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\author{dolly}
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  /Title (genetics.pdf)
  /Creator (Cheatography)
  /Author (dolly)
  /Subject (Genetics Cheat Sheet)
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    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Genetics Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{dolly} via \textcolor{DarkBackground}{\uline{cheatography.com/183950/cs/38348/}}}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}dolly \\
  \uline{cheatography.com/dolly} \\
  \end{tabulary}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 24th April, 2023.\\
   Page {\thepage} of \pageref{LastPage}.
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
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  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
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\begin{multicols*}{4}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Historical views of heredity and inheritance}}  \tn
% Row 0
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\mymulticolumn{1}{x{3.833cm}}{Bricks and mortar theory by Hippocrates} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Elements are originated from all parts of the body and became concentrated in male semen. This will be developed and formed into human in the womb\{\{nl\}\}- Inheritance is an acquired characteristics} \tn 
% Row Count 6 (+ 6)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Blueprint theory by Aristotle} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Transmission of information from parents to offspring\{\{nl\}\}- Heredity is partly assymetric\{\{nl\}\}- Transmission is particulate (definitely one trait or another)} \tn 
% Row Count 11 (+ 5)
% Row 2
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\mymulticolumn{1}{x{3.833cm}}{Lamarckian Inheritance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- To explain while some features persisted while others disappeared\{\{nl\}\}- Traits acquired/ lost when depends on need} \tn 
% Row Count 15 (+ 4)
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\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Modern genetics introduced by Darwin and Mendel}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Darwin's blending inheritance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Offspring inherit the parents' average characteristic\{\{nl\}\}- All parts of the parents can contribute to the evolution and development of the offspring (Pangenesis)} \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Mendel's particulate inheritance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Law of segregation\{\{nl\}\}2. Law of independent assortment\{\{nl\}\}3. Law of dominance} \tn 
% Row Count 8 (+ 3)
% Row 2
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\mymulticolumn{1}{x{3.833cm}}{Exception to independent assortment - Linked genes} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Genes can be linked together if it is located close together on the same chromosome} \tn 
% Row Count 11 (+ 3)
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Rediscovery of Mendel's work}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Allele} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}One of two or more versions of DNA sequence at a given genomic location} \tn 
% Row Count 3 (+ 3)
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\end{tabularx}
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Conflict between Mendelian and Biometrician}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Debates between Mendelian and Biometrician} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Do the hereditary and evolutionary properties for a trait like height were the same as those for Mendel's peas?\{\{nl\}\}- Whether inheritance of complex trait was by 'blending' of parental phenotypes (Darwin) which was seen as different to the inheritance of discrete characters as in Mendel's peas} \tn 
% Row Count 8 (+ 8)
% Row 1
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\mymulticolumn{1}{x{3.833cm}}{Biuometrician's claim} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Traits are continuous (Blending inheritance) and heritable} \tn 
% Row Count 11 (+ 3)
% Row 2
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\mymulticolumn{1}{x{3.833cm}}{Mendelian's claim} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Mendelian genetics work in inheritance} \tn 
% Row Count 13 (+ 2)
% Row 3
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\mymulticolumn{1}{x{3.833cm}}{Achondroplasia} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}\textless{}90cm height} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Marfan Syndrome} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}\textgreater{}200cm height} \tn 
% Row Count 17 (+ 2)
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Emergence of Biometrical genetics}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Whar are Galton's claims in trait hereditary?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Traits like height, weight, arm length are normally distributed, not binary\{\{nl\}\}2. Traits are resemble between parents and offspring} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Galton's claim(1): Traits are "normally distributed" means} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. A trait has a mean value given a population\{\{nl\}\} 2. A trait can be subject to mathematical transformation} \tn 
% Row Count 9 (+ 5)
