Towering sugar pine trees dominate the mountain forests of California and Oregon. They are the tallest pine trees in the world, regularly growing to skyscraper heights of over 100 meters. But these forest behemoths are under attack from a very tiny foe: an invasive fungus. White pine blister rust was accidentally introduced to western North America nearly a century ago. Since then, blister rust infections have been threatening the survival and reproduction of sugar pines, harming the ecosystem and industries that depend on them. Conservation efforts have shown that genetic variation contributes to the likelihood that one tree and not another succumbs to infection, but efforts to track down the genes involved have been complicated by the staggeringly huge genome of this giant tree and the arduous tests. The sugar pine genome is ten times the size of the human genome—a whopping 31 billion base pairs. Kristian Stevens and colleagues announced the complete sequence of the sugar pine genome in the December issue of GENETICS, the largest genome fully sequenced to date. Their work, along with a companion paper on the sugar pine transcriptome published in G3, highlights the evolutionary implications of such a massive genome size, as well as revealing candidate genes for blister rust resistance and a promising path to efficient selection of resistant individuals.

Despite its enormous size, the sugar pine genome contains about the same number of protein coding genes as the human genome. No less than 79% of the DNA in the sugar pine genome is made up of transposable elements, which accounts for its enormous size. These genetic parasites are stretches of DNA that exist only to proliferate within a genome. Rather than contributing to the sugar pine’s phenotype, they encode machinery that lets them make copies of themselves at new sites in the genome. Transposable elements are common in all eukaryotic genomes, but in conifers, and especially the sugar pine, they have multiplied to enormous numbers. In the sugar pine genome, the transposable elements are mostly non-functional relics. These genomic leftovers can tell researchers about the evolutionary history of the sugar pine and also provide insights about how genomes size evolves. They also create substantial problems for researchers trying to work with the sugar pine genome.

Transposable elements are highly repetitive, and when they are present in numbers as large as in the sugar pine, they are extremely difficult to sequence. Whole genome sequencing generally works by breaking a genome up into extremely small pieces and then putting them back together one by one. Repetitive genetic sequences make this process incredibly difficult because when the pieces are assembled, all the repeats look the same and end up incorrectly merged into one sequence. To get around this problem, the researchers assembling the sugar pine genome used several strategies. They obtained most of the sequence data from a single haploid pine nut, avoiding the typical complications of sequencing two parental genomes in a diploid individual.They sequenced the transcriptome to identify those sequences that produce proteins, and then used those sequences to assemble the corresponding genes. They also used sequencing libraries specially prepared with the reads known to be large distances away from one another, which is useful in linking larger genomic structures—the big picture. These techniques, along with others, allowed the researchers to build a useful working draft of the massive sugar pine genome.

A twig infected with white pine blister rust. Photo by Marek Argent via Wikimedia.

Sequencing an entire genome, especially one as large as the sugar pine, is an impressive technological achievement. More importantly, however, it is an incredibly powerful research tool in the fight against white pine blister rust. This fungus has been infecting multiple species of white pines in the North America since it was first introduced from Asia around the turn of the century. White pine blister rust is a slow killer, taking years to destroy a large tree. An infection begins when fungal spores land on the surface of the tree and begin to germinate. They grow through openings into the twigs and branches, and very slowly make their way towards the main trunk of the tree. The infected branches swell up and large sacks of rusty orange-red spores burst through the branches. The fungal infection causes cankers, which prevents the tree from sending water and nutrients to its damaged limbs. Eventually, these limbs will die. If cankers form on the main trunk, the entire tree may die.

Researchers and forest managers have been looking for a way to fight the spread of white pine blister rust for a long time. Some rare sugar pines carry genetic resistance to white pine blister rust, and have been used in reforestation efforts. In the 1970s, these rare individuals were used to identify a major locus of resistance called Cr1, but the daunting size of the sugar pine genome made further analysis difficult. Using this new genome sequence, Stevens and colleagues were able to make a breakthrough in identifying this gene. They used the small amount of genetic information already known to find large Cr1-associated segments and identify previously unknown SNPs that are closely associated with resistance. These markers are a powerful tool that can be used to quickly and cheapy identify trees that carry the resistant allele without waiting for the results of slow and expensive infection assays. Resistant trees can then be harvested for seeds to be used in reforestation. Now armed with a roadmap, scientists can search the sugar pine genome for the secrets that may help save these iconic trees and the ecosystems that depend on them.

