Chris Armit

![GA4GH increases
diversity](http://gigasciencejournal.com/blog/wp-content/uploads/2020/10/timj-ots0EOYuGtU-unsplash-1024x768.jpg){.aligncenter
.wp-image-3500 loading="lazy" decoding="async" width="452" height="339"
srcset="http://gigasciencejournal.com/blog/wp-content/uploads/2020/10/timj-ots0EOYuGtU-unsplash-1024x768.jpg 1024w, http://gigasciencejournal.com/blog/wp-content/uploads/2020/10/timj-ots0EOYuGtU-unsplash-300x225.jpg 300w, http://gigasciencejournal.com/blog/wp-content/uploads/2020/10/timj-ots0EOYuGtU-unsplash-768x576.jpg 768w"
sizes="(max-width: 452px) 100vw, 452px"}**Diversity, Ancestry, and the
Tenacious Concept of Race**  
The Global Alliance for Genomics and Health
([GA4GH](https://www.ga4gh.org/)) is a policy-framing and technical
standards-setting organization, seeking to enable responsible genomic
data sharing within a human rights framework. *GigaScience* are
[organisational
members](https://www.ga4gh.org/community/organizational-members/), and
their meeting often coincides with the American Society of Genetics
meeting that sometimes participate in this initiative (see a [write up
in
GigaBlog](http://gigasciencejournal.com/blog/sharing-genomic-data-precision-medicine-era/)).
This year GA4GH 8th Plenary Meeting was a virtual conference with over
230 attendees from over 60 different countries that took place on 29th
and 30th September 2020. *GigaScience* Data Scientist Chris Armit
attended the talks and reports on why diversity of genomic data is such
a hot and contentious topic. With diversity such a key topic at this
years plenary, being a virtual meeting was a particularly useful way to
increase voices and participation from across the globe.

[Charles Rotimi](https://irp.nih.gov/pi/charles-rotimi) of NIH, who is
also the founder of the [African Society of Human
Genetics](https://www.afshg.org/), delivered an exceptional opening
keynote talk entitled "Diversity in Genome Science: A Scientific &
Social Justice Imperative". As Charles explained, when exploring
diversity, "Africa is a good place to start". "About 99% of human
evolutionary experience, as a species, was spent in Africa before some
migrated out to populate the rest of the world about 100,000 years ago.
This common history is why humans all over the world share over 99% of
our genetic inheritance". Charles further explained the bottleneck
effect that was a key feature of this Out-of-Africa migration, whereby a
parent population with significant genetic variation remained in Africa.
Charles emphasised that "Africa is the only place to study these
variants" and that human genetics will gain immensely from the sampling
of African populations.

*In his keynote talk, Charles Rotimi highlighted the genomic diversity
of African populations.*

In a fascinating study of pathogenic and clinically relevant variation
in Africa, Charles highlighted disease as a strong driver of
genome-level population variation. To illustrate with one example,
Sickle cell disease is an autosomal recessive disorder prevalent in
African populations. The concept here is that of a genetic trade-off, as
heterozygous carriers of the sickle cell trait have a protective
advantage against malaria. This explains why this trait is common in
malaria-endemic areas. As Charles explained there are other examples,
with variation in the gene encoding the serum factor APOL1 being
associated with kidney disease in African populations. APOL1 is a serum
factor that lyses unicellular trypanosomes, and protects against the
lethal form of African sleeping sickness. This would appear to be
another genetic trade-off as the APOL1 variant SNP rs73885319 that
prevails in Yoruba populations is associated with a high risk of kidney
disease. Charles further explained the societal impact of variation in
the APOL1 locus in the context of transplants, as an individual with two
variant copies of the APOL1 gene will also have a high risk of failure
as a kidney donor.

