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Scientific Talk

Speaker:Charleston Chiang, Ph.D. Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California.

Time : 10:00-11:30 am , Apr. 27(Friday)

Venue: Room 258, SIBS Main Building, Yueyang Road 320

Title: The Impact of Demographic History on Human Complex Traits


How complex traits change through time is a central question in evolutionary biology and genetics. One of the major evolutionary forces that shaped the distribution of human complex traits is the demographic history of a population. Therefore, in order for human genetics to provide a compelling context for studying complex trait evolution, it is necessary to integrate trait mapping with a detailed knowledge of population history. A well-known example of demographic impact on complex traits is found in present-day Finland, where a population bottleneck in its founding has been suggested to be the reason a number of rare Mendelian disorders are disproportionately more prevalent in Finland. I will illustrate the impact of demographic history of a population on human complex traits by first drawing examples from European populations of Sardinia and Finland. By utilizing large-scale whole-genome or whole-exome sequencing datasets, I will describe our findings in delineating the population structure and history of these populations, and how the special population history empowered association studies. Finally, I will end by describing our ongoing investigation of the population structure, genetic ancestry, and local adaptation in Han Chinese using ultra-low coverage whole-genome sequencing data from > 10,000 individuals across China.

Speaker: Mark Stoneking  Ph.D,Professor, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Time: 10:00 A.M., Apr 16, 2018

Place: Room 300

Title: The Genomic and Cultural Landscape of Madagascar


Although situated ∼400 km from the east coast of Africa, Madagascar exhibits cultural, linguistic, and genetic traits from both Southeast Asia and Eastern Africa. However, the settlement history remains contentious, as it is not clear if the initial colonization was from Africa, from Southeast Asia, or by an already admixed population. It is also not clear to what extent the dispersal from Africa and Southeast Asia was sex-biased. Moreover, to what extent is African vs. Southeast Asian genetic ancestry correlated with African vs. Southeast Asian cultural and linguistic traits in admixed Malagasy populations?  To address these and other questions about Malagasy populations, a systematic, grid-based sampling of ~3,000 individuals from 257 villages across Madagascar has been carried out.  I shall present and discuss the results of the analyses of these data, together with data on cultural and linguistic traits. In addition, the admixed ancestry of Malagasy populations can be used to detect signals of positive selection occurring after the admixture, and such analysis reveals one of the strongest signals of recent positive selection ever detected in humans.

Speaker: Prof. Shi Huang, Central South University

Time: 13:00-14:45pm, Oct. 25, 2012

Place: Room 223, SIBS main building

Title: Evidence for the Multiregional hypothesis of modern human origins from phylogeny-informative sequences


Recent studies support the Maximum Genetic Diversity hypothesis that nucleotide diversities in fast evolving sequences are mostly at optimum level and hence cannot be informative to phylogeny inference.  Consistently, here we found that fast evolving sequences are enriched with coincident or overlapping substitutions in humans and chimpanzees and also with shared SNPs among human races.  We therefore analyzed the phylogeny-informative slow evolving sequences to revisit the question of modern human origins.   We found that Europeans have greater nucleotide diversity than East Asians and Africans.  The split time between Europeans and non-Europeans and between East Asians and Africans were estimated to be ~1.98 and ~1.78 Myr ago, respectively.  East Asians are slightly closer to Europeans than Africans are, confirming genetic exchange between East Asians and Europeans as previously revealed by morphological studies.  Europeans show distinct SNP patterns in non-synonymous SNPs from non-Europeans. Denisovans maybe Africa H. heidelbergensis who may have migrated to Europe ~0.38 Myr ago and interbred with female H. antecessor in Europe to give rise to Neanderthals who had predominantly Denisovan nuclear genomes. These molecular results are consistent with fossil records and the Multiregional hypothesis.

