FEL-contrast

HyPhy version required	≥ 2.3.4
Parallel support	MP and/or MPI
File path	LIB/TemplateBatchFiles/SelectionAnalyses/FEL-contrast.bf
Standard analysis menu	Evolutionary Hypothesis Testing > FEL-contrast

What biological question is the method designed to answer?

Which sites in a gene may be associated with adaptation to a different environment. You need a tree with branches partitioned (a priori) into two sets: reference and test.

What are the recommended applications?

Suppose you have a gene which was sampled from different selective environments. The specific example for which this tool was developed is evolution of HIV in different hosts or different compartments (blood vs brain) in the host. Similar situations arise when the gene is sampled from species living in different environment, eating different food, having different wavelength eye sensitivity. This division has to be binary, however, so that any branch in the tree is either in the reference environment, or the test environment.

FEL-contrast then allows you to examine selective pressures (measured as dN/dS) at each site in the gene individually, and test whether or not they are different between environments.

Armed with a list of such sites, you could then attempt to explore if evolution at these sites is associated with adaptation to the environment.

What is the statistical procedure and statistical test is used to establish significance for this method?

For each site, three rates are inferred, with other parameters (frequencies, branch lengths) inferred jointly and held at

• α : synonymous substitution rate
• β _r : non-synonymous substitution rate along reference branches
• β _p : non-synonymous substitution rate along test branches

Two models are compared using a likelihood ratio test

• H_A: α, β _r, and β _t are inferred by maximum likelihood as free parameters

• H₀: The β _r := β _t constraint is enforced.

The models are nested and differ by one degree of freedom. p-values are computed using the limit χ² distribution with one degree of freedom.

How should one interpret positive and negative test results?

A significant result at a site means that dN/dS (β/α) is different between the two sets of branches, with either an increase or a decrease on the test branches relative to the reference branches. A significant finding does not make any claims about positive (dN/dS > 1) or negative (dN/dS < 1), just that dN/dS differ among sets of branches, i.e., a difference need not change the mode of selection.

Negative results do not mean that there is no difference, rather that whatever difference there may be does not rise to the level of statistical significance/

Rules of thumb for when this method is likely to work well, and when it is not.

• Generally, you need 10 or more branches in each set to be able to have any statistical power.
• Too little divergence is also likely to severely throttle statistical power.

Example

We will analyze HIV-1 env sequences from a transmission pair: sequences are isolated from the putative source individual and the putative recipient individual from the 2005 study by Frost et al.

1. Partition the tree into the source and recipient (here we include the transmission branch with the source sequences), for example as described here. For convenience, download a NEXUS file with the tree already partitioned.

2. Run HYPHYMP or HYPHYMPI, select Evolutionary Hypothesis Testing from the menu of analyses then select Use a FEL method to test which sites in a gene may be associated with adaptation to a different environment. Alternatively, you can supply the path of the file as a command line argument, e.g. (by default /path/to/hyphylib should be /usr/local/lib/hyphy)

   $HYPHYMP /path/to/hyphylib/TemplateBatchFiles/SelectionAnalyses/FEL-contrast.bf

3. Select Universal genetic code

4. Input the path to the example file downloaded from the link above

5. Choose SOURCE as the test set

6. Select Yes to include synonymous rate variation

7. Input 0.1 for the default p-value

The analysis will now run for a few minutes and output the following results

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Branches to use as the test set in the FEL-contrast analysis

Selected 24 branches to include in FEL calculations: 0564_7, 0564_11, 0564_4, Node6, 0564_1, 0564_21, 0564_5, Node11, Node9, Node5, 0564_17, Node4, 0564_13, 0564_15, Node16, 0564_22, 0564_6, Node20, 0564_3, Node19, Node15, Node3, 0564_9, Node2

Obtaining branch lengths and nucleotide substitution biases under the nucleotide GTR model

• Log(L) = -5524.85, AIC-c = 11151.77 (51 estimated parameters)

Obtaining the global omega estimate based on relative GTR branch lengths and nucleotide substitution biases

• Log(L) = -5436.84, AIC-c = 10991.98 (59 estimated parameters)
• non-synonymous/synonymous rate ratio for background = 0.9178
• non-synonymous/synonymous rate ratio for test = 0.8293

Improving branch lengths, nucleotide substitution biases, and global dN/dS ratios under a full codon model

• Log(L) = -5436.29
• non-synonymous/synonymous rate ratio for background = 1.1136
• non-synonymous/synonymous rate ratio for test = 0.7748

For partition 1 these sites are significant at p <=0.1

Codon	alpha	beta-reference	beta-test	LRT	Difference detected?
4	0.000	22.380	0.000	3.390	Decr. p = 0.0656
52	0.000	20.982	0.000	3.384	Decr. p = 0.0658
83	0.000	20.365	0.000	3.389	Decr. p = 0.0656
118	0.000	17.179	0.000	3.404	Decr. p = 0.0651
124	0.000	23.346	0.000	3.396	Decr. p = 0.0653
155	0.000	0.000	64.943	5.045	Incr. p = 0.0247
187	0.000	20.934	0.000	3.577	Decr. p = 0.0586
218	0.000	20.825	0.000	3.519	Decr. p = 0.0607
222	0.000	22.658	0.000	3.459	Decr. p = 0.0629
224	0.000	25.874	0.000	3.681	Decr. p = 0.0550
352	0.000	19.420	0.000	3.411	Decr. p = 0.0648
386	0.000	20.334	0.000	3.387	Decr. p = 0.0657
417	0.000	21.316	0.000	3.383	Decr. p = 0.0659
455	0.000	22.010	0.000	3.398	Decr. p = 0.0653
462	0.000	69.066	10.567	3.860	Decr. p = 0.0494
466	0.000	55.142	0.000	7.562	Decr. p = 0.0060
506	0.000	33.154	0.000	3.438	Decr. p = 0.0637
526	0.000	50.810	5.313	3.351	Decr. p = 0.0672
533	0.000	21.489	0.000	3.485	Decr. p = 0.0619
598	0.000	18.103	0.000	3.392	Decr. p = 0.0655
633	7.019	20.227	0.000	3.393	Decr. p = 0.0655
748	0.000	36.773	0.000	6.388	Decr. p = 0.0115
751	0.000	18.447	0.000	3.123	Decr. p = 0.0772
762	0.000	18.868	0.000	3.402	Decr. p = 0.0651
788	0.000	26.735	0.000	3.937	Decr. p = 0.0472
820	0.000	56.371	0.000	9.657	Decr. p = 0.0019
824	0.000	19.630	0.000	3.604	Decr. p = 0.0576

** Found 1 sites with increased dN/dS in the test branches relative to the reference branches and 26 sites with decreased dN/dS selection at p <= 0.1**