Gene-by-environment interactions in urban populations modulate risk phenotypes

Environmental exposures, coupled with genetic variation, are known to have an effect on disease susceptibility. Dissecting their respective contributions remains one of the principal challenges in understanding complex diseases. Individuals with different genotypes (DNA sequence changes) may respond differently to environmental variation and generate an array of phenotypic landscapes (variations in the appearance of a trait such as a disease, or response to a drug or environmental toxicant). Such gene-by-environment (GxE) interactions are central to the theme of these GEITP pages and may be responsible for a large fraction of the unexplained variance in heritability and disease risk. Yet, disease risk –– owing to either environmental exposures and/or their interactions with genotype, remains poorly understood.

Canada’s precision medicine initiative, the Canadian Partnership for Tomorrow Project (CPTP; http://www.partnershipfortomorrow.ca) is a cohort comprising more than 315,000 Canadians, and captures over 700 variables –– ranging from longitudinal health information to environmental exposures –– to determine genetic and environmental factors contributing to chronic disease. The program includes the Quebec regional cohort, CARTaGENE, which has enrolled over 40,000, predominantly French-Canadian (FC) individuals between 40 and 70 years of age. Drawing from this founding population of individuals with largely French ancestry, authors [see attached report] selected 1,007 individuals to determine mechanisms by which genomes, the environment, and their interactions –– contribute to phenotypic variation.

They found a substantial impact of the environment on the transcriptome (the RNA transcribed from the DNA genome of each person) and clinical endophenotypes, overpowering that of genetic ancestry (The concept “endophenotype” was coined in a 1966 paper attempting to explain the geographic distribution of grasshoppers; it is a genetic epidemiological term which is used to separate behavioral symptoms into more stable phenotypes with a clear genetic connection). Air pollution was found to impact gene expression and pathways –– affecting cardio-metabolic and respiratory traits, when controlling for genetic ancestry. Lastly, authors capture four expression quantitative trait loci (eQTLs) that interact with the environment (air pollution). These findings demonstrate how the local environment can directly affect disease risk phenotypes. These data also show that genetic variation, including less common variants, can modulate an individual’s response to environmental challenges.

DwN

Nature Commun 2018; 9: 827 doi: 10.1038/s41467-018-03202-2

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More information about “predatory online open-access journals

Thanks, Ken, for your remark.

Beall’s List (although removed) can still be found online (and “last updated Feb 16, 2o18”). The list includes nowhere near 15,000 but it is quite a long list.

https://beallslist.weebly.com/standalone-journals.html

I do not see any “Journal of Cell”, or “Journal of Nature”, or “Journal of Science.” Also, no International Journal of Cell or Nature.

“Internatinal Journal of Science and Research” is perhaps the closest.

In the meantime –– just to give non-scientists on the GEITP List a “flavor” of what many scientists must endure each day –– here are two emails (of more than 35 during the past 48 h), parts of which are pasted below. Note the, um, interesting English grammar:

Honorable Dr. Daniel W Nebert,

Hope you are doing fine!

At first, I feel happy if you could spare 2 minutes of your valuable time to concern on my request.

I am pleased to inform you that “SL Cell Science & Report” is planning to release Special Issue “Embryonic Stem Cells” by the 03rd of May’2018 and we are in need of valuable articles. Hence I have chosen some illubrious people like you to support us for launching this issue. So will you please help us by submitting any type of article (Case Report, Research, Review and Short communication) and help us in achieving our goal for time.

Hope you will not disappoint me and comeback with your email within 24 hours will boost a hope to me.

Await your rapid comeback.

Dear Dr.Daniel W Nebert,

Greetings of the day!!!

We cordially invite you to be Editorial Board Member of our newly launched journal – United Journal of Pharmacology. In view of your past contributions and also as this is your field of expertise, we are inviting you to our organization – United Prime Publications.

The scope of the journal Pharmacology is “Pharmaceutics, Toxicology, Therapeutics, Pharmaceutical Science, Pharmaco-genetics and Drug Research, everything, etc “. We will be very much honorable to be associated to you, and we see a successful future of our journal with your valuable suggestions and contributions.

Kindly send us your latest CV and Passport size photograph as an email attachment to confirm that you are willing to be an Editorial Board Member.

We will provide a Candidacy Certificate for being our Editorial Member.

We are looking forward for your positive response.

