One sided frequency spectrum (Matlab vs. Origin) There are a lot of queries on fft frequency all over the web. I guess the following point not discussed anywhere explicitly. Hope someone can provide an insight here.

If we have and even number of data points, N=10, the fft complex output arranges the data as 

fft = [c0, c1, c2, c3, c4, c-5, c-4, c-3, c-2, c-1], 

where the complex numbers corresponding to positive and negative frequencies. I read somewhere that MATLAB calculates the negative coefficient first, hence we have c-5 but not c5. The author did not explain the reason.

Point no. 1, that the values are not symmetric, there is an extra c-5.

When we wish to make two-sided frequency spectrum, the frequency axis ranges from [-(N/2): (N/2)-1]*Fs/ N. Fs is the sampling rate, N is the number of even data points.

If we wish to make a one-sided positive frequency spectrum, should we choose

A) [0:(N/2)]*Fs/N and ignore the fact the we are using the values corresponding to the negative frequency axis, given that the data is a real number and it is just a mirror image. 

B) [0: (N/2)-1]*Fs/N represents the true positive frequency axis?

If Fs= 250 Hz, the true positive frequency axis will end at 124.9980 Hz

If we happen to choose the negative frequency axis values and ignore the frequency sign, the frequency axis ends at 125 Hz exactly.

The same data when plotted in OriginPro ends the frequency axis at 125 Hz when plotted single sidedly.

Which approach (A) or (B) is rigorously correct, and why would OriginPro plot the frequency upto 125 Hz?
The indexing is a matter of convention.  "Natural" is zero centered, "Computer implementation" is zero based.  

We are having a big discussion right now over several questions on why your $c_{-5}$ should actually be considered as $(c_{-5} + $c_{5})/2$.  You'll find part of the discussion here Convergence of periodic sinc interpolation and the links to the rest are embedded within.

The "fluffy cloud" drawings show what happens when you consider the upper half (from a zero based perspective) as positive frequencies.  How to get Fourier coefficients to draw any shape using DFT?

If I have a circle, and I check your location every minute and it seems you have moved a quarter circle counter-clockwise each time, how do I know you haven't actually moved three quarters of the circle clockwise?

Answer:  You don't.  The convention decides which interpretation to use.