evidence were required to match a suspect to a sample and when extended time periods significantly decreased law enforcement’s ability to find a match, as well as the likelihood of successful prosecution. With the advent of DNA databanks and the possibility of storing samples indefinitely, the very notion of a statute of limitation now seems extremely outdated.

Of course, there are many other debatable issues concerning DNA banking. For instance, should the original tissue sample be stored indefinitely after the DNA profile has been entered into the database? Detractors note threats to genetic privacy, but proponents argue that future DNA typing methods will undoubtedly be developed and that old samples might have to be reanalyzed using new techniques. Also at issue is the reopening of old cases on the basis of new (DNA-based) evidence. Which cases should be eligible for reanalysis in light of this new evidence? Can equitable rules be established to allow reexamination of cases that were analyzed with less powerful lab techniques? Further public awareness of the power of DNA forensic technology will help lawmakers decide these issues in a way that seeks to strike a balance between protecting individuals’ genetic privacy and protecting innocent citizens from crime.

METHOD

SOLVING POPULATION GENETICS PROBLEMS

PROBLEM #1. You have sampled a population in which you know that the percentage of the homozygous recessive genotype (aa) is 36%. Using that 36%, calculate the following: 


The frequency of the “aa” genotype.

The frequency of the “a” allele.

The frequency of the “A” allele.

The frequencies of the genotypes “AA” and “Aa.”

The frequencies of the two possible phenotypes if “A” is completely dominant over “a.”

PROBLEM #2. Sickle-cell anemia is an interesting genetic disease. Normal homozygous individials (SS) have normal blood cells that are easily infected with the malarial parasite. Thus, many of these individuals become very ill from the parasite and many die. Individuals homozygous for the sickle-cell trait (ss) have red blood cells that readily collapse when deoxygenated. Although malaria cannot grow in these red blood cells, individuals often die because of the genetic defect. However, individuals with the heterozygous condition (Ss) have some sickling of red blood cells, but generally not enough to cause mortality. In addition, malaria cannot survive well within these “partially defective” red blood cells. Thus, heterozygotes tend to survive better than either of the homozygous conditions. If 9% of an African population is born with a severe form of sickle-cell anemia (ss), what percentage of the population will be more resistant to malaria because they are heterozygous (Ss) for the sickle-cell gene? 




PROBLEM #3. There are 100 students in a class. Ninety-six did well in the course whereas four blew it totally and received a grade of F. Sorry. In the highly unlikely event that these traits are genetic rather than environmental, if these traits involve dominant and recessive alleles, and if the four (4%) represent the frequency of the homozygous recessive condition, please calculate the following: 


The frequency of the recessive allele.

The frequency of the dominant allele.

The frequency of heterozygous individuals.

PPROBLEM # 4. In a population of 1000 under Hardy-Weinberg Equilibrium, if p2 = AA and has 100 individuals, q2 = BB and has an unknown number of individuals, and r2 = CC and has 16 individuals, estimate the allelic and genotypic frequencies of that population. How many individuals would be heterozygote AB? How many would be BC?

PART B

GIVEN THE FBI STR ALLELIC FREQUENCY DATABASE ASSIGNED TO YOU, CALCULATE THE MATCH PROBABILTY BASED ON THREE STR LOCI ASSIGNED TO YOU AND DESCRIBE WHAT IT MEANS IN THE COURT OF LAW (in terms of the perfect match between the DNA evidence found and the suspect’s DNA).

REFERENCES

Mendel, G. 1865. Versuche über Plflanzenhybriden. (Experiments in Hybridization). Verhandlungen des naturforschenden Vereines in Brünn, Bd. IV für das Jahr 1865, Abhandlungen, 3–47.

Norrgard, K. 2008. Forensics, DNA fingerprinting, and CODIS. Nature EdUcaiton 1:35.

CHOICE 1. Name : __________________________________

Calculate match probability value P for each of the following locus and the total match probability.

Locus TH01 alleles 6, 7 SE Hispanics

Locus D22S1045 alleles 10, 11 SE Hispanics

Locus D2S441 alleles 13 , 14 SE Hispanics

CHOICE 2

Calculate match probability value P for each of the following locus and the total match probability.

Locus D3S1358 alleles 13, 13 Caucasian

Locus D8S1179 alleles 12, 15 Caucasian

Locus DYS391 alleles 9, 10 Caucasian

The chart below is a position specific scoring matrix (PSSM

Bioinformatics assignment: motif finding and transcription factor binding site prediction

Name____________________________________

The chart below is a position specific scoring matrix (PSSM, a logarithmic transformed matrix) for a transcription factor binding site. (1). Evaluate a sequence “GACATTCA” to find out which segment of the sequence fits the binding site best. (2) What is the max score that a sequence can have with this PSSM? (3) What is the minimum score a sequence can have with this PSSM?

There are many programs for transcription binding site prediction available free on the internet. Find a few of them, list the links to at least 2 websites. Test with the following sequence to see how it works and briefly describe your test results.