Speaker: Dr. Teo Yik Ying, National University of Singapore

Time: 13:00, Aug 13 (Tuesday)

Place: Room 300, SIBS Main Building

Title: Detecting and characterizing genomic signatures of positive selection in global human populations and infectious disease pathogens


Natural selection is a significant force that shapes the architecture of the human genome and introduces diversity across global populations. The question of whether advantageous mutations have arisen in the human genome as the result of single or multiple mutation events remains unanswered except for a handful of genes such as those that confer lactase persistence, affect skin pigmentation or cause sickle cell anemia. We have developed a long-range haplotype method for identifying genomic signatures of positive selection that complements existing methods such as the iHS or XP-EHH for locating signals across the entire allele frequency spectrum.  Our method also locates the founder haplotypes that are carrying the advantageous variants and infers their corresponding population frequencies. This presents an unprecedented opportunity to systematically interrogate the whole human genome whether a selection signal that is shared across different populations is the consequence of a single mutation process followed subsequently by gene flow between populations, or convergent evolution due to the occurrence of multiple independent mutation events either at the same variant or within the same gene. Applying our method to data from fourteen populations across the world reveals that positive selection events tend to cluster in populations of the same ancestry. Comparing the founder haplotypes for events that are present across different populations reveals that convergent evolution is a rare occurrence, and the majority of shared signals stem from the same evolutionary event. When applied to genomics data for Plasmodium falciparum, one of the dominant malaria parasites in Asia and Africa, the method successfully identified differential evidence of adaptation at genes that confer resistance to anti-malarial drugs.

Speaker: Dr. Ong Twee Hee, National University of Singapore

Time: 14:00, Aug 13 (Tuesday)

Place: Room 300, SIBS Main Building

Title: Assessing single nucleotide variant detection and identification at different sequencing coverages


Whole-genome sequencing is now routinely used for the detection and identification of genetic variants, particularly single-nucleotide polymorphisms (SNPs) in humans, which is likely to provide insights into human diversity, population history and genetic diseases, as illustrated by the 1000 Genomes Project (1KGP). Many new SNP variant calling algorithms, taking advantage of the large number of short reads produced by the next-generation sequencing platforms have been proposed, particularly from 1KGP. However, there are considerable differences in the SNP variants identified and genotyped from these methods. In addition, these methods implicitly take into account the low sequencing coverage on a large number of samples for variant detection and identification. The Malays, which is a population not included in the 1KGP study, are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. Sequencing at a minimum of 30x coverage, we illustrate the higher sensitivity at detecting low-frequency and rare variants as compared to 1KGP. Using down-sampling of the sequencing reads obtained in SSMP and a set of SNP calls on chromosome 1 from the same individuals on the Illumina Omni1 genotyping array, we assessed the accuracy of SNP detection and genotype concordance at various sequencing coverages with the current widely used methods of CASAVA, SAMTools and GATK. Preliminary results indicate that CASAVA has the highest sensitivity in detecting SNPs from 5x to 30x coverages, while GATK has the highest genotype concordance across coverages of 5x to 30x.

Speaker: Dr. Boon Peng, Hoh

Time: 14:00, Nov.26(Wed), 2014

Place: SIBS Lecture Hall

Title: Population diversity and genetic architecture of multi-ethnic groups in Peninsular Malaysia


Malaysia is a multi-ethnic, multi-lingua, multi-religious and multi-cultural country, located at ta unique crossroad of Southeast Asia. It has a population of ~28.3 million people, of which the Malay is the largest group, follow by Chinese, Indians, and other indigenous populations including the Orang Asli from Peninsular Malaysia, and the most ethnic minorities from East Malaysia by means of Sabah and Sarawak. The Orang Asli consists ~0.6% of the total populations in Malaysia, are subdivided to 3 distinct populations namely Negrito, Senoi and Proto-Malays. They are believed to be the earliest inhabitants in the regions of Southeast Asia and Peninsular in particular. I would like to share with you in this presentation, some findings of an ongoing study to dissect the genetic architecture of the Orang Asli. Some results of the natural positive selection of these people in particular the Negrito will also be discussed. Such knowledge is important to complement the puzzles of the picture of human migration history in Southeast Asia and Asia continent, and to provide important fundamental knowledge for medical implications – a term called “Darwinism Medicine”.


