Severe Bottleneck Research Articles

Phylogeography of Schisandra chinensis (Magnoliaceae) Reveal Multiple Refugia With Ample Gene Flow in Northeast China.

Temperate conifers and broadleaved mixed forests in northeast China are ideal to investigate the genetic consequences of climate changes during the last glacial maximum (LGM), 29 – 16 kya. As previous studies were focused on tree species with long generation time; here, the evolutionary history of Schisandra chinensis, a climber species with a generation time of five years, was investigated using chloroplast DNA (cpDNA), nuclear single copy gene (nSCG), and nuclear single sequence repeats (nSSRs, i.e., microsatellite) markers, along with ecological niche modeling (ENM), which predicted a suitable habitat in Korea Peninsula (KP) during the LGM. Private haplotypes and high genetic diversity of both cpDNA and nSCG were mainly found in KP and Changbai Mt. (CB). Although no significant phylogeographic structure was detected in the cpDNA and nSCG, three nSSRs clusters roughly distributed in west (CB and KP), east (north China), and north (Xiaoxing’an Range, XR) regions were found in Structure analysis. The approximate Bayesian computation analysis showed the west cluster diverged at 35.45 kya, and the other two clusters at 19.85 kya. The genetic diversity calculated for each of the three markers showed no significant correlation with latitude. Genetic differentiation of nSSRs was also not correlated with geographic distance. Migrate analysis estimated extensive gene flow between almost all genetic cluster pairs and BOTTLENECK analysis showed that few populations experienced severe bottlenecks. Overall, results indicate that S. chinensis survived the LGM in situ in multiple refugia, which likely include two macrorefugia (KP and CB) and two microrefugia (XR and north China). Extensive postglacial gene flow among the three nSSRs clusters led to uniformly distributed genetic diversity and low genetic differentiation.

Genetic origins of honey bees (Apis mellifera) on Kangaroo Island and Norfolk Island (Australia) and the Kingdom of Tonga

We examine the origin of honey bee (Apis mellifera) populations in Kangaroo Island (Australia), Norfolk Island (Australia) and the Kingdom of Tonga using a highly polymorphic mitochondrial DNA region and a panel of 37 single nucleotide polymorphisms that assigns ancestry to three evolutionary lineages: Eastern Europe, Western Europe and Africa. We also examine inbreeding coefficients and genetic variation using microsatellites and mitochondrial sequencing. The honey bees of Kangaroo Island have a high proportion of Eastern European ancestry (90.2%), consistent with claims that they are of the subspecies A. m. ligustica. The honey bees of Norfolk Island also had a majority of ancestry from Eastern Europe (73.1%) with some contribution from Western Europe (21.2%). The honey bees of Tonga are mainly of Western European (70.3%) origin with some Eastern European ancestry (27.4%). Despite the suspected severe bottlenecks experienced by these island population, inbreeding coefficients were low.

Adaptive particle representation of fluorescence microscopy images

Modern microscopes create a data deluge with gigabytes of data generated each second, and terabytes per day. Storing and processing this data is a severe bottleneck, not fully alleviated by data compression. We argue that this is because images are processed as grids of pixels. To address this, we propose a content-adaptive representation of fluorescence microscopy images, the Adaptive Particle Representation (APR). The APR replaces pixels with particles positioned according to image content. The APR overcomes storage bottlenecks, as data compression does, but additionally overcomes memory and processing bottlenecks. Using noisy 3D images, we show that the APR adaptively represents the content of an image while maintaining image quality and that it enables orders of magnitude benefits across a range of image processing tasks. The APR provides a simple and efficient content-aware representation of fluosrescence microscopy images.