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\mymulticolumn{1}{x{3.833cm}}{What Galton use to study continuous variation in organism?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Regression\{\{nl\}\}- Correlation} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Galton's claim(2): Traits are resemble between parents and offspring} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- When measuring the height of parents and offspring, the mid-parental height has almost no deviation to their offspring height\{\{nl\}\} - Therefore, traits are resemble between parents and offspring} \tn 
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% Row 4
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\mymulticolumn{1}{x{3.833cm}}{Brownlee's Multi-Gene model to explain Mendelian inheritance in the blending inheritance model} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Parents and Child: 0.5 correlation because parents transmit 50\% of their genome to their child\{\{nl\}\}2. Parents and Grandchild: 0.25 correlation\{\{nl\}\}3. Parents and Great-grandchild: 0.125 correlation\{\{nl\}\}- These correlations are based on Mendelian's segregation law} \tn 
% Row Count 27 (+ 8)
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Polygenic Model}}  \tn
% Row 0
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\mymulticolumn{1}{x{3.833cm}}{Fisher`s Infinitesimal model} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Polygenic inheritance :A quantitative trait could be explained by Mendelian inheritance if several genes affect the trait\{\{nl\}\}- Include additive and dominant factors\{\{nl\}\}- Resemblance between relatives occur due to their genetic covariance} \tn 
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% Row 1
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\mymulticolumn{1}{x{3.833cm}}{Fisher's single locus model} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Assume:\{\{nl\}\}1. Dominant allele is not known\{\{nl\}\}2. A locus either follows dominant or additive\{\{nl\}\}- Used to determine whether the locus follow dominant or additive} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Fisher's single locus model, assume A2A2= -a and A1A1= a} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. If d\textgreater{}0 : A1 is dominant to A2\{\{nl\}\}2. If d\textless{}0 A2 is dominant to A1\{\{nl\}\} 3. If d=a/-a: Complete dominance (Heterozygote)\{\{nl\}\}4. If d=a/-a: Over-dominance\{\{nl\}\}5. If d=0: Locus is additive} \tn 
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% Row 3
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\mymulticolumn{1}{x{3.833cm}}{Continuous distribution of quantitative traits} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Alleles in our genome is limited but environmental factors are not. Therefore, traits are also influenced by environmental factors} \tn 
% Row Count 23 (+ 4)
% Row 4
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\mymulticolumn{1}{x{3.833cm}}{Fisher's partitioning variance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Genetic and non-genetic factors} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Three genetic factors (G)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Additive (A)\{\{nl\}\}2. Dominance\{\{nl\}\}3. Epistasis: Interaction between additive factors/ additive - dominant factors} \tn 
% Row Count 29 (+ 4)
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\mymulticolumn{1}{x{3.833cm}}{Non-genetic factor} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Environment (E)} \tn 
% Row Count 31 (+ 2)
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\vfill
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Polygenic Model (cont)}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Phenotypic variance (P)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Interaction between genetic and environmental factors (GxE)\{\{nl\}\}2. P= G+E+GxE} \tn 
% Row Count 3 (+ 3)
% Row 8
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\mymulticolumn{1}{x{3.833cm}}{Heritability} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}How much of the variation in a trait is due to variation in genetic factors (G)} \tn 
% Row Count 6 (+ 3)
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\mymulticolumn{1}{x{3.833cm}}{Genetic Architecture} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Composition of various genetic factors upon a phenotype\{\{nl\}\} - Include additive, dominance and epiptasis} \tn 
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% Row 10
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\mymulticolumn{1}{x{3.833cm}}{Genetics} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}To identify genetic factor associated with traits/disease but also study the contribution of a genetic factors} \tn 
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% Row 11
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\mymulticolumn{1}{x{3.833cm}}{Trait is not dichotomy (contrast between two things)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The features of an organisms are due to the individual's genotype and environment} \tn 
% Row Count 18 (+ 4)
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\end{tabularx}
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Allele}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Allele and Allele frequencies} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Proportion of chromosomes in population carrying the allele of traits/disease\{\{nl\}\}- Different combination of alleles determine traits or diseases\{\{nl\}\}- Allele frequencies indicate the proportion of observed genotypes in a given population} \tn 
% Row Count 7 (+ 7)
% Row 1