As an additional example of how genetics can help us understand African
tropical disease, Charles offered a case study of
[podoconiosis](https://en.wikipedia.org/wiki/Podoconiosis). This
neglected disease is a non-filarial elephantiasis that is not based on
infection by a pathogen, but is rather a reaction to long-term barefoot
exposure to red clay soil derived from volcanic rock. Podoconiosis has a
high degree of heritability, and genome-wide associations (GWAS) between
variants in HLA Class II loci suggest that this condition may be a
T-cell mediated inflammatory disease. These are invaluable insights that
will help us understand the disease susceptibility in African
populations and also gene flow in African populations.

**The Importance of Diversity in Genomic Data**

This keynote talk was followed by a panel discussion on "The Importance
of Diversity in Genomic Data". [Alice
Popejoy](https://profiles.stanford.edu/alice-popejoy) (Stanford
University) explained that there is "no standard definition of diversity
measures", and further explained the problematic concepts of Race,
Ethnicity and Ancestry. Geneticists and Biomedical Scientists are
primarily interested in ancestry, which is the biological inheritance of
DNA and can be traced through the genome using genotype data. However,
in the USA, patients are often invited to declare their racial
affiliation, which is a socio-political classification mechanism and
which, as Alice explains, is "often tied to status and power". In
European countries, patients are often invited to declare their
ethnicity which, from a genomics and health perspective, is also a
troublesome classification as it is, as Alice explains, "a cultural
construct often linked to community, religion, language". In both
instances, ancestry is being sidelined.

*In her panelist presentation, Alice Popejoy highlighted the need for
standardised diversity measures based on ancestry.*

This message was echoed by [Consuelo
Wilkins](https://medicine.vumc.org/person/consuelo-h-wilkins-md-msci)
(Vanderbilt University) who expounded "race and ethnicity often serve as
surrogates for other constructs that explain differences in health", and
Consuelo considered socioeconomic status, education, and access to
health care are some of these constructs that are often associated with
race. Indeed, as Consuelo explained "race is one of the most imprecise
variables we use in human research". There is a clear need to replace
this outdated concept of race with the biological concepts of diversity
and ancestry.

*In her panelist presentation, Consuelo Wilkins explained how race and
ethnicity are often used as surrogates for other constructs that explain
differences in health.*

[Giorgio
Sirugo](https://www.med.upenn.edu/apps/faculty/index.php/g5455356/p9153923)
(University of Pennsylvania) used an example of dizygotic (fraternal)
twins to highlight the problematic concept of race. In a striking
example of UK-born fraternal twins, one with dark skin and dark brown
hair and the other with alabaster skin and reddish hair, Giorgio made
the point that closely related individuals can look quite different.
Consequently, if we tend to define race based on how people 'look', this
too is problematic because there are clear examples of even very closely
related individuals looking quite different with regard to having iconic
"racial" features. It would be intriguing to know whether siblings with
divergent phenotypes such as these show greater diversity in their
genetic makeup, or whether other epigenetic factors are responsible for
the observed variability in phenotypic penetrance.

*In his panelist presentation, Giorgio Sirugo highlighted the phenotypic
diversity that can be observed in siblings and even fratenal twins.*

Giorgio further explored the transferability of genetic findings across
diverse populations with reference to monogenic (single gene) diseases,
oligogenic diseases (complex traits), and polygenic diseases (multiple
genes), and highlighted that linkage disequilibrium (LD) -- whereby
common causative variants may be tagged by different SNPs in different
populations -- will have a major effect on transferring our
understanding of polygenic diseases across diverse populations.

Continuing the subject of diversity, [Laura
Paglione](https://sphericalcowgroup.com/about) (Spherical Cow Group)
took a deep dive into the core objective of GA4GH in her keynote talk
entitled "Building an Intentional Community for Standards Development"
and explained that "inclusion must be a priority for all of us". Laura
offered an insightful example of the issues associated with a lack of
inclusion by highlighting a case in the US where an imbalance of females
to males in clinical trials led to misleading results. Laura cuts the
phrase, "teams that look alike, arrive at solutions that look alike",
and Laura strongly advocates for inclusion and diversity in the genomic
health community as a means of improving how genomic data are collected,
managed and accessed.