Stevens, K. A., Wegrzyn, J. L., Zimin, A., Puiu, D., Crepeau, M., Cardeno, C., Paul, R., Gonzalez, D., Koriabine, M., Holtz-Morris., A. E., Martínez-García, P. J., Sezen, U.U., Marçais, G., Jermstad, K., McGuire, P. E., Loopstra, C. A., Davis, J. M., Eckert, A., deJong, P., Salzberg, S. L., Neale, & Langley, C. H. (2016). Sequence of the Sugar Pine Megagenome. Genetics, 204(4), 1613-1626. DOI: 10.1534/genetics.116.193227

http://www.genetics.org/content/204/4/1613.abstract

Gonzalez-Ibeas, D., Martinez-Garcia, P. J., Famula, R. A., Delfino-Mix, A., Stevens, K. A., Loopstra, C. A., Langley, C. H., Neale, D. B., & Wegrzyn, J. L. (2016). Assessing the gene content of the megagenome: sugar pine (Pinus lambertiana). G3: Genes| Genomes| Genetics, 6(12), 3787-3802. DOI: 10.1534/g3.116.032805

http://www.g3journal.org/content/6/12/3787.short

In 2009, after five years parching under the arid blue skies of Calcena in northeastern Spain, dozens of neat rows of maritime pine seedlings had grown unevenly. Some of the seedlings had died years ago, some were stunted but hanging on, while others grew tall and green.

The trees were not in their native soil. They had been grown from seeds collected at 19 sites around Spain, Portugal, France, and Morocco, and their growth was being monitored at a single site with an extreme climate to help predict the future of their species.

The experiment was designed to improve models that forecast where forests will grow as the southern European climate grows hotter and drier, and promises to help forestry managers choose tree stocks and decide where to focus reforestation efforts. In the March issue of GENETICS, Jaramillo-Correa et al. reported the results, identifying a handful of SNPs that can be used as predictors of maritime pine survival under different climatic conditions.

The maritime pine (Pinus pinaster Aiton) grows widely in southwestern Europe and parts of northern Africa. But the tree’s important economic value and ecological roles in the region may be at risk as the changing climate threatens the more vulnerable forests and the productivity of commercial plantations.

The species range is expected to move northward as the climate changes, says study leader Santiago González-Martínez, from the Forest Research Centre of Spain’s Institute for Agricultural Research (CIFOR-INIA). “But many populations in the Mediterranean region are already at risk, and we don’t necessarily know what genetic resources and adaptations we will lose if they disappear,” he says. “Another big problem for commercial plantations is that their tree stocks have been intensively bred for productivity, but not for resistance to drought. Forestry breeding cooperatives are very interested in introducing trees that are more resilient to climate change, with increased genetic diversity.”

Maritime pine common garden test site in Calcena, Spain. Image credit: Eduardo Notivol

Range-shift models are key tools for managing forests as the climate changes. These forecasts are based mainly on ecological and physiological data, however, and don’t take into account two major influences on a forest’s fate: genetics and evolution. Genetic differences between tree populations mean that forests vary in the degree to which they cope with changing conditions. Natural selection will also influence the prevalence of such genetic variants as the climate shifts.

Genetic effects can drastically change range-shift predictions, says González-Martínez. The maritime pine project sought to identify and quantify such effects in a way that could be readily incorporated into existing models.

To track down genetic variants that affect maritime pine fitness in different climate conditions, the team decided on a candidate gene approach, which is considerably faster and cheaper than surveying the large and complex maritime pine genome. Pine researchers from around the world pooled their expertise to yield a list of more than 300 SNPs in 200 candidate genes. “It was really a community effort, drawing on 15 years of research across many labs,” said González-Martínez.