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\mymulticolumn{1}{x{3.833cm}}{Allele transmission to next generation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Same with Mendel's first law\{\{nl\}\}- Totally independent  and not influenced by environmental factors} \tn 
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Hardy-Weinberg Equilibrium}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Do segregation in Mendelian inheritance law affected by the segregant (allele)?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}No. This is called "stable"} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Hardy-Weinberg principle} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Assumed that allele frequencies will not change from generation to generation\{\{nl\}\}- p2+2pq+q2=1\{\{nl\}\}- p+q=1} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Assumptions of Hardy-Weinberg equilibrium} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Random mating\{\{nl\}\}2. No natural selection\{\{nl\}\}3. Equal genotype frequencies in two sexes\{\{nl\}\}4. No mutation/migration\{\{nl\}\}5. No differential viability\{\{nl\}\}6. Infinite population size\{\{nl\}\}However, all of these are not realistic!} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Mendelian segregation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Preserved in any organism with sexual reproduction regardless of allele frequency in the population} \tn 
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Chi-Square Test}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Chi square} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Use statistics to determine whether a locus of interest is under HWE or not} \tn 
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% Row 1
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\mymulticolumn{1}{x{3.833cm}}{Null hypothesis} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}There is no difference between observed value and the expected value} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Degree of freedom (DF)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Number of phenotypic possibilities in the cross\{\{nl\}\}- Example DF: 3(AA,Aa,aa)-1=2\{\{nl\}\}- If the level of significance read from the table is greater than 0.05/5\%, the null hypothesis is not rejected} \tn 
% Row Count 12 (+ 6)
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\mymulticolumn{1}{x{3.833cm}}{When the null hypothesis is supported by analysis} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Assumptions\{\{nl\}\}1. Mating is random\{\{nl\}\}2. Normal gene segregation\{\{nl\}\}3. Independent assortment} \tn 
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\mymulticolumn{1}{x{3.833cm}}{When the null hypothesis is not supported by analysis} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Assumptions\{\{nl\}\}1. Non-random occur\{\{nl\}\}2. Genes are not randomly segregating because they are linked on the same chromosome/inherited together.} \tn 
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Introduction of Heritability}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Model to describe heritability} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Fisher's model\{\{nl\}\}2. Falconer's model} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Falconer's Model} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Mathematical formula used in twin studies to estimate the relative contribution of genetics vs environment to variation in a particular trait\{\{nl\}\}- Heritability of the trait based on the difference between twin correlations\{\{nl\}\}- Heritability=2(rMZ-rMD)\{\{nl\}\}- Where r=concordance of the phenotype, MZ=Monozygotic Twins, DZ= Dizygotic twins} \tn 
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\begin{tabularx}{3.833cm}{X}
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\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Heritability}}  \tn
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\mymulticolumn{1}{x{3.833cm}}{Phenotypic similarity in family depends on} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Genetic relationship\{\{nl\}\}2. Traits} \tn 
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\mymulticolumn{1}{x{3.833cm}}{Total phenotypic variance for a character?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- VP=VG+VE\{\{nl\}\}- Combined effects of genotypic and environmental variance} \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Genetic variance (VG)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- The variance among the mean phenotypes of different genotypes\{\{nl\}\}-Additive genetic variance(VA): Variation due to the additive effects of alleles\{\{nl\}\}- Dominance genetic variation (VD): Variation due to dominance relationships among alleles\{\{nl\}\}- Epistatic genetic variation (VI): Variation due to interactions among loci} \tn 
% Row Count 13 (+ 8)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Environmental variance (VE)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The variance among phenotypes expressed by replicate members of the same genotype\{\{nl\}\}- Differences between monozygotic twins are due to environmental factors} \tn 
% Row Count 18 (+ 5)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Dominance genetic variance (VD)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Due to dominance deviations which describe the extent to which heterozygotes are not exactly intermediate between the homozygotes} \tn 
% Row Count 22 (+ 4)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Additive genetic variance (VA)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Responsible for the resemblance between parents and offspring\{\{nl\}\}- The basis for the response to selection} \tn 
