Mitochondrial DNA Variation and the Origins of the Aleuts

This is the publisher's version, also available electronically from http://digitalcommons.wayne.edu/humbiol/vol75/iss6/2/.The mitochondrial DNA (mtDNA) variation in 179 Aleuts from five different islands (Atka, Unalaska, Umnak, St. Paul, and St. George) and Anchorage was analyzed to better understand the origins of Aleuts and their role in the peopling of the Americas. Mitochondrial DNA samples were characterized using polymerase chain reaction amplification, restriction fragment length polymorphism analysis, and direct sequencing of the first hypervariable segment (HVS-I) of the control region. This study showed that Aleut mtDNAs belonged to two of the four haplogroups (A and D) common among Native Americans. Haplogroup D occurred at a very high frequency in Aleuts, and this, along with their unique HVS-I sequences, distinguished them from Eskimos, Athapaskan Indians, and other northern Amerindian populations. While sharing several control region sequences (CIR11, CHU14, CIR60, and CIR61) with other circumarctic populations, Aleuts lacked haplogroup A mtDNAs having the 16265G mutation that are specific to Eskimo populations. R-matrix and median network analyses indicated that Aleuts were closest genetically to Chukotkan (Chukchi and Siberian Eskimos) rather than to Native American or Kamchatkan populations (Koryaks and Itel’men). Dating of the Beringian branch of haplogroup A (16192T) suggested that populations ancestral to the Aleuts, Eskimos, and Athapaskan Indians emerged approximately 13,120 years ago, while Aleut-specific A and D sublineages were dated at 6539 ± 3511 and 6035 ± 2885 years, respectively. Our findings support the archaeologically based hypothesis that ancestral Aleuts crossed the Bering Land Bridge or Beringian platform and entered the Aleutian Islands from the east, rather than island hopping from Kamchatka into the western Aleutians. Furthermore, the Aleut migration most likely represents a separate event from those responsible for peopling the remainder of the Americas, meaning that the New World was colonized through multiple migrations

Lower edge of locked Main Himalayan Thrust unzipped by the 2015 Gorkha earthquake

Large earthquakes are thought to release strain on previously locked faults. However, the details of how earthquakes are initiated, grow and terminate in relation to pre-seismically locked and creeping patches is unclear ^1-4. The 2015 Mw 7.8 Gorkha, Nepal earthquake occurred close to Kathmandu in a region where the prior pattern of fault locking is well documented ^5. Here we analyze this event using seismological records measured at teleseismic distances and Synthetic Aperture Radar imagery. We show that the earthquake originated northwest of Kathmandu within a cluster of background seismicity that fringes the bottom of the locked portion of the Main Himalayan Thrust fault (MHT). The rupture propagated eastwards for about 140 km, unzipping the lower edge of the locked portion of the fault. High-frequency seismic waves radiated continuously as the slip pulse propagated at about 2.8 km s-1 along this zone of presumably high and heterogeneous pre-¬seismic stress at the seismic-aseismic transition. Eastward unzipping of the fault resumed during the Mw 7.3 aftershock on May 12. The transfer of stress to neighbouring regions during the Gorkha earthquake should facilitate future rupture of the areas of the MHT adjacent and up-dip of the Gorkha earthquake rupture.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ngeo251

Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces

The key to obtaining the model-free description of the dynamics of a macromolecule is the optimisation of the model-free and Brownian rotational diffusion parameters using the collected R1, R2 and steady-state NOE relaxation data. The problem of optimising the chi-squared value is often assumed to be trivial, however, the long chain of dependencies required for its calculation complicates the model-free chi-squared space. Convolutions are induced by the Lorentzian form of the spectral density functions, the linear recombinations of certain spectral density values to obtain the relaxation rates, the calculation of the NOE using the ratio of two of these rates, and finally the quadratic form of the chi-squared equation itself. Two major topological features of the model-free space complicate optimisation. The first is a long, shallow valley which commences at infinite correlation times and gradually approaches the minimum. The most severe convolution occurs for motions on two timescales in which the minimum is often located at the end of a long, deep, curved tunnel or multidimensional valley through the space. A large number of optimisation algorithms will be investigated and their performance compared to determine which techniques are suitable for use in model-free analysis. Local optimisation algorithms will be shown to be sufficient for minimisation not only within the model-free space but also for the minimisation of the Brownian rotational diffusion tensor. In addition the performance of the programs Modelfree and Dasha are investigated. A number of model-free optimisation failures were identified: the inability to slide along the limits, the singular matrix failure of the Levenberg–Marquardt minimisation algorithm, the low precision of both programs, and a bug in Modelfree. Significantly, the singular matrix failure of the Levenberg–Marquardt algorithm occurs when internal correlation times are undefined and is greatly amplified in model-free analysis by both the grid search and constraint algorithms. The program relax (http://www.nmr-relax.com) is also presented as a new software package designed for the analysis of macromolecular dynamics through the use of NMR relaxation data and which alleviates all of the problems inherent within model-free analysis

Dry and Humid Periods Reconstructed from Tree Rings in the Former Territory of Sogdiana (Central Asia) and Their Socio-economic Consequences over the Last Millennium

One of the richest societies along the Silk Road developed in Sogdiana, located in present-day Tajikistan, Uzbekistan, and Kyrgyzstan. This urban civilisation reached its greatest prosperity during the golden age of the Silk Road (sixth to ninth century ce). Rapid political and economic changes, accelerated by climatic variations, were observed during last millennium in this region. The newly developed tree-ring-based reconstruction of precipitation for the pastmillennium revealed a series of dry and wet stages. During the Medieval Climate Anomaly (MCA), two dry periods occurred (900–1000 and 1200–1250), interrupted by a phase of wetter conditions. Distinct dry periods occurred around 1510–1650, 1750–1850, and 1920–1970, respectively. The juniper tree-ring record of moisture changes revealed that major dry and pluvial episodes were consistent with those indicated by hydroclimatic proxy data from adjacent areas. These climate fluctuations have had longand short term consequences for human history in the territory of former Sogdiana

Measuring the dynamic photosynthome

Background: Photosynthesis underpins plant productivity and yet is notoriously sensitive to small changes inenvironmental conditions, meaning that quantitation in nature across different time scales is not straightforward. The ‘dynamic’ changes in photosynthesis (i.e. the kinetics of the various reactions of photosynthesis in response to environmental shifts) are now known to be important in driving crop yield. Scope: It is known that photosynthesis does not respond in a timely manner, and even a small temporal “mismatch” between a change in the environment and the appropriate response of photosynthesis toward optimality can result in a fall in productivity. Yet the most commonly measured parameters are still made at steady state or a temporary steady state (including those for crop breeding purposes), meaning that new photosynthetic traits remain undiscovered. Conclusions: There is a great need to understand photosynthesis dynamics from a mechanistic and biological viewpoint especially when applied to the field of ‘phenomics’ which typically uses large genetically diverse populations of plants. Despite huge advances in measurement technology in recent years, it is still unclear whether we possess the capability of capturing and describing the physiologically relevant dynamic features of field photosynthesis in sufficient detail. Such traits are highly complex, hence we dub this the ‘photosynthome’. This review sets out the state of play and describes some approaches that could be made to address this challenge with reference to the relevant biological processes involved

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types