So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Genetics and analysis of quantitative traits

Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated as a nonlinear optimization problem. Automatic Differentiation Model Builder (ADMB) is a programming framework based on automatic differentiation, aimed at highly nonlinear models with a large number of parameters. The benefits of using AD are computational efficiency and high numerical accuracy, both crucial in many practical problems. We describe the basic components and the underlying philosophy of ADMB, with an emphasis on functionality found in no other statistical software. One example of such a feature is the generic implementation of Laplace approximation of high-dimensional integrals for use in latent variable models. We also review the literature in which ADMB has been used, and discuss future development of ADMB as an open source project. Overall, the main advantages of ADMB are flexibility, speed, precision, stability and built-in methods to quantify uncertainty.

/pdf/ad-model-builder-using-automatic-differentiation-for-18b5wunetc.pdf

AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models

A positive temperature coefficient is the term which has been used to indicate that an increase in solubility occurs as the temperature is raised, whereas a negative coefficient indicates a decrease in solubility with rise in temperature.

Effect of Temperature

Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.

https://www.csie.ntu.edu.tw/~kmchao/bioinformatics12spr/presentation/Report_20120604%236.pdf

Repetitive DNA and next-generation sequencing: computational challenges and solutions.

A population genetics theory for piRNA-regulated transposable elements

The protein kinase mTOR is implicated in metabolic-related diseases and chiefly controls organismal growth and homeostasis in response to nutrients. Activation of mTOR promotes cell growth and enhances a glycolytic/lipogenic axis, suggesting that this metabolic axis is required to sustain mTOR-dependent growth. Here, we used Drosophila genetics to investigate this functional link both at the organismal and cell-autonomous levels. mTOR is present in two distinct complexes mTORC1 and mTORC2, which can be independently modulated in most Drosophila tissues. We confirm this independency in the fat body, the organ that fulfils hepatic and adipose functions. We show that ubiquitous mTOR over-activation affects carbohydrate and lipid metabolism, supporting the use of Drosophila as a powerful model to study the link between mTOR and metabolism. We show that targeted glycolytic or lipogenic restriction in fat body cells exclusively impedes mTORC2-induced overgrowth. Additionally, ubiquitous deficiency of lipogenesis (FASN mutants) results in a drop in mTORC1 but not mTORC2 signaling, whereas, at the cell-autonomous level, lipogenesis deficiency in fat body cells affects neither mTORC1 nor mTORC2 activity. These findings thus, reveal differential metabolic sensitivity of mTORC1- and mTORC2-dependent overgrowth. Furthermore, they suggest that local metabolic defects may elicit compensatory pathways between neighboring cells, whereas enzyme knockdown in the whole organism results in animal death. Importantly, our study weakens the use of single inhibitors to fight mTOR-related diseases and strengthens the use of drug combination and selective tissue-targeting. AUTHOR SUMMARY Cell growth is essential for animal development but is also deregulated in several human diseases including cancers. The mTOR signaling network controls cell growth in response to nutrients and growth factors. mTOR stimulation has been shown to promote basal metabolism, including the glycolytic/lipogenic axis, which is essential to provide energetic cofactors and building blocks to sustain cell growth. However, the requirement this metabolic axis for mTOR-dependent growth has been poorly investigated yet. To address this issue, we used Drosophila genetics and focused on the fat tissue that fulfils hepatic and adipose functions. Surprisingly, in mosaic animals, where only a few cells were genetically stimulated for mTOR, we observed that metabolic knockdown only moderates cell overgrowth. Additionally, this growth restriction operates for only one of the two mTOR signaling branches, suggesting that mTOR-dependent compensatory processes operate to circumvent metabolic defects. Given that ubiquitous knockdown of this metabolic axis is essential for juvenile development and adult survival, our study reveals that metabolic restriction is unlikely sufficient to counteract overgrowth disorders.

/pdf/differential-metabolic-sensitivity-of-mtorc1-and-mtorc2-18p4zlc5w7.pdf

Arnaud Le Rouzic

Papers

A population genetics theory for piRNA-regulated transposable elements

Differential Metabolic Sensitivity of mTORC1-and mTORC2-Dependent Overgrowth