Monthly Archives: August 2016

August issue cover: What’s going on here?

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Rhinopithecus bieti

Rhinopithecus bieti{credit}Yong-cheng Long{/credit}

This month’s cover image is inspired by the paper on page 947 reporting the reference genome sequence of the black snub-nosed monkey, the second snub-nosed monkey genome paper published in Nature Genetics. The golden snub-nosed monkey genome was published in 2014.

In their paper, Li Yu and colleagues present the de novo genome sequence assembly of Rhinopithecus bieti as well as whole genome resequencing of all four other snub-nosed monkey species. All five species are among the world’s most endangered primate species. Three species, R. bieti, R. roxellana and R. strykeri, live at very high altitudes—above 3,000 meters. R. bieti lives exclusively on the Yunnan and Tibetan plateaus. The other two species, R. brelichi and R. avunculus, inhabit lowland regions. The authors compared the genome sequences between these species to identify genomic regions showing evidence of positive selection that could be related to living at high altitudes.

The photograph on the cover image was taken by one of the study’s co-authors, Dr. Yong-Cheng Long, who was profiled by the Nature Conservancy for his work on conservation of R. bieti (also called the Yunnan golden monkey by the locals). We asked Dr. Long to tell us a little about the monkey shown in the picture.

“The monkey is [a] male, whose name is ‘Big Guy’, and he is feeding on some leaves,” he said by email. “The Big Guy used to have 4 wives (about 6 years ago) and now has only 2, as he is getting old and is not strong enough to hold all of them because the females are more likely to find a strong shoulder to cry on.”

Dr. Long said there are 57 R. bieti individuals in the habituated “Yunnan snuby” group, which is open to the public. Because many of the individuals in the area are fully habituated to human presence, it is not difficult to get photographs of them. The group is only a small portion of the largest natural monkey troop (approximately 1,000 in total) in the world. Dr. Long emphasized the impact that illegal poaching has had on the monkeys. “This species has been endangered by human’s killing, and the monkeys can certainly survive once the killing is stopped.” In China, 2016 is the Year of the Monkey, and it has turned out to also be a lucky year for these particular monkeys. “We found the monkey group has boomed,” said Dr. Long. “12 of the 57 are the infants born this year.”

monkey

Nature Genetics office mascot

The lead author of the study, Dr. Yu, became interested in studying these species because of his focus on conservation genetics of endangered mammals distributed in Yunnan Province, China. This is one of the core regions of biodiversity in the world. “The most notable among the endangered mammals distributed in Yunnan Province is R. bieti, which is found exclusively on Yunnan and Tibetan Plateau”, said Dr. Yu by email. “It is unique in that it is the only primate having a red mouth like most humans, which [is why it’s called] one of the most beautiful animals.” Dr. Yu also noted that it is the highest altitude-dwelling nonhuman primate. It can survive in very cold and hypoxic environments that other primates cannot tolerate. “So, I was deeply attracted by this mysterious and interesting species, and was eager to come to understand it.”

 

IMG_1863We at Nature Genetics are also celebrating the Chinese Year of the Monkey. Our office mascot is this golden snub-nosed monkey (right), which was produced for marketing purposes in China (I snagged one during a recent visit to the Shanghai office). Scanning a barcode on the monkey’s rear end (left) will take you to the publication of the R. roxellana (golden snub-nosed monkey) genome paper.

 

 

Joint calling of the ExAC publications

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ExAC publications in Nature

We report this week in Nature and Nature Genetics the first publications from the Exome Aggregation Consortium (ExAC), a project that has generated the largest catalogue to date of variation in the protein-coding regions of the genome (known collectively as the exome), aggregating sequence data from over 60,000 individuals from across 21 research studies. Most importantly, they have provided a publicly accessible database (https://exac.broadinstitute.org), which has already become a critical resource for research and clinical studies. While an estimated over 1 million individuals have been exome or whole genome sequenced, only a small fraction of this data has been made publicly available, as there are many challenges to sharing and providing open access to these datasets. We applaud the authors for recognizing this need and meeting these challenges.

This work comes 15 years after we published the Human Genome Project, and follows in a series of community resources to catalogue variation in human genomes within and across populations. We continue to support these efforts, recognizing the necessity of developing these resources to further studies to understand the information encoded in our genome, genetic variation and genetic basis of disease.

Mapping ExAC publications

Very rare genetic variation: a first look

The scale of this sequencing dataset in ExAC has provided some of our first glimpses into very rare genetic variation across populations, with several important early insights. Firstly, the authors identify more than 7.4 million high-confidence genetic variants, on average one every 8 bases, the majority of them entirely novel (not present in any existing database) and extremely rare (more than half of the variants are seen only once across all 60,706 samples). Second, they are able to document recurrent rare mutations emerging independently, providing an estimate of the frequency of recurrence, never observed systematically before due to the need for such large sample sizes. Third, they are able to examine the level of selective constraint against protein-truncating variation, identifying 3,230 genes that appear highly loss-of-function-intolerant. Reassuringly, this includes most known human haploinsufficient disease genes, however 72% do not yet have an established human disease phenotype. While some of these genes may be associated with weaker phenotypes or embryonic lethality, this points to how much more we have yet to understand about the phenotypic consequences of loss of function in human genes.