% Row Count 26 (+ 4)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Degree of relatedness and the components of phenotypic covariance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Identical twins: VA+VD+VE\{\{nl\}\}2. Parent-offspring:1/2VA\{\{nl\}\}3. Full siblings:1/2VA+1/4VD+VE\{\{nl\}\}4. \seqsplit{Grandparent-Grandchild:1/4VA}} \tn 
% Row Count 31 (+ 5)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Heritability (cont)}}  \tn
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Heritability of a trait} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- A measure of the degree resemblance between relatives\{\{nl\}\}- Estimates the degree of variation in a phenotypic trait in a population that is due to genetic variation between individuals in that population that is due to genetic variation between individuals in that population} \tn 
% Row Count 7 (+ 7)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Narrow sense heritability (h2)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The proportion of trait variance that is due to additive genetic factors} \tn 
% Row Count 10 (+ 3)
% Row 9
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Broad sense heritability (H2)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The proportion of trait variance that is due to all genetic factors including VD, VA, VI} \tn 
% Row Count 13 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Normal Distribution}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Two quantities that describe a normal distribution} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Mean\{\{nl\}\}2. Variance} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Deviation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Distribution of a trait in a population= Proportion of individuals that have each of the possible phenotypes\{\{nl\}\} - In normal distribution, half points are above and half points are below mean\{\{nl\}\}- One standard deviation are located in the mean\{\{nl\}\}- The distribution of a trait in a population implies nothing about its inheritance} \tn 
% Row Count 11 (+ 9)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Covariance} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}A measure of the joint variability of two random variables (trait)\{\{nl\}\}- Example: Measure the height deviation of father and son in a population} \tn 
% Row Count 16 (+ 5)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Resemblance between family members} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- When there is genetic variation for a character, there will be a resemblance between relatives\{\{nl\}\}- Relatives will have more similar trait values to each other compared to unrelated individuals} \tn 
% Row Count 22 (+ 6)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Resemblance between relatives} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}-Depends on the degree of relationship\{\{nl\}\}- Use slope, not correlation coefficients to compute resemblance of family members\{\{nl\}\}- Identical twin=100\%, Full siblings=50\%, Parent-offspring=50\%, Half-sibling=25\%} \tn 
% Row Count 28 (+ 6)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Morgan Experiment}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Morgan's experiment} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Proved that chromosomes are the location of Mendel's heritable factors from his fly experiment} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Centimorgan} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The frequency of crossing over} \tn 
% Row Count 5 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Linkage Map/ Genetic Map} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}If the frequency of how often genes crossover is known, the percentage can be used to estimate how far apart the genes are from one another on a chromosome} \tn 
% Row Count 10 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genes}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Definition of gene} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- A core unit of the heredity that control the development of a trait\{\{nl\}\}- Mendel's "discrete particle" in particulate inheritance actually indicated the concept of "gene"\{\{nl\}\}- Those consist of DNA sequences and produces functional elements} \tn 
% Row Count 7 (+ 7)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{How many genes can make protein in human?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}20,000 genes make proteins and most of them involve in determining traits} \tn 
% Row Count 10 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Genotype} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The part of the genetic makeup of a cell which determine one of its characteristics} \tn 
% Row Count 13 (+ 3)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Phenotype} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The set of observable characteristics of an individual resulting from the interaction of its genotype with the environment} \tn 
% Row Count 17 (+ 4)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Components in a gene} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Gene contain exons, introns, UTRs and promoter in its transcript\{\{nl\}\}- Gene can have various transcripts due to alternative splicing} \tn 
% Row Count 21 (+ 4)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Exon} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}A region of a trascribed gene present in the final functional RNA molecule} \tn 