Artificial Intelligence Guided Precision Medicine Approach to Hematological Disease

Background: Next-generation sequencing (NGS) is an attractive tool for prospective use in the field of precision medicine. Using NGS to guide therapy has provided a large volume of genomic data and therapeutic actionability of somatic NGS results. These data are evolving too rapidly to rely solely on human curation. So the interpretation of the clinical significance of such large amounts of genetic data remains the most severe bottleneck preventing the realization of precision medicine. Watson for Genomics (WfG) is a representative artificial intelligence (AI) software, which analyzes and categorizes genetic alterations that are related to disease progression and provides a list of potential therapeutic options within 3 minutes per sample. Recent reports suggested that WfG could empower tumor boards and improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of the up-to-date availability of clinical trials (Patel NM, et.al. Oncologist. 2018). However, only limited data are available regarding the utility of AI-guided precision medicine approach in the field of hematological disease. The purpose of this study is to test the utility of AI in assisting the interpretation of high throughput genomic data from patients with the hematological disease.Methods: After obtaining written informed consent, we enrolled patients with hematological disease at our research hospital between May 2015 to June 2018. Genomic DNA was prepared from malignant cell fractions and normal tissues in each patient and subjected to comparative NGS, mainly targeted deep sequencing (TDS) with ready-made panels and, on demand, whole exome sequencing (WES). Sequence data was analyzed using a pipeline of in-house semi-automated medical informatics. After initial bioinformatics filtering, we used WfG to identify potential driver mutations, which were annotated as “pathogenic” or “likely pathogenic” (WfG version 39.132 and 39.135 as of July 2018). The results were compared with the findings of expert hematologists.Results: 247 paired samples (TDS, n= 143; WES, n= 104) collected from 187 patients were analyzed. Our cohort consisted of 63 patients with acute myeloid leukemia, 40 with myelodysplastic syndromes (MDS), 19 with myeloproliferative neoplasms (MPN), 9 with MDS/MPN, 10 with acute lymphoblastic leukemia/lymphoma, 17 with non Hodgkin lymphoma, 6 with multiple myeloma (MM) and others. In 151 of 187 patients, a total of 290 somatic driver mutations were identified by human curation. The frequently mutated genes were TP53 (n=31), NRAS (n=17), TET2 (n=16), U2AF1 (n=14), FLT3/ASXL1/WT1 (n=13 each), and DNMT3A/RUNX1 (n=12 each). WfG identified 79% (n=229) of driver mutations which human experts also did. There was some discordance between WfG and the human (Figure 1): Sixteen mutations were interpreted as “variant of unknown significance” by WfG, but these mutations were deduced as driver mutation by the human. Conversely, in two representative cases, WfG identified a relevant driver mutation that the human did not: FAM46C and SOCS1, from a patient with MM and with primary mediastinal large-B cell lymphoma, respectively. These examples indicate the potential for a mutually complementary or cooperative relationship between AI “software” and the human expert “hardware” in the interpretation of high throughput genomic data.Conclusion: Combing AI “software” and the human expert “hardware” will allow for the quick delivery of comprehensive information needed for patient care that outperforms what either can achieve individually in the field of hematological disease.Figure1. Comparison of potential driver mutations between human curation and Watson for Genomics. The size of the gene symbol indicates the total number of mutations identified [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Storm-based distributed sampling system for multi-source stream environment

As a large amount of data streams occur rapidly in many recent applications such as social network service, Internet of Things, and smart factory, sampling techniques have attracted many attentions to handle such data streams efficiently. In this article, we address the performance improvement of binary Bernoulli sampling in the multi-source stream environment. Binary Bernoulli sampling has the n:1 structure where n sites transmit data to 1 coordinator. However, as the number of sites increases or the input stream explosively increases, the binary Bernoulli sampling may cause a severe bottleneck in the coordinator. In addition, bidirectional communication over different networks among the coordinator and sites may incur excessive communication overhead. In this article, we propose a novel distributed processing model of binary Bernoulli sampling to solve these coordinator bottleneck and communication overhead problems. We first present a multiple-coordinator structure to solve the coordinator bottleneck. We then present a new sampling model with an integrated framework and shared memory to alleviate the communication overhead. To verify the effectiveness and scalability of the proposed model, we perform its actual implementation in Apache Storm, a real-time distributed stream processing system. Experimental results show that our Storm-based binary Bernoulli sampling improves performance by up to 1.8 times compared with the legacy method and maintains high performance even when the input stream largely increases. These results indicate that the proposed distributed processing model is an excellent approach that solves the performance degradation problem of binary Bernoulli sampling and verifies its superiority through the actual implementation on Apache Storm.

