@article{fdi:010049037,
  title = {{S}ome considerations for analyzing biodiversity using integrative metagenomics and gene networks},
  author = {{B}ittner, {L}. and {H}alary, {S}. and {P}ayri, {C}laude and {C}ruaud, {C}. and {R}eviers de, {B}. and {L}opez, {P}. and {B}apteste, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {I}mproving knowledge of biodiversity will benefit conservation biology, enhance bioremediation studies, and could lead to new medical treatments. {H}owever there is no standard approach to estimate and to compare the diversity of different environments, or to study its past, and possibly, future evolution. {P}resentation of the hypothesis: {W}e argue that there are two conditions for significant progress in the identification and quantification of biodiversity. {F}irst, integrative metagenomic studies - aiming at the simultaneous examination (or even better at the integration) of observations about the elements, functions and evolutionary processes captured by the massive sequencing of multiple markers - should be preferred over {DNA} barcoding projects and over metagenomic projects based on a single marker. {S}econd, such metagenomic data should be studied with novel inclusive network-based approaches, designed to draw inferences both on the many units and on the many processes present in the environments. {T}esting the hypothesis: {W}e reached these conclusions through a comparison of the theoretical foundations of two molecular approaches seeking to assess biodiversity: metagenomics (mostly used on prokaryotes and protists) and {DNA} barcoding (mostly used on multicellular eukaryotes), and by pragmatic considerations of the issues caused by the 'species problem' in biodiversity studies. {I}mplications of the hypothesis: {E}volutionary gene networks reduce the risk of producing biodiversity estimates with limited explanatory power, biased either by unequal rates of {LGT}, or difficult to interpret due to (practical) problems caused by type {I} and type {II} grey zones. {M}oreover, these networks would easily accommodate additional (meta) transcriptomic and (meta) proteomic data. {R}eviewers: {T}his article was reviewed by {P}r. {W}illiam {M}artin, {D}r. {D}avid {W}illiams (nominated by {P}r. {J} {P}eter {G}ogarten) & {D}r. {J}ames {M}c{I}nerney (nominated by {P}r. {J}ohn {L}ogsdon).},
  keywords = {},
  booktitle = {},
  journal = {{B}iology {D}irect},
  volume = {5},
  numero = {},
  pages = {47},
  ISSN = {1745-6150},
  year = {2010},
  DOI = {10.1186/1745-6150-5-47},
  URL = {https://www.documentation.ird.fr/hor/fdi:010049037},
}