*In her keynote talk, Laura Paglione detailed the benefits of inclusion
and the importance of building an intentional community in Genomics and
Health.*

**Real World Implementation of GA4GH Tools and Standards**

Day 2 of the Plenary Meeting explored real-world implementations of
tools and standards. The Global Alliance team detailed their plan for
Genomic and Health-Related Data Sharing. The core concept is that data
are distributed across a federated network, and individual web services
become registered as nodes. By using service registries, researchers can
query multiple datasets simultaneously, ensuring fast and efficient
federated query. Retrieval of datasets can then be performed via API or,
alternatively, Cloud-based analysis with provenance of the various
analytical steps. The latter is exceptionally important as it ensures
that a researcher can check that their bioinformatic analyses were
performed in accordance with their expectations.

Elixir Director Niklas Blomberg asked the question "How far away are we
from a full implementation / demonstrator of the full research data
access cycle?" In reply to this, [Michael
Baudis](https://www.mls.uzh.ch/en/research/baudis.html) (University of
Zurich) explained that we should not think of the proposed GA4GH data
sharing mechanism as a complete platform, but rather as a suite of
tools, and that a major factor in the success of this project is the
degree to which researchers align themselves with the various tools
developed by the GA4GH Global Alliance. On this note, the panel
discussions on "Real-world implementation of tools and standards" were
especially informative, with [Shaikh Farhan
Rashid](https://www.distributedgenomics.ca/team.html) (CanDIG)
highlighting the need for a "visa model for authorisation" and [Augusto
Rendon](https://www.genomicsengland.co.uk/about-genomics-england/the-board/executive-leadership-team/)
(Genomics England) declaring that "our data is read only...you cannot
download primary data".

From the real-world implementations described by the various institutes
in Europe, Canada, Brazil, Japan, and Australia, there was universal
emphasis on the confidentiality of genomic and health-related data, with
the various institutes further addressing the need for a mechanism by
which researchers can access the genomic data that are required for
their study. One of the main benefits of GA4GH is that it will enable
researchers to use genomic data from other countries in their research.
In her talk entitled "GEM Japan -- Real World Implementation", [Takako
Takai](https://www.megabank.tohoku.ac.jp/english/about/member/department05/#takai)
(Japan Agency for Medical Research and Development) provided what could
be the mission statement of the GA4GH, namely that "we could bring a new
research harmonisation that was hardly realised before".

*The GA4GH Work Stream Managers discuss how GA4GH standards can support
a Global Learning Health System.*

At *GigaScience*, we look forward to the fruits of the research that
will be made possible by GA4GH, and as organisational members we'll
watch the development of tools and standards and try to implement them
when we can.

The post [Diversity, Ancestry, and the Tenacious Concept of Race:
GigaScience at
GA4GH](http://gigasciencejournal.com/blog/diversity-ancestry-and-race-at-ga4gh/){rel="nofollow"}
appeared first on
[GigaBlog](http://gigasciencejournal.com/blog){rel="nofollow"}.


Diversity, Ancestry, and the Tenacious Concept of Race

The Global Alliance for Genomics and Health (GA4GH) is a policy-framing and technical standards-setting organization, seeking to enable responsible genomic data sharing within a human rights framework.