% Row Count 24 (+ 3)
% Row 6
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\mymulticolumn{1}{x{3.833cm}}{Intron} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Any nucleotide sequence within a gene that is removed by RNA splicing during maturation of the final RNA product} \tn 
% Row Count 28 (+ 4)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{UTR} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Either of two sections, one on each side of a coding sequence on a strand of mRNA} \tn 
% Row Count 31 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genes (cont)}}  \tn
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Promoter} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The section of DNA that controls the initiation of RNA transcription as a product of a gene} \tn 
% Row Count 3 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Cells and Chromosomes}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Where does genetic recombination occur in meiosis?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}In meiosis I and it occur between Prophase I and Metaphase I} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Pros of asexual reproduction} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Produce more offspring as it takes less time\{\{nl\}\}- Require less energy} \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Cons of asexual reproduction} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- No variation in offspring\{\{nl\}\}- Less variation in population\{\{nl\}\}- Mutation can slightly increase variations\{\{nl\}\}- Fragile to environmental change} \tn 
% Row Count 11 (+ 5)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Pros of sexual reproduction} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Increase variation in offspring\{\{nl\}\}- More resistant to many environmental forces because of genetic variation} \tn 
% Row Count 15 (+ 4)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Cons of sexual reproduction} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Require two organisms for mating\{\{nl\}\}- Requires more cellular energy\{\{nl\}\}-More time required for offspring development} \tn 
% Row Count 19 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Elements in Chromosomes}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Ploidy} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Number of homologous sets of chromosomes in a cell} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Locus} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}A fixed position on a chromosome that may be occupied by one or more gene} \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{The nuclear genome} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Consist of 6 billion nucleotides in 46 chromosomes} \tn 
% Row Count 9 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Chromosomes}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Hereditary factors} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Genes and allele that are located on chromosomes} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Autosomal chromosomes/ autosomes} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Pairs number 1 to 22} \tn 
% Row Count 5 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Sex chromosomes/ somatic cells} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Pair number 23} \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Mitochondrial chromosomes in mitochondria} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Haploid\{\{nl\}\}- Maternal transmission} \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Karyotype} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Visualize chromosome shapes, structures and behaviors of chromosomes during cell division\{\{nl\}\}- Autosomes in metaphase are arranged from the longest to shortest and from number 1 to 22\{\{nl\}\}- Chromosomes number 23 are either XX/XY\{\{nl\}\}- p arm=short, q arm= not p} \tn 
% Row Count 16 (+ 7)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Mutation}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Saltationists} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Claim that evolution take place suddenly (saltating)( so that change instantaneous transition into a new species} \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Gradualists} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Believe gradual process of evolution given large-scale variability in a population} \tn 
% Row Count 7 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Gene can be defined in terms of their behavior as fundamental units based on:} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Hereditary Transmission\{\{nl\}\}2. Genetic recombination 3. Mutation\{\{nl\}\}4. Gene function} \tn 
% Row Count 11 (+ 4)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Darwinian view on mutation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Most mutations have an impact on certain traits\{\{nl\}\}- Natural selection is the primary force of evolution} \tn 
% Row Count 15 (+ 4)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Post-Mendelian geneticists' view on mutation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Natural selection plays little or modest role but occurrence of mutation would be a major evolution force} \tn 