Associate Professor Dr Boon Peng, Hoh, is currently affiliated with Institute of Medical Molecular Biotechnology (IMMB), Faculty of Medicine, Universiti Teknologi MARA, of which is heads the genomic section of the institute. Graduated in year 2006, he was trained as a molecular and population geneticist. Hoh’s major research interest is on the genetics of the indigenous populations in Peninsular Malaysia. Of particular interest, he is interested to dissect the genetic architecture and to locate the signatures of positive natural selections of the hunter-gatherers Negrito populations. Hoh also studies various applications of SNPs array and the newly emerged genetic marker – Copy Number Variation (CNV), and attempt to apply these knowledge in study the genetic susceptibility of complex diseases, in particular infectious disease (dengue) and cardiovascular diseases. Hoh received several awards throughout his career life. He won the university best publication award in year 2011 and 2013. He was also been awarded as the “Ten Outstanding Young Malaysian” under the category of Academic Achievement & Accomplishment in year 2013.

Speaker: Dr. Jun Li, Associate Professor of Human Genetics and Research Associate Professor of Computational Biology and Bioinformatics of U-M.

Time: 10:00-12:00 am, Jan. 22, 2015

Place: Room 258

Title: Classification problems in genomics

Abstract: Dr. Jun Li will discuss several analytical issues frequently encountered when performing unsupervised subtype discovery based on high-dimensional data.  Research in his group has found that ensemble-based methods such as consensus clustering (CC) are highly sensitive and prone to over-interpretation.  CC often leads to the appearance of crisp subgroups when there is none, or to a claim of cluster stability when it is weak.  They developed better simulation procedures and a new metric to ensure the proper use of this method.  They found that intrinsic correlation structure among measured features (such as gene-gene co-expression) could severely impact the permutation-based evaluation of significance.  Related artifacts could explain a recent, highly publicized report of the discovery of eight genetic subtypes for schizophrenia.  Further, he will discuss the Simpson’s Paradox, how it appeared in their analysis of human mutation patterns, and how it led to the conflation of between-tissue variation and between-subject variation in a report in Science in 2015 claiming that most cancer risks can be accounted for stochastic factors.  He will explain why this interpretation is in error and, more generally, how such lessons are important in the training of the next-generation of information scientists who will handle ever larger datasets.

Biography: Dr. Li is Associate Professor of Human Genetics and Research Associate Professor of Computational Biology and Bioinformatics of U-M.  He is also a faculty member in the Center for Statistical Genetics, Cellular and Molecular Biology Program, Comprehensive Cancer Center and the Depression Center. Dr. Li’s background includes a B.Sc. in physics (Beijing University), PhD in biophysics/electrophysiology (California Institute of Technology), and postdoctoral training in human genetics (Stanford).  After postdoctoral training he was a Senior Scientist at the Stanford Human Genome Center, and worked in experimental genomics, bioinformatics, statistical genetics, and data integration across ‘omics datasets.  His expertise is to apply quantitative, data-driven approaches to study genome evolution and complex human diseases, including psychiatric disorders and cancer.  He worked on genome-wide association studies of bipolar disorder, and is recipient of the 2011 Johnson & Johnson Rising Star Translation Research Award for a exome sequencing-based study of the bipolar disorder.  His group has been active in sequencing-based gene discovery: he is co-PI on two NIH funded projects involving exome sequencing for ataxia and thrombosis. In other collaborations his group is also working on human population genetics, and cancer genome evolution as revealed by intratumoral heterogeneity, including a collaboration to study esophageal cancer in Anyang, China. He is PI of a new NIH-funded QTL mapping study in a rat model of metabolic health and aging.  He is recipient of the 2014 Dean’s Basic Science Research Award at the University of Michigan Medical School.