Diversity, Ancestry, and the Tenacious Concept of Race: GigaScience at GA4GH

Scott Edmunds

**3000 Rice Genome Sequences Made Publicly Available on World Hunger
Day**  
![](http://gigasciencejournal.com/blog/wp-content/uploads/2014/05/rice3k.jpeg){.alignleft
.size-full .wp-image-1992 loading="lazy" decoding="async" width="275"
height="183"}Yesterday marked the [publication in
*GigaScience*](http://dx.doi.org/10.1186/2047-217X-3-7 "Rice 3K Data Note"){target="_blank"
rel="noopener"} of the first data from the 3,000 Rice Genomes Project, a
collaboration between the [Chinese Academy of Agricultural Sciences
(CAAS)](http://www.caas.cn/en/ "CAAS homepage"){target="_blank"
rel="noopener"}, [the International Rice Research Institute
(IRRI)](http://irri.org/ "IRRI homepage"){target="_blank"
rel="noopener"}, and
[BGI](http://www.genomics.cn/en/index "BGI homepage"){target="_blank"
rel="noopener"}; as well as [a
commentary](http://www.gigasciencejournal.com/content/3/1/8 "Rice 3K Commentary"){target="_blank"
rel="noopener"} from the Directors of these institutes outlining the
goals of this ambitious project. Our biggest Data Note to date, the
publication and [release of this enormous dataset in our GigaDB
repository](http://dx.doi.org/10.5524/200001 "Rice DOI"){target="_blank"
rel="noopener"} quadruples the current amount of publicly available rice
sequence data, and ranks amongst the largest -- in terms of samples --
genome projects that have been published to date (see Nick Loman's
["biggest sequencing projects uber
list"](http://pathogenomics.bham.ac.uk/blog/2013/12/the-biggest-genome-sequencing-projects-the-uber-list/ "Nick Loman blog"){target="_blank"
rel="noopener"}, where the project would currently rank as the largest
non-microbial genome project). This demonstrates the profound effect
that whole-genome sequencing is having on the study of biology, the size
and scope of where the field of genomics is now. Following closely on
from the [large worm imaging
dataset](http://blogs.biomedcentral.com/gigablog/2014/05/19/the-early-earthworm-catches-on-to-full-data-release/ "Worm blog"){target="_blank"
rel="noopener"} we also published as a Data Note this month, [this
paper](http://dx.doi.org/10.1186/2047-217X-3-7 "Rice 3K Data Note"){target="_blank"
rel="noopener"} further shows the utility of our ("big") data publishing
approach in aiding and incentivizing the rapid release data in such
important areas of research as this.

The
[publication](http://www.gigasciencejournal.com/content/3/1/7 "Rice 3K Data Note"){target="_blank"
rel="noopener"} coincided with [World Hunger
Day](http://www.thehungerproject.co.uk/getinvolved/worldhungerday/world-hunger-day-purpose/ "World Hunger Day Website"){target="_blank"
rel="noopener"}, highlighting one of the primary goals of this
project--- to develop resources that will aid in improving global food
security, especially in the poorest areas of the world. With more than
1/8th of the world's population living in extreme hunger and poverty,
and the world population estimated to reach 9.6 billion by 2050, there
is a huge need to create new resources to improve crop yield, reduce the
impact on the environment, and develop food crops that are of high yield
and nutrition and can grow successfully in environments stressed by
drought, pests, diseases, or soil degradation. While rice research has
greatly advanced since the completion of the first high-quality rice
genome sequence in 2005, there has been limited change in breeding
practices that are important for producing improved and better adapted
rice strains.

[![IMG_2679](http://gigasciencejournal.com/blog/wp-content/uploads/2014/05/IMG_2679-200x300.png){.alignright
.size-medium .wp-image-1120 loading="lazy" decoding="async"
sizes="(max-width: 200px) 100vw, 200px"
srcset="http://gigasciencejournal.com/blog/wp-content/uploads/2014/05/IMG_2679-200x300.png 200w, http://gigasciencejournal.com/blog/wp-content/uploads/2014/05/IMG_2679.png 640w"
width="200"
height="300"}](http://gigasciencejournal.com/blog/wp-content/uploads/2014/05/IMG_2679.png)The
3,000 Rice Genomes Project provides a major step forward for addressing
these challenges by creating and releasing an extensive amount of
genetic information that can ultimately be applied to intelligent
breeding practices, which take advantage of the natural variation
between different plant strains and information on the genetic
mechanisms that underlie these traits to select strains for breeding
that will be more successful in producing hybrid strains with
characteristics that are highly suited for growing successfully in
different environments. This work is only the first stage of an ongoing
the project, and has been funded by the [Bill and Melinda Gates
Foundation](http://www.gatesfoundation.org/ "Gates Foundation Website"){target="_blank"
rel="noopener"} and the Chinese Ministry of Science and Technology, as
part of their goals to kickstart a second green revolution, and develop
badly needed new strains of rice tailored to different environments (see
the recent [economist
article](http://www.economist.com/news/briefing/21601815-another-green-revolution-stirring-worlds-paddy-fields-bigger-rice-bowl "Economist rice paper"){target="_blank"
rel="noopener"} highlighting these efforts). The Gates Foundation has
taken a [particular interest in improving agricultural
development](http://www.gatesfoundation.org/What-We-Do/Global-Development/Agricultural-Development "Gates Agriculture website"){target="_blank"
rel="noopener"} through technological innovations, and Bill Gates
visited our BGI Hong Kong offices last year to see how this (and other
BGI collaborations) were going.

