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. 2015 Oct 28:16:872.
doi: 10.1186/s12864-015-1986-2.

Prospecting major genes in dairy buffaloes

G M F de Camargo  1 , R R Aspilcueta-Borquis  2 , M R S Fortes  3 , R Porto-Neto  4 , D F Cardoso  5 , D J A Santos  6 , S A Lehnert  7 , A Reverter  8 , S S Moore  9 , H Tonhati  10
Affiliations

Prospecting major genes in dairy buffaloes

G M F de Camargo et al. BMC Genomics. .

Abstract

Background: Asian buffaloes (Bubalus bubalis) have an important socio-economic role. The majority of the population is situated in developing countries. Due to the scarce resources in these countries, very few species-specific biotechnology tools exist and a lot of cattle-derived technologies are applied to buffaloes. However, the application of cattle genomic tools to buffaloes is not straightforward and, as results suggested, despite genome sequences similarity the genetic polymorphisms are different.

Results: The first SNP chip genotyping platform designed specifically for buffaloes has recently become available. Herein, a genome-wide association study (GWAS) and gene network analysis carried out in buffaloes is presented. Target phenotypes were six milk production and four reproductive traits. GWAS identified SNP with significant associations and suggested candidate genes that were specific to each trait and also genes with pleiotropic effect, associated to multiple traits.

Conclusions: Network predictions of interactions between these candidate genes may guide further molecular analyses in search of disruptive mutations, help select genes for functional experiments and evidence metabolism differences in comparison to cattle. The cattle SNP chip does not offer an optimal coverage of buffalo genome, thereafter the development of new buffalo-specific genetic technologies is warranted. An annotated reference genome would greatly facilitate genetic research, with potential impact to buffalo-based dairy production.

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Figures

Fig. 1
Fig. 1
a - Association weight matrix gene network. a) Entire gene network formed by 1,068 nodes connected by 3,307 predicted interactions (edges). b – Highest interconnection region in the network whose seed (square) is CA10 gene (MCODE App). c - Subset of the co-association network showing the best duo of transcription factors: RARB and ATF1
See this image and copyright information in PMC

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