% Row Count 19 (+ 4)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{"Hopeful Monster" hypothesis by Richard Goldschmidt} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Macroevolution through macromutations\{\{nl\}\}- Called "Hopeful Monsters" because they were the embodiment of large phenotypic changes that had the potential to succeed as new species (saltation)\{\{nl\}\}- Change early development and thus cause large effects in the adult phenotype} \tn 
% Row Count 27 (+ 8)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Developmental macromutations} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Mutations in developmentally important genes could produce large phenotypic effects} \tn 
% Row Count 30 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Mutation (cont)}}  \tn
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Neo-Darwinism} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Natural selection is assumed to play much more important role than mutation\{\{nl\}\}- Creating new characters in the presence of genetic recombination} \tn 
% Row Count 5 (+ 5)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Kimura's view: Neutral mutation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- The rate of substitution is so high that if each mutation improved fitness, the gap between the most fit and typical genotype would be large\{\{nl\}\}- This rapid rate of mutation means that the majority of the mutations were neutral\{\{nl\}\}- Mutations had little/ no effect on the fitness of the organism\{\{nl\}\}- Not all mutations affect on/ completely determine our trait, including diseases} \tn 
% Row Count 15 (+ 10)
% Row 9
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Mutation is an old term} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Describe the situation for permanent change in evolutionary process} \tn 
% Row Count 18 (+ 3)
% Row 10
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Variant} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- The change in the nucleotide sequences\{\{nl\}\}- Since a change in nucleotide sequence may not be permanent, variants are often called: genetic variant, variation or genetic variation} \tn 
% Row Count 23 (+ 5)
% Row 11
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Polymorphism} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Describe a variant with a frequency above 1\% but broadly variants that we know the frequency in certain population} \tn 
% Row Count 27 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Mutation}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Saltationists} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Claim that evolution take place suddenly (saltating)( so that change instantaneous transition into a new species} \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Gradualists} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Believe gradual process of evolution given large-scale variability in a population} \tn 
% Row Count 7 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Mutation and Population}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Out of Africa Theory} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Explains the origin of modern human beings\{\{nl\}\}- A small subset of this population migrated out in the past 100,000 years and rapidly expanded throughout a broad geographical region} \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Non-Afracan populations have different variant frequency due to} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Bottleneck\{\{nl\}\}2. Long migration history} \tn 
% Row Count 8 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Coalescent Theory} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Two sample lineages find common ancestor\{\{nl\}\}- A model how an allele sampled from a population may have originated from a common ancestor} \tn 
% Row Count 12 (+ 4)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Stochastic} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}When coalescence occurs is a stochastic (random probability( process} \tn 
% Row Count 15 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genomic study of population structure}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Implications of HapMap project and 1000 Genome Project} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Variant frequency is uniquely represented in each population so can identify the population structure\{\{nl\}\}- Genomic data are useful and fundamental resource to identify genes associated with disease and genetic variant in patients} \tn 
% Row Count 7 (+ 7)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genomic study of population structure}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Implications of HapMap project and 1000 Genome Project} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Variant frequency is uniquely represented in each population so can identify the population structure\{\{nl\}\}- Genomic data are useful and fundamental resource to identify genes associated with disease and genetic variant in patients} \tn 
% Row Count 7 (+ 7)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by size}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{SNV - Single Nucleotide Variant} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Substitution of one/another base pair at a particular location in the genome\{\{nl\}\}- Also called SNP if the allele frequency in a population is known\{\{nl\}\}- A point mutation because it only affects a single nucleotide of nucleic acid\{\{nl\}\}- There are \textasciitilde{}3,500,000 SNVs per individual (more in African)\{\{nl\}\}- Everyone have different compositions of SNVs so there us variability in traits\{\{nl\}\}- The ratio of heterozygous and homozygous SNVs is \textasciitilde{}2:1} \tn 