Speaker: Dr. Charleston Chiang, Department of Ecology and Evolutionary Biology, University of California

Time: 10:00-12:00 am, May 06, 2015

Place: Room 300

Title: Population genetic insight to the study of human height


Genetic adaptation of many human traits is likely highly polygenic, occurring at many loci in the genome rather than at a single locus like the example of human lactase gene. Human height is one such example. It is a classic polygenic trait and is known to be differentiated across Europe. Powered by successful genome-wide association studies that provided us with hundreds of known loci, we demonstrate a signature of widespread selection at height loci across Europe. Furthermore, in studying height in Sardinia, an isolated Southern European population, we identify two loci in which the derived alleles strongly decrease height in Sardinia, and are elevated in frequency in Sardinia compared to mainland Europe. For one of the loci, KCNQ1, we show a haplotypic signature consistent with the height-decreasing allele being selected. We also show that beyond the effects of these two loci, shorter height in general seems to be favored in Sardinia. Finally, I will describe an ongoing investigation of the population structure of Sardinia, its demographic history and relationship to ancient European farmers. I will then end with a hypothesis relating what we learned from population history to height variation around the globe.

Speaker: Prof. Xiaofeng Zhu, Case Western Reserve University

Time: 9:30-11:00 A.M., July 28, 2015

Place: Room 300

Title: Genome-Wide Survey in African Americans Demonstrates Epistasis of Fitness in the Human Genome


The role played by epistasis between alleles at unlinked loci in shaping population fitness has been debated for many years and the existing evidence has been mainly accumulated from model organisms. In model organisms, fitness epistasis can be systematically inferred by detecting non-independence of genotypic values between loci in a population and confirmed through examining the number of offspring produced in two-locus genotype groups. No systematic study has been conducted to detect epistasis of fitness in humans owing to the experimental constraints. In the African-American population gene flow from European into African ancestries creates statistical properties in the genome similar to what is observed in recombinant inbred lines. We demonstrate theoretically that fitness epistasis can create correlation of local ancestry between unlinked loci that can be examined. We inferred local ancestry across the genome in 16,252 unrelated African Americans and systematically examined the pairwise correlations between the genomic regions on different chromosomes. Our analysis revealed multiple pairs of genomic regions showing local ancestry correlation (p-value < 6 x 10-8) that can be potentially attributed to fitness epistasis. These genomic regions also harbored multiple genes with strong evidence of selection, including the Duffy locus and the glycosylphosphatidylinositol-anchored serine protease (PRSS21) that is associated with sperm-dysfunction. To our knowledge, this study is the first to systematically examine evidence of fitness epistasis across the human genome. Our results demonstrate that fitness epistasis is widespread in humans and may have an important impact on current efforts to map susceptibility genes.

Speaker: Dr. Xiaoming Liu, University of Texas School of Public Health

Time: 9:30-11:00 A.M., January 04, 2016

Place: Room 300

Title: Exploring Demographic Histories Using SNP Frequency Spectrums


Inferring demographic history using genetic information can shed light on important evolutionary events such as population bottleneck, expansion, migration, and admixture, among others. It is also the foundation of many population genetics analyses, as demographic history is one of the most important forces shaping the polymorphic pattern of DNA sequences. We developed a novel model-free method called stairway plot, which infers detailed population size changes over time using SNP frequency spectrums. This method can be applied to low-coverage sequence data, pooled sequence data and even reference-free sequence data for species whose reference genome are not yet available. Another advantage of this method is the ability to handle whole-genome sequences of hundreds of individuals. Using extensive simulation we compared our method to the state-of-art methods such as pairwise sequentially Markovian coalescent (PSMC) and multiple sequential Markovian coalescent (MSMC). The results show that our method outperformed the PSMC/MSMC for inferring recent population size changes. We applied our method to the genomes of nine non-admixed populations (CEU, GBR, TSI, FIN, CHB, CHS, JPT, YRI and LWK) from the 1000 Genomes Project, and showed a detailed pattern of human population fluctuations from 10 to 500 thousand years ago (kya). The results supported many mainstream viewpoints on the demographic histories of human populations, and at the meantime also produced several interesting observations worth further and more careful investigations.

