In addition to its effects on the golgi apparatus and endoplasmic reticulum-golgi apparatus protein trafficking, mutant SOD1 has been observed to have a drastic effect on neuronal mitochondria. As discussed earlier, the SOD1 protein is normally localized to the intermembrane space. As the outer membrane of the mitochondria expands away from the inner membrane, degenerative vacuoles form as a preceding step to mitochondrial degeneration due to increased membrane permittivity. As a consequence, this membrane degeneration leads to disruptions in the electron transport chain which results in an ATP deficit and neuronal death. That is, the increased permittivity of the membrane results in an inability to regulate an influx of calcium ions. In turn, the ions bind to Miro (MIRO1) - a mitochondrial membrane protein which then binds to kinesin and subsequently causes kinesin to detach from the microtubule. This prevents the anterograde axonal transport of mitochondria in neurons which is crucial to ensuring sufficient ATP distribution across the cell (Ping et al. 2010).
The University is proud to release to the public the ground- breaking findings presented
in the paper, “Target Genes of the MADS Transcription Factor SEPALLATA3: Integration of Developmental and Hormonal Pathways in the Arabidopsis Flower”. The paper explores development in Arabidopsis and the importance of the SEPALLATA3 (SEP3) protein in the regulatory transcriptional network that controls the development of the floral organs.
The development of plants typically occurs post embryonically and are constantly being affected by their environments. In order for plants organs to form and regenerate materials throughout its life span it must have stem cells at the ready. These stem cells exist in the shoot apical meristem (SAM) and these are the areas in which plants create new floral organs. The type of organ produced depends on where the plant is developmentally. The MAD-box genes family have proven to be critical in floral organ development. And although there is still much research to be done regarding all of the transcription factors and the different ways in which plants develop, this paper specifically focuses on SEP3.
The researches found SEP3 is critical in floral development because the sep1, sep2, and sep3 mutants all did not have petals, stamens, and carpels. Also they discovered it is expressed throughout floral development. This is because in order for leaves to become floral organs is needs SEP3. With the help of ChIP followed by ChIP- SEQ, that allows the developmental biologist to see the varying protein interactions with the DNA, they could compare the targets of SEP3 wildtypes and mutants. They found SEP3 binds to many different spots, in the thousands, site in the genome. Based on the ChIP-SEQ data they found that there are many links between SEP3 and auxin signaling pathways. The combination of SEP3 and auxin proved to be responsible for organ growth as mutants without these two create phenotypes with impaired organ development.
This paper helped to piece together the puzzle about how plants use floral homeotic genes to go through critical developmental switches that are responsible for organ identity. Although much of this process is still unknown the breakthroughs thanks to ChIP and ChIP- SEQ are huge advances in the developmental biology field.
The primary aim of this research is to map phenotypic traits onto a phylogeny created by John Iverson which he created using the molecular markers in the DNA of roughly forty species of mud turtles. Utilizing the phylogeny of the genetic variation with physical traits mapped on it the group's goal is to try an answer a few simple questions. How does habitat correlate to the physical characteristics of mud turtles? How do the traits correspond to species recognition and sexual selection? The use of John Iverson's molecular phylogeny is the most recent and complete genetic phylogeny done on this family of turtles to date. The species were tested and compared using three regions of the mitochondrial genome, the entire cytochrome b sequence, and the partial 12S and 16S rRNA genes. Also, three nuclear fragments of the C-mos, RAG1, and RAG2 genes (Iverson et al. 2013). Other genetic phylogenies have been created using similar genetic markers, yet no other has been compiled using the numerous amount of genetic markers like the one Iverson created.