% Row Count 11 (+ 11)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Indel - Insertion/Deletion} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- 1-1000bp changes in our genome\{\{nl\}\}- There are \textasciitilde{}300,000 to 600,000, indels per individual (more in African)\{\{nl\}\}- Less than SNVs as indels have a large phenotypic effect than SNVs so more selective pressure\{\{nl\}\}} \tn 
% Row Count 17 (+ 6)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Indels can be divided to} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Microsatellite polymorphism\{\{nl\}\}2. Mobile element insertion polymorphism} \tn 
% Row Count 20 (+ 3)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Microsatellite polymorphism} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}2-4 nucleotide unit repeated in tandem 5-24 times} \tn 
% Row Count 23 (+ 3)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Mobile element insertion polymorphism} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Cause human genetic diversity through retrotransposition\{\{nl\}\}- Involves transcription into RNA\{\{nl\}\}- Reverse transcription into DNA sequence\{\{nl\}\}- Insertion into another site in genome} \tn 
% Row Count 28 (+ 5)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{SV - Structural variant} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- A genomic change \textgreater{}1000bp} \tn 
% Row Count 30 (+ 2)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by size (cont)}}  \tn
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{SV can be divided to} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Copy Number Variant (CNV) - Deletion/Duplication\{\{nl\}\}2. Copy Number Neutral Variants (CNNV) -  Inversion/Insertion/ Translocation} \tn 
% Row Count 4 (+ 4)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Small variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}SNVs and indels} \tn 
% Row Count 6 (+ 2)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Large variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}SVs} \tn 
% Row Count 8 (+ 2)
% Row 9
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{SV in the gnomAD project} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Represent population structure as small variants\{\{nl\}\}- More singleton SVs are observed in larger SVs\{\{nl\}\}- Singleton: The variant only seen in an individual (rare)\{\{nl\}\}Rare: It's under strong natural selection so only seen in few individuals\{\{nl\}\}- Size of SVs are correlated with the effect size of SVs} \tn 
% Row Count 16 (+ 8)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by size}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{SNV - Single Nucleotide Variant} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Substitution of one/another base pair at a particular location in the genome\{\{nl\}\}- Also called SNP if the allele frequency in a population is known\{\{nl\}\}- A point mutation because it only affects a single nucleotide of nucleic acid\{\{nl\}\}- There are \textasciitilde{}3,500,000 SNVs per individual (more in African)\{\{nl\}\}- Everyone have different compositions of SNVs so there us variability in traits\{\{nl\}\}- The ratio of heterozygous and homozygous SNVs is \textasciitilde{}2:1} \tn 
% Row Count 11 (+ 11)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Indel - Insertion/Deletion} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- 1-1000bp changes in our genome\{\{nl\}\}- There are \textasciitilde{}300,000 to 600,000, indels per individual (more in African)\{\{nl\}\}- Less than SNVs as indels have a large phenotypic effect than SNVs so more selective pressure\{\{nl\}\}} \tn 
% Row Count 17 (+ 6)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{x{1.47619 cm} x{1.95681 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by Frequency}}  \tn
% Row 0
\SetRowColor{LightBackground}
Selection and Frequency & - Natural selection work on trait so the frequency of variants that contribute to trait can be changed\{\{nl\}\}- Level of natural selection is varied by traits and diseases\{\{nl\}\}- Some traits are favored by selection, therefore, the frequency variants increase\{\{nl\}\}- According to Polygenic model, a single variant is lilkely contributing partially/highly partially to a trait. Therefore, there is a wide range of the frequency of variants \tn 
% Row Count 20 (+ 20)
% Row 1
\SetRowColor{white}
Selection and Allele Frequency & - Allele frequencies can be changed by selection - Increase beneficial alleles and removes deleterious one\{\{nl\}\}- Traits not favored over mating are likely under natural selection (high selective pressure)\{\{nl\}\}- Natural selection tends to make allele with higher fitness more common over time, resulting in Darwinian evolution \tn 
% Row Count 35 (+ 15)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{x{1.47619 cm} x{1.95681 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by Frequency (cont)}}  \tn
% Row 2
\SetRowColor{LightBackground}
Fecundity & - Based on fertility ratio (FR)\{\{nl\}\}- Lower fecundity: Higher selective pressure on the trait\{\{nl\}\}- If a trait is not suited to mating/.reproduction, allele for this trait disappeared in a population\{\{nl\}\}- Similar to reproductive fitness \tn 
% Row Count 11 (+ 11)
% Row 3
\SetRowColor{white}
FR & Calculated based on the number of children individuals in that group had compared with the general population\{\{nl\}\}- If a disease have 0.5 FR, they have average half as many children as the general population \tn 
% Row Count 21 (+ 10)
% Row 4
\SetRowColor{LightBackground}