Speaker: Prof. Dr. Saitou Naruya, Division of Population Genetics, National Institute of Genetics Mishima, Japan

Time: 14:00-15:00 P.M., February 22, 2016

Place: Room 300

Title: First people who reached Sundaland during ice age


After out-of-Africa, modern humans started to spread over Eurasia. How and when those ancient human populations diverged is very interesting topic in human evolutionary studies. We analyzed genome-wide SNP data of three Negrito populations living in Philippine Islands, Malay Peninsula, and Andaman Islands as well as other human populations. DNA samples of Philippine Negritos (Aeta, Agta, Batak, and Mamanwa) were originally collected in 1970s-80s by Keiichi Omoto’s group at University of Tokyo, while data for Malaysian Negritos and Andamanese were obtained through collaborations with Malaysian and Indian researchers, respectively. Phylogenetic relationship varied depending on data compared and methods used, however, these Negrito people were first people who reached Sundaland area during ice age. We also found that transmitted proportion of Denisovan genomes to Negritos in Luzon Island was as high as that to Papuans. This study was mainly conducted by Dr. Timothy A. Jinam of my laboratory.

Speaker: Prof. Dr. Kai Ye, Xi’an Jiaotong University, Bioinformatics pharmacology cancer

Time: 10:00 A.M., May 09, 2016

Place: Room 300

Title: Novel algorithms for next-generation sequence data analysis and their applications in pan-cancer genome data and the genome of the Netherlands


Recently the concept of Precision Medicine has gained popularity with both China and US setting it as a national development strategy for the next decades. Precision medicine includes precision diagnose and precision treatment. For precision diagnose, we will rely on the powerful next-generation sequencing technology to precisely determine the types, sizes and locations of mutations in one’s genome, either in healthy or affected tissue types. Prof. Ye will explain the algorithm design of his software package, Pindel, for the precision detection of short indels and complex structural variation. He will next talk about the new Pindel-C module for the detection of complex indels and its application in the Cancer Genome Atlas (TCGA) data. Finally he will cover his recent work on de novo mutation rate of short indels and structural variants using the whole genome sequence data of 250 families from the Netherlands.

Speaker: Prof. Dr. Yufeng Wu, Dept. of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA

Time: 16:00 P.M., May 25, 2016

Place: Room 258

Title: Algorithms and Applications for Probability Computation on Multispecies Coalescent


Coalescent theory is a major research subject in population and evolutionary genetics. Applying coalescent theory to inference problems in genetics and phylogenetics requires the development of efficient and accurate methods for computing the coalescent likelihood. However, accurate computation of coalescent likelihood in many settings is computationally difficult.

In this talk, I will present some of my recent work on developing algorithms for accurate computation of coalescent likelihood under the multispecies coalescent model. In multispecies coalescent, we consider lineages that originate from multiple related populations (species), where coalescent may occur outside the population boundary. The stochastic nature of multispecies coalescent may lead to the well-known “gene tree and species tree” problem. It is commonly observed that phylogenetic trees (called gene trees) inferred from DNA sequences of individual genes may be different from the species-level phylogenetic tree (called the species tree). Given a gene tree topology and a species tree, the likelihood of the gene tree (called gene tree probability in the literature) is the probability of observing the gene tree topology on the species tree under coalescent theory. I will describe an algorithm (published in a paper in Evolution, 2012) for computing this coalescent probability, which is much faster than a previous algorithm. I will then present an application (published in a paper in Bioinformatics, 2015) of using the coalescent likelihood in inferring population evolutionary history inference using all gene trees implied by the haplotypes of a gene if the infinite sites model is assumed.

Speaker: Prof. Dr. Qiaomei Fu, Head of the Ancient DNA Lab at the Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences

Time: 10:00 A.M., Sep 23, 2016

Place: Room 300

Title: Tracing modern human history using ancient DNA


DNA sequences from early modern humans (EMH) (fossil record: 45,000-25,000 YBP) provide insight into the population histories of present day human populations. Two things of particular interest are the relationship between early modern humans and present-day populations from the same region and evidence of interactions between early modern humans and archaic populations present in Europe and Asia at the same time. Here, we present several projects that have helped to resolve several questions regarding EMH history. 1) Using a capture approach, we sequenced the first whole chromosome of an early modern human. Analyses show that EMH present in the Beijing area 40,000 years ago are related to the ancestors of many present-day Asians as well as Native Americans. Furthermore, they show that although there is no evidence for admixture with Denisovans, the EMH share an admixture signal with Neandertals common to all non-African populations. 2) A high coverage genome was sequenced from a femur of an EMH individual discovered near Ust-Ishim, Siberia. Analyses determining the relationship between this EMH individual to present-day humans show that he is closely related to the ancestral population shared between present-day Europeans and Asians. The amount of genomic admixture from Neandertals is similar to that found in present-day non-Africans and there is no evidence for admixture from Denisovans. However, the size of the genomic segments of Neandertal ancestry in the Ust-Ishim individual is substantially larger than those found in present-day individuals. 3) We have also captured ancient DNA from a mandible found in 2002 in Peştera cu Oase, Romania. This specimen, Oase 1, has a plausible range of ~37,000-42,000 years based on direct 14C dates. Analyses of the relationship of the Oase 1 individual to present-day humans show that he is closely related to the ancestral population shared between present-day Europeans and Asians. The over-all amount of genomic admixture from Neandertals is higher than that in present-day non-Africans. Importantly, we observe three segments that are over 50 Mb in size and several that are over 5 Mb, suggesting that the Neanderthal contribution to the Oase 1 individual occurred so recently in his family tree that the segments of Neandertal have had little time to break up due to recombination.  These projects illustrate how studying ancient genomes can increase our understanding of the interactions between modern and archaic humans.

Speaker: Li Guo  Ph.D,Associate Professor, School of Electronic and Information Engineering,Xi’an Jiao Tong University

Time: 13:00 P.M., Apr 07, 2017

Place: Room 258

Title: Compartmentalized Gene Regulatory Network of the Pathogenic Fungus Fusarium graminearum


Head blight caused by Fusarium graminearum threatens worldwide wheat production, resulting in both yield loss and mycotoxin contamination. We reconstructed the global F. graminearum gene regulatory network (GRN) from a large collection of transcriptomic data using Bayesian network inference, a machine learning algorithm. This GRN reveals connectivity between key regulators and their target genes. Focusing on key regulators, this network contains eight distinct but interwoven modules. Enriched for unique functions, such as cell cycle, DNA replication, transcription, translation, and stress responses, each module exhibits distinct expression profiles. Evolutionarily, the F. graminearum genome can be divided into core regions shared with closely related species and variable regions harboring genes that are unique to F. graminearum and perform species-specific functions. Interestingly, the inferred top regulators regulate genes that are significantly enriched from the same genomic regions (P<0.05), revealing a compartmentalized network structure that may reflect network rewiring related to specific adaptation of this plant pathogen. This first-ever reconstructed filamentous fungal GRN primes our understanding of pathogenicity at the systems biology level and provides enticing prospects for novel disease control strategies that involve targeting master regulators in pathogens.

Speaker: Xiaofei Yang  Ph.D,Associate Professor, School of Electronic and Information Engineering,Xi’an Jiao Tong University

Time: 14:00 P.M., Apr 07, 2017

Place: Room 258

Title: Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns


Abnormal DNA methylation is an important epigenetic regulator involving tumorigenesis. Deciphering cancer common and specific DNA methylation patterns is essential for us to understand the mechanisms of tumor development. We investigate cancer common and specific DNA methylation patterns among 5480 DNA methylation profiles of 15 cancer types from TCGA. We first define differentially methylated CpG sites (DMCs) in each cancer and then identify 5450 hyper- and 4433 hypomethylated pan-cancer DMCs (PDMCs). Moreover, we identify six distinct motif clusters, which are enriched in hyper- or hypomethylated PDMCs and are associated with several well-known cancer hallmarks. We also observe that PDMCs relate to distinct transcriptional groups. Additionally, 55 hypermethylated and 7 hypomethylated PDMCs are significantly associated with patient survival. Lastly, we find that cancer-specific DMCs are enriched in known cancer genes and cell-type-specific super-enhancers. In summary, this study provides a comprehensive investigation and reveals meaningful cancer common and specific DNA  methylation patterns.