Sent: Thursday, March 15, 2018 12:27 PM
To: Nebert, Daniel
Subject: RE: More information about “predatory online open-access journals”

I particularly like the predatory journal with the prestigious title, Journal of Nature and Science. Any scientist that publishes in there can tell his/her colleagues that “I’ve published all my work in ‘Nature’ and ‘Science’.” It’s just a matter of time before some predatory publishing house will come out with a journal having the title, Journal of Cell, Nature and Science.

[For those non-scientists sharing this GEITP List, among the most prestigious of all journals – in which to have an article accepted – include Cell, Nature and Science.]

Ken

From: Nebert, Daniel (nebertdw)
Sent: Thursday, March 15, 2018 2:28 PM
Subject: More information about “predatory online open-access journals”

Today I was directed to this web site College & Research Libraries News, where an interesting 4-page Dec 2o17 article had recently appeared [see attached]. The topic concerns all the “predatory online open-access journals” –– which these GEITP pages have often shared.

As most of you know, around 2oo8–2o1o some (not-so-trustworthy) publishing companies began setting up pseudo-scientific journals –– often with fictitious names of editors and members of the editorial board. Their advertised claims were “Send your articles to us, 2 pages or 50 pages, anything, on any topic, as soon as possible; we’ll have it ‘reviewed by our experts’ within 2-3 days, following which we’ll publish it online. Oh, by the way, did I tell you we have page charges of $600 per page?” This became so successful (financially) that we now have at least 15,000 such journals.

Many have incredibly complicated and comprehensive names (usually with “International”, “Global”, “World”, “National” and/or “American” in the name) –– to make it sound important and all-inclusive. Although there are addresses and phone numbers in the U.S., the “editor-in-chief” is usually located in India or Southeast Asia. In fact, many of us receive 15-30 of these annoying email invitations EVERY DAY –– inviting us to “contribute an article to our new journal.” (If these emails arrive in our laptop at 11 pm or 3 am in the U.S., you KNOW it is very likely that they are originating from Asia.)

A librarian at University of Colorado, Jeffrey Beall, began (in 2oo8) a very popular web site –– attempting to distinguish between REAL scientific journals and these prediatory online open-access journals by LISTING what he thought were the shady publishing companies. Also, credible journals such as Nature and Science have published stories about “sting operations”, designed to expose the predatory nature of these shady journals. However, as is true with everything in Life, all is not black-and-white; what we see is always a gradient. Some legitimate journals were trying to start up, during these past 10 years (preferably being sponsored by a legitimate established professional society). Consequently, there were complaints (by some editors claiming to be credible) about Beall’s judgment.

In Jan 2o17, Jeffrey Beall removed his web site and all of its contents (probably developing a stress ulcer and perhaps fearing for his life). Beall claimed he was “pressured” by his boss and higher-up authorities, but this interesting article [attached] denies any such pressure.

C&RL News Dec 2o17; pp 603–606

https://crln.acrl.org/index.php/crlnews/article/view/16837/18435

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“May the Force be with you” — Environmental signal of MECHANICAL FORCE that regulates stem cell differentiation !!

Over the past decade, advances in bioengineering have led to newly appreciated methods to study effects of mechanical force on single cells. Micrometer-scale culture systems that can subject individual cells to highly specific physical distortion have allowed scientists to demonstrate that force can modulate stem-cell behavior. Authors [see attached full-length article] combined sophisticated genetic approaches and innovative physical manipulations to inves­tigate the role of force on stem cells in the fruit fly. They make the intriguing discovery that mechanical force drives differentiation of a very specialized population of progenitor cells in the midgut of adult Drosophila melanogaster flies.

The fruit-fly midgut is equivalent to the stomach and small intestine of humans and other vertebrates (animals with a spine). All digestive organs experience physical forces that are inherent in their physiological functions: ingested food distends the gut; muscle contractions compress the gut. These forces contin­uously deform the gut’s epithelial lining. Like their mammalian counterparts, fly intestinal stem cells (ISCs) produce two major classes of cells that comprise the adult intestinal epithelium: absorptive enterocytes and secretory enteroendocrine cells. Many extrinsic signals –– including chemicals, nutrition, pathogens and cytokines –– have been shown to regulate ISC proliferation and differentiation. However, until now, whether midgut stem cells can sense biomechanical signals remained unknown.

