Genomic Analysis Reveals Novel Genes and Adaptive Mechanisms for Artificial Diet Utilization in the Silkworm Strain Guican No.5

The transition from traditional mulberry leaf feeding to artificial diet cultivation represents a major advancement in modern sericulture, yet the genetic mechanisms driving this adaptation remain largely unexplored. This study investigates the genomic basis of artificial diet adaptation in the silkworm strain Guican No.5 through whole-genome resequencing and transcriptome analysis. We identified 8,935,179 single-nucleotide polymorphisms (SNPs) across all chromosomes, accounting for 2.01% of the genome, with particularly high densities observed in chromosomes 23, 26, and 28. Our analysis also revealed 879 novel transcripts, many of which are involved in digestion, detoxification, and stress response pathways. Key novel genes, including three carboxylesterases, two cytochrome P450s, one heat shock protein, and one copper/zinc superoxide dismutase, exhibited varying degrees of sequence similarity to known proteins, suggesting modifications to existing genetic frameworks. Notably, one novel P450 gene displayed only 74.07% sequence identity with its closest homolog, indicating the emergence of a new protein sequence. Additionally, several key genes showed high similarity to wild silkworm (<i>Bombyx mandarina</i>) proteins, underscoring their evolutionary origins. These findings provide valuable insights into the molecular mechanisms underpinning artificial diet adaptation in silkworms and offer genomic resources to enhance artificial diet formulations and breeding programs in sericulture.

Authors

Institutions

Publication Details

Journal
Insects
Published
2024-12-20
DOI
https://doi.org/10.3390/insects15121010
Citations
4
Primary Topic
Silkworms and Sericulture Research
Type
article
Field-Weighted Citation Impact
2.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genomic Analysis Reveals Novel Genes and Adaptive Mechanisms for Artificial Diet Utilization in the Silkworm Strain Guican No.5

Jing Song, De‐Long Guan, Wei-An Deng, Xiaoyan Zhang et al.
4 citations
Insects
Silkworms and Sericulture Research
2.16
article

Genomic Analysis Reveals Novel Genes and Adaptive Mechanisms for Artificial Diet Utilization in the Silkworm Strain Guican No.5

Jing Song, De‐Long Guan, Wei-An Deng, Xiaoyan Zhang, Xiaodong Li, Xin Lei, Nan Wei
article en
4 citations

Abstract

The transition from traditional mulberry leaf feeding to artificial diet cultivation represents a major advancement in modern sericulture, yet the genetic mechanisms driving this adaptation remain largely unexplored. This study investigates the genomic basis of artificial diet adaptation in the silkworm strain Guican No.5 through whole-genome resequencing and transcriptome analysis. We identified 8,935,179 single-nucleotide polymorphisms (SNPs) across all chromosomes, accounting for 2.01% of the genome, with particularly high densities observed in chromosomes 23, 26, and 28. Our analysis also revealed 879 novel transcripts, many of which are involved in digestion, detoxification, and stress response pathways. Key novel genes, including three carboxylesterases, two cytochrome P450s, one heat shock protein, and one copper/zinc superoxide dismutase, exhibited varying degrees of sequence similarity to known proteins, suggesting modifications to existing genetic frameworks. Notably, one novel P450 gene displayed only 74.07% sequence identity with its closest homolog, indicating the emergence of a new protein sequence. Additionally, several key genes showed high similarity to wild silkworm (<i>Bombyx mandarina</i>) proteins, underscoring their evolutionary origins. These findings provide valuable insights into the molecular mechanisms underpinning artificial diet adaptation in silkworms and offer genomic resources to enhance artificial diet formulations and breeding programs in sericulture.

InsectsVol. 15(12)
Hechi University (CN)
Zero hunger
Openalex Percentile: Top 13%
Silkworms and Sericulture Research
2.16
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.