Understanding the Hidden Complexity of Latin American Population Isolates

Most population isolates examined to date were founded from a single ancestral population. Consequently, there is limited knowledge about the demographic history of admixed population isolates. Here we investigate genomic diversity of recently admixed population isolates from Costa Rica and Colombia and compare their diversity to a benchmark population isolate, the Finnish. These Latin American isolates originated during the 16th century from admixture between a few hundred European males and Amerindian females, with a limited contribution from African founders. We examine whole-genome sequence data from 449 individuals, ascertained as families to build mutigenerational pedigrees, with a mean sequencing depth of coverage of approximately 36×. We find that Latin American isolates have increased genetic diversity relative to the Finnish. However, there is an increase in the amount of identity by descent (IBD) segments in the Latin American isolates relative to the Finnish. The increase in IBD segments is likely a consequence of a very recent and severe population bottleneck during the founding of the admixed population isolates. Furthermore, the proportion of the genome that falls within a long run of homozygosity (ROH) in Costa Rican and Colombian individuals is significantly greater than that in the Finnish, suggesting more recent consanguinity in the Latin American isolates relative to that seen in the Finnish. Lastly, we find that recent consanguinity increased the number of deleterious variants found in the homozygous state, which is relevant if deleterious variants are recessive. Our study suggests that there is no single genetic signature of a population isolate.

Purging of Strongly Deleterious Mutations Explains Long-Term Persistence and Absence of Inbreeding Depression in Island Foxes

The recovery and persistence of rare and endangered species are often threatened by genetic factors, such as the accumulation of deleterious mutations, loss of adaptive potential, and inbreeding depression [1]. Island foxes (Urocyon littoralis), thedwarfed descendants of mainland gray foxes (Urocyon cinereoargenteus), have inhabited California's Channel Islands for >9,000 years [2-4]. Previous genomic analyses revealed that island foxes have exceptionally low levels of diversity and elevated levels of putatively deleterious variation [5]. Nonetheless, all six populations have persisted for thousands of generations, and several populations rebounded rapidly after recent severe bottlenecks [6, 7]. Here,we combine morphological and genomic data withpopulation-genetic simulations to determine the mechanism underlying the enigmatic persistence of these foxes. First, through analysis of genomes from 1929 to 2009, we show that island foxes have remained at small population sizes with low diversity for many generations. Second, we present morphological data indicating an absence of inbreeding depression in island foxes, confirming that they are not afflicted with congenital defects common to other small and inbred populations. Lastly, our population-genetic simulations suggest that long-term small population size results in a reduced burden of strongly deleterious recessive alleles, providing a mechanism for the absence of inbreeding depression in island foxes. Importantly, the island fox illustrates a scenario in which genetic restoration through human-assisted gene flow could be a counterproductive or even harmful conservation strategy. Our study sheds light on the puzzle of island fox persistence, a unique success story that provides a model for the preservation of small populations.

Historical biogeography of the leopard (Panthera pardus) and its extinct Eurasian populations