Authors studied PiezoP-GAL4, a GAL4 transgene under control of a cloned promoter region of Piezo, expressed in a subpopulation of stem cells in the adult fly midgut. PIEZO is a cation ion channel that directly senses mechanical tension in lipid bilayers; it was initially identified in mammalian cells as a touch sensor, and was later found to be responsible for mechano-reception (able to perceive mechanical energy as a signal) in other cell types. The Drosophila genome contains a single Piezo homolog.

Authors [see attached] showed that mechanical stress regulates stem-cell differentiation in adult Drosophila midgut through the stretch-activated ion channel PIEZO. Loss of the Piezo gene lowers the generation of enteroendocrine cells in the adult midgut. Increases in cytosolic Ca2+ resemble the PIEZO overexpression phenotype, suggesting that PIEZO functions through Ca2+-signaling. Further studies suggested that Ca2+ signaling promotes stem-cell proliferation and differentiation through separate pathways. This interesting paper demonstrates the existence of a specific group of stem cells in the fly midgut that can directly sense mechanical signals through PIEZO, encoded by the fly gene, Piezo.

DwN

Nature 1 Mar 2o18; 555: 103–106 & News’N’Views pp 34–36

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Genes involved in “degree of empathy,” — Empathy Quotient (EQ) is very much a multifactorial trait

As these GEITP pages have often described, the genetic basis of variability in any disease phenotype, in a quantitative phenotype such as height or body mass index, or in response to a drug or an environmental toxicant can be grouped into three categories: (a) monogenic (Mendelian) traits that typically represent one or a few rare coding variants; (b) predominantly oligogenic traits that represent variability contributed by a small number of major genes; and (c) multifactorial traits –– produced mostly by numerous small-effect variants, together with epigenetic effects and environmental factors. EMPATHY is the ability to perceive other people’s thoughts, intentions, desires, and feelings –– and to respond to others’ mental states with an appropriate emotion. Obviously, DEGREE OF EMPATHY (if it can be quantitated at all) would fall into the category of multifactorial traits. Authors of the attached paper attempt to answer three questions: (a) what is the polygenic architecture of empathy? (b) Is empathy genetically correlated with various psychiatric conditions, psychological traits, and/or education? (c) Is there a genetic contribution to sex differences in empathy?

Authors performed gender-stratified and non-stratified genome-wide association study (GWAS) analyses of empathy in research participants from 23andMe (a personalized genetics company). They calculated the narrow-sense heritability explained by all the single-nucleotide polymorphisms (SNPs) tested, and investigated sex differences. Finally, they conducted genetic correlation analyses with six psychiatric conditions –– anorexia nervosa, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, major depressive disorder, and schizophrenia –– as well as psychological traits, and level of education attained.

This report represents the largest GWAS of empathy to date –– using a well-validated self-report measure of empathy, the Empathy Quotient (EQ), in 46,861 research participants from 23andMe, Inc. Authors identified 11 suggestive SNPs (P <1 × 10–6), although none were significant at P < 2.5 × 10–8 after correcting for multiple-testing. The most significant SNP was identified as an intronic SNP in the gene encoding transmembrane protein-132C (TMEM132C). As predicted, based on earlier work, authors confirmed a significant female advantage on the EQ (P <2 × 10–16). Authors identified similar SNP heritability and high genetic correlation between the sexes, suggesting the same genes are involved in empathy for both sexes. Also, as predicted, authors identified a significant negative genetic correlation between autism and the EQ (P = 1.63 × 10–4). Authors also identified significant positive genetic correlations between the EQ and risk for schizophrenia, anorexia nervosa, and extrovert behavior. This intriguing study represents the first GWAS of self-reported empathy. These data suggest that the genetic variations associated with empathy also play a role in certain psychiatric conditions and psychological traits. Translational Psychiatry 2018; 8: 35

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Single-Cell RNA-Seq of Mouse Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic Parkinson Disease

Students in grade school these days learn that DNA (containing genes) is transcribed into full-transcript RNA, which is then spliced into messenger RNA (mRNA), which gets translated into protein. By knowing the DNA sequence of any individual’s gene therefore leads to our knowing the sequence of the RNA transcript and subsequently, inference of the translated protein. Not only has whole-genome sequencing (WGS) become very popular –– but “RNA-seq”, which measures the DNA-specific transcribed RNA, is now also widely performed; this study is termed “transcriptomics.” In recent years, WGS and RNA-seq were carried out on tissues or total organs. Recently, these techniues have been scaled down so that individual cells can be identified, isolated, and then these methods performed on individual cells. This is the topic of the attached article.