From this candidate list, the team tested whether any of the SNPs were associated with climate variables across 36 natural populations, after correcting for geographic patterns in SNP frequency due to the different demographic histories at each site. Eighteen of the candidate SNPs showed significant associations with climate factors. These variants affected many different biological processes, including growth and response to heat stress.

The researchers then looked for evidence that these SNPs are important for fitness. They planted over 6,000 seedlings from 520 families and 19 locations together in the “common garden” in Calcena, where the climate falls at the extreme dry end of the species’ range. After five years, tree survival was significantly correlated with the frequency of SNP alleles predicted to be beneficial in the Calcena climate. In other words, the seedlings that were still thriving after five years in their new home tended to be the ones genetically well equipped to survive the harsh climate.

These results demonstrate the feasibility of this relatively fast approach of finding and confirming genetic variants associated with climate. Now that they have shown the method works, González-Martínez and his colleagues are expanding the project to cover more genes and more traits. “The single biggest climate change threat to pine forests is the increased frequency of wildfires, so we’re searching for variants that affect fire tolerance,” he says. They are also planting common gardens at many different locations—growing thousands more little seedlings whose fate will help geneticists predict the maritime pine’s future.

Read the press release: http://www.genetics-gsa.org/media/releases/GSA_PR_201503_pine.html

CITATION:

Jaramillo-Correa J.P., D. Grivet, C. Lepoittevin, F. Sebastiani, M. Heuertz, P. H. Garnier-Gere, R. Alia, C. Plomion, G. G. Vendramin & S. C. Gonzalez-Martinez & (2014). Molecular Proxies for Climate Maladaptation in a Long-Lived Tree (Pinus pinaster Aiton, Pinaceae), Genetics, 199 (3) 793-807. DOI: http://dx.doi.org/10.1534/genetics.114.173252 
http://www.genetics.org/content/199/3/793.full

The loblolly pine genome is big. Bloated with retrotransposons and other repetitive sequences, it is seven times larger than the human genome and easily big enough to overwhelm standard genome assembly methods.

This forced the loblolly pine genome sequencing team, led by David Neale at the University of California, Davis, to look for ways to reduce the enormous complexity of their task.
The draft genome sequence, described in the latest issue of GENETICS and the journal Genome Biology, was pieced together from over 16 billion sequence reads. Spanning around 23 billion base pairs, it only just beats out the Norway spruce as the largest genome ever sequenced, but it is substantially more complete. For example, the N50 scaffold size of the current loblolly assembly is 66.9 Kbp, compared to 0.72 Kbp in the Norway spruce.

So how did they do it?

One strategy was to generate most of the sequence from part of a single pine nut. This tiny source material was the megagametophyte, which is the haploid tissue that provides nutrients to the developing diploid embryo. Despite the limited amount of DNA that can be extracted from this source, the reduced complexity of a haploid genome makes it easier to assemble. To link up all the sequence fragments from the haploid genome, the team also created DNA libraries from diploid needles of the parent genotype.

But this still left the assembly team, led by Steven Salzberg at Johns Hopkins University and James Yorke at the University of Maryland, with more data than their computational methods could handle.

The solution was a method of pre-processing the data into “super reads”, or larger chunks of contiguous haploid sequence that condensed many individual reads. In essence, they were dealing with the unambiguous parts of the problem first, and getting rid a huge amount of overlapping and redundant data in the process.

The result was a 100-fold reduction in the amount of megagametophyte sequence that needed to be held in the memory of the assembly computer. That kind of reduction is not just handy for giant genomes; Salzberg says it also speeds up projects of more modest scale.

Luckily, says Salzberg, the loblolly genome project wasn’t held back by the masses of repeats that are typical of conifers. Even though around 82% of the loblolly pine genome is repetitive, it turns out that most of the repeats are evolutionarily ancient. That means they have diverged enough to no longer be a big stumbling block for assembly.

All this is good news for sequencing other conifer species, especially since the team is already tackling an even larger behemoth: the 35 gigabase genome of the sugar pine.

Check out the loblolly genome articles and other highlights of this month’s GENETICS.