The purpose of this study is to identify relationships between the habitat and phenotypic characteristics in the family of turtles called Kinosternidae and if these traits researched correlate to any varying level of interspecies communication. Nine cladograms were created based on nine unique characteristics of the group Kinosternidae; the phenotypic traits mapped on the phylogenies that were created using genetic variation among the species. Direct trends observed between the carapace shape and the current of the water the turtle inhabited when the two phylogenies were analyzed side by side. The trait of distinct head coloration seems to have a prevalence among newly destinated subspecies which their habitats overlap as well as, a more northern relative which the character first appeared. Specific trends of phenotypic characteristics seem to diverge with the habitat of the species and particularly how much the territories overlap, possibly lending itself to speciation events. Within the construction of these phylogenies, we were able to correlate the habitat of these turtles to their phenotypic characteristics and possible ways that these turtles can communicate with one another through physical markings. The phylogeny also depicts when some of these traits evolved or were inherited, the species where the divergence occurred, and when and which characteristics were lost and gained. The family of Kinosternidae has an extensive, and varied habitat, which suggests a highly mutable genetic lineage within this particular group of turtles.
In this paper researchers examined the effect of activation a competing, artificially generated, neutral representation on encoding of contextual fear memory in mice. They used a transgenic approach to induce the hM3Dq DREADD receptor. This is a designer receptor exclusively activated by a designer drug. Neural activity could then be specifically and inducibly increased in the hM3Dq expressing neurons by an exogenous ligand. Figure 1 of the study shows the two transgenes encoded in the mice. The figure showed the distribution of the gene in the hippocampus from immunofluorescence. Figure 2 showed the incorporation of synthetic neural activity in a 24 hour representation. Figure 3 showed the distribution of memory retrieval by synthetic neural activation. Finally figure 4 showed that memory performance during synthetic reactivation is network specific. The results of this study infer that learning new memories are not produced de novo. But instead, new memories form based on old ones. New information coded is based on pre-existing circuit activity. One drawback of the study was that stimulation of the artificial gene does not replicate the temporal dynamics of this naturally occurring phenomenon. However the results do support the idea that the internal dynamic of the brain at the time of learning contribute to memory encoding.
For the purification of the extracted dog DNA, the Nanodrop indicated that the DNA concentration was 29.6 nanograms/ microliter and that the 260/280 ratio was 1.77.
The gel electrophoresis of the MC1R PCR of the dog DNA for JP displayed on Well 2 showed that it had a band near 1 kb which was similar to the other samples of dog DNA from other groups. The band for JP appeared horizontally straight with no curvatures (Fig. 1).
In the analysis of the DNA sequence of JP, there was a single nucleotide polymorphism of 790 A > G. After the BLAST, the first top hit was Canis lupus familiaris boxer breed chromosome 5 which was 99% identical to the contiguous sequence. Also, 16A and 16C did not show any heterozygous bases while 16B showed one at C402: C/T.
In the analysis of the protein structure of JP, there was a mismatch between the reference sequence of amino acids and the sequence for JP at p.Met264Val.
A restriction digest was performed on the dCAPS PCR products to observe the differences in the two alleles of each SNP. The methods from “Restriction digest of dCAPS PCR products” were followed for this section. The restriction digest conditions were researched on the NEB website and the amount of each ingredient for the digest were calculated. It was determined that for DS12, the enzyme HpaII would be used with 1xCutsmart buffer while for DS1S, the enzyme BamHI would be used with NE buffer 3. Each needed an incubation time of 1 hour at 37°C. A chain of eight PCR tubes were provided. Four would be cut and four would be uncut mixes. For the uncut mixes, 10 microliters of PCR product and 10 microliters of water were added. For the cut mixes, 10 microliters of PCR product and 7 microliters of water were added. Instead of the intended 2 microliters of buffer, 20 microliters of buffer were added to each of the regular mixes accidentally. With no remaining PCR product, a new batch was not available and so the 1 microliter of restriction enzyme was not added since the ratio would restrict the function of the reaction anyway. The digests were incubated for 1 hour. After incubation, 12 microliters of each sample was mixed with 3 microliters of loading dye on a Parafilm sheet and loaded into separate columns of a gel for gel electrophoresis (Loomis 2017).