Copy number variation in ExAC

In a companion paper in Nature Genetics, Douglas Rudefer, Shaun Purcell and colleagues examine rare copy number variation (CNV) with the ExAC dataset, specifically the rates and properties of genic CNVs with <0.5% frequency. They use their previous method XHMM to characterize CNV calls from this exome sequencing dataset. They find that ~70% of individuals carry at least one rare genic CNV, with an average of 0.81 deleted and 1.75 duplicated genes. The authors also estimate relative intolerance to CNVs for each gene. This CNV dataset is incorporated into ExAC and will be useful for continuing population and disease association studies, together with other measures of genic intolerance, and the authors provide an example of this in analysis of a schizophrenia case-control study.

Clinical genetics: classifying pathogenic variation

The current work also brings an important message for clinical genetics in the need for reexamining the literature on classifying pathogenic variation for rare disorders. The average ExAC participant harbors ~54 variants that have previously been classified as causal for a disease, and considering the ascertainment of the study it is likely that most of this may be due to misclassified variants.

Using ExAC as a reference panel for classifying disease relevant variation, Lek et al. review the evidence for pathogenicity of 192 previously reported pathogenic variants for rare Mendelian disorders. Only 9 of these variants had sufficient support for disease association, with a high proportion of these variants present at an implausibly high frequency in the ExAC dataset. This suggests that many of these were false positive associations and incorrectly classified as pathogenic, the implications of which are not merely academic, as these findings are often used in clinical diagnoses and treatment.

In two additional companion publications, the authors take this a step further and demonstrate what is needed to move towards resolution of the nature of these prior associations, by bringing together large case series combined with ExAC. Walsh et al. (Genetics in Medicine, 10.1038/GIM.2016.90 published online August 17, 2016) systematically reexamine evidence for genes implicated in cardiomyopathy, one of the most common and severe rare disorders, and find many well known purported cardiomyopathy genes do not show support for pathogenicity, including some that are included in routine clinical genetic testing. Similarly, Minikel et al. collect 16,025 prion disease cases, the largest case series ever available for prion disease, for which ~10-15% of cases are estimated to be caused by mutations in the PRNP gene. They find a number of variants in PRNP thought to be pathogenic and with high penetrance appear to be likely benign (Minikel et al. Science Translational Medicine 10.1126/scitranslmed.aad5169). This led to a corrected patient diagnosis soon after this report, as Robert Green explained in his Perspective accompanying this publication (Lebo et al. Science Translational Medicine 10.1126/scitranslmed.aad9460).

These findings highlight the necessity to carefully evaluate the literature for rare genetic disorders. This also reinforces the value of large reference panels such as ExAC for filtering variants seen in patient exomes, a practice most of the genomics community has adopted in establishing standards for assessing sequence variants in human disease (MacArthur et al. Nature 508, 469–476 (2014), 10.1038/nature13127). The ExAC project continues to expand in size, hoping to increase to more than 120,000 exome sequences over this next year, as well as 20,000 whole genome sequences, bringing additional sample size, diversity and exploration of non-coding regions that will aid these efforts.

ClinVar and contributing to variant interpretation databases

This project, which relied on the willingness of many large research consortia to provide their raw data, demonstrates the extreme value of promoting the sharing, aggregation and harmonization of genomic data. This is true also for patient genetic variants, as there is a need for databases that provide greater confidence in variant interpretation. NCBI’s ClinVar database, which accepts contributions of clinically annotated genetic variation from clinical labs, clinicians and researchers, has become a key resource for clinical variant interpretation.

Improvements to the landscape of clinical genetics will require continued investment in such variant databases, continued expansion of human genetic reference panels, as well as efforts to link these to phenotype data. Recontacting to obtain phenotype data will be trialed on a subset of the ExAC dataset where consents allow, while new initiatives such as the UK 100,000 Genomes Project and the US Precision Medicine Initiative will also provide linked genome and phenotype information. Finally, enabling the ethical sharing of linked genetic and clinical data without violating participant privacy will require fundamental innovation in regulation and ethics policy, work that has been started by bodies such as the NIH and the Global Alliance for Genomics and Health, but around which considerable uncertainty remains.