Speaker: Hoh Boon Peng, Professor, faculty of medicine and health sciences, UCSI university

Time: 10:00 A.M., Nov 07, 2018

Place: Room 315

Title: Population Genetic and Signature of Positive Selection Against Knowlesi Malaria in the Native Populations from North Borneo


The region of northern Borneo is located closest to the southern Philippine islands. It may have served as a viaduct for the ancestrors of the anatomical mordern human migration onto or off of Borneo Island. North Borneo is home to more than 40 native populations that are predominantly categorized under “Austronesian” language family, residing in the inland region of North Borneo. North Borneo have been persistently recognized as a malaria endemic region over the last centuries. Studies over the years have recorded circulations of a number of Plasmodium sp. in North Borneo including simian plasmodium. Notably, high prevalence of malaria infection had been recorded since a century ago. More intriguingly, recent report revealed up to 70% of the malaria cases in North Borneo were knowlesi malaria. In this study five selected native populations from North Borneo were genotyped using a panel of ~2.5 millions genome-wide single nucleotide polymorphisms. We first assessed the genetic structure of these populations. The North Bornean natives exhibited near-absolute proportions of a genetic component that is also common among Austronesians from Taiwan and the Philippines. Phylogenetic analysis showed that they are closely related to non–Austro-Melansian Filipinos as well as to Taiwan natives but are distantly related to populations from mainland Southeast Asia. Relatively lower heterozygosity and higher pairwise genetic differentiation index (FST) values than those of nearby populations suggests possible genetic drift and population isolation of the natives from North Borneo, which resulted differentiation from other Austronesians. Then we attempted to trace the footprints of positive selection against knowlesi malaria. A ~13 kb length haplotype in the MHC Class II region was identified, encompassing candidate genes C6orf10 – BTNL2. This putative signature of positive selection was estimated to have arisen ~5,500 years ago, which coincided with the period of Austronesian expansion. In addition, the frequency for haplotype group was consistent with the prevalence of knowlesi malaria in North Borneo. Although we could not rule out possibilities of other protozoa or parasitic infections, our results showed consistent agreement to the plausibility of knowlesi malaria. We suggest future studies by expanding the population range involving full MHC sequence to assess the differential contributions of selection and recombination in shaping the contrasting evolutionary history of ancestral haplotypes.

Speaker : Prof. Manolis Kellis,MIT Computer Science and Artificial Intelligence Lab Member, Broad Institute of MIT and Harvard

Time : 15:00-17:00 , Aug 7th(Wednesday)

Venue : Room 300, SIBS Main Building, Yueyang Road 320

Title From genomics to therapeutics: dissection and manipulation of human disease circuitry at single-cell resolution


Perhaps the greatest surprise of genetic association is that more than 90% of disease-associatednucleotides lie in non-coding regions,greatly increasingstheurgency of understanding how gene-regulatory circuitry impacts human disease. To address this challenge, we generate transcriptional and epigenomic maps of 100s of tissues, 1000s of individuals, and 100,000s of cells across patients and controls. We link variants to target genes, upstream regulators, cell types of action, and perturbed pathways, and predict causal genes and regions to provide unbiased views of disease mechanisms, sometimes re-shaping our understanding. We find that Alzheimer’s variants act primarily through immune processes, rather than neuronal processes, and the strongest genetic association with obesity acts via energy storage/dissipation rather than appetite/exercise decisions. We combine single-cell profiles, tissue-level variation, and genetic variation across healthy and diseased individuals todeconvolvebulk profiles into single-cell profiles, to recognize changes in cell type proportion associated with disease and aging, to partition genetic effects into the individual cell types where they act, and to recognize cell-type-specific and disease-associated somatic mutations in exonic regions indicative of mosaicism. We expand these methods to electronic health records to recognize meta-phenotypes associated with combinations of clinical notes, prescriptions, lab tests, and billing codes, to impute missing phenotypes in sparse medical records, and to recognize the molecular pathways underlying complex meta-phenotypes in genotyped individuals by integration of molecular phenotypes imputed in disease-relevant cell types. Lastly, we develop programmable and modular technologies for manipulating these pathways by high-throughput reporter assays, genome editing,and gene targeting in human cells and mice, demonstrating tissue-autonomous therapeutic avenues in Alzheimer’s, obesity, and cancer. These results provide a roadmap for translating genetic findings into mechanistic insights and ultimately new therapeutic avenues for complex disease and cancer.

