Project description:The analysis of differentially expressed genes is a powerful approach to elucidate the genetic mechanisms underlying the morphological and evolutionary diversity among serially homologous structures, both within the same organism (e.g., hand vs. foot) and between different species (e.g., hand vs. wing). In the developing embryo, limb-specific expression of Pitx1, Tbx4, and Tbx5 regulates the determination of limb identity. However, numerous lines of evidence, including the fact that these three genes encode transcription factors, indicate that additional genes are involved in the Pitx1-Tbx hierarchy. To examine the molecular distinctions coded for by these factors, and to identify novel genes involved in the determination of limb identity, we have used Serial Analysis of Gene Expression (SAGE) to generate comprehensive gene expression profiles from intact, developing mouse forelimbs and hindlimbs. To minimize the extraction of erroneous SAGE tags from low-quality sequence data, we used a new algorithm to extract tags from -analyzed sequence data and obtained 68,406 and 68,450 SAGE tags from forelimb and hindlimb SAGE libraries, respectively. We also developed an improved method for determining the identity of SAGE tags that increases the specificity of and provides additional information about the confidence of the tag-UniGene cluster match. The most differentially expressed gene between our SAGE libraries was Pitx1. The differential expression of Tbx4, Tbx5, and several limb-specific Hox genes was also detected; however, their abundances in the SAGE libraries were low. Because numerous other tags were differentially expressed at this low level, we performed a 'virtual' subtraction with 362,344 tags from six additional nonlimb SAGE libraries to further refine this set of candidate genes. This subtraction reduced the number of candidate genes by 74%, yet preserved the previously identified regulators of limb identity. This study presents the gene expression complexity of the developing limb and identifies candidate genes involved in the regulation of limb identity. We propose that our computational tools and the overall strategy used here are broadly applicable to other SAGE-based studies in a variety of organisms. [SAGE data are all available at GEO (http://www.ncbi.nlm.nih.gov/geo/) under accession nos. GSM55 and GSM56, which correspond to the forelimb and hindlimb raw SAGE data.]

Project description:The analysis of differentially expressed genes is a powerful approach to elucidate the genetic mechanisms underlying the morphological and evolutionary diversity among serially homologous structures, both within the same organism (e.g., hand vs. foot) and between different species (e.g., hand vs. wing). In the developing embryo, limb-specific expression of Pitx1, Tbx4, and Tbx5 regulates the determination of limb identity. However, numerous lines of evidence, including the fact that these three genes encode transcription factors, indicate that additional genes are involved in the Pitx1-Tbx hierarchy. To examine the molecular distinctions coded for by these factors, and to identify novel genes involved in the determination of limb identity, we have used Serial Analysis of Gene Expression (SAGE) to generate comprehensive gene expression profiles from intact, developing mouse forelimbs and hindlimbs. To minimize the extraction of erroneous SAGE tags from low-quality sequence data, we used a new algorithm to extract tags from -analyzed sequence data and obtained 68,406 and 68,450 SAGE tags from forelimb and hindlimb SAGE libraries, respectively. We also developed an improved method for determining the identity of SAGE tags that increases the specificity of and provides additional information about the confidence of the tag-UniGene cluster match. The most differentially expressed gene between our SAGE libraries was Pitx1. The differential expression of Tbx4, Tbx5, and several limb-specific Hox genes was also detected; however, their abundances in the SAGE libraries were low. Because numerous other tags were differentially expressed at this low level, we performed a 'virtual' subtraction with 362,344 tags from six additional nonlimb SAGE libraries to further refine this set of candidate genes. This subtraction reduced the number of candidate genes by 74%, yet preserved the previously identified regulators of limb identity. This study presents the gene expression complexity of the developing limb and identifies candidate genes involved in the regulation of limb identity. We propose that our computational tools and the overall strategy used here are broadly applicable to other SAGE-based studies in a variety of organisms. Keywords: other

Project description:How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures.

Dataset Information

First use of anatomical networks to study modularity and integration of heads, forelimbs and hindlimbs in abnormal anencephalic and cyclopic vs normal human development.

Publications

First use of anatomical networks to study modularity and integration of heads, forelimbs and hindlimbs in abnormal anencephalic and cyclopic vs normal human development.

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