Genomic Prediction

         December 16, 2014

The major interest in genomic prediction is best understood by looking at the growth of the human population. Over the last few hundred years we have experienced an increase in population due to medical advances and massive increase in agricultural productivity. The planet’s population continues to explode: from 1 billion in 1820 to 2 billion in 1930, 3 billion in 1960, 4 billion in 1974, 5 billion in 1987, 6 billion in 1999, and 7 billion in 2012. Just between 1990 and 2010 the world population grew by 30% (see Fig 1). In short, people live longer due to advances in science and medical care. This growth compels us to develop a better food supply.

Rank

Country

Population
2010

Population
1990

Growth (%)
1990–2010

  World

6,895,889,000

5,306,425,000

30.0%

1  China

1,341,335,000

1,145,195,000

17.1%

2  India

1,224,614,000

873,785,000

40.2%

3 United States

310,384,000

253,339,000

22.5%

4  Indonesia

239,871,000

184,346,000

30.1%

5  Brazil

194,946,000

149,650,000

30.3%

6  Pakistan

173,593,000

111,845,000

55.3%

7  Nigeria

158,423,000

97,552,000

62.4%

8  Bangladesh

148,692,000

105,256,000

41.3%

9  Russia

142,958,000

148,244,000

-3.6%

10  Japan

128,057,000

122,251,000

4.7%

Fig 1: Growth rates of the world’s most populous countries

While the growth rates are expected to decline going forward, we expect to see a steady growth of the population in absolute numbers until 2050. At that time we expect the human population will have increased to about 9.6 billion.

As we must prepare for a planet with over 9.6 billion people, scientists in our field are starting the New Green Revolution, leveraging genetic markers to discover opportunities to increase the yield achievable in both plant and animal production. Technologies that allow us to select candidates of a given species based on their predicted performance, allows us to speed up research and development. We want to create crops with the highest possible yield that can survive in potentially harsh environments and that require the minimum amount of water, fertilization, herbicides and pesticides. We want to find ways to optimally produce animal protein, be it beef, chicken, pork or any other type. In the end this field may be more important to us than all the research taking place  in human genetics. Certainly, we would like to feed three meals every day of the year to every human on the planet. Compared to that, a much lower percentage of us actually need to see a doctor on any given day.

We have improved SVS by introducing methods such as gBLUP and Bayes C-pi that are widely used to conduct genomic prediction analysis. Our goal is to shorten the time from study design to final analysis. Ultimately, this is key in turning relevant research into publication; it’s a space that we continue to pay attention to. Please look for my new e-book on genomic prediction, and join us Dec. 16th for our webcast: Genomic Prediction with Golden Helix SVS. Register here.

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