ATCAGGCCCCCAAGGAAGATTTGAAGGGGGCGACTGCATAGTCGGGGTAT

CTCCCATATACCCAAGGAGATGGGTTTCTCTAACAGCACCCACGTCAGTC

CTAAATCTTCTTACTCTCCTGGATTAGAAGACTGTGTTTCCCAGGCCACA

TCTGAGAAGCCTGAGCTCCTTAGCCCTGAAATAGCAGAGTGCTGACAAGA

CACAGGGGCCTAGGGGCTCTGGAGTCCAAGGGGAGTCCTCAGCAGAAGAC

ACATAGGAGGCATTCTTTGTTGGGGCTGGCTTTTCTGTTTGCAAAGCCTG

CTTGAAATATCCTGCCCTTTCTATGGACACTTTCCTTAGGATATAACCTA

ATCTGTGGTTAATCACTATTCTT

The following is the alignment of a putative transcription factor binding site from various genes.

Position 123456

AGAACC

ACAAAG

CGAGGA

TCAAGT

AACAGA

AGATGA

GGAAGA

AGTAGA

ATGCTA

AGTAGA

Based on the alignment, (1) generate a position specific scoring matrix (PSSM), and (2) show what DNA sequence could get the highest score (or the highest probability fitting the model, (3) indicate a DNA sequence that could be scored the lowest (fit with the lowest probability in this matrix (4) determine which substring in the sequence “AACCGTAAC” has the most likely binding site for this transcription factor if there is one, and what substring is the least likely binding site.

DNA motif search

DNA motifs are normally very subtle and can only be detected using “alignment-independent” methods such as expectation maximization (EM) and Gibbs motif sampling approaches.

a. Use the DNA sequence at the botton of the file and generate alignment using the EM-based program Improbizer (www.cse.ucsc.edu/~kent/improbizer/improbizer.html) with default parameters. Copy and paste your results to your report file.

b. Do the same search using a Gibbs sampling-based algorithm AlignAce (http://www1.spms.ntu.edu.sg/~chenxin/W-AlignACE/). Copy and paste the sequences below to the correct input box. Change the number in the box following the Number of Column to Align to 6, and change the value in the box following Number of Sites Expected to 3. Copy and paste your results to your report file.

c. Compare the results of best scored motifs from both methods. Are there overlaps?

d. Copy and paste the first motif derived from AlignAce to nedit. Remove the illegal characters (spaces and numbers).

e. Cut and paste the motif alignment into the WebLogo program

(http://weblogo.berkeley.edu/logo.cgi) Click the “Create logo” button. Copy your result by hold ctrl and print screen at the same time. Paste your result to your report file.

f. Does the program find the highlighted region in the sequence?

Modified by Xiaofei Wang, 2017

Updated 2020

>Seq1

CACATCCCACCACAACCTTCCAGCAGCACGTGCAGGAACAGACAGGGGAA

TGGACGTAAGCGGCTCCTTAATATAATGTTGGGTCGTCGTAGGGATACCT

AGAAAGGTGTCCTGATATTAACCAC

>Seq 2

GAGCTAACATCAAAGCAGCACGTTTCCTAACTAAGACTACACATTTTCCA

TCTCACGTGCACAACTGAGTCCCCACTAGGACACTTTACAGACATTTGGA

>Seq 3

AAAGTGATGATCCTTCCTTTCCCTCCTAGATTAAATACTCATGTCCCACG

TGTACATCAGACTCAGCGCTGCTCGTAGCTGGAAACAAGATGGTGAAACT

>Seq 4

AGATCTGAATAATGAAGTAAGTTGTTCCCTTACACATGCAGCAGAAACTG

CCATTGCCTTCAAGAGCTGCAGAATAACACACGTGTGCTGTTCTGCGGGG

>Seq 5

TCAAGACCACGTGAAAGGCCGAGGTGGGTGGATCACTTGAGGTCAGGAAT

CAGCCAGGCCAACACGGCAAAAGCCTGTCTCTACAAAAAATACAAAAAAT

TAGCAGGGGATGGTGGTGTGTGTCTGTAGTCCCAGCTATTGCAGTGAGCA

>Seq 6

CAAGCAGGCTTAAACAAAATTCAATATCTGGACACATTGTAGTTAAACCA

CGTGACACTGTTATCACTGTCACACACATCTGTGTGAAGAGACCACCAAA

ACCTAGTAGATCGTA

>Seq 7

TAGGCTTCATGTGAGCAATAAAGCTTTTTAATCACCTGGGTGCACGTGGG

CTGAGTCCAAAAAAGGAGTCAGCAAAGGGTGGTAGGATTATCATTAGTTC

TTGAGATCCGATCAAATGCTATCCCCGTTATHAY

>Seq8

CACACATACACACACCAGACACACACCACACGTGCATACACAGACACACA

CCACACGCACTCGCTCGCGCGCACACACACACACACTTTTTATATACAAA

>Seq 9

CCAAATTCAGAAAACATCACGTGGCTTTTTACAATGTTTTCAGCAGCATA

GAACTTTTGCTGCAATGTCGTCGTATATGTTCCCTAGGATATAGTCTCAATCT

TGGTATTGTAGCTGATAGTCTGTAAGGGTTTCCCCCAGTAACT