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Published on: February 5, 2014
Unveiling population structure and selection signatures of riverine and genetically improved rohu, Labeo rohita using
Priyanka Nandanpawar1, Bismay Sahoo2, Lakshman Sahoo2
1ICAR-Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India. priyacife@gmail.com.
Background:
Captive breeding, along with artificial selection can significantly impact population structure by influencing allele frequencies and driving populations towards specific adaptation. Selective sweeps are powerful forces in shaping genetic variation within populations and can drive rapid spread of beneficial alleles while simultaneously reducing genetic diversity in localized regions of the genome. The present work was undertaken to assess the genetic structure and consequences of artificial selection in 10th generation of genetically improved rohu by comparing with wild populations.
Methods And Results:
The present study used 11,022 high-quality genome wide SNPs to compare the population genetic structure and signatures of selection between Jayanti rohu population and its wild counterpart. Outlier analysis revealed presence of 14 adaptive SNPs, out of which 5 were classified to be under decisive selection pressure. Notably, Jayanti rohu (JR) displayed 297 private alleles exclusive to its population. Chromosomes 7 and 16 emerged as potential hotspots containing a majority of the identified SNPs. Structure and principal component analysis revealed two distinct clusters, effectively distinguishing the JR and wild rohu populations. Phylogenetic analysis indicated a separate cluster of JR population distant from wild groups.
Conclusion:
The results of present study shall help in elucidating patterns of genetic variation and characterizing selection signatures associated with captive bred and natural populations of rohu. The genomic resources generated through this work shall be helpful in improving the traceability of selectively bred germplasm for developing future strategies of genetic management.
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