Molecular Genetics and Genomics
Publication Analysis 2007-2013
by Kathleen Gransalke, Labtimes 06/2016
In the last ten years, the genetics and genomics community saw the rise of so called Genome-Wide Association Studies, or GWAS. It is no surprise that these types of study also predominate our publication analysis. A hotspot in GWAS research is the “Hinxton locus”.
Photo: Genome Museum, Georgetown
“Amongst our experienced silk-worm breeders it is known that certain breeds occasionally throw off some red worms, but as to how they are produced and how they behaved in inheritance much obscurity still prevails.” So, wrote, in 1909, a certain K. Toyama from the Tokyo Imperial University. He did so in the world’s first journal on genetics, Zeitschrift für Induktive Abstammungs- und Vererbungslehre, which was founded a year earlier in Germany.
Today, the very same journal operates under the name Molecular Genetics and Genomics, MGG – conveniently also the title of our current publication analysis. Throughout the years, many more journals have joined MGG in publishing the latest research findings from genetics and genomics research. Currently, the SCImago Journal & Country Rank portal lists more than 300 journals under the Genetics tag. As you may know, these expert journals play a leading role in our publication analyses, to determine the nations’ performances. But before we look into these numbers, what did our dear Toyama find out more than a hundred years ago? “We are now inclined to believe that the sporting which aise [sic] commonly met with in the silk-worm is mostly due to hybridization, that is to say, hybrid-mutation as Lidforss says, and not mutation in the sense of De Vries.”
Back to the year 2016 and we see that England is the number one in genetics and genomics research, according to total citations. Not far behind is Germany. All other European nations couldn’t quite keep up with these two strong performers. Italy in fourth place, for instance, published only half as many articles, proceedings papers and reviews as England and, to that effect, collected only half as many citations. Of course, it is also possible to look at these numbers from a different angle – the citations-per-article angle. Here, not very surprisingly, Iceland with its deCODE genetics company, takes number one spot with 156.1 average citations per article. In second place is Finland (69.9), followed by Estonia (64.7; 26th according to total citations) and Switzerland (62.5). Globally, European geneticists and genomics researchers wrote more publications than their US peers, as usual, but they are “out-cited” when it comes to total citations and average citations per article (35.6 vs 46.3).
What are now the papers’ and authors’ main research themes? Back in 2010, the Molecular Genetics and Genomics ranking, covering publications between 1997 and 2008, revealed that the field was dominated by bioinformational genomics. The top papers, for instance, included descriptions of the Clustal sequence alignment programme and quantification models of Real-Time PCR. Other top fields included epigenetics, DNA repair, RNA function, transcription control and chromosome structure. A potpourri of research subjects.
Six years on, bioinformatics tools are still highly cited, see top papers in places 1 and 2 of our current publication analysis, but these papers stand side-by-side with those that successfully applied these tools. Genome-Wide Association Studies, GWAS, are such application and the top paper in position four is regarded as the starting point of GWAS research. “The study was the first large, well-designed GWAS for complex diseases to employ a SNP chip that had good coverage of the genome,” reason Mark I. McCarthy and colleagues in the 2012 paper “Five Years of GWAS Discovery” (Am J Hum Genet, 90(1):7-24). McCarthy is also one of the GWA study’s co-authors, together with seven more of our top 30 European geneticists and genomics researchers. Interestingly, all top papers have their reprint addresses in England, two at the Wellcome Trust Sanger Institute, one in Cambridge, another one in Leicester and the last one, describing the findings of the ENCODE (Encyclopedia of DNA Elements) project, at EMBL-EBI.
Just as six years ago, the top 30, highly-cited author list was dominated by bioinformational geneticists; the current ranking is ruled by researchers browsing the genome for genetic variants, predisposing carriers to certain diseases. In a recent essay, one of these top 30 authors, André Uitterlinden (6th), neatly sums up the rest of our publication analysis: “Although GWASs essentially combine epidemiological study designs with molecular genetic analysis techniques, it has also fundamentally changed the way in which research was done in human genetics by the introduction of large consortia of collaborating investigators. GWASs have over-flooded many clinical and basic research areas with gene discoveries” (Semin Reprod Med, 34(04): 196-204).
And these consortia and collaborations were also the crux of this publication analysis. The stumbling block, however, was not the question whether all members of consortia are true authors of a given study – this time, we simply assumed they are. The problem was that Web of Science ignores collaborating scientists or scientists in consortia and simply pools them under the monicker “group authors”. Hence, one or the other top 30 author might miss a few papers. But, working together in large collaborative studies has its advantages. Uitterlinden says, “It is my personal view that we have to see this as a (positive) result of the new culture of doing science in our field of complex genetics, that is, large-scale studies involving massive amounts of data and much collaboration without one particular group or individual taking the credit as single first author or last author. It also is the result of such large-scale studies containing the immediate replication of a discovery result, preventing false-positive study results and strongly working against data manipulation or even fraud.”
Be that as it may, 14 of our top 30 authors conduct their genetics/genomics studies in the United Kingdom; five of them at Hinxton (at the Wellcome Trust Sanger Institute and the EMBL-EBI). Five highly-cited authors are located in Iceland as well as in Germany. The top 30 is completed by three researchers from The Netherlands, two from Finland and one from Switzerland. With four female researchers among our top 30, the women’s quota is pleasingly high in genetics and genomics research.
As already mentioned, the majority of our top 30 geneticists have turned their professional attention to genetic epidemiology. Some of them (Panos Deloukas, 1st; Nilesh Samani, 11th; Vilmundur Gudnason, 28th) focus on the heart, trying to pinpoint genetic loci robustly associated with, for instance, coronary heart disease, myocardial infarction or hypertension. Others, like Mark I. McCarthy (2nd) and Timothy Frayling (17th), put their main focus on diabetes and obesity susceptibility loci. And yet others, including Michael Stratton (12th) and Douglas Easton (19th), want to identify gene variants, predisposing to certain cancers.
In addition, there’s a large group of scientists, who study a mix of different diseases and their genetic risk factors. Among them: Kari Stefansson (3rdh), André Uitterlinden (6th), H. Erich Wichmann (7th), Unnur Thorsteinsdottir (9th), Cornelia van Duijn (10th), Marjo-Riitta Järvelin (21stt), Veikko Salomaa (23rd), David Strachan (26th) and Emmanouil Dermitzakis (30th).
Besides all those genetic epidemiologists, a few other geneticists and genome researchers gathered enough citations to make our top 30. Richard Durbin (8th), for instance, studies human genetic variation, evolutionary and population genetics; Ewan Birney (15th), EMBL-EBI’s co-director, focusses on functional genomics, assembly algorithms and statistical methods to analyse genomic information; Paul Flicek (24th) employs computational models for genome annotation and evolution to learn more about vertebrate genomics and Peer Bork (27th) wants to understand evolution through, for example, comparative gene, genome and metagenome analysis.
“Although geneticists initially thought that after the first round of GWAS successes its use would be diminishing, the opposite has happened. Still more and more studies are generating GWAS data in their biobanks and thereby even larger meta-analyses are performed for still more phenotypes and diseases.” Cheaper, more efficient and accurate sequencing equipment, “will result in a continuous activity of GWAS efforts to discover more genes and explain more genetic variance,” Uitterlinden predicts.
So, we shouldn’t be surprised if, in a few years time, genetic epidemiologists occupy all the spots in our top 30 authors’ ranking.
View the Picture: Most Cited Authors
Last Changed: 28.11.2016