scispace - formally typeset
Search or ask a question
Author

Benjamin Brachi

Bio: Benjamin Brachi is an academic researcher from University of Chicago. The author has contributed to research in topics: Population & Genetic variation. The author has an hindex of 15, co-authored 24 publications receiving 3438 citations. Previous affiliations of Benjamin Brachi include Centre national de la recherche scientifique & University of Bordeaux.

Papers
More filters
Journal ArticleDOI
03 Jun 2010-Nature
TL;DR: This study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms, particularly when inbred lines are available.
Abstract: Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases, genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits. Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms.

1,525 citations

Journal ArticleDOI
07 Oct 2011-Science
TL;DR: A genome-wide scan to identify climate-adaptive genetic loci and pathways in the plant Arabidopsis thaliana provided a set of candidates for dissecting the molecular bases of climate adaptations, as well as insights about the prevalence of selective sweeps, which has implications for predicting the rate of adaptation.
Abstract: Understanding the genetic bases and modes of adaptation to current climatic conditions is essential to accurately predict responses to future environmental change. We conducted a genome-wide scan to identify climate-adaptive genetic loci and pathways in the plant Arabidopsis thaliana. Amino acid-changing variants were significantly enriched among the loci strongly correlated with climate, suggesting that our scan effectively detects adaptive alleles. Moreover, from our results, we successfully predicted relative fitness among a set of geographically diverse A. thaliana accessions when grown together in a common environment. Our results provide a set of candidates for dissecting the molecular bases of climate adaptations, as well as insights about the prevalence of selective sweeps, which has implications for predicting the rate of adaptation.

622 citations

Journal ArticleDOI
TL;DR: A study about the genetics of flowering time that differs from previous studies in two important ways: first, it is measured in a more complex and ecologically realistic environment; and, second, it combines the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping.
Abstract: Flowering time is a key life-history trait in the plant life cycle. Most studies to unravel the genetics of flowering time in Arabidopsis thaliana have been performed under greenhouse conditions. Here, we describe a study about the genetics of flowering time that differs from previous studies in two important ways: first, we measure flowering time in a more complex and ecologically realistic environment; and, second, we combine the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping. Our experiments involved phenotyping nearly 20,000 plants over 2 winters under field conditions, including 184 worldwide natural accessions genotyped for 216,509 SNPs and 4,366 RILs derived from 13 independent crosses chosen to maximize genetic and phenotypic diversity. Based on a photothermal time model, the flowering time variation scored in our field experiment was poorly correlated with the flowering time variation previously obtained under greenhouse conditions, reinforcing previous demonstrations of the importance of genotype by environment interactions in A. thaliana and the need to study adaptive variation under natural conditions. The use of 4,366 RILs provides great power for dissecting the genetic architecture of flowering time in A. thaliana under our specific field conditions. We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters. We show that QTL mapping increases our power to distinguish true from false associations in GWA mapping. QTL mapping also permits the identification of false negatives, that is, causative SNPs that are lost when applying GWA methods that control for population structure. Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study. Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock. Furthermore, we identified new genomic regions lacking obvious candidate genes.

470 citations

Journal ArticleDOI
TL;DR: Genome-wide association studies (GWAS) have been even more successful in plants than in humans and mapping approaches can be extended to dissect adaptive genetic variation from structured background variation in an ecological context.
Abstract: Genome-wide association studies (GWAS) have been even more successful in plants than in humans. Mapping approaches can be extended to dissect adaptive genetic variation from structured background variation in an ecological context.

443 citations

Journal ArticleDOI
TL;DR: Through this case study of oak, the accumulation and transmission of somatic mutations and the expansion of disease-resistance gene families in trees are demonstrated.
Abstract: Oaks are an important part of our natural and cultural heritage. Not only are they ubiquitous in our most common landscapes1 but they have also supplied human societies with invaluable services, including food and shelter, since prehistoric times2. With 450 species spread throughout Asia, Europe and America3, oaks constitute a critical global renewable resource. The longevity of oaks (several hundred years) probably underlies their emblematic cultural and historical importance. Such long-lived sessile organisms must persist in the face of a wide range of abiotic and biotic threats over their lifespans. We investigated the genomic features associated with such a long lifespan by sequencing, assembling and annotating the oak genome. We then used the growing number of whole-genome sequences for plants (including tree and herbaceous species) to investigate the parallel evolution of genomic characteristics potentially underpinning tree longevity. A further consequence of the long lifespan of trees is their accumulation of somatic mutations during mitotic divisions of stem cells present in the shoot apical meristems. Empirical4 and modelling5 approaches have shown that intra-organismal genetic heterogeneity can be selected for6 and provides direct fitness benefits in the arms race with short-lived pests and pathogens through a patchwork of intra-organismal phenotypes7. However, there is no clear proof that large-statured trees consist of a genetic mosaic of clonally distinct cell lineages within and between branches. Through this case study of oak, we demonstrate the accumulation and transmission of somatic mutations and the expansion of disease-resistance gene families in trees.

262 citations


Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

Proceedings Article
01 Jan 1994
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

2,134 citations

Journal ArticleDOI
TL;DR: This study identifies ∼3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method, demonstrating that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.
Abstract: Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ∼ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ∼ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.

1,718 citations