Farm to Genomes: African Rice

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Meyer at al., Nature Genetics, 2016

Meyer at al., Nature Genetics, 2016

Rice is one of the most important crops on the planet, responsible for feeding billions of people. Given this global significance, studying rice in different geographies can be useful and aid in harnessing genetic diversity underlying particular traits and adaptations favorable to different environments. African rice (Oryza glaberrima Steud.) is mainly grown in sub-Saharan Africa and known for its stress tolerance. In a new article this week in Nature Genetics, Michael Purugganan and colleagues report the whole genome re-sequencing of 93 African rice landraces from various regions of Western coastal and sub-Saharan Africa. They create a genome-wide SNP map and through comparative genomic analysis study the domestication and population history of African rice. They use their map to perform GWAS for salt tolerance and find 11 significantly associated regions, highlighting the value of this unique genetic resource.

Meyer et al., Nature Genetics, 2016

Meyer et al., Nature Genetics, 2016

By studying various regions with distinct environments, the authors were able to get clues about adaptation and geographic spread of the populations. They focused on coastal Senegal and inland Togo, which have higher and lower levels of soil salinity, respectively, and interviewed farmers in the region to understand the agricultural practices they employ in each region. The knowledge of the farmers helped to inform the genetic analysis and contributed to the model of African rice domestication and dispersal.

You can watch some of the interviews with the farmers here:

African rice farmers- interviews

Additionally, we spoke with authors Michael Purugganan and Rachel Meyer to get some background on this research.

Why do you think that rice is understudied in Africa compared to other places?

MP: I think it’s because it is not widely grown, unlike its Asian counterpart which has pretty much taken over the world.  But there definitely is more interest in African rice as breeders are trying to figure out how to increase food production in Africa, as well as to try to see what genes in African rice can be used to improve Asian rice.

RM: There is a lot of great research on improving Asian rice for African farmers that is being done by brilliant AfricaRice scientists, and they are working hard on the social science side too. But there are so many challenges that Africa disproportionately faces – particularly climate variation – that demands ramping up rice research. There is insufficient support for programs that integrate crop experiments and trials into the different farmlands. A better connection between scientists and small-scale farmers would really help farmers adopt new varieties too- because there is sometimes resistance to trying new ones.

How did you choose which samples to include in your analysis?

RM: Recognizing that a lot of NGO work encouraging farmers to grow Asian rice ramped up in the 80’s and 90’s, we took advantage of the germplasm largely donated in the 70’s to the West Africa Rice Development Association, which were duplicated and available through IRRI (International Rice Research Institute). We chose accessions with the most metadata available, preferring ones with georeferenced location and a cultivar name. It wasn’t until later that we realized water tables far inland were high in salinity, so we just tried to make sure we had a fair number of samples within 250km of the coast, or along rivers connecting to the ocean.

Were you surprised by any of your findings?

MP: There definitely were a few surprises in the data, but the big revelation for me was the long time for the population bottleneck that led to domestication.  We found from the genomic data that it may have taken more than 10,000 years of steady population decline before full-blown domesticated African rice shows up in the archaeological record.  This suggests the possibility that humans were already cultivating or managing its ancestor for thousands of years, and I think if this pattern holds for other domesticated crop species it will change our thinking on how domestication has taken place.

RM: I was surprised we got nice GWAS results with so few samples, and even more surprised that we saw several of those exhibiting signatures of geographic selection. We were lucky to find a broad distribution of traits in the landraces we chose to sequence, for we had made the DNA libraries ahead of the phenotyping experiments.

What was it like to meet and talk with the farmers?

RM: It was one of the highlights of my life to meet the farmers! I’m grateful to have gotten a glimpse of their heritage, their pride, and their struggles. We were all so impressed with the generosity of women, in particular, to help each other. We were also shocked by how many farms are run by the elderly; their children don’t see farming as profitable and many have left. For the three of us in the field, it made us think hard about how we can give back to the communities that gave us their time. I hope that crop science, publicity (like this blog) and policy changes can raise the profile of the small-scale farmer.

In each interview, the farmers also had a chance to interview us, and that part was especially interesting. Several asked really good questions about African and Asian rice domestication. You could see the cultural value of the basic science.

You chose to focus on salinity tolerance as a trait particularly relevant to farming in Africa.  In what ways do you see your results being used for crop improvement?

RM: One of the authors, from AfricaRice, Dr. Kofi Bimpong, had actually been working on salt tolerance separately as well, and has two graduate student collecting African rice landraces in Casamance. If from this paper we can consider that domestication possibly occurred in the Inner Niger Delta region and also in the West, then these collecting efforts are all the more important because they are from a center of origin, promising more genetic variation than people would have ever estimated. If you look through the available germplasm there is so little that has been collected or studied from Casamance. It’s tricky collecting there, for there is social unrest, and landmines. Hats off to the young graduate students, Mamadou Sock and Bathe Diop, doing that fieldwork; I’m sure there is a lot of discovery to be made with those collections, and more promising salt tolerant landraces to integrate into breeding programs.

In addition, our results suggesting many of the salt tolerance genes are shared in both rice species make them more valuable to explore in other crops.  Shared adaptive mechanisms are especially fascinating to evolutionary biologists and are powerful assets of the breeder’s toolbox.