Derived cleaved amplified polymorphic sequences (dCAPS) were performed to identify the genotype of the SNP that is highly associated with the trait for Earbend (CFA34, DS12). The procedure was taken from “dCAPS PCR Primer Design Protocol.” All of the SNP and primer information were recorded onto a spreadsheet. The dCAPS primer was designed by using a website that searches for a compatible restriction endonuclease to digest the specific amplified product. The wildtype and mutant SNP sequences were formatted and added to the site. The number of mismatches for primers were determined to limit the different potential enzymes to ones more readily available; there were two mismatches before finding an available enzyme. The enzyme HpaII with the recognition site CCGG was chosen. A second primer was found using the Primer3 program and entering the full sequence and the forward primer. The reverse primer was found and the size of the digested PCR product was calculated. A positive control primer was designed using the forward primer (Loomis 2017).
In plants, flower induction is when a plant has started floral production, and it is irreversible. More specifically, it is when the apical meristem starts to produce floral organs instead of stem or leaf organs. Plants become induced due to favorable conditions in the environment. Due to the irreversible nature of them, once induced, even if conditions then become non-inductive, the plants will continue to flower.
There is a critical day length in determining LDP or SDP in plants. LDP is promoted when day length exceeds a certain duration, while SDP is promoted when day length is less than the critical day length. Previously, it was a question of whether plants measure the length of day or the length of night. It turns out, plants really measure night length, or the length of darkness. This was demonstrated because in SDPs, they will flower when the length of day is less than a certain critical duration in a 24 hour cycle. In other words, the length of night must exceed a critical point for flowering to occur. In an experiment, the critical period of darkness exceeded the critical point, but it was also interrupted by a flash of light. This caused the flower to not bloom. For this reason, it would probably make more sense for SDPs to be called Long-Night plants instead. Conversely, LDPs flower when the day length exceeds a critical amount of time within a 24 hour cycle, or when the amount of night time and darkness is less than a critical period. This can be shown from experiments in which experimenters expose an LDP to a certain of night time that is too long, so it should not induce flowering. However, when a light is shined during the dark period, flowering occurs in these LDPs. Similarly, it would probably be more accurate to call these plants “Short-Night Plants”. Other experiments were done in both SDPs and LDPs, and it is now known that the dark period is the critical one, not the amount of light period. This is exceptionally noticeable in experiments where the entire days were less than 24 hours or longer than 24 hours. When less than 24 hours, there appeared to be about an even amount of light and darkness, but since it was less than 24 hours, it was a short cycle of each condition. This condition therefore induced the LDP into flowering while the SDP remained in its vegetative state, because the night length was less than the critical periods for both the SDPs and LDPs. When the days were over 24 hours, there was an extra long night time period. This led to he SDPs flowering and the LDPs remaining in their vegetative step. This also makes sense, because the night period would have exceeded the critical point for the SDPs and the LDPs.
- Energy consumption in terms of locomotion
- Unit of mass, distance, and time in terms of kinetic energy
- Ek= 1/2mv2
- Unit of mass, distance, and time in terms of kinetic energy
- Efficiency of biological movements is calculated by the ratio of mechanical work produced to chemical energy consumed
- Efficiency= mechanical work produced/chemical energy consumed
- Molecular motors convert chemical energy to mechanical energy
- E.g sperm uses a flagella for motion
- Not very efficient
- Vertebrate muscle efficiency is 25% the rest is lost as heat
- In animals with muscles, muscles and tendon produce force for locomotion
- Muscles use energy (ATP) to produce force, and tendons recover energy to produce force like a spring
- Mass effects how tendons act as springs
- Large animals like kangaroos can take advantage of these elastic savings because of gravity
- Kinetics is the study of forces during locomotion
- force plates & the rate of oxygen consumptions can be used to measure kinetics
- flowmeters or flow tanks
- force plates & the rate of oxygen consumptions can be used to measure kinetics