Evidence map›Paper›PMID 33413124›Full record

ArticleBMC genomics2021

Hepatic transcriptome perturbations in dairy cows fed different forage resources.

S T Gao, Lu Ma, Y D Zhang, J Q Wang, J J Loor, D P Bu

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

S T GaoState Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Lu MaState Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Y D ZhangState Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
J Q WangState Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
J J LoorDepartment of Animal Sciences and Division of Nutritional Sciences, University of Illinois, Urbana, IL, USA.
D P BuState Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Beijing, 100193, China. budengpan@126.com.
Chinese Academy of Agricultural Sciences · CNUniversity of Illinois Urbana-Champaign · US

Funding

Beijing Dairy Industry Innovation Team BAIC06-2020National Key Research and Development Program of China 2018YFD0501600Scientific Research Project for Major Achievements of The Agricultural Science and Technology Innovation Program (ASTIP) ASTIP-IAS07Scientific Research Project for Major Achievements of The Agricultural Science and Technology Innovation Program (ASTIP) CAAS-XTCX2016011-01Scientific Research Project for Major Achievements of The Agricultural Science and Technology Innovation Program (ASTIP) CAAS-ZDXT2019004
6 · The paper itself

Abstract

backgroundForage plays critical roles in milk performance of dairy. However, domestic high-quality forage such as alfalfa hay is far from being sufficient in China. Thus, more than 1 million tons of alfalfa hay were imported in China annually in recent years. At the same time, more than 10 million tons of corn stover are generated annually in China. Thus, taking full advantage of corn stover to meet the demand of forage and reduce dependence on imported alfalfa hay has been a strategic policy for the Chinese dairy industry. Changes in liver metabolism under different forage resources are not well known. Thus, the objective of the present study was to investigate the effect of different forage resources on liver metabolism using RNAseq and bioinformatics analyses.

resultsThe results of this study showed that the cows fed a diet with corn stover (CS) as the main forage had lower milk yield, DMI, milk protein content and yield, milk fat yield, and lactose yield than cows fed a mixed forage (MF) diet (P <  0.01). KEGG analysis for differently expressed genes (DEG) in liver (81 up-regulated and 423 down-DEG, Padj ≤0.05) showed that pathways associated with glycan biosynthesis and metabolism and amino acid metabolism was inhibited by the CS diet. In addition, results from DAVID and ClueGO indicated that biological processes related to cell-cell adhesion, multicellular organism growth, and amino acid and protein metabolism also were downregulated by feeding CS. Co-expression network analysis indicated that FAM210A, SLC26A6, FBXW5, EIF6, ZSCAN10, FPGS, and ARMCX2 played critical roles in the network. Bioinformatics analysis showed that genes within the co-expression network were enriched to "pyruvate metabolic process", "complement activation, classical pathway", and "retrograde transport, endosome to Golgi".

conclusionsResults of the present study indicated that feeding a low-quality forage diet inhibits important biological functions of the liver at least in part due to a reduction in DMI. In addition, the results of the present study provide an insight into the metabolic response in the liver to different-quality forage resources. As such, the data can help develop favorable strategies to improve the utilization of corn stover in China.

Indexed as

Animal FeedLactationAnimalsCattleChinaDietFemaleLiverMedicago sativaRumenSilageTranscriptomeZea maysCorn StoverForage resourcesLiver transcriptomeRNAseq

Identifiers

PMID33413124
PMCPMC7792104
OpenAlexW3100338336

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.