Parkinson Disease (PD) is the most common progressive neurodegenerative movement disorder. Incidence of PD increases with age, affecting world-wide an estimated 1% of the population over 70 years of age. PD is a multifactorial trait (phenotype), i.e. representing the contribution of hundreds if not thousands of genes, plus epigenetic factors, plus environmental effects. Several large-cohort genome-wide association studies (GWAS) have identified ~49 genetic loci statistically significantly associated with (non-familial or) sporadic PD. Although PD ultimately affects multiple neuronal centers, preferential degeneration of dopamine neurons in the substantia nigra (a specific location in the base of the brain), leading to loss of fine-motor control. One can reasonably assert that a significant fraction of PD-associated variation likely mediates its influence specifically within the substantia nigra. There is a mouse model for PD in which the Cplx1 gene is deleted. Authors [attached article] thus carried out single-cell RNA-seq analyses of multiple dopamine nerve-cell populations in the PD-mouse brain, including those in the substantia nigra.

Characterizing dopamine-containing neuron populations in the mouse brain at embryonic vs early postnatal time-points, authors determined unique transcriptional profiles –– including a postnatal neuroblast population (immature cells similar to stem cells) and substantia-nigra dopamine-containing neurons. They used these population- specific findings to develop a scoring system to prioritize candidate genes in all 49 DNA segments that had been implicated in PD risk (by GWAS), including genes with known PD associations and many with extensive supporting literature. As proof of principle, authors confirmed that the substantia nigra-striatal pathway is compromised in the Cplx1-null mouse model. Authors believe that this systematic approach “establishes biologically-pertinent candidates and testable hypotheses for sporadic PD, opening up a new avenue in PD genetics research.”

Am J Hum Genet 1 Mar 2o18; 102: 427–446

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Large-Scale Multi-Ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

As these GEITP pages have often emphasized –– complex diseases, quantitative phenotypes such as height or body mass index, drug efficacy or adverse effects, or toxicity caused by environmental agents –– are almost always examples of multifactorial traits. The phenotype of blood pressure is an excellent example of a multifactorial trait (i.e. contributions from hundreds if not thousands of genes, plus epigenetic effects, plus environmental factors such as lifestyle and diet). Blood pressure is known to be partially under genetic control (heritability index = 30% – 60%). However, only a very small fraction of the heritability has been explained by single-nucleotide variants (SNVs) identified through genome-wide association studies (GWAS): i.e. only between 0.5% and 3.5% in various GWAS of several different ethnic groups.

Incorporating interactions between genetic variants and environmental exposures (GxE) represents an additional approach to discovering genetic effects on multifactorial traits. Understanding these interactions may more generally extend our knowledge of the genetic architecture (the total underlying genetic basis of any trait including all variants pertaining to that trait) of complex traits. Many lifestyle factors (e.g. amount of physical activity, tobacco use, alcohol consumption, stress, dietary factors, and prescription drugs) influence blood pressure. The recently established Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium has designed a series of multi-ancestry genome-wide interaction projects focused on assessing the impact of interactions with multiple lifestyle factors on genetics of cardiovascular traits.

Authors [see attached report] performed a genome-wide association meta-analysis, incorporating gene-smoking interactions to identify systolic- and diastolic-associated loci and to understand the modulating role of cigarette smoking in the genetic architecture of blood pressure. Studying a total of 610,091 individuals from five ancestral groups is shown herein to provide adequate statistical power for discovery of new genes. “Stage 1” analysis examined ~18.8 million SNVs and small insertion/deletion (indel) variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) –– with follow-up “Stage 2” analysis of promising variants in 480,178 additional individuals from five ancestries. Authors identified 15 loci that showed genome-wide significance (P < 5 x 10–8) in Stage 1 and formally replicated in Stage 2. A combined Stages 1 and 2 meta-analysis identified 66 additional genes having genome-wide significance. This MASSIVE STUDY (notice the number of coauthors in the many hundreds; this is definitely not a 'hunter-gatherer', but rather an 'agricultural community' research project) underscores the likelihood that multifactorial traits involve a very large number of genes. Clearly, the larger the cohort, the more discovered genes will reach statistical significance..!! Am J Hum Genet Mar 2o18; 102: 375–400

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This clinical study proposes that there should be five types of diabetes mellitus, not two

Diabetes represents a multifactorial trait –– manifested by the contribution of many genes plus epigenetic and environmental factors. Clinically, in any reasonably sized populatin, this disorder is always seen as a gradient.