Speaker : Prof. Yi Xing, Ph.D., Perelman School of Medicine, University of Pennsylvania

Time : 15:30-17:00 , Sept 2(Monday)

Venue : Room 315, SIBS Main Building, Yueyang Road 320

Title Alternative splicing variation across human tissues and individuals


Alternative splicing is a tightly regulated biological process by which the number of gene products for any given gene can be greatly expanded. Genomic variants in splicing regulatory sequences can disrupt splicing and cause disease. Recent developments in sequencing technologies and computational biology have allowed researchers to investigate alternative splicing at an unprecedented scale and resolution. Population-scale transcriptome studies have revealed many naturally occurring genetic variants that modulate alternative splicing and consequently influence phenotypic variability and disease susceptibility. In this talk, I will describe our efforts in characterizing alternative splicing variation across human tissues and individuals, and in mapping such variation to genotypes and phenotypes across human populations.

Speaker : Lei Li, Ph.D., assistant professional researcher, University of California, Irvine

Time : 15:00-17:00 , Dec 30(Monday)

Venue : Room 315, SIBS Main Building, Yueyang Road 320

Title : Genetic Basis of Alternative Polyadenylation as an Emerging Molecular Phenotype for Human Traits and Diseases


Genome-wide association studies (GWAS) have identified thousands of non-coding variants that have been associated with human traits and diseases. However, the functional interpretation of these variants remains a major challenge. Here, I will describe the first atlas of human 3′untranslated region (UTR) alternative polyadenylation (APA) quantitative trait loci (3′aQTLs), containing approximately 0.4 million common genetic variants associated with the APA of target genes, identified in 46 Genotype-Tissue Expression (GTEx) tissues isolated from 467 individuals. Our CRISPR-based experiments revealed that 3’aQTLs are sufficient to alter APA regulation. Mechanistically, 3′aQTLs could alter poly(A) motifs and RNA-binding protein (RBP) binding sites, leading to thousands of APA changes. Furthermore, 3′aQTLs demonstrates to be a new discovery tool for novel APA regulators, such as LARP4. Finally, 3′aQTLs can be used to interpret approximately 16.1% of trait-associated variants and are largely distinct from other QTLs, such as eQTLs. Together, 3′aQTLs represent the genetic basis of APA as an emerging molecular phenotype to explain a large fraction of non-coding variants and to provide new insights into complex traits and disease etiologies.

SpeakerProf. Rayner, Simon, Oslo University Hospital/University of Oslo (UiO), Norway

Time: 10:30, January 13 (Monday)

Venue: Room 258, Main Building, 320 Yueyang Road

TopicmiRNAs in diagnosis and treatment in Norwegian population


The advent of Next Generation Sequencing opened up a range of possibilities for genome characterization. In the Dept of Medical Genetics at Oslo University Hospital we have focused on developing tools for providing diagnosis pipelines and predicting treatment options for the patients within the Norwegian population based on their genetic information. While Whole Genome Sequencing is now the default approach, the analysis still focuses on the coding regions of the genome. Nevertheless, the non-coding regions represent a rich source of information that has the potential interpretive value in a disease context.

One well studied non-coding RNA feature is microRNAs (miRNAs). miRNAs function in RNA silencing and post-transcriptional regulation of gene expression by partial binding to their mRNA targets. Nowadays, miRNAs are a somewhat unfashionable area of study as they are considered well understood and consequently can be studied in an automated fashion using off the shelf software tools. In reality, there is significant variation the quality of their annotation, the precision in how and where they are expressed and how they bind to their mRNA targets. Perhaps most surprisingly of all, there is no consideration of the impact of ethnic specific variation on miRNA studies.

In my group we have been developing computational and experimental tools to investigate these unfashionable molecules to understand (i) the impact of inaccuracies in annotation and (ii) the effect of population variation on miRNA function. In this way we hope to provide more directed analyses that can be relevant to specific ethnic groups. In my talk I will present some of our initial findings.

This post is also available in: Chinese (Simplified)

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