Dr. Zhikang Li (the Project Director at CAAS), stated that the 3000 Rice
Genomes Project is part of an ongoing effort to provide resources
specifically for poverty-stricken farmers in Africa and Asia, aiming to
reach at least 20 million rice farmers in 16 target countries. "Rice is
the staple food for most Asian people, and has increasing consumption in
Africa," said Dr. Li. "With decreasing resources (water and land), food
security is ---and will be--- the most challenging issue in these
countries, both currently and in the future. As a scientist in rice
genetics, breeding and genomics, it would be a dream to help to solve
this problem."

Dr. Jun Wang (BGI Director and member of our Editorial board), added to
this, saying that, "the population boom and worsening climate crisis
have presented big challenges on global food shortage and safety. BGI is
dedicated to applying genomics technologies to make a fast, controllable
and highly efficient molecular breeding model possible. This opens a new
way to carry out agricultural breeding. With the joined forces with
CAAS, IRRI and Gates Foundation, we have made a step forward in
big-data-based crop research and digitalized breeding. We believe every
step will get us closer to the ultimate goal of improving the wellbeing
of human race."

According to the corresponding author of our [accompanying
commentary](http://www.gigasciencejournal.com/content/3/1/8 "Rice 3K Commentary"){target="_blank"
rel="noopener"}, IRRI director general Dr. Robert Zeigler, "access to
3,000 genomes of rice sequence data will tremendously accelerate the
ability of breeding programs to overcome key hurdles mankind faces in
the near future." This collaborative project, added Zeigler, "will add
an immense amount of knowledge to rice genetics, and enable detailed
analysis by the global research community to ultimately benefit the
poorest farmers who grow rice under the most difficult conditions."

**Genomics-assisted breeding to the rescue**  
To reach their goals, the three-institute collaboration has not only
released 13.4 terabytes of data into the public domain, they have also
collected seeds from each strain (available in the [International Rice
Genebank
Collection](http://irri.org/our-work/research/genetic-diversity/international-rice-genebank "IRRI genebank homepage"){target="_blank"
rel="noopener"} housed at IRRI). Having banked seeds is essential to
make full use of these now genetically defined strains to develop and
sustain the most appropriate hybrid strains for different environments.
There remains, however, one additional component to achieve this goal:
this is information that allows researchers and breeders to directly
link the genetic information (genotype) to the physical traits
(phenotype) of these different strains. This requires careful assessment
and curation of each rice strain for agriculturally important traits,
which can then be linked to genetic markers in the now available genome
sequences.

Current breeding practices, which have essentially remained the same
since the development of agriculture, typically use apparent physical
traits to guide strain selection for crossbreeding with the hope that
the offspring will manifest a combination and improvement of the desired
traits, such as drought, pest and disease resistance and increased crop
productivity and improved nutritional value. However, the underlying
genetic makeup can often confound breeder expectations because unknown
genetic interactions can block, modify, or alter the development of the
selected physical characteristics when two strains are bred. Thus, trial
and error and multiple successive breeding stages are often required.

Having full knowledge of the genetic makeup of a plant allows
researchers to identify genetic markers related to specific physical
traits, and better understand how different genetic interactions effect
plant phenotypes. This information allows a breeder to make more
intelligent choices in strain selection, resulting in more accurate and
rapid development of rice strains that are better suited to different
agricultural environments in poor and environmentally stressed
economies.