BackgroundResolving the historical biogeography of the leopard (Panthera pardus) is a complex issue, because patterns inferred from fossils and from molecular data lack congruence. Fossil evidence supports an African origin, and suggests that leopards were already present in Eurasia during the Early Pleistocene. Analysis of DNA sequences however, suggests a more recent, Middle Pleistocene shared ancestry of Asian and African leopards. These contrasting patterns led researchers to propose a two-stage hypothesis of leopard dispersal out of Africa: an initial Early Pleistocene colonisation of Asia and a subsequent replacement by a second colonisation wave during the Middle Pleistocene. The status of Late Pleistocene European leopards within this scenario is unclear: were these populations remnants of the first dispersal, or do the last surviving European leopards share more recent ancestry with their African counterparts?ResultsIn this study, we generate and analyse mitogenome sequences from historical samples that span the entire modern leopard distribution, as well as from Late Pleistocene remains. We find a deep bifurcation between African and Eurasian mitochondrial lineages (~ 710 Ka), with the European ancient samples as sister to all Asian lineages (~ 483 Ka). The modern and historical mainland Asian lineages share a relatively recent common ancestor (~ 122 Ka), and we find one Javan sample nested within these.ConclusionsThe phylogenetic placement of the ancient European leopard as sister group to Asian leopards suggests that these populations originate from the same out-of-Africa dispersal which founded the Asian lineages. The coalescence time found for the mitochondrial lineages aligns well with the earliest undisputed fossils in Eurasia, and thus encourages a re-evaluation of the identification of the much older putative leopard fossils from the region. The relatively recent ancestry of all mainland Asian leopard lineages suggests that these populations underwent a severe population bottleneck during the Pleistocene. Finally, although only based on a single sample, the unexpected phylogenetic placement of the Javan leopard could be interpreted as evidence for exchange of mitochondrial lineages between Java and mainland Asia, calling for further investigation into the evolutionary history of this subspecies.

"Out of the Can": A Draft Genome Assembly, Liver Transcriptome, and Nutrigenomics of the European Sardine, Sardina pilchardus.

Clupeiformes, such as sardines and herrings, represent an important share of worldwide fisheries. Among those, the European sardine (Sardina pilchardus, Walbaum 1792) exhibits significant commercial relevance. While the last decade showed a steady and sharp decline in capture levels, recent advances in culture husbandry represent promising research avenues. Yet, the complete absence of genomic resources from sardine imposes a severe bottleneck to understand its physiological and ecological requirements. We generated 69 Gbp of paired-end reads using Illumina HiSeq X Ten and assembled a draft genome assembly with an N50 scaffold length of 25,579 bp and BUSCO completeness of 82.1% (Actinopterygii). The estimated size of the genome ranges between 655 and 850 Mb. Additionally, we generated a relatively high-level liver transcriptome. To deliver a proof of principle of the value of this dataset, we established the presence and function of enzymes (Elovl2, Elovl5, and Fads2) that have pivotal roles in the biosynthesis of long chain polyunsaturated fatty acids, essential nutrients particularly abundant in oily fish such as sardines. Our study provides the first omics dataset from a valuable economic marine teleost species, the European sardine, representing an essential resource for their effective conservation, management, and sustainable exploitation.

Trade Liberalization and Import Intensity in the Mongolian Manufacturing

This article presents an empirical analysis of the consequences of trade liberalization on import intensity in Mongolia, a ‘least-developed landlocked country’ with weak institutions and severe infrastructure bottlenecks. The theoretical framework employed in modelling is based on industrial organization and international trade literature. Our results suggest that foreign investment stimulates import intensity possibly due to the prevalence of intra-firm trade between subsidies, while the protection of domestic market and state ownership reduces import intensity. There is no statistically significant evidence to suggest that import intensity is lower in unskilled labour-intensive industries. These findings have significant policy implications for further liberalization in order to improve Mongolia’s trade competitiveness.

A Framework for Identifying Recurring Bottlenecks in the State Planning Process in Colorado

Traditional methods used in transportation planning to identify bottlenecks and mobility issues, such as the Volume-to-Capacity Ratio and the Planning Time Index, have limited usefulness in identifying the exact location and extent of bottlenecks. Moreover, existing bottleneck identification tools flag all bottleneck types without distinction, despite the fact that strategies and resources used to address each type are different. This research first proposes a taxonomy of congestion to distinguish between different types of bottlenecks. It then describes a new methodology for identifying the location of recurring bottlenecks. Recurring bottleneck locations must experience a reduction in speed, an upstream accumulation of vehicles, and recurrence at the same location over three consecutive months. The methodology is currently used in long-term transportation planning and project selection in Colorado to identify and address the most severe bottleneck locations in the state.