Penetrance & The proportion of individuals carrying a particular variant of a gene that also express an associated trait \tn 
% Row Count 26 (+ 5)
% Row 5
\SetRowColor{white}
Fitness & - Determine the allele frequency in population\{\{nl\}\}- If fitness is not affected by variant, it will be remained in a population, ultimately increasing its frequency \tn 
% Row Count 34 (+ 8)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by Transmission}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Type of genetic variants by transmission mode} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Inherited variants\{\{nl\}\}2. De novo variants\{\{nl\}\}3. Somatic variants} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{De novo variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- new variants arise during cell division\{\{nl\}\}- different nucleotide changes compared to DNA template\{\{nl\}\}- Errors are not present in genome thus called de novo=new\{\{nl\}\}- Errors in somatic cell: de novo somatic variants\{\{nl\}\}- Errors in germ cells: de novo germline variants} \tn 
% Row Count 10 (+ 7)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Mutability/Mutation rates} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}How much errors are occured during replication} \tn 
% Row Count 12 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Mutation signatures} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}The pattern of somatic mutations in disease} \tn 
% Row Count 14 (+ 2)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Human germline mutation rate} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1.0\textasciitilde{}1.5x 10-8 bp per generation} \tn 
% Row Count 16 (+ 2)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{How many total of de novo variant from mother and father ?} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- \textasciitilde{}70 de novo variants\{\{nl\}\}- 80\% of de novo variants are from father's sperm} \tn 
% Row Count 20 (+ 4)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Main contributor to de novo variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Advanced parental age\{\{nl\}\}- Father is higher than mother- Because spermatogonial cells continue to divide throughout life which allow the progressive accumulation of mutations due to errors during DNA replication/failure to repair non-replicative DNA damage between cell divisions} \tn 
% Row Count 28 (+ 8)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Rarest variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Have greatest potential to carry for disorders} \tn 
% Row Count 30 (+ 2)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by Transmission (cont)}}  \tn
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Variant frequency and its penetrance for disease} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Inverse relationship\{\{nl\}\}- Allele frequency is low but penetrance is high} \tn 
% Row Count 3 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Genetic variant by consequence}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Missense variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Single base pairs substitution produce different amino acid} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Trucating variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}A genetic variant which results in a shorter version of the protein being produced} \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Nonsense mediated decay} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Destroys the mRNA leading to no protein} \tn 
% Row Count 8 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Noncoding variants} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Variants located outside the coding regions\{\{nl\}\}- Located in promoters, transcription factor binding sites, enchancers} \tn 
% Row Count 12 (+ 4)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Protein isoform} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}Protein that are similar to each other and perform similar roles within the cells} \tn 
% Row Count 15 (+ 3)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Variant annotation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- The process of assigning functional information to DNA variants\{\{nl\}\}- Can be varied by transcript\{\{nl\}\}- A gene can have more than one transcript\{\{nl\}\}} \tn 
% Row Count 20 (+ 5)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Two schemes for variant annotation} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}1. Per gene annotation: Choose the most critical consequence by the variant per gene\{\{nl\}\}2. Per-transcript annotation: All consequence for every transcript} \tn 
% Row Count 25 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{3.833cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{3.833cm}}{\bf\textcolor{white}{Linkage Disequilibrium and Haplotype}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{3.833cm}}{Linkage disequilibrium (LD)} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}- Non-random association of alleles at two or more loci in a given population\{\{nl\}\}- LD between two alleles is related to time of the mutation events, genetic distance and population history\{\{nl\}\}- LD around an ancestral mutation on founder chromosome} \tn 
% Row Count 7 (+ 7)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{3.833cm}}{Haplotype} \tn 
\mymulticolumn{1}{x{3.833cm}}{\hspace*{6 px}\rule{2px}{6px}\hspace*{6 px}A group of alleles in an organism that are inherited together from a single parent} \tn 
% Row Count 10 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}