This genomics-assisted breeding approach (which differs from GMO) is a
process that requires a great deal of care and manpower. Thus, the
release of these data, and making the genetic information freely
available to plant breeders and scientists across the world, will
greatly aid in defining genotype/phenotype relationships as well as
serve as an extensive resource improving our understanding of plant
biology.

On top of hosting the terabytes of supporting data [in
GigaDB](http://dx.doi.org/10.5524/200001 "Rice DOI"){target="_blank"
rel="noopener"}, sequence reads for this project have also been
submitted to the SRA repository at PRJEB6180.

### **References**

[1.](http://www.gigasciencejournal.com/content/3/1/7 "Rice 3K Data Note"){target="_blank"
rel="noopener"} The 3,000 Rice Genomes Project. The 3,000 Rice Genomes
Project. *GigaScience* **3**:7
[http://dx.doi.org/10.1186/2047-217X-3-7](http://dx.doi.org/10.1186/2047-217X-3-7 "Rice 3K Data Note"){target="_blank"
rel="noopener"}

[2.](http://www.gigasciencejournal.com/content/3/1/8){target="_blank"
rel="noopener"} Li, J-Y, Wang, J. and Zeigler The 3000 Rice Genomes
Project: new opportunities and challenges for future rice research.
*GigaScience* 2014, **3**:8
[http://dx.doi.org/10.1186/2047-217X-3-8](http://www.gigasciencejournal.com/content/3/1/8 "Rice 3K Commentary"){target="_blank"
rel="noopener"}

[3.](http://dx.doi.org/10.5524/200001 "Rice DOI"){target="_blank"
rel="noopener"} The 3000 Rice Genomes Project (2014): The Rice 3000
Genomes Project Data. GigaScience Database.
[http://dx.doi.org/10.5524/200001](http://dx.doi.org/10.5524/200001 "Rice DOI"){target="_blank"
rel="noopener"}

[Save]{style="border-radius: 2px; text-indent: 20px; width: auto; padding: 0px 4px 0px 0px; text-align: center; font: bold 11px/20px 'Helvetica Neue',Helvetica,sans-serif; color: #ffffff; background: #bd081c no-repeat scroll 3px 50% / 14px 14px; position: absolute; opacity: 1; z-index: 8675309; display: none; cursor: pointer;"}

[Save]{style="border-radius: 2px; text-indent: 20px; width: auto; padding: 0px 4px 0px 0px; text-align: center; font: bold 11px/20px 'Helvetica Neue',Helvetica,sans-serif; color: #ffffff; background: #bd081c no-repeat scroll 3px 50% / 14px 14px; position: absolute; opacity: 1; z-index: 8675309; display: none; cursor: pointer;"}

[Save]{style="border-radius: 2px; text-indent: 20px; width: auto; padding: 0px 4px 0px 0px; text-align: center; font: bold 11px/20px 'Helvetica Neue',Helvetica,sans-serif; color: #ffffff; background: #bd081c  no-repeat scroll 3px 50% / 14px 14px; position: absolute; opacity: 1; z-index: 8675309; display: none; cursor: pointer;"}

The post [Publish Data: Fight World
Hunger](http://gigasciencejournal.com/blog/publish-data-fight-world-hunger/){rel="nofollow"}
appeared first on
[GigaBlog](http://gigasciencejournal.com/blog){rel="nofollow"}.


3000 Rice Genome Sequences Made Publicly Available on World Hunger Day

Yesterday marked the publication in

 GigaScience

of the first data from the 3,000 Rice Genomes Project, a collaboration between the Chinese Academy of Agricultural Sciences (CAAS), the International Rice Research Institute (IRRI), and BGI; as well as a commentary from the Directors of these institutes outlining the goals of this ambitious project.

Publicaciones de Rogue Scholar

Diversity, Ancestry, and the Tenacious Concept of Race: GigaScience at GA4GH

Publish Data: Fight World Hunger