Computational Optics Enables Breast Cancer Profiling in Point-of-Care Settings.

The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded health care systems are fueling the need for inexpensive, rapid, and treatment-informative diagnostics. On the basis of advances in computational optics and deep learning, we have developed a low-cost digital system, termed AIDA (artificial intelligence diffraction analysis), for breast cancer diagnosis of fine needle aspirates. Here, we show high accuracy (>90%) in (i) recognizing cells directly from diffraction patterns and (ii) classifying breast cancer types using deep-learning-based analysis of sample aspirates. The image algorithm is fast, enabling cellular analyses at high throughput (∼3 s per 1000 cells), and the unsupervised processing allows use by lower skill health care workers. AIDA can perform quantitative molecular profiling on individual cells, revealing intratumor molecular heterogeneity, and has the potential to improve cancer diagnosis and treatment. The system could be further developed for other cancers and thus find widespread use in global health.

A study of Kibbutzim in Israel reveals risk factors for cardiometabolic traits and subtle population structure.

Genetic studies in isolated populations often increase power for identifying loci associated with complex diseases and traits. We present here the Kibbutzim Family Study (KFS), aimed at investigating the genetic basis of cardiometabolic traits in extended Israeli families characterized by long-term social stability and a homogeneous environment. Extensive information on cardiometabolic traits, as well as genome-wide genotypes, were collected on 901 individuals. We observed that most KFS participants were of Ashkenazi Jewish (AJ) genetic origin, confirmed a recent severe bottleneck in the AJ recent history, and detected a subtle within-AJ population structure. Focusing on genetic variants relatively common in the KFS but very rare in Europeans, we observed that AJ-enriched variants appear in cancer-related pathways more than expected by chance. We conducted an association study of the AJ-enriched variants against 16 cardiometabolic traits, and found seven loci (24 variants) to be significantly associated. The strongest association, which we also replicated in an independent study, was between a variant upstream of MSRA (frequency ≈1% in the KFS and nearly absent in Europeans) and weight (P = 3.6∙10-8). In conclusion, the KFS is a valuable resource for the study of the population genetics of Israel as well as the genetics of cardiometabolic traits.

Reduced representation sequencing detects only subtle regional structure in a heavily exploited and rapidly recolonizing marine mammal species.

Next‐generation reduced representation sequencing (RRS) approaches show great potential for resolving the structure of wild populations. However, the population structure of species that have shown rapid demographic recovery following severe population bottlenecks may still prove difficult to resolve due to high gene flow between subpopulations. Here, we tested the effectiveness of the RRS method Genotyping‐By‐Sequencing (GBS) for describing the population structure of the New Zealand fur seal (NZFS, Arctocephalus forsteri), a species that was heavily exploited by the 19th century commercial sealing industry and has since rapidly recolonized most of its former range from a few isolated colonies. Using 26,026 neutral single nucleotide polymorphisms (SNPs), we assessed genetic variation within and between NZFS colonies. We identified low levels of population differentiation across the species range (<1% of variation explained by regional differences) suggesting a state of near panmixia. Nonetheless, we observed subtle population substructure between West Coast and Southern East Coast colonies and a weak, but significant (p = 0.01), isolation‐by‐distance pattern among the eight colonies studied. Furthermore, our demographic reconstructions supported severe bottlenecks with potential 10‐fold and 250‐fold declines in response to Polynesian and European hunting, respectively. Finally, we were able to assign individuals treated as unknowns to their regions of origin with high confidence (96%) using our SNP data. Our results indicate that while it may be difficult to detect population structure in species that have experienced rapid recovery, next‐generation markers and methods are powerful tools for resolving fine‐scale structure and informing conservation and management efforts.

Nonlinear mapping method for the generation of an elemental image array in a photorealistic pseudoscopic free 3D display.