This [below] would appear to be a very reasonable study, and the conclusions represent an idea whose time has come. Especially for the benefit of highly variable (heterogeneous) patients when first diagnosed with diabetes melitus.

DwN

Diabetes: Study proposes five types, not two
Published 2 March 2018
By Honor Whiteman
Fact checked by Jasmin Collier

Adults with diabetes could benefit from better treatment if the condition was categorized into five types, rather than just two. This is the conclusion of a new study published in The Lancet Diabetes & Endocrinology. The research was led by Prof. Leif Groop, of the Lund University Diabetes Centre in Sweden and the Institute for Molecular Medicine Finland in Helsinki.

In the United States alone, around 30.3 million people are living with diabetes. Excluding gestational diabetes — diabetes that develops during pregnancy — there are two main types: type 1 and type 2. In type 1 diabetes, the beta cells of the pancreas — which produce insulin, the hormone that regulates blood sugar levels — are mistakingly attacked and destroyed by the immune system. Type 2 diabetes is by far the most common form, accounting for around 90–95 percent of all cases. This occurs when the body’s cells stop responding to insulin, or the beta cells are unable to produce sufficient amounts of the hormone.

In both forms of the condition, blood sugar levels can become too high — a condition known as hyperglycemia. Unless controlled, this can lead to a number of complications, including kidney disease, cardiovascular disease, and nerve damage. The opposite, during excessive treatment, is low blood sugar levels, known as hypoglycemia and which can cause coma and death.
The heterogeneity of diabetes

A diabetes diagnosis is normally made using the fasting plasma glucose (FPG) test or the A1c test. The FPG test assesses a person’s blood glucose level at a single time-point, whereas the A1c test measures average blood glucose levels over the previous four months.

When it comes to determining which type of diabetes a person has, healthcare professionals might look for diabetes-related auto-antibodies in the blood. These are proteins produced by the immune system that can attack the body’s own cells. The presence of such auto-antibodies is an indicator of type 1 diabetes. If a person does not have these auto-antibodies, they are considered to have type 2 diabetes.

But, as Prof. Groop and colleagues note, the classification guidelines for diabetes have not been updated for 20 years — despite increasing evidence that diabetes has high heterogeneity. “Diabetes is a group of chronic metabolic disorders,” says Dr. Rob Sladek, of the McGill University and Génome Québec Innovation Centre in Canada, in an editorial linked to the study, “that share the common feature of hyperglycemia, meaning that, in principle, diabetes can be diagnosed via measurement of a single blood component.”

Prof. Groop and his team say that a “refined classification” of diabetes based on its heterogeneity could help healthcare professionals better predict which individuals are most likely to develop complications and allow a more personalized approach to treatment. In their study, the researchers propose that diabetes should no longer be categorized as two types. Instead, they say that the condition should be classified into five distinct types.
The five ‘clusters’ of diabetes

The researchers came to their proposal by analyzing the data of four study cohorts. These included a total of 14,775 adults from Sweden and Finland, all of whom had been newly diagnosed with diabetes. As part of the analysis, the scientists looked at six measures in each subject that each represent different features of diabetes. These measures were: body mass index (BMI); age at which diabetes was diagnose; hemoglobin A1c (HbA1c), a measure of long-term blood sugar control; pancreatic beta-cell functioning; insulin resistance; and presence of diabetes-related auto-antibodies.

As well as conducting genetic analyses of the participants, the researchers also compared their disease progression, complications, and treatment. The study revealed five distinct forms of diabetes, three of which were severe and two that were mild. The team categorized these as follows:

· Cluster 1: severe auto-immune diabetes (currently known as type 1 diabetes), characterized by insulin deficiency and the presence of auto-antibodies. This was identified in 6–15 percent of subjects.

· Cluster 2: severe insulin-deficient diabetes, characterized by younger age, insulin deficiency, and poor metabolic control, but no autoantibodies. This was identified in 9–20 percent of subjects.

· Cluster 3: severe insulin-resistant diabetes, characterized by severe insulin resistance and a significantly higher risk of kidney disease. This was identified in 11–17 percent of subjects.

· Cluster 4: mild obesity-related diabetes, most common in obese individuals. This affected 18–23 percent of subjects.

· Cluster 5: mild age-related diabetes, most common in elderly individuals. This was the most common form, affecting 39–47 percent of subjects.

