Evolving notes, images and sounds by Luis Apiolaza

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Big blob thesis OR chapter = publication?

I have a PhD student that should be submitting by approximately Christmas time, so the last week has been a lot of reading and editing. Three chapters, which will eventually become articles, are now “thesis ready”, meaning they may need minor polish before submission but they are ready for external thesis evaluation.

As a supervisor, I have a strong preference for a thesis to be made out of a number of publications (or pieces that will turn into publications) over the long document, big blob approach. Some reasons:

  • Once the thesis goes for external review, some of the chapters will have already undergone peer review. It’s hard to fault a chapter that was already published. 😉
  • Once the students finish, they already have some publications under their belt. They have gone through the process, and I insist they do, so it is less mysterious.
  • We don’t have to chase a students after they finished just to write publications. It has happened that they get a job and publications become a distant priority.

There are some drawbacks too:

  • There is some level of repetition, often there are variations of similar introductions (although it depends on the structure of the chapters).
  • There is a need for writing a general introduction and general conclusions (albeit often short).
  • Completing each part requires more work, because students are targeting a higher standard of writing (publication rather than thesis).

I am sure there will be vastly different experiences in this topic.

Are we working with a model organism?

There are organisms that are highly popular in research, like fruit flies or mice in animals,Arabidopsis or poplars in plants. There are very good reasons to work with those species (model organisms), as there are very good reasons not to work with them.

If you work in primary production—cereals, veggies, fruits, animals, or trees as I do—in essence feeding the world and providing biomaterials, we tend to think as not working with model organisms. However, once we have been working in a breeding programme for a while, we start accumulating measurements of a very broad set of traits under wide-ranging environmental conditions. Not only that, but then we start using some of that same genetic material in cultivation/management trials.

Progressively we start managing enough information that some of the genotypes in our breeding programme start acting/feeling like model organisms. So, yes, Pinus radiata (radiata pine, Monterrey pine) is my model organism.


A month ago I said “trees are much more than wood and one of our PhD students at the School of Forestry, University of Canterbury had a look at production of Eucalypts essential oils, particularly cineole”. We could easily see seasonality of production (peak in Spring & Summer) and the difference between juvenile and mature foliage. (Eucalypts essential oil)

Today, fresh from the oven, we have our new article moving from phenotypic variability to the genetic control of 20 essential-oil compounds with exciting names like 1,8-cineole and aromadendrene. A tale of alternative species and products, progeny trials and gas chromatography.

Of the 85 tested E. bosistoana families, seven families possessed breeding values indicating that their oil would meet the British Pharmacopoeia standard specification of a minimum of 70% 1,8-cineole. However, the negative correlation between total oil content and 1,8-cineole concentration indicates that families with higher-quality oil have less oil in their leaves.

Chamira Rajapaksha, Luis A. Apiolaza, Marie A. Squire and Clemens Altaner. 2023. Genetic parameters of essential-oil traits for Eucalyptus bosistoana, Australian Forestry DOI: 10.1080/00049158.2023.2270681 (Open Access)

Negative genetic relationship between cineole yield and total oil production.

At the core of your breeding programme

Surely you have been in this situation: meeting, there is coffee and biscuits at the back, some fruit if you’re lucky, and people with ideas flying about how to improve or change the breeding programme. Some of the ideas look easy to implement, others need a huge amount of work, and everyone has a different favourite.

Breeding programmes are vehicles to deliver genetic gain, which results on extra profit (or, at least, on maintaining your competitive position). So it makes sense to evaluate the effect of every suggested change to the programme under the lens of the Breeder’s Equation.

The Breeder’s Equation

Typically books present the simplest formula:

\(Gain = i h^2 \sigma_p\)

which works fine when dealing with a single trait, during the first round of selection based on an individual’s own record.

In reality, we are likely dealing with multiple traits and a more advance breeding programme. We move to \(G = i r_{IH} \sigma_H\). Now H is a total genetic economic value involving multiple traits, targeted by a selection index I, that takes into account all the genetic and economic information. This is great for calculations but harder to communicate.

It is probably easier to keep in mind that
Gain = (selection intensity x accuracy x variability) / time.

The meaning of each equation term is much easier to relate to something tangible. Focusing the meeting on these terms seems much more productive to me.

Did you develop a new way of phenotyping a hard-to-assess characteristic? We can now push selection intensity. Are we bringing new material to the breeding programme? That will increase variability. Are we paying for a new chip with N thousand SNP? That shortens time, maybe at lower accuracy but may also affect selection intensity.

We can look at the ideas, have basic discussions and later simulate those ideas (work in silico if you want to be posh).

A few ways of thinking of genetic gain and the Breeder’s Equation

In between plant and animal breeding 1: economic weights

Unless you live in paradise and you have a single objective trait—so your whole breeding objective is “more X”—you have to take into account trade-offs between traits. On the genetics front we deal with this via genetic correlations, but on the value front we have to figure out how much is an extra unit of X worth compared to an extra unit of Y (at least in relative terms).

You might be thinking “I don’t use no stinking economic weights, mate”. Instead you could used desired gains, independent culling levels, etc. You are not using explicit economic weights, but there are undeclared, implicit weights in your selections.

There are a few things that make tree breeding economic weights a bit different from the ones used in crop and animal breeding:

  1. Time or, better, TIME! We are selecting trees to go to the breeding programme, which later will be deployed and go for a full rotation (7 years for pulp in the tropics or 15 in temperate environments, 25~40 years for solid wood). This create huge uncertainty for the value of traits in 15~50 years in the future. We did some work on dealing with economic uncertainty here:

Evison, D.C. and Apiolaza, L.A. 2015. Incorporating economic weights into Radiata pine breeding selection decisions. Canadian Journal of Forest Research 45(1): 135-140 (PDF).

  1. The relationship between wood properties and end products is harder to quantify, particularly if dealing with solid wood products. If you come from the animal world, imagine the difference between breeding for milk (that can be homogenized, a bit like pulp) and for meat (where mixing filet with rump is a major loss of value, a bit like solid timber).

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