Limited available elemental image array resources may be the most severe bottleneck for the promotion and application of integral-imaging-based 3D display. We propose a nonlinear mapping method for the generation of an elemental image array to get a photorealistic pseudoscopic free 3D display based on the parallel light field reconstruction nature of the integral imaging system. All the light rays emitted from the display panel are classified into a corresponding parallel light field according to its direction, and all the parallel light fields are captured as orthogonal projections of the scene before synthesizing all the orthogonal projections using a nonlinear mapping method to form the final elemental image array. Preliminary optical experiments as well as ray optical analysis are conducted to prove the feasibility and validity of the proposed method. The proposed method can exploit most of the current 3D platform. It is an effective and efficient way to generate an elemental image array.

Application-Arrival Rate Aware Distributed Run-Time Resource Management for Many-Core Computing Platforms

Modern many-core computing platforms execute a diverse set of dynamic workloads in the presence of varying application arrival rates. This inflicts strict requirements on run-time management to efficiently allocate system resources. On the way towards kilo-core processor architectures, centralized resource management approaches will most probably form a severe performance bottleneck, thus focus has been turned to the study of Distributed Run-Time Resource Management (DRTRM) schemes. In this article, we examine the behavior of a DRTRM of dynamic applications with malleable characteristics against stressing incoming application interval rate scenarios, using Intel SCC as the target many-core system. We show that resource allocation is highly affected by application input rate and propose an application-arrival aware DRTRM framework implementing an effective admission control strategy by carefully utilizing voltage and frequency scaling on parts of its resource allocation infrastructure. Through extensive experimental evaluation, we quantitatively analyze the behavior of the introduced DRTRM scheme and show that it achieves up to 44 percent performance gains while consuming 31 percent less energy, in comparison to a state-of-art DRTRM solution. In comparison to a centralized RTRM, the respective metric values rise up to 62 and 45 percent performance and energy gains, respectively.

Small Bottleneck Size in a Highly Multipartite Virus during a Complete Infection Cycle.

Multipartite viruses package their genomic segments independently and thus incur the risk of being unable to transmit their entire genome during host-to-host transmission if they undergo severe bottlenecks. In this paper, we estimated the bottleneck size during one infection cycle of Faba bean necrotic stunt virus (FBNSV), an octopartite nanovirus whose segments have been previously shown to converge to particular and unequal relative frequencies within host plants and aphid vectors. Two methods were used to derive this estimate, one based on the probability of transmission of the virus and the other based on the temporal evolution of the relative frequency of markers for two genomic segments, one frequent and one rare (segment N and S, respectively), both in plants and vectors. Our results show that FBNSV undergoes severe bottlenecks during aphid transmission. Further, even though the bottlenecks are always narrow under our experimental conditions, they slightly widen with the number of transmitting aphids. In particular, when several aphids are used for transmission, the bottleneck size of the segments is also affected by within-plant processes and, importantly, significantly differs across segments. These results indicate that genetic drift not only must be an important process affecting the evolution of these viruses but also that these effects vary across genomic segments and, thus, across viral genes, a rather unique and intriguing situation. We further discuss the potential consequences of our findings for the transmission of multipartite viruses.IMPORTANCE Multipartite viruses package their genomic segments in independent capsids. The most obvious cost of such genomic structure is the risk of losing at least one segment during host-to-host transmission. A theoretical study has shown that for nanoviruses, composed of 6 to 8 segments, hundreds of copies of each segment need to be transmitted to ensure that at least one copy of each segment was present in the host. These estimations seem to be very high compared to the size of the bottlenecks measured with other viruses. Here, we estimated the bottleneck size during one infection cycle of FBNSV, an octopartite nanovirus. We show that these bottlenecks are always narrow (few viral particles) and slightly widen with the number of transmitting aphids. These results contrast with theoretical predictions and illustrate the fact that a new conceptual framework is probably needed to understand the transmission of highly multipartite viruses.