The researchers note that each of these five types “were also genetically distinct,” meaning that there were no genetic mutations that were shared across all five clusters.
A ‘step toward precision medicine’

When the researchers assessed the treatment received by adults in each of the five clusters, they noticed that some were being treated inappropriately. As an example, the team points out that just 42 percent of patients in cluster 1 and 29 percent of patients in cluster 2 received insulin therapy from the point of disease onset. They say that this indicates that the current classifications of diabetes fail to target the underlying features of the disease.

While further research is required to refine each of these five clusters — by using biomarkers and genetic risk scores, for example — the team believes that this study represents a great stride toward tailored treatments for diabetes. “Existing treatment guidelines,” concludes Prof. Groop, “are limited by the fact the patients respond to poor metabolic control when it has developed, but do not have the means to predict which patients will need intensified treatment.

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Reconstructing an African haploid genome from the 18th century

This article is an example of what can be done by commercial DNA-sequencing cmpanies such as MyHeritage, Ancestry, Vitagene, LivingDNA, GPS Origins, 23andMe and dozens of other similar companies. The population of Iceland was founded by settlers from continental Scandinavia and the British Isles ~1100 years ago, and Iceland remained relatively isolated until recently. Post-settlement immigration to Iceland was rare, occurring mostly from Denmark and, to a lesser degree, from other neighboring countries. Records from 1930 to 1980 show that the number of individuals in Iceland from outside Europe ranged from 73 to 1,322 (0.07% to 0.6% of the entire population); in the early 1800s, it was most likely a much smaller percentage.

Because of his African ancestry, Hans Jonatan (HJ) –– born in the Caribbean in 1784 to an African mother and European father –– was an unusual immigrant when he arrived in Iceland in 1802. Consequently, the chromosomes transmitted by HJ to his two children would have been a mosaic of African-derived and European-derived fragments. Because his wife was Icelandic, their children would have inherited African fragments only from HJ. Owing to recombination and Mendelian segregation, authors [see attached article] expected to find fewer and smaller fragments from HJ in successive generations of descendants.

When chromosome fragments of one ancestor (e.g. HJ) can be distinguished from those of other ancestors among a group of descendants, his or her genome can be at least partially reconstructed. Thus, assuming that African chromosomal fragments can be reliably identified in genotyped descendants of HJ from Iceland, and that assuming these individuals have no other recent African ancestors, the reconstruction of HJ’s mother’s genome amounts to identifying and joining these fragments — similar to pieces in a jigsaw puzzle. To the knowledge of these authors, there is no evidence (apart from HJ) of African gene flow to Iceland before 1900. Therefore, authors expected African chromosomal fragments to be extremely rare in the Icelandic gene pool.

Anyone’s genome therefore represents a mosaic of chromosome fragments from ancestors who existed some arbitrary number of generations earlier. Authors decided to genotype 182 of HJ’s 788 descendants –– using single-nucleotide variant (SNV) chips, plus whole-genome sequencing (WGS) of 20 descendants. From their data, authors reconstructed 38% of HJ’s maternal genome and inferred that his mother had originated from the region encompassed by Benin, Nigeria and Cameroon.

Nature Genet Feb 2o18; 50: 199–205

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The expanding world of small RNAs in plants: what the heck is easiRNA ???

Gene-environment interactions in plants are often similar to those in animals, but there are also distinct differences. Small RNAs, transcribed from the DNA of a plant’s genome, are involved in plant development, repro­duction, and genome reprogramming –– as described in the attached (2o15) review. The large variety of small‑RNA pathways in plants likely contributes to their phenotypic plasticity (i.e. ability to adapt to any changing environment). Most likely, these pathways evolved as a cellular defense mechanism against RNA viruses and transposable elements, again emphasizing the constant drive of survival of the species. Later in evolution, these pathways most likely then became involved in regulating the expression of endogenous genes having other functions.

The abundance and diversity of small‑RNA classes varies among plant species, suggesting co-evolution between environmental adaptations and gene‑silencing mechanisms. Authors [first paper attached] review the field of plant small RNAs (e.g. microRNAs, secondary small-interfering RNAs (siRNAs) and heterochromatin-associated siRNAs) (heterochromatin plays a role in the expression of genes. Although this chromosomal structure is tightly packed, much of this DNA gets transcribed, but it is continuously turned over via RNA-induced transcriptional silencing). These small RNAs exhibit diverse cellular and developmental functions –– including plant reproductive function, genomic imprinting, and paramutation (in epigenetics, paramutation is an interaction between two alleles at a single locus –– whereby one allele induces a heritable change in the other allele; these changes often involve DNA-methylation or histone modifications).