Modeling, Analysis, and Implementation of Universal Acceleration Platform Across Online Video Sharing Sites

User-generated video sharing service has attracted a vast number of users over the Internet. The most successful sites, such as YouTube and Youku, now enjoy millions of videos being watched every day. Yet, given limited network and server resources, the user experience of existing video sharing sites (VSSes) is still far from being satisfactory. To mitigate such a problem, peer-to-peer (P2P) based video accelerators have been widely suggested to enhance the video delivery on VSSes. In this paper, we find that the interference of multiple accelerators will lead to a severe bottleneck across the VSSes. Our model analysis shows that a universal video accelerator can naturally achieve better performance with lower deployment cost. Based on this observation, we further present the detailed design of Peer-to-Peer Video Accelerator (PPVA), a real-world system for universal and transparent P2P accelerating. Such a system has already attracted over $180$ million users, with $48$ million video transactions every day. We carefully examine the PPVA performance from extensive measurements. Our trace analysis indicates that it can significantly reduce server bandwidth cost and accelerate the video download speed by $80$ percent.

Improved riboflavin production with Ashbya gossypii from vegetable oil based on 13C metabolic network analysis with combined labeling analysis by GC/MS, LC/MS, 1D, and 2D NMR

The fungus Ashbya gossypii is an important industrial producer of riboflavin, i.e. vitamin B2. In order to meet the constantly increasing demands for improved production processes, it appears essential to better understand the underlying metabolic pathways of the vitamin. Here, we used a highly sophisticated set-up of parallel 13C tracer studies with labeling analysis by GC/MS, LC/MS, 1D, and 2D NMR to resolve carbon fluxes in the overproducing strain A. gossypii B2 during growth and subsequent riboflavin production from vegetable oil as carbon source, yeast extract, and supplemented glycine. The studies provided a detailed picture of the underlying metabolism. Glycine was exclusively used as carbon-two donor of the vitamin’s pyrimidine ring, which is part of its isoalloxazine ring structure, but did not contribute to the carbon-one metabolism due to the proven absence of a functional glycine cleavage system. The pools of serine and glycine were closely connected due to a highly reversible serine hydroxymethyltransferase. Transmembrane formate flux simulations revealed that the one-carbon metabolism displayed a severe bottleneck during initial riboflavin production, which was overcome in later phases of the cultivation by intrinsic formate accumulation. The transiently limiting carbon-one pool was successfully replenished by time-resolved feeding of small amounts of formate and serine, respectively. This increased the intracellular availability of glycine, serine, and formate and resulted in a final riboflavin titer increase of 45%.

A Population Phylogenetic View of Mitochondrial Heteroplasmy.

The mitochondrion has recently emerged as an active player in myriad cellular processes. Additionally, it was recently shown that >200 diseases are known to be linked to variants in mitochondrial DNA or in nuclear genes interacting with mitochondria. This has reinvigorated interest in its biology and population genetics. Mitochondrial heteroplasmy, or genotypic variation of mitochondria within an individual, is now understood to be common in humans and important in human health. However, it is still not possible to make quantitative predictions about the inheritance of heteroplasmy and its proliferation within the body, partly due to the lack of an appropriate model. Here, we present a population-genetic framework for modeling mitochondrial heteroplasmy as a process that occurs on an ontogenetic phylogeny, with genetic drift and mutation changing heteroplasmy frequencies during the various developmental processes represented in the phylogeny. Using this framework, we develop a Bayesian inference method for inferring rates of mitochondrial genetic drift and mutation at different stages of human life. Applying the method to previously published heteroplasmy frequency data, we demonstrate a severe effective germline bottleneck comprised of the cumulative genetic drift occurring between the divergence of germline and somatic cells in the mother, and the separation of germ layers in the offspring. Additionally, we find that the two somatic tissues we analyze here undergo tissue-specific bottlenecks during embryogenesis, less severe than the effective germline bottleneck, and that these somatic tissues experience little additional genetic drift during adulthood. We conclude with a discussion of possible extensions of the ontogenetic phylogeny framework and its possible applications to other ontogenetic processes in addition to mitochondrial heteroplasmy.