Authors [second paper attached] studied the regulation of parental genome dosage in Arabidopsis thaliana (a flowering plant in the mustard family, its small genome size, rapid life cycle, large production of seeds, and ability to grow under laboratory conditions –– have made it a model organism for studying plant genetics, physiology, biochemistry and development). Regulation of parental genome dosage is of fundamental importance in animals and plants (examples include X-chromosome inactivation and dosage compensation). The “triploid block” (i.e. three sets of chromosomes instead of the normal two) is a classic example of dosage regulation in plants –– establishes a reproductive barrier between species that differ in chromosome number. This barrier is active in the (embryo-nourishing) endosperm tissue and is able to abort hybrid seeds through as-yet-unknown mechanism. Authors [2nd paper attached] show that depletion of paternal epigenetically-activated small-interfering RNAs (easiRNAs) bypasses the triploid block in response to increased paternal ploidy (number of chromosome sets).

Paternal loss of a particular RNA polymerase enzyme is able to suppress easiRNA formation and rescue triploid seeds by restoring small-RNA-directed DNA-methylation at transposable elements (“jumping genes”), and this restoration is correlated with decreased expression of paternally expressed imprinted genes (PEGs). These data suggest that easiRNAs represent a quantitative signal for paternal chromosome number, and that a balanced chromosomal dosage is required for post-fertilization genome stability and seed viability.

Nat Rev Mol Cell Biol Dec 2o15; 16: 727–741 & Nature Genet Feb 2o18; 50: 193–198

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“DNA.Land” — a framework to collect genomes and phenomes in the present era of abundant genetic information

With publications of genome-wide association studies (GWAS) comprising increasingly larger cohorts, it has become clear that virtually all multifactorial traits (e.g. height, body mass index, type-2 diabetes, asthma, cancer, autism spectrum disorder) must reflect hundreds if not thousands of genes, plus epigenetic factors, plus environmental effects over time. And, most genes are “small-effect” contributors to the multifactorial trait being studied –– each gene contributing to the trait (phenotype) 0.1% or 0.0001%. This means the larger the population size, the more small-effect genes that can be identified.

Explaining the genetic basis of complex traits requires substantial quantities of genomic data –– which has been greatly helps by exponential decline in cost of genomic technologies. Currently, a genotyping array costs on the order of tens of dollars, and whole-genome sequencing (WGS) costs ~$1,000. However, collecting combined genetic data AND phenotype data is a time- and resource-consuming task that poses massive logistical and operational challenges. On top of the costs of genotyping, researchers first need to advertise the study, recruit participants, obtain consent, provide DNA collection kits, track and store samples, extract DNA, and prepare the DNA library –– before data can be available in a digital format.

Phenotyping requires further resources, even when done using online questionnaires. These operations are labor-intensive and incur massive costs. For example, the U.S. National Institutes of Health’s Precision Medicine Initiative (“All of Us”) has recently allocated $50 million for recruitment centers and biobank operations that collectively propose to recruit and handle biospecimens and basic phenotypic information from a total of ~500,000 participants. The past 5 years have witnessed the advent of large-scale direct-to-consumer (DTC) genetic services for genealogy –– with companies such as 23andMe, AncestryDNA, FamilyTreeDNA, and MyHeritage. These services provide a dense genotyping array with ~0.5 million single-nucleotide variants (SNVs) for ~$69–$99 per participant. As of today, more than 8 million individuals have been tested with these services, and >10,000 new DTC kits are purchased daily..!!

Building upon these observations, authors [see attached article] developed DNA.Land, a website to crowdsource genomic and phenotypic information for human genetics research. DNA.Land has two overall goals: (a) to demonstrate the potential for genotype and phenotype collection by crowdsourcing data from users of DTC companies and (b) to promote the idea of patient-led genetic research, with controls left to the participants (for example, the consumer has the choice of the degree to which they approve the sharing of phenotype data, and the possibilities needed for providing feedback to researchers). In 20 months of operation, DNA.Land has collected more than 50,000 genomic datasets from DTC participants, and the datasets are growing daily.

Nature Genet Feb 2o18; 50: 160–165

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